Mohammad Yamin
email: 1myamin@kau.edu.sa

Moteb Ayesh Albugami
email: 2malbugami@ut.edu.sa

An Architecture for Improving Hajj Management

Keywords: Management, Crowd, Hajj, Kumbh, Stampedes, RFID, Sensor Networks, Biometric, pilgrims, tawaf

The effective management of crowded events such as the Muslim Hajj in Saudi Arabia and the Hindu Kumbh in India continues to remain a challenge mainly due to uncontrollable buildup of crowds or mismanagement. Despite regular occurrence of catastrophes such as stampedes and fires, resulting in significant loss of lives, there are no international binding standards for controlling and managing large crowds. Indeed, the use of advanced technology, including tracking and monitoring tools, and sensor and biometric identification methods, can assist towards better crowd management but technology alone cannot be a solution to overcrowding. Because of the congestion, resulting from overcrowding, timely cleaning and sanitation becomes unmanageable, which causes spread of diseases. This article discusses some factors which are critically important and provide an architecture for better management of Hajj.

Introduction

In the last decade alone, thousands of people have perished in stampedes, fires and other incidents resulting from overcrowding or mismanagement of large gatherings of people. Ironically most of the crowded events happen to be religious in nature. On 13 th October 2013, more than one hundred people died due to overcrowding on a bridge in India [START_REF]Scores dead after bridge stampede near Hindu temple in India[END_REF]. On 10 th February 2013, dozens of people were crushed to death in Kumbh [START_REF] Guardian | Kumbh Mela stampede leaves dozens of Hindu pilgrims deadvideo[END_REF]. On the eve of 2013, more than sixty people were killed and hundreds injured in Ivory Coast [START_REF] Cnn | Ivory Coast mourns 60 killed in New Year's stampede[END_REF]. Excessive death toll (over eleven hundred) and injuries (over two and a half thousands) in a building collapse in Bangladesh on 24 th April, 2013 was also partly due to overcrowding [START_REF]Savar Building Collapse[END_REF]. In Hajj alone, during the last twenty years, several stampedes and fires have resulted in thousands of deaths, the most recent [START_REF]Hajj stampede[END_REF] being in October 2012. To analyze and describe the problems of overcrowding, we have chosen the case of Hajj, which is an annual event involving a gathering of more than three million with very intense activities.

The Hajj is a pilgrimage to Makkah in Saudi Arabia that takes place every year during 8 th -12 th Dhulhijja, a month in the Islamic (lunar) calendar. Every year millions of pilgrims from more than one hundred and fifty countries perform Hajj. Although the Hajj rituals span only four fixed days, but partly due to limited air and sea transportation, many of the pilgrims spend four to six weeks in and around Makkah (Mecca) and Madinah (Medina), the two holiest cities for Muslims. The Hajj is a unique, very complex, challenging and costly exercise to manage as it involves frequent mass movement of more than three million pilgrims. Some of the problems and aspects of Hajj can be found in [START_REF] Mohammad | Crowd Management with RFID & Wireless Technologies[END_REF], [START_REF] Mohammad | Wireless & Sensor Technology and Crowd Management[END_REF], [START_REF] Yamin | RFID Technology and Crowded Event Management[END_REF], [START_REF] Mohammad | A Framework For Improved Hajj Management And Future Research[END_REF], [START_REF] Mohammad | A Framework For Improved Hajj Management And Future Research[END_REF] and [START_REF] Mohammad | Wireless Systems to Manage Large Congregations[END_REF] The most critical factors in crowd management are the extent of the crowd and its management. To minimize the chances of stampedes and other catastrophes, event organisers need to limit the crowds to acceptable levels. However, there is no binding international standard for setting a limit on the number of people which could be allowed to gather in a specified space or area. Event organization would become significantly easier to manage if such standards were agreed upon and implemented. Crowd management can also be improved significantly with the help of sensor and biometric technology, tools and gadgets. Some of the intensely crowded events like the Hajj often involve simultaneous movement of the entire congregation, which creates problems of transportation and uncontrollable buildup of crowd. In such situations, tracking, accessibility and identification of pilgrims becomes very difficult. Many of the sensor and wireless devices available today, including Radio Frequency Identification (RFID) [START_REF] Finkenzeller | RFID Handbook: Fundamentals and Applications in Contactless Smart Cards, Radio Frequency Identification and Near-Field Communication[END_REF] can be used for controlling and monitoring the movement of crowds. These technologies are now being widely used for improving management and administration of many business functions. However, these technologies are still going through a transitional phase [START_REF] Talevski | SOA and Web Based Approaches for Remote Operation and Control[END_REF] and one would hope to see significant refinement of them to become usable and effective for managing very large and dense crowds. Nevertheless, these technologies in their present form could have been used in saving thousands of precious lives in many of the past incidents of stampedes and fires. A description of ubiquitous technologies including RFID, sensor networks, biometric and scanning devices can be found in [START_REF] Finkenzeller | RFID Handbook: Fundamentals and Applications in Contactless Smart Cards, Radio Frequency Identification and Near-Field Communication[END_REF].

There are serious health issues for crowded events with a span of three or more days, if cleaning and disposal of rubbish cannot be carried out regularly. Lack of cleaning gives rise to the growth of dangerous bacteria, which has been witnessed in some cases [START_REF] Mcconnell | Mass gatherings health Series[END_REF]. Another serious health risk is from the mismanagement of the pilgrims carrying communicable and contagious viruses, bacteria and diseases. Due to inability to control entry, many pilgrims may carry deadly bacteria such as HIV Aids and Hepatitis. Many of these infected pilgrims may not be known to the management and hence cannot be isolated. Indeed the infected pilgrims must be isolated from the rest of the pilgrims. For managing the health and wellbeing of the pilgrims, including those infected with contagious bacteria, the RFID technology can play a very significant role [START_REF] Yao | The use of RFID in healthcare: Benefits and barriers[END_REF].

In this paper we present and analyze a number of problems of hajj management, and offer some solutions including architecture for improving the management. These solutions can indeed be applied in many other and similar crowded events such as Kumbh.

The Hajj Management Issues

Hajj is a set of highly complex and intense activities which makes it a very challenging event to manage. Overseas pilgrims start arriving in Saudi Arabia five weeks before the actual hajj period. Late arrivals stay back for up to five weeks after the event. The hajj rituals however only span over four days, from 8-12 of the Arabic (lunar) month of Dhulhijja. The problems and challenges of Hajj are generally not known to many researchers mainly because of the entry restrictions and poor press and media coverage.

Pilgrims Numbers

Due to an overwhelming number of requests, which cannot be accommodated, people (including the Saudi citizens) are restricted to perform Hajj once in five years. However, this moratorium has so far not been successfully implemented. Current facilities for hajj are adequate only for two million people. One of the main problems for the Hajj mangers is to deal with a large number of illegal pilgrims. Makkah region, which has a population of about two million, largely contributes to the illegal pilgrims. According to the governor of Makkah [START_REF][END_REF], in 2012, up to 3.65 million pilgrims performed hajj, which nearly doubled the maximum accommodation capacity. Some other sources, including eye witness accounts of congestions put these figures even much higher which demonstrates that the number of the hajj pilgrims is often uncontrollable. Most of the expatriates, living in the kingdom of Saudi Arabia, are always very eager to perform hajj every year and many of them happen to be illegal migrants. Presence of the unauthorized pilgrims, especially the illegal immigrants, is a cause of great concern, particularly in relation to law and order agencies. The hajj managers do not have any personal and health data for these pilgrims. Hence they also pose serious health risks, severely strain the pilgrim movement, sometimes causing stampedes. During the 2012 Hajj, due to overcrowding, walking on roads became very strenuous and sometimes resulted in minor stampedes. In the case of an emergency, due to the lack of data, illegal pilgrims are very vulnerable

Visa and Immigration

Anyone outside Saudi Arabia, intending to perform Hajj, applies for a visa through a travel agent in their country of residence by furnishing information and undergoing some medical examination and immunisation. The hajj visa is granted by the Saudi government if the visa conditions are met. Once a Hajj visa is granted, each pilgrim is assigned to a Hajj Management group, known as Munazzim, who are responsible for organising travel and accommodation before, during and after the hajj. The Munazzim groups are the official representatives of the Ministry of Hajj.

For an overseas pilgrim, there are very strict visa requirements for entering in the kingdom of Saudi Arabia. The foreign pilgrims are mainly processed at Jeddah and Madinah airports, which are about ninety and four hundred kilometers away from Makkah, respectively. Jeddah is not only the designated airport of Makkah but also has the main sea port where hundreds of thousands of pilgrims, mainly from Africa, are processed. So far there is only one 4x4 lane road link between Jeddah and Makkah but currently a rail link is also under construction. Most of the pilgrims also visit Madinah, which houses the grand mosque of the prophet Muhammad and is also his final resting place. After the immigration processing, the pilgrims are required to hand over their passports to their Munazzim and travel to their hotels in Makkah or Madinah in the care of the Munazzim group.

Assemblies in Mina, Arafat and Muzdalifah

As part of the core activities of Hajj, all pilgrims are required to spend some time in Mina, Arafat and Muzdalifah. The tent city of Mina [7], separated from Makkah by about seven kilometers of very thick hills, has historically predefined perimeters. It covers an area of about twenty square kilometers and has thousands of nonflammable tents that can accommodate about one and half million pilgrims . All pilgrims are required to spend three days in Mina. By a very simple arithmetic calculation, it is easy to determine that Mina cannot accommodate more than two million pilgrims. The Valley of Arafat [START_REF] Wikipedia | [END_REF] hills are about twenty kilometers away from Mina. All pilgrims must spend the best part of the day of 9 th Dhulhijja there. This area has a capacity to accommodate about two million pilgrims. Muzdalifah is a small village between Mina and Arafat. All pilgrims are required to spend the night of 9 th Dhulhijja in Muzdalifah, which nowadays can accommodate up to a maximum of one million people as a large portion of its area has been consumed by the multiple roads running between Mina and Arafat. On their way back from Arafat valley, all pilgrims are required to spend the night of the 9 th Dhulhijja in the open space, previously a hill, near the town of Muzdalifah. The space in Muzdalifah is much smaller than that of Arafat or Mina. There is not enough space for even one million people. As a result, roads get jammed for many hours and many pilgrims cannot make it to Muzdalifah until the morning of the next day.

