Nungki Selviandro
email: nungki.selviandro@ui.ac.id

Zainal A Hasibuan
email: zhasibua@cs.ui.ac.id

Cloud-Based E-Learning : A Proposed Model and Benefits by Using E-Learning Based on Cloud Computing for Educational Institution

Keywords: E-Learning, Cloud Computing, Cloud-Based E-Learning

The increasing research in the areas of information technology have a positive impact in the world of education. The implementation of e-learning is one of contribution from information technology to the world of education. The implementation of e-learning has been implemented by several educational institutions in Indonesia. E-Learning provides many benefits such as flexibility, diversity, measurement, and so on. The current e-learning applications required large investments in infrastructure systems regardless of commercial or open source e-learning application. If the institution tended to use open source e-learning application it would need more cost to hire professional staff to maintain and upgrade the e-learning application. It can be challenging to implement e-learning in educational institutions. Another problem that can arise in the use of e-laerning trend today is more likely to institution building their own e-learning system itself. If two or more institutions are willing to build and use an e-learning so they can minimize the expenditure to develop the system and share learning materials more likely happened. This paper discuss the current state and challenges in e-learning and then explained the basic concept and previous proposed architectures of cloud computing. In this paper authors also proposed a model of cloud-based e-learning that consists of five layer, namely : (1) infrastructure layer; (2) platform layer; (3) application layer; (4) access layer; and (5) user layer. In addition to this paper we also illustrated the shift paradigm from conventional e-learning to cloud-based elearning and described the expected benefits by using cloud-based e-learning.

Introduction

Nowadays e-learning widely use by educational institutions for supporting their learning process and provide anytime service for learners to access learning material and information. The implementation of e-learning has been implemented by several educational institutions in Indonesia. E-Learning provides many benefits such as flexibili-ty, diversity, measurement, and others [START_REF] Masud | An E-learning System Architecture based on Cloud Computing[END_REF], even though its implementation still exist many difficulties. The main problem experienced when to start applying e-learning is the high initial cost or in other words is the economic factor [START_REF] Chuang | The Cost Effective Structure For Designing Hybrid Cloud Based Enterprise E-Learning Platform[END_REF]. It is becoming a major focus for the institutions that will implementing e-learning. Institutions are categorized as low budget certainly be very difficult to implement e-learning, even if the institution has an adequate budget also expects a minimal budget that can be spent to implement e-learning. The inadequate infrastructure becomes a major problem in the implementation of e-learning. Institutions that want to implement e-learning difficulties in the procurement of server/PC, storage, and network [START_REF] Dong | An E-learning Ecosystem Based on Cloud Computing Infrastructure[END_REF]. Besides provide infrastructure The next issue is human resources, not all of the institutions have the professional staff for designing, developing systems to manage e-learning, in addition to the growing applying of e-learning as well is required expert in designing teaching materials commonly known as the instructional designer. It is also a consideration in the implementation of e-learning for each institution to implement it. Because institutions will also estimate the cost to employ them in order to provide specifically for elearning systems.

Along with the development of the IT world, cloud computing is gradually become the new paradigm of innovation in the IT world, cloud computing is a computing services that can be used through the Internet in accordance with the needs of users with little interaction between service providers and users. Cloud computing technology as well described as a computing resource that provides a highly scalable as external services through the Internet. Therefore, cloud computing can be considered as an alternative to minimize the cost of infrastructure and human resources for development and maintenance process of e-learning systems [START_REF] Chandran | Hybrid E-Learning Platform Based On Cloud Architecture Model : A Proposal[END_REF].

In this paper the author will discuss the current state and challenges of e-learning as well as basic concepts of cloud cover and the implementation of the service model, and the author will discuss some of the architecture of cloud-based e-learning that has been proposed by previous researchers. In addition the author will introduce the model proposed in the implementation of e-learning in the cloud environment as an alternative to conventional e-learning implementations are widely used in educational institutions today. The author will also explain the expected benefit by adopting the model of cloud-based e-learning.

E-Learning : Current State and Challenges

E-Learning is an internet-based learning process which aims to support conventional learning process that using internet technology and will not replace traditional education method [START_REF] Masud | An E-learning System Architecture based on Cloud Computing[END_REF]. Usually, e-learning systems are based on client-server architecure and web-based technology [START_REF] Grewal | The E-Learning Lifecycle and its Services: The Web Services Approach[END_REF]. This architecture has some limitation so that e-learning can not be used to its full potential, because has some limitation such as lack of interoperability and accessibility. Based on previous study, in order to solve interoperability issue, the use of web services has been implemented by several previous researchers as practiced by [START_REF] Grewal | The E-Learning Lifecycle and its Services: The Web Services Approach[END_REF], [START_REF] Pankratius | Retrieving Content With Agents In Web Service e-Learning Systems[END_REF], [START_REF] Xu | A Web Services Oriented Framework for Dynamic E-Leaming Systems[END_REF]. The using of web service has successfully answered the issue of interoperability from e-learning with focusing on selecting and combining the learning objects [START_REF] Phankokkruad | Implement of Cloud Computing For E-Learning System[END_REF].

With the development of mobile technology make e-learning is increasingly being used. The use of mobile technology in the implementation of e-learning is commonly known as mobile learning. There are many definitions of mobile learning, one of which is mobile learning defined by Lan & Sie (2010) as a learning model that enables participants to achieve the teaching learning materials anywhere and anytime using mobile technology and the internet. This definition may mean that mobile learning could include mobile phones, smartphones, personal digital assistants (PDAs) and their peripherals. Using mobile learning can help address the issue of accessibility in accessing the e-learning system.

Nowadays the use of e-learning applications can be based on commercial products or from open source. The advantage of using commercial products are the implementation time is quick due to technical support from the vendor and there will be ongoing maintenance cost. The disadvantage of using commercial e-learning applications are the initial cost of procuring commercial e-learning software is very high and there will the cost of insfrastructure [START_REF] Chandran | Hybrid E-Learning Platform Based On Cloud Architecture Model : A Proposal[END_REF]. Open source e-learning applications widely used in university. The initial cost of e-learning software is very low, but there still need expensive investment for the infrastructure and need more cost to hire professional staff for maintaining and upgrading the e-learning applications.

Based on the above phenomenon, the current e-learning applications required large investments in infrastructure systems regardless of commercial or open source. If the institution tended to use open source e-learning application it would need more cost to hire professional staff to maintain and enhance the e-learning application. It can be challenging to implement e-learning in educational institutions. Another problem that can arise in the use of e-laerning trend today is more likely to institution building their own e-learning system itself. If two or more institutions are willing to build and use an e-learning so they can minimize the expenditure to develop the system and share learning materials more likely happened.

Cloud Computing

Cloud Computing is a new paradigm to organize and manage ICT resources. There are various definitions of cloud computing, one of which is the definition according to The National Institute of Standards and Technology (NIST) which defines cloud computing as "model for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction" [22]. Generally speaking, the cloud computing service model consists of three layers [START_REF] Phankokkruad | Implement of Cloud Computing For E-Learning System[END_REF], among others: (1) Software as a Service (SaaS); (2) Platform as a service (PaaS); (3) Infrastructure as a service (IaaS) [START_REF] Yan | Infrastucture Management Of Hybrid Cloud For Enterprise Users[END_REF]. In practice, cloud computing has four implementation models where each model has certain characteristics [START_REF] Ghazizadeh | Cloud Computing Benefits And Architecture In E-Learning[END_REF], among others: (1) Private, the model is aimed at an organization where cloud operations are managed by a third party or the organization itself;

(2) Public, service on this model is intended for the general public or the industry in which the various services provided by the cloud computing service provider organization (3) Community, this model is managed by several organizations that form a community of practice in which the operations are managed by the community with the division of tasks particular; (4) Hybrid, this model is a combination of various models existing cloud distribution. Typically, this is done with a combination of specific purposes where there is an attachment for example: technological standards and data ownership.

The implementation of cloud computing is growing due to have advantages such as that illustrated in Figure 1, it can be seen that the efficiency cost is a major indicator of the advantages possessed by Cloud Computing. Cost efficiency can be realized due to several components such as the cost of financing the purchase of infrastructure and application development and operational expenses (management fees and maintenance) can be reduced. Cloud Computing on the implementation can be categorized two types, namely free service or pay per use (pay-as-you-go services) [START_REF] Jones | Cloud computing and storage with OpenStack : Discover the benefits of using the open source OpenStack IaaS cloud platform[END_REF], users will only be charged when using services from providers the service.