The journey from Mina to Arafat on the morning of the 9 th of Dhulhijja and then from Arafat to Muzdalifah in the evening is a very complex exercise. The hajj management ought to be congratulated for transporting more than three million people from Mina to Arafat and back on the same day. Since 2010, there is a train service linking Mina, Muzdalifah and Arafat; however this service can transport only a fraction of the three million passengers. Sometimes, the number of pilgrims' swells to four millions as it did in 2012. In desperate situations, many pilgrims would find alternative accommodation in adjoining townships, roadsides, hills, pathways, and rooftops, endangering their lives and those of others. In the morning of the 10 th day of Dhulhijja, all pilgrims arrive back in Mina where they perform a set of rituals. These rituals include symbolic stoning, known as 'Rami' at sites of devils, popularly known as Jamarat, and a journey to grand mosque in Makkah where they perform tawaf (circumvolution) of Kaaba and offer prayers in the holy mosque. On the 11 th day of Dhulhijja, pilgrims remain in Mina and perform a set of rituals including another act of stoning at Jamarat. On the 12 th day of Dhulhijja, after another set of stoning rituals, the hajj is completed and the pilgrims return back to their hotels or homes. After a few days, foreign pilgrims gradually start returning back to their home countries. Some pilgrims have to wait for up to five weeks to return to their home countries.

Health Risks and Lost Pilgrims

Currently hajj permissions may be granted for people suffering from serious medical conditions. However, the management of pilgrims suffering from contagious and communicable diseases is highly desirable. It is extremely dangerous to allow pilgrims carrying HIV, hepatitis, swine flu, bird flu, and tuberculosis to live with other pilgrims. Such pilgrims must be identified and isolated. On the other hand, lack of cleaning and sanitation due to intense crowding, especially during the four days of hajj, causes many pilgrims to develop a cough and fever.

As the hajj involves frequent mass movement and activities, many pilgrims disperse from their groups and lose their way. Due to communication problems, lack of education, congestion, poor network reception and many other reasons these pilgrims go on missing for days and sometimes weeks. Some of these pilgrims are injured and require urgent medical attention. Currently, pilgrims carry a nonelectronic wristband, which only identifies a pilgrim belonging to group of thousands of pilgrims under a Munazzim.

Some Solutions

Although the Saudi Arabian government has provided extensive and superior infrastructure to facilitate Hajj but still, some problems of congestion, resulting in disasters like stampedes, fires and spread of diseases persist. In the case of road congestion, extra infrastructure just increases the usage and doesn't reduce congestion [START_REF] Duranton | The fundamental law of road congestion: Evidence from US cities[END_REF]. Thus a good infrastructure is not necessarily a viable substitute for effective management. Here we present some solutions to the problems, including an architecture, to improve the management of hajj.

Controlling the Pilgrim Numbers

In order to be able to effectively manage hajj, it is absolutely necessary to limit the number of pilgrims to an acceptable level. Some extraordinary measures are required to be implemented for stopping illegal pilgrims. The lack of these measures has witnessed a swelling crowd in 2012. Learning from the problems encountered earlier, during the hajj of 2013, the management ran a very successful campaign of effective advertisements at all levels of media vowing to very severe punitive measure for unauthorized pilgrims. These measures did succeed in limiting the number of pilgrims to about two million, but still there were no significant reduction in the number of illegal pilgrims from Makkah region. To minimize the chances of locals contributing to the catastrophes, it is highly desirable to organize crowd management training programs and encourage the people, especially the ones from Makkah region, to participate.

Pilgrim Tracking and Identification

Currently many organizations and businesses are using RFID chips with a sensor or a WiFi network to track and monitor people and products. For example, passports of many countries are now RFID enabled, which leads to immigration processing without human intervention. Some RFID tags [8] such as shown in Fig 2 can be used to replace traditional wristbands. The RFID tags can carry vital data and can be supported with a sensor, GPS or a 3G network to relay data to the data center. An account of the description, usage and usefulness of RFID can be found in [START_REF] Finkenzeller | RFID Handbook: Fundamentals and Applications in Contactless Smart Cards, Radio Frequency Identification and Near-Field Communication[END_REF].

Fig 2:

RFIDs for human use and tracking

Prevention of Spread of Diseases

There are two prerequisites for preventing the spread of diseases during hajj namely, controlling the number of illegal pilgrims and availability of data of every pilgrim's health including diseases that can affect others. By preventing illegal pilgrims, the management can effectively get the hajj precinct regularly cleaned and hence prevent the outbreaks of bacteria that normally develop within seventy-two hours of nondisposal of garbage. Instead of preventing pilgrims with diseases like HIV Aids, tuberculosis and Hepatitis, hajj management should create a secluded isolation area for the infected pilgrims. Socially and religiously, it would be very hard to deny pilgrimage to people on their deathbeds. So if they cannot be stopped, they should be properly managed.

The problems of crowding in Mina, Arafat and Muzdalifah are dependent on pilgrim numbers, religious interpretations and infrastructure. It is simply impossible to accommodate two million people in Muzdalifah, prompting religious decree to ease the overcrowding. Some traffic congestion problems may ease in coming years once the rail links (under construction) between Jeddah, Makkah, Mina, and Madinah become operational. Currently, there are hundreds of towers and many other large buildings under construction to meet the increasing demand of accommodation.

Operations Overview

While there are a lot of issues associated with the Hajj, the most important is the need to managing the crowd and facilities during the Hajj period. As shown in Fig 3, the crowd controller will be responsible for monitoring and managing, transportation, health care services, security services and ritual sites. The transportation is managed by scheduling, based on the number of people in a ritual site at given time. In case of emergency, the controller will inform and request help from health care and security services. The controller will liaise with the security services in a two ways communication, where they can report and receive reports about security issues. The controller receives information about the situation and status in the various ritual sites. Accommodation will be available for all pilgrims upon arrival in the ritual sites, of Mina, Arafat and Muzdalifah, which would be equipped with the required facilities. Buses and trains would transport pilgrims between sites. The rituals sites would be monitored and receive instructions or request help from the controller. Additionally, the controller would monitor the movements of individuals and crowd for security, health and traffic reason.

The architecture and other solutions proposed in this paper can be useful in managing many other crowded events such as Kumbh and Badrinath Yatra [START_REF] Wikipedia | [END_REF].

Conclusions

People continue to die due to mismanagement of crowded events. The culture of blame game needs to change by squarely making the local management and government responsible for all overcrowding and preventable catastrophes in their jurisdiction. Surely, better and improved infrastructure may help in checking overcrowding but infrastructure alone is not sufficient to prevent hazardous incidents.

There is a need for well-coordinated management of crowds with modern tools and technology. The technology, if used as part of a whole solution, can be very effective in controlling crowds but may not bring desired results if used in a standalone mode as is the case of hajj or Kumbh management. The hajj rituals are based on Abrahamic traditions mentioned in the holy Quran which were enacted by Mohammed, the prophet of Islam. Thus being deeply enshrined in religious teachings and faith, some changes cannot be implemented unless approved by the clerics. Technological solutions, irrespective of their sophistication, become ineffective because of the ignorance, which prevails in almost all religious gatherings. Incidentally, most of the large gatherings are religious in nature and sadly most of the stampedes are associated with religious gatherings. These religious assemblies gather people from diverse ethnicities, beliefs and cultures, which make it very difficult to make simple changes against sectarian religious perceptions. However, through persistent cross-cultural consultation, and discussions at national and international levels, managers of such events can bring many desirable changes.

Fig 1 :Fig 1

 11 Fig 1: Diagram of core activities of hajj

  The component diagram in Fig 3 shows an overview of the proposed operations architecture.

Fig 3 :

 3 Fig 3: An Overview of the Architecture

Acknowledgment

The inspiration for this article has come from personal experiences of the authors who have performed hajj several times, and who have also participated in many other crowded events including the Kumbh. The authors acknowledge support from the faculty of Economics and Administration of the King Abdulaziz University. The authors also acknowledge the help provided by various individuals and organisations involved in the hajj management including the Hajj Research Centre in Makkah and the Ministry of Interior of Saudi Arabia.


Jiong Fu
email: fu9jiong2@163.com

Aimin Luo
email: amluo@nudt.edu.cn

Xueshan Luo
email: xsluo@nudt.edu.cn

An UML-Based Meta-modeling Method of Building Architecture Product

Keywords: Architecture, Meta-model, Meta-modeling, UML

Architecture product modeling is an important means to collect enterprise-wide decision-making data. DoDAF2.0 proposes meta-model theory to facilitate organizing and collecting data, but still no clear concrete modeling methods for collecting data are available. This paper presents an UML-based meta-modeling method of building architecture product. This method contributes by solving the existing problem within product modeling, and by using the method we can get the modeling tool easily.