Cloud-Based E-Learning Architecture

In this chapter will discussed about the previous cloud-based architecture that developed by former researcher in this area and also the proposed cloud-based e-learning archictecture from this paper. In addition for this chapter also will be discussed the contribution from the proposed architecture. Phankokkruad ( 2012) proposed e-learning architecture based on cloud computing consists of three layers: (1) infrastructure layer, (2) platform (middle) layer, and, (3) application layer. Infrastructure layer is a hardware layer that supplies the computing and storage capacity for the higher level and this layer, which is used as e-learning and software virtualization tehcnologies, ensures the stability and reliability of the infrastructure. The second layer is Platform layer, this layer is a middle layer consisting middleware that is Web service. It is used for providing the learning resources as a service. This layer consists of two modules: item classification module (ICM) and course selection module (CSM). They are used for accessing the items from the item bank and selecting suitable learning content from the content database. The third layer is Application layer which is responsible for interface provision for the students. The first layer is infrastructure layer. It is employed as the e-learning resource pool that consists of hardware and software virtualization technologies to ensure the stablility and reliability of the infrastructure. This layer also supplies the computing and storage capacity for the higher level. The second layer is middleware layer. It focuses in providing a sharable platform consisting of two modules: CNRI's (Corporation for National Research Initiatives) Handler System Module and Metadata Transformation System Module. The final layer is application layer. At this layer, cloud computing provides convenient access to the e-learning resources.

The next architecture proposed by Masud & Huang (2012) consists of five layers. The First layer is infrastructure layer. It is composed of information infrastructure and teaching resources. Information infrastructure contains internet/intranet, system software, information management system and some common hardware. Teaching resources stored up mainly in traditional teaching model and distributed in different departments and domain. The second layer is software resource layer. This layer is composed by operating system and middleware. A variety of software resources are integrated through middleware technology to provide a unified interface for software developers to develop applications and embed them in the cloud. The third layer is resource management layer. In order to effectuate on demand free flow and distribution of software over various hardware resources, this layer utilizes integration of virtualization and cloud computing scheduling strategy. The fourth layer is service layer. This layer has three levels of services namely, SaaS, PaaS, and IaaS. In SaaS, cloud computing service is provided to customers, contrasting to traditional software, cloud customers use software via the internet without any need to purchase, maintain, and upgrade. They simply to pay a monthly fee. The last layer is application layer. This layer is a specific layer consisting of applications of integrated teaching resources, including interactive courses and the teaching resources sharing. The teaching resources include teaching material, teaching information, as well as the full sharing human resources.

Proposed Cloud-Based E-Learning Architecture

In this paper we propose the architecture that we have designed by modifying previous architectures that we used as references. Our proposed architecture consists of five layers (as shown in Figure 5), namely : (1) infrastructure layer; (2) platform layer;

(3) application layer; (4) access layer; and (5) user layer.

First layer is infrastructure layer. This layer contains architecture supporting infrastructure, such as: Cloud platform, virtual machine, virtual repositories and physical infrastructure such as servers, network devices, storage, buildings and other physical facilities. The infrastrucuter layer shares IT infrstructure resources and connects the system huge system pool together to provide services. Cloud computing enable the hardware layer to run more like the internet, to make the hardware resources shared and accessed the data resources in secure and scalable way. The second layer is platform layer. In this layer running the operating system where e-learning application will be running. Besides the operating system, this layer also consists of variety of software that support the application layer so that it can run properly. The third layer is application layer. This layer is a specific e-learning application that is utilized for sharing learning resources and interaction among users that includes synchronous or asynchronous discussion and chatting. We added the access layer in our architecture. This access layer is the fourth layer in our proposed architecture. This layer is in charge of managing access to cloud e-learning services which is available on the architecture such as: types of access devices and presentation models. This study adopts the concept of multi-channel access which enables a variety of available services that accessible through a variety of devices (such as mobile phones, smartphones, computer, etc.) and a variety of presentation models (such as mobile applications, desktop applications, and others) [START_REF] Mell | The NIST Definition of Cloud Computing[END_REF]. The purpose of the adoption of this concept is to increase the availability of devices that access the cloud service e-learning can be found in the architecture used untrammeled access devices. Besides the addition of the access layer, the architecture we propose the user layer consists of various educational institutions.

Fig. 2. Proposed Cloud E-Learning Architecture Conventional E-Learning Towards Cloud-Based E-Learning

Based on [START_REF] Carroll | Secure Cloud Computing Benefits, Risks and Controls[END_REF] which is also illustrated in Figure 1, the main advantages of the adoption of cloud computing is efficient in terms of cost, this is an interesting point of view that can be adapted to develop e-learning based on cloud computing. Conventional elearning commonly used by the university developed by the university itself (shown in Figure 6) tend to cause lots of problems such as time to designing e-learning systems will be developed, costs for infrastructure, selecting commercial or open source e-learning platform , the cost to hire professional staff to maintain and upgrade the system of e-learning, and so on. This process is more likely need more time.

By introducing cloud computing adopted by e-learning, as shown in Figure 6, institutions can use a single e-learning based on the cloud provided by a cloud provider of elearning. This model can reduce the initial costs incurred by the institution for the implementation of e-learning by using cloud computing services, because institutions do not need to pay for the purchase of infrastructure, both in terms of procurement of servers and storage. With cloud computing, as an institution of the client can rent the infrastructure to cloud computing service providers [START_REF] Ghazizadeh | Cloud Computing Benefits And Architecture In E-Learning[END_REF]. Likewise with the human resources for the development stage, the cloud environment of e-learning has been provided by the cloud service provider, as well as maintenance of the e-learning [START_REF] Pocatilu | Cloud Computing Benefits for E-learning Solutions[END_REF]. The paradigm shift in the implementation of e-learning is an innovation that can help any institution in implementing e-learning. In general, the implementation conventional e-learning, e-learning web-based design, system development and maintenance as well as by internal governance institutions [START_REF] Méndez | Implementing Motivational Features in Reactive Blended Learning: Application to an Introductory Control Engineering Course[END_REF]. It had a lot of problems, both in terms of flexibility, scalability, and accessibility [START_REF] Phankokkruad | Implement of Cloud Computing For E-Learning System[END_REF] [7] [START_REF] Masud | An E-learning System Architecture based on Cloud Computing[END_REF]. According to [START_REF] Jones | Cloud computing and storage with OpenStack : Discover the benefits of using the open source OpenStack IaaS cloud platform[END_REF] are discussed in [START_REF] Dong | An E-learning Ecosystem Based on Cloud Computing Infrastructure[END_REF], one of the main important features that can be presented in the use of e-learning in the cloud is scalability, which allows virtualization provide infrastructure layer provided by the cloud service provider. Virtualization helps solve the problem of the physical barriers that are generally inherent in the lack of resources and infrastructure to automate the management of these resources as if they were a single entity through hypervisor technologies such as virtual machine (VM).

Expected Benefits

The expected advantages by adopting the cloud-based e-learning model are as follows :

(1) Large capacity, this criteria could adress on-demand self service characteristic from could computing. Large scale storage in cloud environments provide advantages to the consumer to determine the storage capacity they intend to use that are adjusted to their needs and capabilities of the institution as a consumer of cloud-based elearning; (2) Short implementation process, by using cloud-based e-learning services, educational instition could minimize their expenditure to develop the e-learning system and shorten the implementation process because the e-learning system already developed and maintained by the cloud e-learning provider; (3) High Availability, by utilizing large storage and high performance computing power, cloud e-learning could provide a high quality of service. This may happened because of the support system that supports cloud e-learning can detect the node failure and can be immediately diverted to another node. Besides the high level of availabilitas system, with a large storage so that many learning resources can be gathered by combining learning resources from any educational institution who joined the cloud e-learning by integrating the learning resources with integrated database system mechanism; (4) Just in time learning, using cloud computing for e-learning system encourages the use of elearning more dynamic with added services through mobile devices, of course, by adding an integrated mobile learning services in a cloud-based e-learning. With add-ing mobile learning features, cloud-based e-learning become more powerful so the users could access the learning material any-time and any-where and just utilize their mobile devices like smartphones as an example.

Conclusion and Future Work

This paper proposes a model of e-learning based on cloud computing. Implementation of e-learning is now generally constructed separately by each institution, the implementation of such this conventional models is costly, because it takes the cost for provision of infrastructure, systems development, and hiring IT staff to maintain and enhance e-learning systems. Cloud computing as one of the technologies used currently rife in the IT world can be utilized for the implementation of e-learning. With the implementation of e-learning in a cloud environment, educational institutions no longer have to pay for the provision of infrastructure because infrastructure has been provided by the cloud service provider of e-learning and agencies that wish to use it only pay according to the usage by the institution. For the cost of developing elearning systems and staff to maintain and enhance e-learning systems, cloud service providers also provide service for it, and educational institutions will only pay for the services they already use.

In this paper we propose the architecture that consists of five layers, namely : (1) infrastructure layer; (2) platform layer; (3) application layer; (4) access layer; and (5) user layer. The first three layers are the basic of cloud services, then we added two additional layers, namely access layer and user layer. Access layer consists of a variety of devices used to access the cloud e-learning, whether in the form of notebooks, PCs, Smartphones, Tablets, etc. At the users layer consists of various educational institutions that will use cloud e-learning. As the implementation of the proposed architecture, authors have developed a prototype of a cloud-based e-learning is being piloted at three higher education institutions that are used in teaching and learning, and in the future we will perform an evaluation of the use of cloud-based e-learning.

Fig. 1 .

 1 Fig. 1. The Advantages of implementing Cloud Computing [8]

4 . 1 Previous

 41 Cloud-Based E-Learning Architecture The research of e-learning in the cloud environment have been carried out by previous researchers, such as those conducted by Chuang, Chang, and Sung (2011), Dong et al (2009), Vishwakarma & Narayanan (2011), Pocatilu (2010) and Ghazizadeh (2012). Research on the application of e-learning in a cloud environment is one form of cloud services education services. There are several architectural cloud-based e-learning have been proposed by previous researcher. In this paper will discuss three architectural cloud-based e-learning, such as architecture proposed by Phankokkruad (2012), Wang, Pai, & Yen (2011), and Masud & Huang (2012).

  Not much difference can be inferred from the comparison of the architecture delivered by[START_REF] Phankokkruad | Implement of Cloud Computing For E-Learning System[END_REF] and Wang, Pai, & Yen (2011). They proposed an architecture of e-learning-based cloud computing consists of three layers, namely: (1) infrastructure layer, (2) middleware layer, and, (3) application layer.

Fig. 3 .

 3 Fig. 3. Conventional E-Learning Towards Cloud-Based E-Learning


Hery Harjono Muljo

Bens Pardamean
email: bpardamean@binus.edu

Information Systems Strategic Planning for a Naval Hospital

Keywords: strategic planning, hospital information systems, telemedicine, medical tourism

This article discusses the Information System (IS) strategic planning for a naval hospital in Indonesia. Its purpose is to improve competitive advantage among hospitals through the addition of new services and products that would lead to improvements in the current patient services. The merging of Hospital Information System (HIS), Radiology Information System (RIS), and Laboratory Information System (LIS) into a single network with a concept of telemedicine is the main topic of this article. The hospital's website is also developed with medical tourism in mind, which attracts more patients, generating more revenue for the hospital.

Introduction

For a company that is planning to upgrade and improve its IS/IT infrastructure, Henderson and Sifonis [START_REF] Henderson | The Value of Strategic IS Planning: Understanding, Consistency, Validity, and IS Markets[END_REF] states it should perform an Information System Strategic Planning (ISSP). The IS Strategic Planning is a useful management tool for identifying the main objective, focus, and work needed for the upgrade [START_REF] Adams | Successful Strategic Planning: Creating Clarity[END_REF].

ISSP could also be used as a reference by any organization in designing its IS to perform current business strategics [START_REF] Hartog | Opinion Survey of MIS mMnagers: Key Issues[END_REF] as well as creating new business strategy [START_REF] Porter | Competitive Advantage: Creating and Sustaining Superior Performance[END_REF] and IT architectural policy [START_REF] Earl | Management Strategies for Information Systems Planning[END_REF]. A well-designed strategy would lead to a competitive advantage [START_REF] Wagnera | Configuring and Managing Strategic Supplier Portfolios[END_REF] while a controlled strategy, which is a critical component in the design, would satisfy both the customer needs and the investor demands [START_REF] Davis | Critical Competitive Strategy Issues Every Entrepreneur should Consider before Going into Business[END_REF].

A naval hospital in Indonesia handles not only patients from the Navy but also from the general population that contributes more than 350,000 patients per annum, all of whom are covered by government insurance. The hospital itself has had an IS in place, maintaining the effectiveness and efficiency of day-to-day operations. However, the current system is not equipped for improving service levels or gaining more revenue. Upgrading the system to include these practices place the hospital on par with other competitors that have identified these potentials.

The research question that the author attempts to answer is how would the IS strategic planning be able to perform the following: support the hospital's business strategy, provide a competitive edge, improve current services, and eventually, become the backbone of the hospital's day-to-day operations?

The objectives of the research are to develop an IS strategic planning by analyzing the internal and external side of the hospital's business and the Information Technology (IT) infrastructure, and defining the IT/IS management strategy. The benefit that the hospital could gain from the development is having IT/IS strategies with competitive advantages among the competitors, supporting the hospital's management during the implementation of the IT/IS strategies, and creating new services that would strengthen the hospital as a whole.

Methodology

The development of the ISSP refers to the IS/IT strategy development model by Ward and Peppard [START_REF] Ward | Strategic Planning for Information System[END_REF] that consists of five stages. The first stage is preparation and data collection. The preparation sub-stage consists of defining the objectives, limitations, and the problem statement. The second stage is analyzing both the internal and external side of the business environment as well as both the internal and external side of the IT/IS infrastructure.

The tools for analyzing the hospital's external business environment were PEST (Politic, Economic, Social, and Technology), Porter's Five Forces, and Boston Consulting Group (BCG). As for the internal business environment, Value Chain was used to identify the hospital's strengths and weaknesses. Once all the opportunities, threats, strengths, and weaknesses were identified, a SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis was performed to identify the hospital's "position" to achieve the goals. The next step was to find the Critical Success Factors (CFS) of the hospital to find necessary elements required by the hospital for achieving the goals. The third step of the analysis was performing a Gap analysis. The fourth was identifying the business IS strategy, IS/IT management strategy, and the IT strategy.

The last stage was planning the IT/IS implementation strategy that would be the blueprint for the hospital.

In this study, a qualitative descriptive analysis approach was utilized for describing the actual hospital condition/environment, identifying the problems, collecting data, analyzing data and situation, as well as finding the answers to the research questions in IS/IT strategic planning form.

The study used surveys, observations, and interviews as primary sources for data analysis. The naval hospital in central Jakarta and two other hospitals were selected as primary data sources. Secondary sources were also collected, such as the population data, inflation rate, gross domestic incomes, and gross domestic expenditures from the Badan Pusat Statistik (Central Bureau of Statistics) website.

Result and Discussions

External Business Environment Analysis

This analysis was used to identify both the external factors related to the organization and the organization's competitive advantages against the competitor. The analytical tools were PEST, Porter's Five Forces, and BCG.

PEST (Politic, Economic, Social, and Technology) Analysis

PEST is a useful tool for summarizing the external factors of a business. PEST prepares a business for handling external factors such as politic, economic, social, and technology. PEST factors tests predictive models for current and future scenarios [START_REF] Ha | E-Government in Singapore A SWOT and PEST Analysis[END_REF]. PEST analysis would also be used to test the current practice and develop a new framework [START_REF] Ayo | A Framework for e-Commerce Implementation: Nigeria a Case Study[END_REF].

Politic. Indonesian Law No. 4 of 2009 Section 6 states that the hospital financing for the poor will incur additional costs for the hospital. Section 7 of the same law states that a hospital has to be established at a geographically strategic location with sufficient treatments, services, and logistics.

Economy. High inflation rate and crude oil prices (more than a $100/barrel in 2012) resulted in sharp increase in drug prices and medical equipment. These conditions place the hospital at an unfavourable disadvantage.

Social.

A dense population around the hospital, an increase in revenue and welfare, and various lifestyles are affecting the public health issues of the population.

Technology. Rapid growth in technology and technological literacy population has forced the naval hospital to periodically update its technological infrastructure as often as possible. Competitors that frequently update their technology could be a threat for the naval hospital's management.