Introduction

Information system architecture is defined as the structure of components consisting of its system, relationships, and the disciplines and guidelines governing their design and evolution over time [START_REF]IEEE Recommended Practice for Architecture Description, IEEE Std 1471[END_REF]. At present, much research on information system architecture is generally conducted based on the research of DoDAF, and thus research around modeling of architecture product is an important part. Though DoDAF2.0 [START_REF]DoD Architecture Framework Version 2.0: Architect's Guide-Architecural Data and Models[END_REF] provides the criterion and method for data organizing and collecting, the method and process for product modeling is left absent. As a result, there is a lack of maneuverable guidance for product modeling, and this lack will affect data collecting and moreover affect decision-making. Presently, Object Management Group(OMG) recommended MOF as the standard of meta-meta-model, but still not accepted widely [START_REF] Liu Hui | Progress of Research on Metamodeling[J][END_REF]. Lan [START_REF] Qingguo | Research on the Key Technology of Executable Metamodel[END_REF] introduced the basic building process of executable meta-model in MDA domain. However, the research on architecture product modeling has little progress. In order to settle the problem, refer to the meta-modeling method and technologies in MDA domain, this paper proposes a meta-modeling method framework and elaborates the basic process of information system architecture product modeling. Further, this paper studies three key technologies of the meta-modeling of architecture product, i.e., (I) meta-meta-model, (II) meta-model and (III) meta-modeling tool. By using the method of meta-modeling of architecture product, we can solve the problem of product modeling, and it can provide the modeling tool easily.

This paper is organized as follows. In section 2, we present the architecture of the product element modeling framework. Section 3 discusses the method and basic process of modeling meta-meta-model. In section 4, we propose a construction method based on UML for architecture product meta-modeling. In Section 5 we take Operational Resource Flow Description (OV-2) as an example to illustrate our method and the meta-model tool. Section 6 concludes the paper by noting the future works.

2

The Meta-modeling Method Framework of Architecture Product

No unified and standardized definition of architecture meta-model is available now.

Based on its application, the architecture meta-model can be categorized into two categories, i.e., data meta-model and product meta-model. Data meta-model focuses on the criterions of architecture data, it can better support us to collect and store data. This part (Data meta-model) is the core of DoDAF2.0; while product meta-model focuses on the direct guidance for various architecture products modeling. It (product meta-model) is very important in process of architecture development and design. This paper mainly focuses on latter one, i.e., product meta-model. The meta-modeling of architecture product is defined as the process of characterizing the meta-model of the modeling language of architecture product, customizing the modeling language of view product and configuring the modeling tool which supports the modeling language. The process of meta-modeling involves several important elements, including meta-meta-model, meta-model, model, metamodeling tool and modeling tool. Different from the methods used to build DoDAF Meta Model(DM2), the product meta-modeling approach is mainly to solve the problem as to how to build meta-meta-model, product meta-model and to customize modeling tool. Fig. 1 The meta-modeling method framework of architecture product

For the problem of the lack of guidance and progress of the architecture product meta-modeling, refer to the meta-modeling method and technologies in MDA domain, this section presented a meta-modeling method framework of architecture product and analyzed basic processes and main technologies of meta-modeling. Through the research, we improve the modeling framework of architecture product under the meta-model theory, and provide a method for architecture product modeling.

The meta-modeling method framework of architecture product is presented here, as shown in Figure 1. The meta-modeling method framework includes two main processes. One is the process of product meta-model built by meta-meta-model, and the other is the process of configuring modeling tool by product meta-model. Two processes are all based on the architecture meta-modeling tool.

Architecture Meta-meta-model

Architecture meta-meta-model is the basis for building architecture product metamodel, the contents of meta-meta-model directly impact on the contents of the product meta-model. In this section, we build a set of meta-meta-model that can be used to construct and describe architecture product meta-model. The basic method of establishing architecture meta-meta-model is to extract all the essential attributes that describe the architecture, under the deep analysis of the 52 View product models in DoDAF2.0. And then extend specific attributes in architecture domain, refer to Ecore model [START_REF] Ecore | The Core of EMF[END_REF] in MDA. Specific steps can be divided into the followings:

Step 1: Classify the 52 products of DoDAF2.0 by different visual styles, shown in Table 1.

Digraph/Graph OV-1 、 OV-2 、 SV-1 、 SV-2 、 CV-1 、 CV-2 、 SvcV-1 、 SvcV-2 、 SvcV-4、DIV-1 Table/Matrix OV-3、SV-3、SV-5a、SV-5b、SV-6、SV-7、SV-9、AV-1、AV-2、 CV-4、CV-5、CV-6、CV-7、SvcV-3a、SvcV-3b、SvcV-5、SvcV-6 、SvcV-7、SvcV-9、StdV-1、StdV-2、PV-1、PV-3 Hierarchy Diagram OV-4、OV-5、SV-4、CV-2 State Transition Diagram OV-6b、SV-10b、SvcV-10b Timing Diagram OV-6c、SV-10c、SvcV-10c Timeline Diagram SV-8、CV-3、SvcV-8、PV-2
Step 2: For each visual style, analyze and extract essential elements. The visualization styles in step 1 can be roughly divided into two categories: "Node + Connection" type , including digraph/graph, hierarchy diagram, state transition diagram, timing diagram; and "Table" type, including table and matrix , timeline diagram.

For the "Node + Connection" type, entity and relationship are the core data elements. There are some other data elements, e.g. property and type. Entity can be in place of icon, vertex and node in products, also refers to specific activities or functions. Relationship can be in place of connection, arc, input connection or output connection. Entity and relationship can have a number of categories and attributes, relationship can be subdivided into binary relationship, inheritance relationship, association, aggregation relationship, etc.

For the "Table" type, the row, column, or cell of the table can be seen as an entity, while other data elements include property, type and comment.

Therefore, summarizing the above analyses, the essential elements of different visualization style are shown in Table 2. The essential data elements of architecture products include: Entity Relationship (binary relations, inheritance, association and aggregation), property, type and comment. MetaClass is used to define building blocks of the modeling language, for example, when building meta-model of Operational Resource Flow Description (OV-2), the MetaClass is used to describe operational nodes and operational activities. MetaRelationship is used to define binary relationship in modeling language, such as association, generalization, realization, etc. MetaEnum is used to define enumeration types of modeling language. MetaPackage is used to manage and organize the blocks defined. MetaComment is used to define the annotation to aid in understanding the modeling language. MetaReference is used to define association and aggregation relationship between blocks. MetaGeneralization defines inheritance relationship between blocks. MetaAttribute defines the properties of elements defined. syntax model describes the manifestation of modeling language. In contrast, semantic model describes the meaning of the concept of modeling language.

In this paper, we use UML-based extensional semantics [START_REF] Clark | Applied Metamodeling A Foundation for Language Driven Development Version 0[END_REF] approach to describe the semantic model. The so-called UML-based extensional semantics approach is to extend the existing UML semantics specification to adapt the semantic description of architecture model language. The way of extension is by the way of object-oriented inheriting with precise semantics of the UML model elements, thus reusing existing language semantics.

The core elements of UML models with precise semantics include Class, Package, Association and Property, while the sorts of the core elements of the abstract syntax model of the architecture modeling language include MetaClass, MetaPackage, MetaRelationship and MetaAttribute. Let them inherit from Class, Package, Association and Property of the UML language, as shown in Fig. 5, so that they have semantics when building abstract syntax model.

The Architecture Meta-modeling Tool and Case Study

Architecture meta-modeling tool is the carrier of meta-modeling process, as well as the manifestation of the meta-modeling method of architecture product. Architecture meta-modeling tool should be able to construct product meta-model, and also can customize the corresponding modeling tool. So compared with the traditional architecture modeling tool, meta-modeling tool has better expansibility, and metamodeling can greatly reduce workload of tool development. By developing our architecture meta-modeling tool prototype, we use Java language which is platform-independent to code, and use integrated development platform Eclipse to develop the tool. Besides we use Graphical Editing Framework (GEF) to achieve the graphical representation of modeling elements. The visual interface of the tool includes six parts, followed by toolbar, palette, editing area, navigation area, property area and outline area, as shown in Fig. 6.

We take Operational Resource Flow Description (OV-2) as an instance to illustrate the meta-modeling method and the tool introduced above.

Operational Resource Flow Description (OV-2) describes the resource information exchanged between operational activities. Now assume a simple scenario: we assume that a combat unit has a simple process including intelligence gathering, information processing, combat command ordering and combat performing. Table 3 lists all the scenarios including operational activity, operational information and operational node. Besides, by analyzing OV-2 abstract syntax model, we can find that Activity, OperationalNode, Information, Organization, Condition are instances of MetaClass, so they inherit semantics from Class. NeedLine is an instance of MetaRelationship, and it inherits semantics from Association. Attribute is an instance of MetaAttribute, and therefore it inherits semantics from property.

(2) Configure to generate OV-2 modeling tool Architecture meta-modeling tool is able to analyze the product meta-model we build, and customize the modeling tool which supports the product. Fig. 9 shows the modeling interface of OV-2 modeling tool, which is created by the meta-modeling tool after analyzing OV-2 meta-model. From the content and visual style of the OV-2 product we built, we can find they correctly reflect the meaning of OV-2. Thus, the architecture meta-modeling tool has validated our meta-modeling method of architecture product.

Conclusions

This paper presents a meta-modeling method of architecture product. We analyze the main technical issues of meta-modeling, including meta-meta-model, product meta-model and meta-modeling tool. Based on the tool, we analyze and validate the meta-modeling method of architecture product via a case. This research provides a new method for architecture product modeling with the theory of meta-modeling. This new method enables enterprise modeling with meta-models. Future work will be conducted with a focus on integrating other modeling methods into the as is tool.

Fig. 2

 2 Fig. 2 Architecture meta-meta-modelThe elements used for meta-modeling in architecture meta-meta-model shown in Fig.2include: MetaClass, MetaRelationship, MetaEnum, MetaPackage, MetaComment, MetaReference, MetaGeneralization and MetaAttribute.MetaClass is used to define building blocks of the modeling language, for example, when building meta-model of Operational Resource Flow Description (OV-2), the MetaClass is used to describe operational nodes and operational activities. MetaRelationship is used to define binary relationship in modeling language, such as association, generalization, realization, etc. MetaEnum is used to define enumeration

Fig. 5

 5 Fig. 5 UML-based Extensional Semantics

Fig. 6

 6 Fig.[START_REF] Jiang Zhi-Ping | The Research on the Datacentered C4ISR System Architecture Development Method[END_REF] The Visual Interface of The Tool Table 3 Activities, Information and Node Operational Activity Operational Information Operational Node Intelligence gathering Intelligence information Accused node Information processing Processed information Processing node Combat command ordering Combat command Firepower node Combat performing

( 1 )

 1 Build meta-model of OV-2Firstly, we need to build OV-2 abstract syntax model. The concepts meaning entity include Activity, OperationalNode, Information, Organization, Condition, and they can be created by MetaClass. NeedLine is a kind of relationship and can be created by MetaRelationship, while ActivityConsumesResource, ActivityProducesResource, ActivityPerformedUnderCondition and ActivityPerformedByPerformer are detailed description of relationships, and they can be created by MetaReference. So OV-2 abstract syntax model is shown in Fig.7. Fig.7shows that OperationalNode contains Activity, while Activity contains Condition and Organization. NeedLine contains Information, and both source end and target end of NeedLine are Activity.Then, build OV-2 surface syntax model. Since Organization and Condition can be regard as attributes of Activity, they don't need graphical symbols, the same to Information. Only OperationalNode, Activity and NeedLine need to define graphical symbols. The OV-2 surface syntax model is shown in Fig.8. Fig. 8(a) shows that rectangle represents OperationalNode, and round rectangle represents Activity, while the combined symbol of a solid line with an arrow represents NeedLine. The location of OperationalNode and Activity is belong to block-block attached type, while the location of Activity and NeedLine is belong to connected type. Fig. 8(b) shows the modeling interface of surface syntax model.

Fig. 7 OVFig. 8

 78 Fig. 7 OV-2 Abstract Syntax Model

Fig. 9

 9 shows that yellow round rectangle represents Activity, and rectangle represents OperationalNode, and the straight line with arrow represents Needline. When modeling, Activity can only attach to the boundary of OperationalNode, while Needline can only be created between activities.

Fig. 9

 9 Fig. 9 The Modeling Interface of OV-2 Modeling Tool

Table 1

 1 Classification of Architecture Products by Visualization Style

	Visualization Style	Architecture Products

Table 2

 2 Essential Elements of Different Visual Style Refer to Ecore model, extend specific attributes in architecture domain, and we get architecture meta-meta-model, as shown in Fig. 2.

	Type		Visual Style		Core Data Elements	Other Data Elements
	"Node + Connection" Type	Digraph/Graph Hierarchy Diagram State Transition Diagram Timing Diagram	Entity Relationship	、	Property、Type
	"Table" Type		Table/Matrix Timeline Diagram	Entity	Property 、 Type 、 Comment
	Step 3: MetaElement
			MetaModelElement
	MetaComment		MetaNamedElement		MetaGeneralization
	MetaPackage		MetaClassifier	MetaEnumLiteral	MetaTypedElement
	MetaClass		MetaDataType	MetaStructuralFeature	MetaOperation	MetaParameter
	MetaRelationship	MetaEnum	MetaAttribute		MetaReference

Table 3

 3 Activities, Information and Node

	Operational Activity	Operational Information Operational Node
	Intelligence gathering	Intelligence information	Accused node
	Information processing	Processed information	Processing node
	Combat command ordering	Combat command	Firepower node
	Combat performing

4

The Architecture Meta-model

The meta-model of architecture product includes abstract syntax model, surface syntax model, semantic model. This section uses UML-based approach to build metamodel of architecture product. The idea is shown in Fig. 3. In Fig. 3, the UML-based approach to build meta-model of architecture product contains the following three aspects: the abstract syntax model built by meta-metamodel, the surface syntax model and its mapping with abstract syntax model, the semantic model and its mapping with abstract syntax model.

Abstract Syntax Model

Abstract syntax model mainly describes concepts, the relationships between concepts and constraint rules. The build process of abstract syntax model can be broken down into several stages, namely concepts identifying, concepts modeling, building formal rules between concepts, add necessary operations, model validating and model testing [START_REF] Jiang Zhi-Ping | The Research on the Datacentered C4ISR System Architecture Development Method[END_REF]. Fig. 4 shows the abstract syntax model building process and the corresponding relevant contents.

Concepts Relationships Constraint Rules

Concepts Identifying

Concepts Modeling

Validating, Rules,etc Fig. 4 The Abstract Syntax Model Building Process Concepts modeling is the core stage of building the abstract syntax, it can be divided into the following two steps:

Step1: Classify the identified concepts. Here to sort out which concepts are MetaClass, which concepts are MetaRelationship, which concepts are MetaAttribute. Typically, the concept which means entity can use MetaClass to describe, the relationship between entities can use MetaRelationship to describe, and the attributes of entity or relationship can use MetaAttribute to describe.

Step2: Use UML-based approach for modeling. After classifying the identified concepts, we can use UML-based approach to model the concepts and relationships of abstract syntax model.

Surface Syntax Model

Surface syntax model describes the details of the abstract syntax model. Surface syntax model divides into two parts: text surface syntax and graphical surface syntax, this paper only discusses its graphical surface syntax, specifically including four aspects, namely, graphical elements, combination layout, location and mapping between the abstract syntax model and graphical surface syntax model [START_REF] He Xiao | A Metamodel for the Notation of Graphical Modeling Languages[END_REF]. Graphical elements are the basic structural elements of graphic symbols, such as line, rectangle, ellipse, and so on. In follow of the principles of usability, completeness, conciseness, we get the basic graphical elements, including rectangle, round rectangle, diamond, triangle, polygon, ellipse, circle, line, polygonal line, arc, text object, image object and angular rectangle.

Combination layout is a combination of several elements combined in a certain way to become a complex graphical symbol. Combination layout reflects the internal structure of the surface syntax model. Combination layout divides into two types: one is nested combination between block graphical elements, while the other is the combination of linear graphical elements combined with other graphical elements.

Unlike combination layout, location reflects possible positional relationship of graphic symbols. There are many kinds of positional relationships between graphic symbols, and we summarize as five types: nested type, connected type, block-block attached type, block-line attached type and line-line attached type.

After defining combination layout and basic positional relationships between graphical symbols, the mapping between the abstract syntax model and graphical surface syntax model is also very important. The mapping can be divided into element mapping and positional relationship mapping. The element mapping is to attach graphical symbols to modeling elements, while positional relationship mapping is to attach location to the relationships between modeling elements.

Semantic Model

Abstract syntax model describes the structure of modeling language, and surface syntax model describes the manifestation of modeling language. In contrast, semantic model describes the meaning of the concept of modeling language.


Li Huang

Guang-Qi Huang

Yao-Hong Zhang
email: zhang_yaohong@263.net

Wei-Zi Li
email: weizi.li@henley.ac.uk

Xue-Shan Luo
email: luoxueshan@gmail.com

A Component Data-Focused Method to Build the Executable Model for a DoDAF Compliant Architecture

Keywords: Architecture, Architecture Verification, Executable Model, DoDAF, DM2

An executable model plays an important role on verifying the behavior and performance of an architecture. This paper summarizes the state of the art on the synthesis methods of the executable model for an architecture that is compliant with the Department of Defense Architecture Framework (DoDAF). To overcome the deficiencies of current executable modeling studies, a component data-focused method is proposed. Following the introduction of an executable modeling language named OPDL, the data elements of DoDAF Meta-model (DM2) required for building executable model is analyzed. The mapping relations between partial DM2 and OPDL elements are built. Finally, a process to create executable model is explained in detail.

Introduction

The Department of Defense (DoD) Architecture Framework (DoDAF) [START_REF]DoD Architecture Framework version 2.0 Volume 1: Introduction, Overview, and Concepts[END_REF] is the overarching, comprehensive framework and conceptual model enabling the development of architectures in the DoD. A DoDAF compliant architecture is presented by dividing all kinds of architecture descriptive data into manageable pieces, according to the stakeholder's viewpoint. Furthermore, data pertained to each viewpoint are described by a few predefined models respectively. In order to verify the behavior and performance of the architecture and address the concerns of the customer, Levis and Wagenhals [START_REF] Levis | C4ISR Architectures I : Developing a Process for C4ISR Architecture Design[END_REF] proposed that an executable model which is synthesized from architecture models is needed. An executable model of architecture enables the architect to analyze the dynamic behaviors of the architecture, identify logical and behavioral errors that are not easily seen in the static descriptions of its models, and demonstrate the capabilities of the architecture to the users.

Wagenhals et al. [START_REF] Wagenhals | C4ISR Architectures II : Structured Analysis Approach for Architecture Design[END_REF][START_REF] Wagenhals | Synthesizing Executable Models of Object Oriented Architectures[END_REF][START_REF] Wagenhals | Toward Executable Architectures to Support Evaluation[END_REF] use Colored Petri Nets (CPN) language for creating the executable model of the architecture. The approaches have also been developed that allow the derivation of CPN model of an architecture designed by either structured analysis or object-oriented methodology. Wang et al. [START_REF] Wang | An Executable System Architecture Approach to Discrete Events System Modeling Using SysML in Conjunction with Colored Petri Net[END_REF] proposes the method of transforming System Modeling Language (SysML) based architecture models to CPN. Baumgarten and Silverman [START_REF] Baumgarten | Dynamic DoDAF and Executable Architectures[END_REF] converted several architecture models to ExtendSim model which enables workload, timing, and process analysis that can help identify gaps, bottlenecks and overloads to queues. Mittal, Zeigler, et al. [START_REF] Mittal | Extending DoDAF to Allow Integrated DEVS-based Modeling and Simulation[END_REF][START_REF] Zeigler | Enhancing DoDAF with a DEVS-based System Lifecycle Development Process[END_REF] presented extensions to the DoDAF to support specification of DoDAF architectures within a development environment based on Discrete Event System Specification (DEVS) model, and demonstrated how DoDAF-DEVS model mapping can actually take place from the existing DoDAF UML specifications. As part of the Architecture-based Technology Evaluation and Capability Tradeoff (ARCHITECT) methodology developed by Griendling and Mavris [START_REF] Griendling | Development of a DoDAF-Based Executable Architecting Approach to Analyze System-of-Systems Alternatives[END_REF], an approach adopting a standard set of DoDAF models and the associated data to create four types of executables models is detailed.