Porter's Five Forces 1. Rivalry among Existing Competitors

There are four regular hospitals within the naval hospital area's geographical scope that can be considered as competitors: PELNI Hospital, PK St. Carolus Hospital, PGI Cikini Hospital, and Jakarta Hospital. These competitors are experienced and constantly improving their services, upgrading their medical equipments, renovating their faciities, and upgrading their IS.

Threat of New Parties

Sahid Sahirman Memorial Hospital (SSMH) is a new party to watch in the healthcare business competition. SSMH is equipped with modern technology, excellent services, big investment support, and a state-of-the-art IT/IS infrastructure.

Threat of Products or Services Substitution

Healthcare products and services substitution such as small local clinics, accupunture clinics, reflexology clinic must also be considered. It is highly likely that patients at one point, will opt to try alternative treatments for their illnesses due to several reasons, such as healthcare cost and treatment effectiveness.

Bargaining Power of Buyer

The main customers of the naval hospital are navy officers and the general population. The naval hospital has a strong bargaining power because of the requirement that navy officers check-in to this hospital when they are on duty. The naval hospital also offers a hyperbaric therapy that not many hospitals offer.

Bargaining Power of Supplier

The large number of suppliers that exist in the healthcare industry is also a big advantage for the naval hospital because they do not have to rely solely on one party for its hospital supplies. Thus, the hospital is able to negotiate its payment to the suppliers; the negotiation period can last between one to three months.

Boston Consulting Group (BCG)

BCG Matrix is a trusted and effective technique in product market decisions [START_REF] Armstrong | Effects of Portfolio Planning Methods on Decision Making: Experimental Results[END_REF]. The matrix is also used to formulate concept-based restructuring of portfolio analysis and is useful for strategic decision making [START_REF] Santosa | Penerapan Analisis Portofolio untuk Pengambilan Keputusan bagi Pemerintah Provinsi DKI Jakarta pada Perusahaan Patungan[END_REF].

According to the BCG Matrix as shown in Figure 1, "outpatient" and "radiology" are both in the "Question Marks" category, which means that both have a low market share but a high market growth. For "inpatient", "laboratory", and "Hyperbaric" are in the "Dogs" category due to their slow market growth and low market share. "Surgical procedure" falls under the "cash cow" category due to its low market growth but high market share. The naval hospital could support all other services through the high profit and high cash generated from the "surgical procedure" service. With low market growth and no recurring investment needed, the naval hospital could keep its profit high. All the cash surplus from the "surgical procedure" service can be used to transform the "Question Marks" category to a "Share Leader" category. It can also be used to subsidize the "Dogs" category, cover the administration fees, fund research and development, as well as cover its debt.

Market Growth Rate

Internal Business Environment Analysis

This analysis is used to identify the strengths and weaknesses of an organization. Value Chain, SWOT, and Critical Success Factors (CSF) are all the tools that were used to analyze the situation.

Value Chain

Value Chain model by Martinelly, Riane, and Guinet [START_REF] Martinelly | A Porter-SCOR Modeling Approach for the Hospital Supply Chain[END_REF] is specifically developed for hospital environment. The main activities from the model include Admissions Logistics, Care Services, Discharge Logistics, Marketing and Sales. Other supporting activities include Infrastructure, Human Resource Management, Technological Development, and Procurement. Figure 2 shows the Value Chain model for the naval hospital.

Figure 2. Value Chain Model

SWOT Analysis

SWOT analysis is a tool that can be used to identify the internal and external strengths and weaknesses of a company [START_REF] Pesonen | Assessing the Priorities using a SWOT among Resource Management Strategies at the Finnish Forest and Park Service[END_REF]. SWOT analysis can help the organization in developing a strategy as well as in preparing for a better future [START_REF] Chan | A SWOT Study of the Development Strategy of Haier Group as One of the Most Successful Chinese Enterprises[END_REF]. In an industry, SWOT analysis is used to provide the leader/management team with basic information regarding the company's development policies for future growth [START_REF] Narayan | Fiji's Tourism Industry: A SWOT Analysis[END_REF].

Figure 3 shows the result of SWOT analysis.

Figure 3. SWOT Analysis

Critical Success Factors (CFS)

Critical Success Factors are critical activities needed to obtain a successful (or failing) company. CSF can help provide a better understanding on the needs of customers, as well as better construct the marketing division's strategy, management, and evaluation [START_REF] Sahney | Critical Success Factors in Online Retail -An Application of Quality Function Deployment and Interpretive Structural Modeling[END_REF]. The result of the CSF analysis for the naval hospital is shown in Table 1. The number of joint agreements in the current year is larger than the previous year's

To increase patient satisfaction

Increasing patient satisfaction

The number of complaints from patients in the current year is fewer than the previous year's

External IT/IS Environment Analysis

Progress made in the Hospital Information System (HIS), such as Radiology Information System (RIS) and Laboratory Information System (LIS) significantly impacts the hospital's operation. LIS creates a dynamic link among the laboratory analyzers, medical technologists, and clinical providers. LIS, combined with an automated process, has the potential to increase work efficiency and quality, reduce human errors, and lab sample tracking (a task often hampered by human errors) [START_REF] Voegele | A Laboratory Information Management System (LIMS) for a High Throughput Genetic Platform Aimed at Candidate Gene Mutation Screening[END_REF]. Additionally, developments in telemedicice and SMS gateway can also increase the competitive field within the healthcare industry. For the current available services, the naval hospital lacks two aspects, the Radiology Information System (RIS) and Laboratory Information System (LIS). On the other hand, both the naval hospital and its competitors lack the version of HIS that integrates telemedicine, SMS gateway, and medical tourism. Table 2 below lists a comparison between the naval hospital and its competitors in terms of their service applications as well as recommended services that should be developed in order to improve treatment quality.

• Stand Alone • Integrated X X X RIS X X LIS X Telemedicine Service X X X SMS Gateway Service X X X Medical Tourism X X X
The development of Mobile Clinical Assistant (MCA) C5 from the previous version also tremendously impacts the hospital's operations. The development of MCA C5 was propelled by an increase in access patients graphics, especially at the point of care, an increase in clinic's documentation, patient care, and to improve the satisfaction of service providers [START_REF] Baltimore | Clinician Usability Study: Workflow and Clinician Satis-faction Improvement for Physician CPOE and Nursing eMAR using the Motion C5 with Cerner[END_REF].

Internal IT/IS Environment Analysis

The current hospital applications does not cover many hospital operations; it only comprises of outpatient, inpatient, and emergency patient registrations. Additionally, the hardware that the hospital owns is rarely upgraded. The Information System Management (IMS) that is currently utilized is developed with Microsoft Visual Studio .NET 2005 and SQL Server 2005. The architecture is a Web-based and Client-Server combination. All the modules use a Web-based architecture, except for the pharmacy and finance modules, which use the Client-Server architecture. The naval hospital application portfolio can be seen in Table 3. HIS development is aligned with the business strategy to improve services and data processing. Its development also begins with the development of an integrated hospital application that is then followed by the online module. The newly designed modules consist of Patients Master Index module (contains detailed information o the patients), Appointments module (assists patients in appointment set-ups with the hospital), Queue Management module (links the data between receptionists and schedulers), Registration module (records patient registrations manually, online, or through SMS), Outpatient module (manages outpatient transaction), Inpatient and Labor module (manages inpatient transaction), Medical Record Tracking module (records and tracks patient medical records), Surgical module (manages surgical patients), Emergency module (manages emergency medical records), Pharmacy module (records and manages prescriptions), Billing module (tracks all billing and payments from patients and/or their affiliated third-party entities), and Logistic module (tracks logistical data).

Following the HIS, Radiology Information System (RIS) is developed to meet radiology's needs for consistency in the database that manages modality, material and medical equipment, and data delivery. RIS is a repository for reports and patient data, as well as electronic records for patient data that could help facilitate appointments, track patient information, and provide online reports on diagnostic results [START_REF] Nor | Medical Imaging Trends and Implementation: Issues and Challenges for Developing Countries[END_REF].

LIS helps screen more people by increasing the capacity of a health promotion center, and brings in more revenue to the center [START_REF] Chae | The Development of an Intelligent Laboratory Information System for a Community Health Promotion Centre[END_REF]. The LIS, combined with a Clinical Information System such as Computerized Physician Order Entry and Electronical Medical Record, can support improvements in health care services [START_REF] Harrison | The Role of Laboratory Information Systems in Healthcare Quality Improvement[END_REF].