Overall, the aforementioned executable modeling studies have the following characteristics: 1) every method has its specific executable modeling languages, most of which are some extensions to original Petri net. 2) every method contains algorithms to transform static architectural models described by different methodologies into executable models. These algorithms are generally different in various architecture methodologies due to the emphasis on architectural model instead of the underlying architecture data, which is one of the deficiencies of previous version of DoDAF. 3) most methods focus on validating the correctness of the logic and behavior of architecture, hence they usually extract much information from activity or state related models in the architecture to build executable models, but little information from component related models.

Methodology-specific executable model conversion algorithms need architect to be familiar with both original architectural modeling languages and target executable formalisms, and it is also difficult to be commonly understood and compared across multiple instances [START_REF] Ge | A Data-Centric Capability-Focused Approach for System-of-Systems Architecture Modeling and Analysis[END_REF]. Hence, it is almost impossible to popularize these methods widely. As the latest DoDAF version 2.0 [START_REF]DoD Architecture Framework version 2.0 Volume 2: Architectural Data and Models[END_REF] has shifted to a "data-centric" approach by building the DoDAF Meta-model (DM2), it places greater emphasis on architecture data as the necessary ingredient for architecture development. DM2 defines architectural data elements, their associations and attributes, thus providing a high-level view of the data normally collected, organized, and maintained in an architectural description effort. It is feasible to make research on new executable model synthetic methods which are architectural modeling methodology-independent, such as those done by [START_REF] Ge | A Data-Centric Capability-Focused Approach for System-of-Systems Architecture Modeling and Analysis[END_REF] and [START_REF] Zhang | Method of Architecture Executable Evaluation Based on DM2[END_REF].

But the executable models built by these new studies still lack system component information. System component information plays an important role on the verification of architectural behavior and performance, which are affected by architectural components and structure. The lack of system component information in the generated executable models will constrain their ability in evaluating more user concerns such as system structural fitness, measures of performance and measures of effectiveness of system, and etc.

In order to solve the issues mentioned above, we propose a component datafocused method to build the executable model for a DoDAF based architecture. It will build the executable model upon DM2, which is architectural modeling methodologyindependent. At the same time, component information will be extracted from the underlying data of architecture models and embodied in the generated executable model as a main part. As to the selection of executable modeling language, we select the Object Petri Nets based Description Language (OPDL) [START_REF] Luo | OPMSE: An Object Petri Nets based Modeling and Simulation Environment[END_REF], which was developed by our laboratory. OPDL is an extension of original Petri net. It offers an advantage of combining a well-defined mathematical foundation, the graphical representation and interactive simulation capabilities to check both the logical and functional correctness of a system and to make performance analysis. Many architectural elements, e.g. information, materiel, and data can be defined by different types of tokens in OPDL. These features make OPDL flexible and capable of modeling complex systems. Furthermore, OPDL is simple to use, whereas CPN is relatively more complicated.

The remainder of this paper is organized as follows. Section 2 gives a brief introduction of OPDL. Section 3 examines DM2 data elements which are related to component information for building executable model. In the meantime the mapping relations between DM2 and OPDL elements are established. Section 4 presents the steps for building OPDL based executable model.

OPDL

To implement object model in the original Petri net, an Object Petri Nets based Description Language (OPDL) is designed [START_REF] Luo | OPMSE: An Object Petri Nets based Modeling and Simulation Environment[END_REF]. OPDL extents Petri nets on two aspects. First, it introduces object-oriented methodology into Petri nets to form Object Petri Nets (OPN), where the object is the basic modeling unit and reusable module. Second, OPDL adds new model elements to original Petri net, such as switch, and attributions to all of the model elements.

Below is a simple explanation for the basic model elements of OPDL.

Class. An OPN class includes four parts, which are property table, OPN description, initialization function and post-instancing function. 1) Property table is a data space used by the object. Each item in the table is composed of a property name and a property value. A property value can be accessed via its name. 2) OPN description is an OPN graph. Different graphs connect together through their input ports and output ports. 3) Initialization function is used to initialize the object instance when it is created, such as setting the initial value of a property. 4) Post-instancing function will be executed after the object instance has been created. All the classes are stored in a class library. Modeler builds and organizes model based on the class library. Class quotation mechanism supports the reuse of model. Hence, modeling is the process of designing and using classes.

Object. An OPN object is an instance of some class. The attributions of an object can be modified by its instance function. There are two sorts of relations between two different objects, i.e. interactive relation and nesting relation. By interactive relation, two objects connect together via their input ports and output ports. By nesting relation, two objects form hierarchy model.

Place.

A place is a kind of data structure, which has a queue to buffer tokens. Each place corresponds to a color. Only those tokens which have the same color can enter into the place. The attributions of a place include rule of queue, token capacity and the event processing function. When a token enters or gets out the place, its event processing function will be invoked. OPDL also defines a special kind of place named port. A port has the same attributions as a place. Ports are divided into input ports and output ports. The successor of an output port should be an input port, and the predecessor of an input port should be an output port.

Transition. The attributions of a transition include priority, delay function, predicate function, action function, and event processing function. Priority is used to handle conflicts. Delay function is used to determine the process time of a transition. Predicate function is a condition which needs to be satisfied for a transition to be enabled. Action function is a sequence of operations that a transition will carry out after it fires. When a transition begins to fire, the event processing function will be executed.

Switch. A switch can be regarded as a special kind of transition. Unlike a common transition, it does not distribute any tokens automatically at the end of its firing, and it is up to the modeler to determine how to distribute the tokens to its successive places.

Arc. An Arc is used to connect the place and the transition just as the original Petri nets. Moreover, it is used to connect an input port and an output port.

Token. A token is defined as a structural data and corresponds to a color. A token has a property table. In the functions of a transition, the items of property table can be inserted and accessed.

To implement OPDL, we developed a software tool named OPMSE [START_REF] Luo | OPMSE: An Object Petri Nets based Modeling and Simulation Environment[END_REF], which is a kind of integrated modeling and simulation environment.

DM2 Data Elements Required for Building Executable Model

As mentioned above, the aim of our method is to create an executable model that can be used to verify system structural fitness, measures of performance and measures of effectiveness of system, and so on. Thereby, component information of the whole architecture which describes a system is required for building the executable model. The data elements in DM2 related to component information need to be examined. Then, the mapping relations between DM2 and OPDL elements need to be established to create OPDL based executable model.

DM2 Data Elements Related to System Component

The essence of DM2 is to answer the set of standard interrogatives, which are the set of questions, Who, What, When, Where, Why, and How [START_REF]DoD Architecture Framework version 2.0 Volume 1: Introduction, Overview, and Concepts[END_REF]. Accordingly, data elements in DM2 is divided into 12 categories of data groups, which are Performers, Resource Flows, Information and Data, Activities, Training/Skill/Education, Capability, Services, Projects, Goals, Rules, Measures, and Locations. We begin by finding the data element that is used to represent system component information. It is easy to determine that the Performers data group answers the Who question, and its System data element represents system component information. Then, the data element that represents system function information is Activity, which is in the Activities data group. A System may have several Activities. And also, a system function transforms input information into output information, which is represented by Information data element in the Information and Data group. A system may have several performance parameters, which are represented by Measure data element in the Measures data group. Thus, System, Activity, Information and Measure form the basic DM2 data elements related to system component, as shown in Fig. 1.

System Information Activity

Activity Information Information Information M ea su re Fig. 1. DM2 data elements related to system component Besides data elements, the associations between them need to be considered. We can find these associations which are activityPerformedByPerformer, activityResourceOverlap, wholePartType, and measureOfTypeResource. The activityPerformedByPerformer association represents that an Activity is performed by a System. The activityResourceOverlap association represents that a piece of Information is produced by an Activity and consumed by another Activity. The wholePartType association represents that a System is a part of another System. The measureOfTypeResource association represents that a Measure belongs to a System.

According to DM2, architecture data can be saved in XML format. The figures from Fig. 2 to Fig. 6 illustrate some architecture data segments related to system component information of a notional system.