The next two developments are telemedicine and SMS gateway. Telemedicine is a medical application in which information is transferred through an interactive audio and visual media. Telemedicine aims to deliver medical consultations and examinations to remote area, thereby reducing the patient's need to travel [START_REF] Fabbrocini | Teledermatology: From Prevention to Diagnosis of Nonmelanoma and Melanoma Skin Cancer[END_REF]. Telemedicine could potentially overcome geographical barriers, improve access to patients, facilitate collaboration between health care providers in patient treatment, leading to reduction in patient mortality [START_REF] Selinger | Internet-Based Support for Cardiovascular Disease Management[END_REF]. This technology is also useful for setting primary and specialty care targets in the public health care system, facilitating electronic communication within the specialty care's referral system, assisting hospitals with a primary care focus in remote areas, and improving cooperation between specialists and the rest of the medical staff [START_REF] Coelho | Identifying Telemedicine Services to Improve Access to Specialty Care for the Underserved in the San Francisco Safety Net[END_REF].

Through the use of video conferencing, patients are better prepared at counseling and expressing their ailments, which would lead to improvments in patients satisfaction levels [START_REF] Dansky | How Telehomecare Affects Patients[END_REF]. Telemedicine could also improve the patients' well-being, independence, self management, medical knowledge, and their overall health. A module of Virtual Communities for Healthcare can also be used as a virtual self-help guide by the patients [START_REF] Chorbev | Virtual Communities for Diabetes Chronic Disease Healthcare[END_REF]. Short Message Service (SMS) gateway is a platform that provides a mechanism to deliver and receive SMS from mobile devices as another way to improve services. It can also be used by the organization to monitor, control, and manage the organization's assets [START_REF] Hakim | Aplikasi Monitoring Suhu Ruangan Berbasis Komputer dan SMS Gateway[END_REF]. In a service industry, SMS gateway has been used to increase customer satisfaction e.g. its usage in the hospitality industry for hotel reservations [START_REF] Rahayu | Perancangan Aplikasi Reservasi Kamar untuk Pelanggan Tetap dengan Menggunakan SMS Gateway[END_REF]. Additionally, the SMS gateway can also be used to distribute information and to ensure that the customers make a wilfull complaints and able to be contacted again when needed [START_REF] Utomo | Pengembangan Sistem Pengaduan Konsumen Terkait Bisnis Online Berbasis Facebook Open Graph Protocol dan SMS Gateway[END_REF].

The high cost of treatments in the United States, Europe, Australia, and other developed countries calls for an increasing demand for a more affordable service. That demand can be answered by the expansion of medical tourism, which is a sector of the healthcare service with a more affordable price [START_REF] Jones | Medical Tourism and Reproductive Outsoursing: The Dawning of a New Paradigm for Healthcare[END_REF]. This can be done if the system is supported by an international standard for hospital management. Hospital website development is one IT/IS strategy that can be implemented to support medical tourism in order to recruit patients worldwide as well as provide prospective patients with hospital information, such as service rates and available facilities.

The next development is a collaborative information system that aims to store all data from external parties. This module require the collaboration of drug suppliers, competitors, referral hospitals, and medical schools.

The last development is an IS patient service that consists of office visits, home care, hospice comfort care, and taxi. Office visit is a patient session with physicians at the doctor's office but not necessarily at the hospital. An appointment module is needed to support this effort. It is a strategy that is developed as a follow-up treatment for post-treatment ambulatory patients. Home care service is provided by the hospital for patients who feel uncomfortable being treated at the hospital. This service could lead to quality enhancement, error reduction, and patient satisfaction improvement [START_REF] Thomas | The Medical Home: Growing Evidence to Support a New Approach to Primary Care[END_REF]. A module needed for this effort is a registration module that can be integrated with the registration module from the HIS. A hospice service is for patients who can no longer be treated and is given comfort care for the "final call". This service can also be integrated with the HIS especially with the registration, billing, and payment modules.

Conclusion

The development of information system strategy provided several added values for the naval hospital's competitive edge. Furthermore, it also redesigned the hospital's applications portfolio. The result of this new strategy offered new products and services such as telemedicine, medical short message service gateway, medical tourism, and home care.

Figure 1 .

 1 Figure 1. BCG Matrix

Figure 4

 4 Figure4shows the overall network architecture for the proposed IT/IS strategic planning that includes HIS, RIS, LIS, Telemedicine supported, SMS gateway, medical tourism, as well as all other non-medical services.

Figure 4 .

 4 Figure 4. Overall Strategy IT/IS Network Infrastructure

Table 1 :

 1 CSF Analysis for the Naval Hospital

	Objective	Critical Success Factor	Indicator
	To attract out-of-state	The number of out-of-	Out-of-state Patient
	patient (outside DKI	state patient (outside DKI	10%
	Jakarta)	Jakarta)
	To develop an IT-based	The number of IT-based	IT-based service level
	data processing	service	50%

Table 3 .

 3 The Naval Hospital Applications Portfolio

	Strategic	High Potential
		1. HIS
		2. RIS
		3. LIS
		4. Telemedicne
		5. SMS gateway
		6. Medical tourism
		7. Home care, hospice
	Key Operational	Support
	Registration Information Systems:	Microsoft Office
	1. In-patient Application
	2. Out-patient Application
	3. ER Application


Wayan Suparta

Maulana Kemal

Alhasa

Estimation of Precipitable Water Vapor Using an Adaptive Neuro-fuzzy Inference System Technique

Keywords: PWV, Adaptive neuro-fuzzy inference system, Estimation, Meteorological applications

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

One of the most important factors in meteorology is determining the rate of water vapor in the atmosphere. Water vapor content and its variability have an important role in human activities and environments. It has been balancing the energy in the preservation atmosphere, the weather process and ultimately important for operational weather forecasting. Water vapor comes from the evaporation of sea water, ground water, rivers, swamps, glaciers, snow, and water in the atmosphere in the form of clouds. Therefore, accurate estimation of water vapor circulation is of primary importance for monitoring and prediction of precipitation rates to indicate climate change takes place at small scales as well as at regional scales. Many efforts have been invested to study the water vapor changes, especially from the science communities such as meteorology, hydrology and climatology [START_REF] Zhang | Advance in Neural Network Research & Application: A Neural Network Based Algorithm for the Retrieval of Precipitable Water Vapor from MODIS Data[END_REF]. Atmospheric water vapor content in terms of precipitable water vapor (PWV) was derived from GPS and the surface meteorically data with superior in temporal and spatial resolution [START_REF] Bevis | GPS Meteorology Remote Sensing of Atmospheric Water Vapor Using the Global Positioning System[END_REF], [START_REF] Suparta | Observation of Antarctic Precipitable Water Vapor and Its Response to The Solar Activity Based on GPS sensing[END_REF]. This technique is still had good capability in comparison with the ground-based techniques that are traditionally made through balloon-borne radiosondes and water vapor radiometers (WVRs). Although the GPS networks currently distributed thousands around the world, there is a still lacking of GPS data, especially in the remote locations that could potentially give the extreme effects on the local weather conditions. One of the tools of soft computing is the adaptive neuro-fuzzy inference system (ANFIS). ANFIS is a class of adaptive networks that are functionally equivalent to fuzzy inference systems. ANFIS represents both the Sugeno and the Tsukamoto fuzzy models. It has emerged as a powerful tool in solving problems in engineering and non engineering. With uses a hybrid-learning algorithm, it has an ability to do adjustments of rules by using learning set of data and allow the rules to adapt. Thus, it is profoundly suitable for control, pattern recognition and forecasting task. Several researchers have been employed the ANFIS techniques due to its computational speed, robustness, and also its ability to handle complex problems of non-linear functions. Among them is estimation of evaporation using Artificial Neural Networks (AAN) and ANFIS techniques [START_REF] Kumar | Evaporation Estimation Using Artificial Neural Networks and Adaptive Neuro-Fuzzy Inference System T echniques[END_REF], which found that the ANFIS models are better than ANN although the difference is small. Estimation of time series on earthquake events with mapping function [START_REF] Joelianto | Time Series Estimation on Earthquake Events Using ANFIS with Mapping Function[END_REF], and estimation of subsurface strata of Earth [START_REF] Srinivas | Estimation of Subsurface Strata of Earth Using Adaptive Neuro-Fuzzy Inference System (ANFIS)[END_REF] reported that the interpretation using ANFIS technique will give the promising results with much fewer percentage error.

The main objective of this study is to investigate the potential use of ANFIS model to predict PWV that influenced by meteorological factors. The second is to evaluate the performance of ANFIS model in estimating the water vapor value by comparing the PWV data obtained from the Global Positioning System (GPS).

Methodology

Data Collection

Two types of data were used in proposed ANFIS. There are the surface meteorological data (pressure, temperature and relative humidity) as the original input and PWV data as the target output. The tested data were taken from the Universiti Malaysia Sabah Kota Kinabalu, Malaysia (UMSK: Monsoon that much of the rainfall received during this period. For this work, data gathered from 4 to 10 April 2011 is processed. The meteorological data were taken data of air temperature, barometric pressure, and relative humidity. The PWV data were collected using the ground-based GPS receiver, and the surface meteorological data were collected using the Paroscientific MET4A Broadband meteorological sensors. All the data collected were taken at one-minute interval.

Adaptive Neuro-Fuzzy Inference System

Adaptive neuro-fuzzy inference system is a method that combines neural networks and fuzzy inference system. This method using Sugeno inference model or Takagi-Sugeno-Kang (TSK) fuzzy structures interface, which adapt the rules that are used to fix the parameters so that resulting in a minimum error. ANFIS consists of five components, namely input and output database, fuzzy generator, fuzzy inference system and adaptive neuro. To study the estimation of PWV mode, combination between Sugeno model and TSK inference as a fuzzy inference system (FIS) and adaptive neuron were employed. The optimization method is done by using a hybrid learning algorithm. Suppose there are two inputs x 1 , x 2 to the node and one output is y, then there are two rules in the base Sugeno models [START_REF] Jang | ANFIS: Adaptive Network-Based Fuzzy Inference Systems[END_REF]:

where x 1 and x 2 are the crisp inputs to the node, and A 1 , B 1 , A 2 , B 2 are fuzzy sets, the reasoning mechanism on this Sugeno model is [START_REF] Zhang | Advance in Neural Network Research & Application: A Neural Network Based Algorithm for the Retrieval of Precipitable Water Vapor from MODIS Data[END_REF] where w 1 and w 2 are the degree of membership of a fuzzy set, while f 1 and f 2 are linear equations for the output from a first-order of Sugeno inference model.

ANFIS network consist of five layers (see Figure 1) as follows: (2)

A 1 A 2 B 1 B 2 Π Π N N ∑ X 1 X 2 W1 W2 Ŵ1 Ŵ2 X1,X2 X1,X2 Ŵ1f1
(3)
where x or y is the input value to node i and A i or B i-2 is a linguistic label (fuzzy set) associated to the node. While O 1 , i is membership degree of fuzzy set. For example, suppose the membership function of fuzzy set A is given as follows:

(

) 4
where {a,b,c} are the parameter set, generally value of b is equal to 1. As the value of these parameters change, the bell curve shape will change as well. The parameter in this layer is usually called the name of the premise parameters. Layer 2: Every node from this layer is fixed node with labeled π, which output of the result is the incoming signal to entire node. Every output node in this layer present the firing strength of each rule, generally used the AND operator (t-norm operator).

(

) 5
For convenience, outputs from this layer generally are called normalized firing strengths. Layer 3: Every node in this layer is non-adaptive or fixed with denoted by N. Every node serves only to calculate the ratio between the firing strength of i th rule towards total firing strength of all rules.

(

) 6
where is normalized firing strengths output of layer 3 and is parameter set on first order Sugeno fuzzy inference system model. The parameters in this layer are referred to as consequent parameters. Layer 5: A single node in the fifth layer is a fixed node which is the sum of all incoming signals. [START_REF] Jang | ANFIS: Adaptive Network-Based Fuzzy Inference Systems[END_REF] Thus, the fifth layer will build an adaptive network that is functionally equivalent to the first order Sugeno fuzzy inference Model.

Result and Discussion

In this study, ANFIS was set with the epoch number of 700, step size 0:01 with a membership function 'gaussmf'. The learning method (adaptive network) used the hybrid algorithm. The data used in this study is the surface meteorological data and the GPS PWV data as mentioned in section 2.1. The data are constructed into two parts, training data and checking data. The data used for training as much 2/3 data and 1/3 the data used for checking.

Before the data input is processed by the ANFIS, the first work is to construct initial FIS. In forming the initial FIS, needed a plan. Among them is the establishment of membership functions and rule formation. The curve used in the formation of the membership function is 'gaussmf'. This is due to the Gaussian curve represent the changing of continuous data. PWV is a continuous, which means its value can change over time depending on the season changes, particularly temperature and air pressure conditions. A Gauss curve using two parameters: the central curve domain and the standard deviation that shows the width of the curve. The where P is the surface pressure (mbar), T is the surface temperature (in degree Celsius), and H is the relative humidity (in percent). If the predicate α for the four rules are W 1 , W 2 , W 3 , and W 4 , then the weighted average can be calculated as (12)

PWV Result at UMSK

Figures 2a and2b show the PWV result between ANFIS technique and observed by GPS at UMSK station. In general, the pattern of PWV predicted by ANFIS follows the pattern of PWV observations. Comparing to both figures, data are found blank in Figure 2b due to lack of GPS data at that time and only the surface meteorological data are available and therefore, the time series is contrast to Figure 2a. This is the advantage of the ANFIS model, which use the surface meteorological data as input. ANFIS model was successfully estimating the PWV value and clearly follow the pattern of PWV observation. Figure 3 shows the scatterplot standard deviation (STD) of PWV between ANFIS and GPS at the UMSK station. The STD calculation was done with one-hour interval of data. The STD pattern between ANFIS and GPS showed a binomial trend where the maximum curve reached to 2.4 mm.

PWV Result at NTUS

A similar PWV result between ANFIS and GPS was also found for NTUS station as depicted in Figures 4a and4b. From Figure 4a, the final shape of PWV ANFIS is clearly similar to the shape of PWV GPS. Looking at the Figure 4b, some data blank for GPS PWV was recorded at NTUS station. This is same case happened like UMSK station, where there is no GPS data provided at this time. From this lacking, ANFIS model successfully solved the problem as demonstrated in Figure 4a. Figure 5 shows the scatterplot of standard deviation (STD) of PWV between ANFIS and GPS. The STD trend at NTUS was found a similar pattern with the UMSK station with a maximum curve reached to 1.82 mm. The correlations between the predicted results and observational data show that the ANFIS technique can be used to predict the PWV value, using meteorological data as the input parameter. The relationship with the highest correlation value is o b s e r v e d at UMSK station (r = 0.95), while the modest value is observed at NTUS station (r = 0.73). From calculation of RMSE value, the resulting error is very small which less than 5%. The PWV difference between the prediction error and the observation are obtained -0.06 mm for UMSK station and -1.31 mm for NTUS station. The negative value indicates that the PWV value from ANFIS is lower than those of PWV obtained from GPS. On the other hands, this method is more convenient, cost-effective and practical when compared to the GPS observations. The promising method only needs the meteorological data (pressure, temperature and relative humidity) as input parameters and very helpful for meteorological station with absent of GPS data.

Conclusion

In this study, a new method for estimating the PWV value was developed by using one of the tools soft computing, ANFIS techniques. The correlation coefficient between the predicted results and the observational data was found strongest relationship. Looking at UMSK and NTUS stations as an example of examination, the highest correlation coefficient was found at UMSK and the modest correlation coefficient was at NTUS with a resulting error was less than 5%.

A model approaches adaptive neuro fuzzy system interfaces with the input meteorological data (temperature, pressure and relative humidity) can be used as an alternative method in the estimation of PWV value when absent of GPS data in a particular station. In the future, it is recommended to use more extensive data to improve the estimation of PWV value. It is either by adding a new parameter or increases the amount of interval data used to further clarify the accuracy of PWV model developed.

Fig. 1 . 1 :

 11 Fig. 1. Architecture of Adaptive Neuro Fuzzy Inference system

  two values are determined by using Fuzzy C-Means clustering. The value of the central domain curve is taken from the average value of the data cluster and the standard deviation values were obtained from the standard deviation of a data cluster. The formation rules in Sugeno-Takagi type FIS using a linear equation. There are four linear equations in this FIS that has been optimized to estimate PWV. The reasoning mechanisms on this Sugeno model after training by ANFIS are:

Fig. 2 .Fig. 3 .