-<System ideas:FoundationCategory="IndividualType" id="s2"> <ideas:Name exemplarText="System A" namingScheme="ns1" id="n89" /> </System> -<System ideas:FoundationCategory="IndividualType" id="s3"> <ideas:Name exemplarText="System B" namingScheme="ns1" id="n90" /> </System> -<System ideas:FoundationCategory="IndividualType" id="s4"> <ideas:Name exemplarText="System C" namingScheme="ns1" id="n91" /> </System> -<System ideas:FoundationCategory="IndividualType" id="s5"> <ideas:Name exemplarText="System D" namingScheme="ns1" id="n92" /> </System> Fig. 2. System segment of architecture data -<Activity ideas:FoundationCategory="IndividualType" id="a18"> <ideas:Name exemplarText="Act A" namingScheme="ns1" id="n74" /> </Activity> -<Activity ideas:FoundationCategory="IndividualType" id="a19"> <ideas:Name exemplarText="Act B" namingScheme="ns1" id="n75" /> </Activity> -<Activity ideas:FoundationCategory="IndividualType" id="a20"> <ideas:Name exemplarText="Act C" namingScheme="ns1" id="n76" /> </Activity> -<Activity ideas:FoundationCategory="IndividualType" id="a21"> <ideas:Name exemplarText="Act D" namingScheme="ns1" id="n77" /> </Activity> Fig. 3. Activity segment of architecture data -<Information ideas:FoundationCategory="IndividualType" id="di14"> <ideas:Name exemplarText="Info A" namingScheme="ns1" id="n84" /> </Information> -<Information ideas:FoundationCategory="IndividualType" id="di15"> <ideas:Name exemplarText="Info B" namingScheme="ns1" id="n85" /> </Information> -<Information ideas:FoundationCategory="IndividualType" id="di16"> <ideas:Name exemplarText="Info C" namingScheme="ns1" id="n86" /> </Information> -<Information ideas:FoundationCategory="IndividualType" id="di17"> <ideas:Name exemplarText="Info D" namingScheme="ns1" id="n87" /> </Information> Fig. 4. Information segment of architecture data <activityPerformedByPerformer ideas:FoundationCategory="TripleType" id="app19" place1Type="s2" place2Type="a18" place3Type="apuc17" /> <activityPerformedByPerformer ideas:FoundationCategory="TripleType" id="app20" place1Type="s2" place2Type="a19" place3Type="apuc18" /> <activityPerformedByPerformer ideas:FoundationCategory="TripleType" id="app21" place1Type="s3" place2Type="a20" place3Type="apuc19" /> <activityPerformedByPerformer ideas:FoundationCategory="TripleType" id="app22" place1Type="s3" place2Type="a21" place3Type="apuc20" /> Fig. 5. activityPerformedByPerformer segment of architecture data <activityResourceOverlap ideas:FoundationCategory="TripleType" id="aro14" place1Type="a18" place3Type="a20" place2Type="di14" /> <activityResourceOverlap ideas:FoundationCategory="TripleType" id="aro15" place1Type="a18" place3Type="a21" place2Type="di15" /> <activityResourceOverlap ideas:FoundationCategory="TripleType" id="aro16" place1Type="a19" place3Type="a22" place2Type="di16" /> <activityResourceOverlap ideas:FoundationCategory="TripleType" id="aro17" place1Type="a18" place3Type="a19" place2Type="di17" /> Fig. 6. activityResourceOverlap segment of architecture data

Mapping relations between DM2 and OPDL elements

After the analysis of DM2 data elements related to system component information, the mapping relations between DM2 and OPDL elements is established according to their features, which is shown in Table 1. Each System can be mapped to an object in OPDL. For those objects have the same properties and OPN graphs, a class can be defined. If a wholePartType association exists between two Systems, then a parent-child relation exists between their corresponding objects.

Each Activity can be mapped to a transition in OPDL. If an activityPerformedByPerformer association exists between an Activity and a System, it means that the corresponding transition is part of the corresponding class's OPN graph.

Each piece of Information can be mapped to a place, an input port, an output port, or a property of class in OPDL. If an activityResourceOverlap association exists between two Activities and a piece of Information, then two arcs are needed to connect between each corresponding transition and the corresponding place or port.

Each Measure can be mapped to a property of class. If a measureOfTypeResource association exists between a Measure and a System, it means that the corresponding property belongs to the corresponding class.

Process of Building Executable Model

A process to build executable model is shown in Fig. 7. Firstly, we extract part information from architecture data that is saved following DM2, including System, Activity, Information, Measure and their associations. Then convert into their OPDL counterparts according to above established mapping relations. Some OPN classes will be created at this step, which we call initial OPN classes. Secondly, depending on the simulation purposes of executable model, some edits on these initial OPN classes need to be done, such as adding new places and transitions in their OPN graphs, initializing properties of classes in their initialization functions and post-instancing functions, and defining the process time and operations of transitions in their delay functions and action functions respectively. All the OPN classes will be ready and organized in an OPN class library at this step. Lastly, we instantiate the top level OPN class in the library, which will also instantiate its descendent objects, and an executable model will be produced.

Fig. 7. A process to build executable model

The first step in above process can be subdivided into several sub steps as follows.

(1) Determination of OPN objects. For each System in architecture data, we define an object with the same name.

(2) Creation of OPN classes. For each object with particular features, a class is created. For those objects have similar features, we only create one class for them. Additionally, a top level class is always created in view of the modeling mechanism of OPDL. For composite classes determined by wholePartType association, their child objects are built into their OPN graphs.

(3) Creation of graph elements for OPN classes. Each activityResourceOverlap association involves three elements, i.e. an Activity which produces information, a piece of Information, and an Activity which consumes information. The System which performs activity to produce or consume information can be determined by activityPerformedByPerformer association. For each Activity that produces or consumes information, we create a transition in the class which is the counterpart of System that produce or consume information. For an activityResourceOverlap association, if it is the same System that produce and consume information, we create one place in the class; otherwise, we create an output port in one class and an input port in another class. Two arcs are built to connect two pairs of transitions and places respectively. Arcs connecting the ports of child objects of a composite class need to be created based on activityResourceOverlap association too.

(4) Creation of properties for OPN classes. Measures in measureOfTypeResource association and Information in activityResourceOverlap association can be used to define candidate properties for class.

According to above process, we can build an OPN class library based on the part architecture data shown in Fig. 2 to Fig. 6. The OPN graph of top level class in the library is shown in Fig. 8. Fig. 9 illustrates the OPN graph of class "System A". We can get an executable model by instantiating the top level OPN class in OPMSE.

Conclusion

This paper presents a component data-focused method to synthesize the executable model for an architecture that is described compliant with the DoDAF. It is modeling methodology-independent and is fit for the verification of architectural behavior and performance. Future research will involve adding additional data elements which are related to service, rule, and communication. This helps the transformation from architecture data into the executable model to enable more widely evaluation on user concerns. At the same time, a method to enable automatic executable model generation will also be studied.

Fig. 8 .

 8 Fig. 8. The OPN graph of top level class

Fig. 9 .

 9 Fig. 9. The OPN graph of class "System A"

Table 1 .

 1 Elements mapping between partial DM2 and OPDL

	DM2 data elements	OPDL model elements
	data elements	System	class, object
		Activity	transition
		Information	place (input port, output port) ,
			property of class
		Measure	property of class
	associations between	activityPerformedByPerformer transition of class's OPN graph
	data elements
		activityResourceOverlap	arcs
		wholePartType	constituent relation between
			two objects
		measureOfTypeResource	property of certain class

Acknowledgments. This research was supported in part by the State Scholarship Fund (No. 201206115006) from China Scholarship Council.


Lee Li
email: leeli@yorku.ca

What Do Partners Share in Strategic Alliances?

Keywords:

This study categorizes resources into firm-specific and general resource; costs into accounting and non-accounting cost; and risks into visible and invisible risks. Using data from 167 Canadian firms in technology industries, we find that sharing firm-specific resources and non-accounting costs are negatively correlated with environmental dynamism but sharing general resources, accounting costs and visible risks are positively correlated with environmental dynamism. Findings suggest that sharing certain resources, costs and risks do not necessarily incur high transaction costs.

Introduction

What do partners share in their strategic alliances? The mainstream management literature suggests that they share resources, costs and risks [START_REF] Borch | Resource configuration, competitive strategies, and corporate entrepreneurship: An empirical examination of small firms[END_REF]. However, the literature also acknowledges that such sharing increases transaction costs which are positively correlated with environmental dynamism [START_REF] Das | Strategic alliance constellations: A social exchange perspective[END_REF]. The costs include partner opportunism, coordination costs, equity hostage and dependence, etc. Empirical studies show that these costs, under certain conditions, can surpass benefits provided by strategic alliances and may even make partners' R&D and production activities unproductive. As such, an important question emerges as to why partners share resources, costs and risks even at such high transaction costs. A logical answer to the question would be the possibility that partners share different resources, costs and risks in diverse environments to minimize the transaction costs and maximize the sharing benefits. However, the existing studies do not differentiate between these resources, costs and risks and associate them with sharing costs and sharing environments.

This paper aims to make such contributions. It develops and tests the hypotheses that both the costs and the benefits of sharing depend, to a great extent, on categories of resources, costs and risks that partners share and the environments within which such sharing occurs. In a highly dynamic market, for example, the costs of sharing knowledge resources between technology-based partners may be much higher than the costs of sharing financial resources between the same partners. The partners can specify how they share the risks and costs when they share financial resources in the contract but they can hardly determine accurately the partner's opportunistic behavior in sharing the knowledge resources and the impacts of environmental dynamism on such sharing. This study will differentiate between these resources, costs and risks and clarify the relationships between the benefits and the cost of sharing against the background of environmental dynamism.

In this study, we define resources as assets that are tied semipermanently to a firm; costs as the sacrifice a firm makes to achieve a particular purpose; and risks as negative variance in performance beyond the control of decision makers. Accordingly, we classify resources, costs and risks, each into two categories: resources into firm-specific and general resources; costs into accounting costs and non-accounting costs; and risks into visible and invisible risks. Firm-specific resources are those unique to a particular firm while general resources are those available in the market. Accounting costs include operation costs, such as fixed and variable costs, which are specified in firms' income statements. Non-accounting costs are those costs unidentified in firms' income statements, including transaction costs and opportunity costs. Visible risks are the possibilities predicted and specified in the partnership contracts while invisible risks are those unspecified in the contracts.

Evidence collected in this study shows that partners share firm-specific resources and non-accounting costs in a relatively stable environment. In contrast, they share general resources, accounting costs and visible risks when environments grow highly dynamic. The findings of this study make significant contributions to the existing literature on two fronts. First, it clarifies the fact that the benefits and the costs of sharing resources, costs and risks between partners depend on the types of resources, costs and risks they share and the environments within which the sharing occurs. Second, it explains why firms use strategic alliances even when sharing resources, costs and risks may lead to high transaction costs.

2

Hypotheses development

Firm-specific and general resources

Research-based view (RBV) suggests that firms' ability to sustain their competitive advantage is based on their firm-specific resources which are not easily tradable or redeployable outside the firm and thus are difficult for competitors to imitate [START_REF] Glover | International strategic alliances, joint Ventures & strategic alliances[END_REF]. Firm-specific resources include property based resources and knowledge-based resources. Property-based resources are protected by property rights while knowledge-based are protected by knowledge barriers which are subtle, hard-tounderstand, or built on accumulation of experiences and knowledge, and continuous financial and human investments [START_REF] Goerzen | Alliance networks and firm performance: The impact of repeated international strategic alliances[END_REF]. Partners may share property-based and knowledge-based resources through licensing/franchising, joint ventures or R&D consortia. In other words, partners give up, to varying degrees, the property rights or knowledge barriers in partnership cooperation. Therefore, the firms who own the property-based and knowledgebased resources have to use partnership contracts to safeguard the value of these resources in order to maximize its economic rents from alliances and sustain the value of these resources. Environmental dynamism makes such safeguards difficult because, with the ambiguity associated with the environmental dynamism, partners can hardly specify each partner's responsibilities and obligations in the contracts [START_REF] Gulati | Unilateral commitments and the importance of process in alliances[END_REF]. Monitoring partners' behavior is difficult in a highly dynamic environment. Moreover, sharing property-based and knowledge-based resources is a firm-specific investment and such investments have, by definition, limited economic value in alternative settings. If the alliance agreements are terminated unexpectedly due to the environmental changes, firms can hardly recoup their initial investments.

General resources are different from firm-specific ones in that general resources are subject to ready imitation by other firms. Capital, land and unskilled labor are examples of general resources. Environmental dynamism provides a flow of opportunities that typically is fast, complex, ambiguous, and unpredictable [START_REF] Lecocq | Strategizing industry structure: The case of open systems in a low-tech industry[END_REF]. Firms may not have sufficient general resources under their direct control to exploit these opportunities. Direct control over abundant general resources results in inflexibility which makes firms inefficient to manage the complexities and ambiguity. Strategic alliances enable these firms to get access to external general resources. Through joint venture in foreign countries, for example, partners can have access to local production infrastructure and low-cost labor. Sharing general resources rather than owning general resources provides important strategic benefits, such as loose coupling, ambidexterity and improvisation, which increase firms' learning speed and responsiveness to manage environmental dynamism More importantly, sharing general resources reduces investment risks. As such, firms tend to get access to these resources through strategic alliances when they experience high environmental dynamism. Accordingly, we predict that: Hypothesis 1a: The higher the environmental dynamism, the more general resources partners will share.

Hypothesis 1b: The higher the environmental dynamism, the fewer firm-specific resources partners will share.

Accounting costs and non-accounting costs

Environmental dynamism raises firms' accounting costs because the dynamism leads to both opportunities and threats, and managing increased opportunities and threats incurs accounting costs. Partners may not have sufficient financial resources to cover the costs on their own. More importantly, unexpected accounting costs may increase substantially in dynamic environments due to the high unpredictability and velocity and sourcing from partners is an effective way to manage such sharp cost fluctuations. Sourcing cash from partners, for example, is a frequently used option for firms in high-tech industries. Because accounting costs are specified in numbers, both parties' responsibilities and obligations in sharing these costs can be relatively precisely defined in partnership contracts. In other words, transaction costs for such sharing is minimal.

Non-accounting costs include transaction costs and opportunity costs. Nonaccounting costs are mutual between partners. Both partners share such costs when they form strategic alliances. Existing studies have shown that both parties may earn private benefits unilaterally from the alliance [START_REF] Ireland | The management of strategy: Concepts and cases[END_REF]. Such private benefits vary from cheating to learning by observation without other party's permission. Consequently, both partners have to monitor each other's behavior to reduce the possibilities of opportunism because both partners invest in the alliances and they have to protect such partner-specific investments.

High levels of environmental dynamism not only increase non-accounting costs but also make the non-accounting cost forecasting inaccurate. Dynamism creates the causal ambiguity which blurs the links between non-accounting costs and the effectiveness to reduce transaction costs and opportunity costs, and many contingencies will distort cost estimates [START_REF] Dess | Dimensions of organizational task environments[END_REF]. Because accurate cost forecasting is difficult to achieve, partners have to identify and correct their forecasting problems by frequently re-estimating and reallocating costs between them. Such frequent reestimation and reallocation not only make existing partnership agreements nonbinding, but also create enormous uncertainties for the future of these agreements. Accordingly, we predict that: Hypothesis 2a: The higher the environmental dynamism, the more accounting costs partners will share.

Hypothesis 2b: The higher the environmental dynamism, the less non-accounting costs partners will share.

Visible and invisible risks

Visible risks are the possibilities that a hazard may occur in a decision-maker's perception. In other words, they can be defined and specified in partnership contracts [START_REF] Qian | Profitability of small-and medium-sized enterprises in high-tech industries: The case of the biotechnology industry[END_REF]. When partners jointly develop a new product, for example, they may predict the possible failure of the new product. Invisible risks are unforeseeable risks. For example, the sudden death or resignation of a firm's CEO may cause sharp fluctuations in the firm's stock value. Because of such unforeseeablity and unexpectedness, invisible risks can hardly be specified and each party's responsibility and obligations in sharing these invisible risks can hardly be clearly determined in the partnership contracts. Environmental dynamism increases both visible and invisible risks. However, its impacts on these risks are different. Environmental dynamism enhances partners' desire to share the visible risks because the dynamism increases the risks and the costs to cover the risks [START_REF] Lu | The internationalization and performance of SMEs[END_REF]. Firms may not have sufficient resources, such as cash, to manage these risks on their own [START_REF] Amburgey | Resetting the clock: The dynamics of organizational change and failure[END_REF]. More importantly, the responsibilities and obligations to share risks between partners can be specified in partnership contracts so the possibilities of partner opportunism are minimal [START_REF] Hannan | Structural inertia and organizational change[END_REF].

Because the invisible risks are unforeseeable, the responsibilities and obligations in sharing invisible risks are mainly based on partners' mutual trusts [START_REF] Baum | Don't go it alone: alliance network composition and startup's performance in Canadian biotechnology[END_REF]. However, existing studies have shown that such trusts are negatively correlated with environmental dynamism. Generally, firms share invisible risks only when they are confident that the risk-adjusted returns of a joint project will be positive [START_REF] Luo | Are joint venture international strategic alliances more opportunistic in more volatile environment[END_REF]. High levels of environmental dynamism may reduce or even damage the confidence because risk forecasting and measurements become highly inaccurate, if not impossible, in such environments. Accordingly, we predict that: Hypothesis 3a: The higher the environmental dynamism, the more visible risks partners will share.

Hypothesis 3b: The higher the environmental dynamism, the less invisible risks partners will share.

Method

Setting, Sample, and Data

This study used data of Canadian technology firms to test the hypotheses. Two waves of questionnaires were mailed to the CEOs or the highest-ranking officers of the target firms. All questions in the questionnaires were presented as a seven-point Likert-type scale (ranging from 1 = strongly disagree to 7 = strongly agree).

Main variables

Firm-specific resources consist of five measurement items: ( We used a composite index of four items to measure sharing of each abovementioned category between partners. These four items include necessity, magnitude, duration, and possible impacts of sharing. Measurement of environmental dynamism (EV) was based on the items developed by Boyd and associates (1993) and Zahra and associates (1997), and there were seven such items that compose the construct (see Appendix 1). Both linear and squared terms of the variable (EV and EV 2 ) were used to denote low and high levels of environmental changes. All data will be provided upon request.

Discussion and Conclusions

The evidence collected in this study indicates that sharing firm-specific resources and non-accounting costs is feasible at low level of environmental dynamism. In other words, a low level of environmental dynamism does not impede such sharing. When environmental dynamism grows high, however, sharing firm-specific resources and non-accounting costs becomes unlikely. In contrast, partners share general resources, accounting costs and visible risks in a highly dynamic environment. It should be noted that sharing invisible risks between partners may not be affected by the levels of environmental dynamism. Two possible interpretations emerge from this study. Frist, invisible risks increase substantially when environments grow dynamic. As such, partners have to share more invisible risks if they want to keep their partnerships. Second, it is difficult for managers to define invisible risks regardless of the level of environmental dynamism and they cannot negotiate and specify such risks in the partnership contracts. Consequently, they do not have a clear idea of how to deal with such risks. Perhaps both causes co-exist and they work in combination. The findings of this study have important theoretical implications. First, partners share more general resources, accounting costs and visible risks when environments grow dynamic. As such, sharing general resources, accounting costs and visible risks may not necessarily increase transaction costs and increased environmental dynamism enhances the needs for partners to share general resources, accounting costs and visible risks. The evidence explains why firms use strategic alliances in highly dynamic environments. Transaction costs are associated not only with environmental dynamism but also with the nature of the resources, costs and risks that partners share. Second, sharing firm-specific resources and non-accounting costs between partners decreases with environmental dynamism. The evidence confirms the traditional belief that sharing firm-specific resources incurs transaction costs in dynamic environments. Moreover, such sharing may also increase opportunity costs which have been ignored in the mainstream literature. Both transaction costs and opportunity costs vary positively with environmental dynamism and both of them are sacrifice partners make in their partnerships. Transaction costs have been widely discussed in the existing literature but opportunity costs do not receive a similar attention. Finally, in contrast to the existing literature, partners are willing to share more visible risks when environments are dynamic. Even their sharing of invisible risks may not necessarily decrease in highly dynamic environments. In other words, the traditional belief that environmental dynamism is negatively correlated with partners' wishes to share risks may not be true.


Zoltan Horvath

Hanna Horvath

More Sensors or Better Algorithm?