 23 Fig. 2. PWV results between prediction using ( a) ANFIS technique and ( b ) observation using GPS at UMSK station, Malaysia

Fig. 4 .

 4 Fig. 4. PWV results between prediction using (a) ANFIS technique and (b) observation using GPS at NTUS station, Singapore.

Fig. 5 .

 5 Fig. 5. The scatterplot of STD PWV between ANFIS and GPS for NTUS station

  6.03 o N, 116.12 o E and height of 63.49 m) and Nanyang Technological University, Singapore (NTUS: 1.350 o N, 103.680 o E and height of 75.38 m). Sabah as a main base of this study has an equatorial climate and naturally more affected by two types of surges associated with East Asian Winter

Table

Table 1 .

 1 1. Statistical parameters of the PWV comparison

	Quantity	UMSK	NTUS
	R	0.95	0.73
	RMSE	1.29 mm	1.68 mm
	Mean	-0.06 mm	-1.31 mm

Acknowledgment

This work was partially supported by the Ministry of Higher Education Malaysia (MOHE) under grants UKM-LL-07-FRGS0211-2010 and PKT 1/2003.


Muhammad Asfand-E-Yar
email: asfandeyar@ifs.tuwien.ac.at

Min Tjoa

Using Semantic Web to Enhance User Understandability for Online Shopping License Agreement

Keywords: License Agreements, Semantic Web, License Ontological Model, Digital License Agreement

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

In general, installing software or using any services requires the user's agreement to terms and conditions. The terms and conditions describe issues such as functionality, restrictions of use, and about other legal acts such as jurisdiction restriction and intellectual property rights. These terms and conditions describe various legal acts of an agreement. The legal acts contained in agreements are often difficult for a user to understand. Therefore, users do not read such lengthy agreements and bypass the agreement by signing, without understanding. In such situations user might commit illegal act unintentionally. Therefore, an easy understandable solution is required in order to facilitate user's requirements. Hence, a solution in form of agreements' repository is provided that is easy for a user to select an appropriate product. Moreover, Semantic model for online shopping license agreements is discussed in this paper. With the help of the Semantic model user queries are answered in conjunction with user's requirements.

License Agreements: The agreement is a legal binding between two parties and if any violation occurs then defined penalties are applied. Similarly, using web services requires the user's agreement to the terms and conditions. Agreements describe issues related to product's functionality, restrictions on its use, may specify the number of users that can work in a connected environment, state relevant laws if any, rules pertaining to the distribution of the product, modifications that can be made and the payment procedure [START_REF] Alliance | Why a License matters?[END_REF]. In online shopping centers a legal contract occurs between a buyer and seller while purchasing a product.

The concepts contained in agreements are often difficult for a user to understand. Moreover, the terms and conditions are different nearly in every license agreement. Therefore, user agrees with agreement, without deeper understanding, which might lead to a user's inadvertent implication in an illegal act. Approximately every agreement applies penalties, if terms and conditions are violated.

User Awareness: For the awareness and understanding agreements, few efforts are done for example; GPL-violations, it is an awareness project about the violation of GNU licensing agreements. "GPL-violation" is a communication platform between all parties that are involved in licensing of open source software for example authors and copyright holders, vendors and users [START_REF] Welte | About the gpl-violations[END_REF].

Business Software Alliance (BSA) is an IT industry group that helps their member groups in controlling piracy of software and hardware tools. BSA provides awareness and educate people about the ethical and digital security risk associated with use of unlicensed software [START_REF] Bsa | About BSA & Members[END_REF].

The work done by GPL-violations and BSA serves for user awareness; while the Semantic model provides a solution, in selecting a required license according to the needs of a user, and also make awareness of penalties.

Related Work

In the literature, a plethora of studies has been conducted for developing a Semantic Web model to fulfill user requirements. The research is based on two sections, initially, it summaries fundamental concepts of license agreements, by considering different type of existing licenses. Secondly, it highlights the use of ontology in information retrieval, management, automatic extracting of meta-data and different concepts related to Semantic Web. According to the multifaceted nature of the research work, we will describe the problem from more than one angle.

2.1

License Agreements

Organizations do their best to control the misuse of License Agreements. Hence, penalties are defined to assure the legal use, defined in "terms and conditions".

Various license verifying systems have been developed. These systems help to ensure that a licensed version of a product is properly and legally installed on each computer in an organization. Microsoft verifies the installing products online, before completing the installation of the software product on a system [START_REF]Genuine Windows: FAQ[END_REF]. This clarifies that the granter of license wants her product to be used legally and according to the terms and conditions defined in the license agreement.

Online shopping agreements are mostly similar to each other and have a lower degree of complexity as software licenses [START_REF] Asfandeyar | Exploiting ontology for software license agreements[END_REF]. In these types of agreements, rights of service providers and customers are clearly defined. In some agreements service providers are the sellers and provide a facility of purchasing from Web sites. While other agreements are totally different from service provides, for example in case of eBay. Only two types of online shopping agreements are explained and used as pars pro toto in this paper, i.e. Amazon [START_REF] Services | AWS Customer Agreement[END_REF] and eBay [START_REF] Ebay | Your User Agreement[END_REF][START_REF] Post | License Agreement-eBay Trading Post[END_REF] license agreements.

Semantic Web

Digital Right Expression Languages and Policy Management are the two areas, covered in this paper. Digital Right Management is an access control technology that is used to impose limitations on usage of digital contents and devices. It controls the illegal use of digital media by preventing access, copy or conversion to other formats by end users. Semantic Web technologies facilitates in creating ontology for copyright agreements. These copyright agreements are digital rights used to implement legal limitation.

Digital Rights Expression Languages

Rights Expression Languages (REL) reflects licenses legal requirements, by gathering terms and required relations of contents. REL creation is based on an ontology using existing standards for example ODRL, XrML and Creative Commons. Usage of contents depends on the rights of a license provider, granted to licensee. REL with DRM translates licenses and uses ontology to deduce copyrights, context description and different type of expressions used in a license agreement. The REL ontology terms are mapped to a legal dictionary, which consists of legal classifications and legal rules used in the license law [START_REF] Nadah | License Digital Content With a Generic Ontology Escaping From The Jungle of Rights Expression Languages[END_REF].

Privacy Policy Matching

Nyre discusses the issues related to "privacy policy matching" [START_REF] Nyre | A Server-Side Approach to Privacy Policy Matching[END_REF]. They suggested, arranging policies of service providers according to customer requirements. Customer requirements are translated to policies using privacy preferences of the provider, for matching the customer requirements with the service provider polices. Privacy preference provider is introduced as an intermediate channel between service provider and customers; to solve, the issue of matching and arranging the policies for service providers.

The word "policy" used in this method is similar as terms and conditions of license agreement. These policies are defined by the service provider, for example in online shopping license agreements. The main problem of this method is to maintain an intermediate channel as "privacy preference provider" for updates of customer requirements. The second problem is to translate customer's requirements to policies, at this intermediate level, and then match these policies to service provider's policies. Handling these problems, according to the above method, is worse in case to deal with complex policies of service providers. To solve the above mentioned problem, we propose in this paper a solution using Semantic Web technologies.

Use Case Scenarios

Use case scenario elaborates user's requirements to achieve specific results. License model is constructed to facilitate a common user. Therefore, each license is categorized similarly. The model facilitates a common user to acquire her required information from a license. The model is designed to easily adopt documented agreement using Semantic technologies. The Semantic Web model of agreements covers all common features of an agreement. A user scenario is discussed below;

Online Shopping

Using services of online shopping web sites, the policies should be agreeable by both sellers and buyers. Sellers defined their own polices, without conflicting the police of online shopping. In case of conflicting policies, seller has either to face penalties or in worst case could be ban to use the services. This scenario is explained below:

A seller wants to sell her items through online shopping web site. The used items are placed for biding by the seller. One of the buyers received the item, with functionality problem. According to polices of online shopping, a buyer can claim for reimbursement. Therefore, the buyer claimed for reimbursement. In this case, the seller didn't define a proper procedure for reimbursement. The online shopping company paid for the damages, and ceased the seller's account and banded him from selling her item from the site. Such problems normally happens when user bypass the agreement, before using services.

Semantic Web and License Agreements

Semantic Web uses ontology as its basic component and uses taxonomy of information as an expressing knowledge to design ontology. Defining a domain of knowledge for license agreements, a root ontology (named; License Ontology) is created using bottom up approach, as discussed in [START_REF] Asfandeyar | Exploiting ontology for software license agreements[END_REF][START_REF] Asfandeyar | Blending the sketched use case scenario with license agreement using semantics[END_REF].