Keywords: GPS, L1 regression analysis, Kalman Filter, GLONASS

For the development of a successful indoor navigation system it is essential to know the nature of signals broadcasted by different access points and other signal broadcasting/transmitting equipments, since we can't rely on the help of navigation satellites inside buildings. However we need to use the original signal in each case for accurate positioning, so we have to be able to filter out the interfering signals with the help of different algorithms.

Introduction

We examined the precision and inaccuracy of GPS sensors built in different smartphones in a previous research of ours [START_REF] Horvath | The Measurement Preciseness of the GPS Built in Smartphones and Tablets[END_REF]. From the experiment it turned out, that the data provided by the devices are quite inaccurate. The primary cause of this is attributable to the scattered signal, which stems from the device not always seeing the original "clear" signal broadcasted by the navigation satellites. This is why the spread of GLONASS system is of great importance, as smartphones using GLONASS provide more precise data for the users. On the one hand the device uses two independent navigation system here, also GLONASS has ground reference stations where the device gets further clarification. Nevertheless it does not always mean a solution. This is why the usage of different "signal-cleaner" algorithms is necessary, because these algorithms are able to filter out scattered, disturbing signals from the originals. Thereby the measurement becomes much more accurate. Filtering out the scattered signals and those which come from the interference is also essential, because when using indoor navigation, the ratio of scattered signals increases significantly compared to the original.

2

Material and Method

Devices

In our research we used the next smart phones and a tablet. These were the following: HTC HD (Windows mobile 6), HTC 8x (Windows mobile 8), Sonny Xperia J (Google Android OS v4,0), iPhone 4 ( iOs 4), iPad2 (iOs 6), Nokia Lumia 1520. By choosing these devices, we can try out most of the used operation systems of our times'. In addition, the HTC 8X device applies GLONASS support in order to allocate our location. This support is available up from the series of iPhone 4S.

GLONASS

Before the research, we required the HTC 8X to be the most precise since this device has GLONASS support besides GPS [7]. This means that the traditional GPS system is expanded with the data of the satellites developed by Russians, therefore it makes it more precise to the users. Presently there are 51 reference stations in Hungary. Pecs is a good location in this network because there are three stations near at hand. These are Siklos (20km from Pecs), Barcs (50km from Pecs) and Kaposvar (50km from Pecs). Structure of GPS signal All signal components are derived from the output of a highly stable atomic clock. In the operational (Block II/IIA) GPS system each satellite is equipped with two caesium and two rubidium atomic clocks. The clocks generate a pure sine wave at a frequency f0 = 10.23MHz, with a stability of the order of 1 part in 1013 over one day. This is referred to as the fundamental frequency.

Multiplying the fundamental frequency f0 by integer factors yields the two microwave L-band carrier waves L1 and L2 respectively (above two figures). The frequency of the two waves is obtained as follows: fL1 = f0 x 154 = 1575.42MHz (1) equivalent wavelength: 𝜆 L1 = c / fL1≈19cm fL2 = f0 x 120 = 1227.60MHz

(2) equivalent wavelength:𝜆 L2 = c / fL2 24cm These are right-hand circularly polarised radio frequency waves capable of transmission through the atmosphere over great distances, but they contain no information. All satellites broadcast the same frequencies (though the received frequencies are slightly different because of the Doppler shift).

Clear GPS Signal

We performed measurements on planes during flight, when the aircrafts reached the altitude. During the measurements we experienced that certain mobiles were unable to detect GPS signal. The mensuration was necessary, because we couldn't get closer to the satellites broadcasting navigation signals than the aforementioned altitude, furthermore no artificial object could interfere with the signals. This way we can work with relatively clean signals, free of scattered signals. Since at flight altitude we can't designate a fixed length area, every measurement lasted for exactly 10 minutes. The results can be seen in the following figure.

L1 regression analysis

We investigate our results first time with L1 regression. Consider the linear regression model (1):

(3) Where are unknown parameters and { are unobservable independent, identically distributed random variables each with median 0. For simplicity, we will assume that the 's are non-random although the results will typically hold for random 's. We will consider the asymptotic behavior of L1-estimators of ( ); that is ⏞ ⏞ ⏞ minimize the objective function (2) ( ) This minimization problem can be solved using standard Linear Programming techniques. L1 Linear regression assumes that an intercept term is to be included and takes two parameters: the independent variables (a matrix whose columns represent the independent variables) and the dependent variable (in a column vector). L-1 regression is less affected by large errors than least squares regression [START_REF] Fisher | Statistical analysis of circular data[END_REF]. Reflectanced GPS signal filtering with Kalman filter

( ) ∑ (

Kalman filter

We can filter the reflectanced GPS signal with Kalman filter because we can monitor the GPS. If we know which particular signal our smartphone is using then we know what this satellite frequency is. After this, we can use the Kalman filter where we give the original frequency (this will the right data) and we say that the other results are the errors [START_REF] Yang | Handling Nonlinearity in an Ensemble Kalman Filter: Experiments with the Three-Variable Lorenz Model[END_REF]. It is instructive first to review the analysis step in the standard Kalman filter where the analyzed estimate is determined by a linear combination of the vector of measurements d and the forecasted model state vector ψ f [START_REF] Jung | Ensemble Kalman Filter Analyses of the 29-30 May 2004 Oklahoma Tornadic Thunderstorm Using One-and Two-Moment Bulk Microphysics Schemes, with Verification against Polarimetric Radar Data[END_REF]. The linear combination is chosen to minimize the variance in the analyzed estimate ψ a , which is then given by the equation

( ) (6)
The Kalman gain matrix K is given by

( ) (7)
The error covariance of the analyzed model state vector is reduced with respect to the error covariance of the forecasted state as

( )( ) T ( ( ) ( )( )( ) T ( )T ( )( ) T ( ) ( ) ( ) ( ) (8)
The analyzed model state is the best linear unbiased estimate [START_REF] Burgers | Analysis Scheme in the Ensemble Kalman Filter[END_REF]. This means that ψa is the linear combination of ψf and d that minimizes ( )( ), if model errors and observations errors are unibased and are not correlated [START_REF] Cheng | Right-invariant metrics applied to rank correlation coefficients[END_REF].

Results

During our research we examined how much some algorithm can refine the results of the measurements compared to the raw data. In fig. 3 we can see how the result changes if we clean the data measured at high altitude with the help of the algorithms. ), the data collected by these the devices has only a digression of a couple of centimetres. To sum up, we can say that if we measure one point in an open area, where the zenith is 92% visible; there is no significant difference between the two operation systems.

Fig. 1. Average distance (Ground altitude) without Kalman filter

When we started our research we were in an opinion that the most homogeneous data will be collected by the device which applies GLONASS support as well. As it can be seen in Fig. 4, the WP8 device was the one which made this result. From the second place, we did not experience big difference. That is to say, there is no significant difference between the results achieved by the devices which only use GPS. On the other hand, the HTC 8X (WP8) is the absolute number one with big difference. As we can see, there are two results for the iPad: results from Sports Tracker as well as Outdoor Navigation. The difference is evident and interesting as a single device produced two different results during the same time interval. It is extremely important to point out that the measurement circumstances were exactly the same! Will similar devices using different applications bring similar results or will the same problem not be there in such a case. And most importantly: can this problem be solved using different algorithms? We will examine this in the frame of another project.

What is then if we can filter the satellite signal at the measurement? Because the smart phones can use small mobile apps where this application can recording all signal. After we can analysed this results and we can separate the signal and the reflectance signal, we can see the results between the original data and the filtered data on the next figures (fig. 5.).

Fig. 5. Modify distance with Kalman Filter, Glonass and without Glonass

We can see in these figures that the different is huge. In the first situation, where we used the GPS+Glonass than was the deviation 22.36 and the average distance 352.19m until then when we used the filter the deviation was 1.47 and the average distance was 371.65 meter. If our smartphone use just the basic GPS system then the deviation is 14.35 and the average distance was 378 meter. As shown in fig. 6, we can see how the values of average distance change if we clean the original raw data with the algorithms. In this case we can provide comparatively accurate (few meters difference) data also with smartphones with not so good sensors.

Conclusion

In our measurements, we have proved that the sensor itself does not provide enough accurate information in terms of navigation. To access the precise information we need different algorithms. Thus, a full-whipped cheaper smart can be achieved in a more accurate geolokalizációt. The indoor navigation also it will be the most important thing is that the original signal can be filtered out of the scattered signals.

Since most of the signals (according to preliminary measurements) seem close to 74% of the scattered or reflected signal. This greatly reduces the accurate position determination. At indoor navigation is not enough to precision some thirty feet. After filtration of the signal device with GPS with the smooth result of the device and result in GLONASS + GPS, the average was 8.68% of the difference. We can see in fig 7. The measurements are all available today, operating systems performed. As a reference, and the higher layers of the airspace (flight altitude) measurements were performed in order to eliminate inaccuracies caused by stray signals.

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Fig. 1 .

 1 Fig. 1. Clear GPS Signal

Fig. 3 .

 3 Fig. 3. Average distance (Transition altitude) with and without algorithmBefore the purification of the original signals we expected not to have significant difference, for at flight altitude the devices detects the original signal. It is not distorted so much by atmospheric phenomena, natural and artificial objects. The analyzed values confirms this, as we can see it. Perhaps the data measured by iPad 2 is the only exception. As we can see in the graph (fig.4.), the data collected by these the devices has only a digression of a couple of centimetres. To sum up, we can say that if we measure one point in an open area, where the zenith is 92% visible; there is no significant difference between the two operation systems.

Fig. 6 .

 6 Fig. 6. Average distances with and without algorithm

Fig. 7 .

 7 Fig. 7. Differences between the original signals and the filtered signals

Acknowledge

Supported by the SROP-4.2.2.C-11/1/KONV-2012-0005 grant.