The ontological structure for license agreements is categorized in two parts, i.e. License Ontology and sub license ontologies. The License Ontology is developed from common features of different license agreements. The License Ontology is extended to sub license ontologies, in order to design ontology as a meaningful license agreement. Sub-license ontology describes a specific license agreement.

The resulting model is equipped with rules according to license agreements. Functionality of entire process depends on search and comparison of user requirements using License Ontology. Query results obtained from sub license ontologies are sent to user for final approval.

Sub license Ontology

Sub ontology is extracted from parent ontology to elaborate a section of domain knowledge. The extracted sub-ontology has following two features 1) consistency and 2) completeness. Sub-ontology concept is explained by proposing four methods i.e. extend, add, merge and replace. We used extended method of sub-ontology concept. The extend method depends on new features of sub-ontology engineering, which includes concepts, properties, relationships and mapping. These sub license ontologies are categorized into Online Shopping License Ontology and Software License Ontology. The Software License Ontology is explained in detail in [START_REF] Asfandeyar | Exploiting ontology for software license agreements[END_REF].

Online Shopping License Ontology

Construction of Online Shopping License Ontology is based on two different agreements. These include Amazon license agreement and eBay license agreement. These agreements have most common features. Online Shopping License Ontology is an extension of License Ontology, as shown in Fig. 1. The Online Shopping License Ontology extends all the features of License Ontology. A class named "Reimbursement" is added to Online Shopping License Ontology. The class is required to provide a concept of reimbursement method for customer, after purchasing product. Required properties are added to define the relationship of reimbursement class with customer and seller classes in the Online Shopping License Ontology.

Online Shopping License Ontology has defined individuals. These defined individuals are connected with each other, according to agreements, to define complete meaning of License Ontology

Rules used for Constructing License Ontology

Rules are needed for inference about classes and properties, mapping ontologies, transforming data in different format, using complex queries, axioms and many more. The aim is to populate the domain of License Ontology by means of rules, created form analyzing set of text documents. The entities are used in License Ontology and sub license ontologies on basis of terms and condition of agreements. Rule applied on Online Shopping License Ontology is described as follows;

Disjoint Classes in Ontology

In License Ontology only those classes that have information related to terms and conditions of agreement are considered disjoint. In License Ontology, classes used under "Agreement Items" class, i.e. "Breach", "Core Agreement" and "Non Core Agreement", and also the sub-classes of these defined classes are disjoint to each other.

Restriction used for Product Class

Details about product's legal usage are documented by license agreement i.e. reflected as below; Product isDocumentedBy . License It states that for all values of product should have an agreement (i.e. "License"). Vice verse the restriction applied also on "License" class because both properties are inverse to each other; isDocumented ≡ documents -

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Reasoning License Ontology

Acquiring information from ontology can be determined by rules. After having information from ontology by applying rules, then the next step is to represent the information. In this section, ten rules are introduced that are built according to previously discussed user scenarios. These rules describe complete requirements of a user, to search for appropriate license using ontologies.

Online Payment

Rule for online payment provides information, about procedure of payment according to an agreement. The rule describes, that a product have ontology. And according to the ontology, it is inquired that payment procedure supports online payment of the product or not. Then availability of user permissions is checked, for online purchasing of the product, according to the ontology. Thus, according to this rule, an end user is allowed to purchase the product according to an agreement as described below;

(?product LicenOnto:hasLicense ?license) (?license LicenOnto:supportPaymentMethod LicenOnto:Online) (?user profile:paymentMethod profile:Online) → (?user profile:canPayOnline ?product)

Method of Receiving a Product

The following rule is about downloading a product according to ontology. It states that a product having agreement and allows a user to download the product. The rule examines whether a user can download the product or not. According to ontology, if antecedent part holds answer then consequent part of the rule will also hold answer and allow user to download the product online. The product could be e-book, etc.

(?product LicenOnto:hasA ?license) (?license LicenOnto:receiveMethod SoftOnto:Download) (?user profile:receiveMethod profile:Online) → (?user SoftOnto:canDownload ?product)

Replacing of Damaged Product

"Replacing of Damaged Product" rule is about replacing a product, if the product is damage before receiving. Therefore, according to ontology the availability of replac-ing damaged product is evaluated against respective agreement. If a method of replacing a damaged product is allowed according to ontology then the product is allowed for replacement. According to this rule, the possibility of replacing the damaged product is determined according to agreement.

(?user profile:ownsProduct ?product) (?product LicenOnto:hasLicense ?license) (?license LicenOnto:replaceMethod SoftOnto:Return) → (?user SoftOnto:canReturn ?product)

Reimbursement of Payment

Rule of reimbursement describes the method of reimbursement of expenses after identifying fault in a received product. In agreement normally the reimbursement procedure is defined for customers. Therefore, in ontology a rule is used to inform customer about availability of reimbursement procedure according to an agreement. Whenever, such situation occurs then following rule is used to find out the availability of reimbursement method, according to agreement.

(?user profile:hasPurchased ?product) (?product LicenOnto:hasLicense ?license) (?license LicenOnto:replaceMethod OnliShopOnto:reimbursement) → (?user OnliShopOnto:canReturn OnliShopOnto:reimbursement)

Conclusion

Initially, undertaking an agreement without understanding is a major issue. Habitually customers agree with terms and conditions of an agreement without understanding. Incomplete knowledge and understanding about a license agreement in general and agree with an agreement without understanding specifically -is a main problem for one's own self. To solve the issue, a License Ontology is constructed, which is not only a platform for different license agreements to reside but users can access their required information by querying ontology. The application is designed in such a way that different license agreements can be easily plotted on same platform with minor changes according to agreement.

Based on ontologies, Digital License Agreement application (user interface of License Ontology) uses triples to define a meaningful sentence. Therefore, the results are based on the triples. These triples are defined so that the meaning of a statement in a license agreement should not be changed and the triples should be meaningful according to common user understanding.

Future work

The Semantic Web model for license agreements is extendable, to adopt other license agreements, for example agreements of service providing companies, hardware products, etc. Following agreements could also be model using the License Ontology.

Cross Boundary Agreements and its Conflicts

"Airline's Terms and Condition" could be constructed with similar method, as used for previous explained sub ontologies. Whenever, centralization of same categories of license agreements are achieved, then the ontology will be able to find out the conflicts between different laws (i.e. terms and conditions or license agreements). For example, airlines have to make agreements to use airports and airspace of other territories. Normally, settling downing the conflicts in agreements, consumes maximum time. Such system will not only explain the terms and conditions of each partner but will also explain the compromising statements that took place between them. These compromising statements will be helpful for upcoming organization to settle down their conflicts with the same/other organization.

SLAs and Business Processes

Cloud computing is a blend of concepts evolved from the SOA, grid computing and Virtualization. Adapting to this new way of computing is a hindrance for the companies to meet their requirements [START_REF] Tjoa | How the Cloud Computing Paradigm Could Shape the Future of Enterprise Information Processing[END_REF]. Laws and policies issues that must be addressed while adopting cloud computing for particular jurisdiction. Some of the challenging issues are; access, reliability, security, liability, IPR, ownership, portability and audit-ability. The failure of these issues causes resistance to provide services. Lingering mistrust has a negative impact on service providers. Cloud providers also face jurisdictional issues, such as: government intervention and costs of doing business [START_REF] Paul | Where is the cloud? Geography, economics, environment and jurisdiction in cloud computing. 1st Monday[END_REF].

We propose a Semantic solution for SLA cloud services which supports the consumers in finding the appropriate services that matches their specific requirements. As well as with awareness, consumers have choices to select the proper service according to their requirements. The proposed approach aims at globally unified SLA ontology. Organizations using this approach are believed to be benefited as (i) the categorization of agreements helps to define their "terms and conditions" using Semantic Web technology accordingly (ii) easy in understanding and comparing the different agreements for choosing a better option.

Mapping ontology will be used to relate business process and functions to cloud computing. Semantic rules encapsulate the tacit knowledge of enterprise business. The rules and relations used in Semantic Web technology facilitates businesses in selecting proper service of cloud computing. The selection of services depends on the requirements of customers according to business processes and functions.

Fig. 1 .

 1 Fig. 1. Online Shopping License Ontology