Marcos O Morais

Antônio S Brejão

Pedro O Costa Neto

João Helcio Raymundo

Gilberto Mendes

Dos Reis

Oduvaldo Vendrametto

Emerson Abraham

Carla C Parizi

Teixeira Sivanilza

Helton O Machado

Silva

Pedro L O Costa Neto

João G M Reis

Sivanilza T Machado

Helton R O Silva

Knowledge and Quality for Continuous Improvement of Production Processes

Keywords: Organizational Change, Process Improvement, Knowledge, Quality

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

Introduction

The organizations need to prepare people for the challenges of daily life are far beyond numbers and manage conflicts. It is necessary to rethink, learn and lead forms of sharing among the various types and levels of employees within organization.

Knowledge is created by individuals, and the organization must support employees with creativity and interest, providing them with contexts for knowledge creation, making it concrete. For an organization to remain competitive in the market, knowledge is a key strategic resource [START_REF] Choi | Effects of knowledge management strategy on organizational performance: a complementarity theory-based approach[END_REF].

The knowledge management is the collection of processes that govern the creation, dissemination and use of knowledge. Thus, to fully achieve the companies' goals, a new confluence of information technology and administration, a new link between strategy, culture and the organization's information systems are necessary [START_REF] Texeira Filho | Gerenciando conhecimento: como a empresa pode usar a memória organizacional e a inteligência competitiva no desenvolvimento dos negócios[END_REF]. Figure 1 shows the integration between departments.

The changes that are occurring and those that occur are not seen as mere trend, but permanent changes and favorable to all segments, as organizations have extremely important role also in the professional growth of its employees.

The purpose of this paper is analyze how the kind of knowledge (tacit and explicit) is related to use of tools of quality to continuous improvement in production process.

Organizational Change

It is configured as organizational change the modification of existing resources patterns, whether is structural, human, strategic or technological, reflecting an a systematic way or parts of the organization [START_REF] Junior | Mudança organizacional: aprofundando temas atuais em administração de empresas[END_REF]. A process of change, to be successful, must be well planned, well publicized, well justified and well executed. It is necessary to take on consideration the climate and the culture of the organization [START_REF] Neto | Administração com qualidade: conhecimentos necessários para a gestão moderna[END_REF].

Everyone in the organization should be aware and willing to carry out these changes, from the lowest organizational level to senior management. Therefore, for change to happen occur, it is necessary that the organizational values and attitudes change at all levels [START_REF] Duck | The change monster: the human forces that fuel or foil corporate transformation and chang[END_REF]. Actions such as hiring consultants and/or internal and external training help improve and speed the results, starting to promote awareness of the team. Emphasizes that the leader's role is necessary for the implementation of any change [START_REF] Falconi | O verdadeiro poder. INDG[END_REF].

Every change generates mistrust and resistance, since the comfort zones are affected. This resistance is inherent in any process of organizational change. The shift in paradigm becomes one of the points decisive in the success of the change. The cultural issue is a factor that should be treated with due importance by organizations in breaking paradigms, aiming to promote a culture of excellence that should be pursued and developed [START_REF] Falconi | O verdadeiro poder. INDG[END_REF].

Process Improvement

The improvement process within organizations becomes very important because it affects all sectors and levels. Improvement is always the order, because perfection, although it should always be purse, is unattainable [START_REF] Neto | Administração com qualidade: conhecimentos necessários para a gestão moderna[END_REF].

The improvement can be classified as continuous or incremental, where the first is accomplished through the analysis of how processes are operating. Incremental improvements are obtained by more drastic changes, offering deeper transformations and having a timely and more intense effect.

Continuous improvements are softer, but use simpler tools for analysis; already incremental improvements are more emphatic and use more advanced statistical tools or innovations to a stronger improvement of the shares.

Integrated Management: Quality and Knowledge

Quality tools are a first step to improving the profitability of the process and productivity through optimization of operations [START_REF] Lobo | Gestão da qualidade[END_REF]. Figure 2 shows the interaction between the stages of the continuous improvement of the Quality Management System process. The methodology of integrated management was proposed by [START_REF] Rodrigues | Ações para a qualidade: gestão estratégica e integrada para a melhoria dos processos na busca da qualidade e competitividade -planejamento e estratégia[END_REF], in order to achieve better organizational results, and is represented by strategic actions, structural, behavioral and operational. The main purpose is the focus of eliminating flaw in the processes to maximize and provide service and products closer to perfection. In support of continuous quality improvements are listed the basic quality tools [START_REF] Neto | Administração com qualidade: conhecimentos necessários para a gestão moderna[END_REF].

Quality Tools

For continuous quality improvement are listed the basic quality tools [START_REF] Neto | Administração com qualidade: conhecimentos necessários para a gestão moderna[END_REF]:

-Check Sheet: important to ensure that nothing that should be done or checked is forgotten. -Histogram: basic statistical tool of graphic sample description of variables, useful to understand their behavior. -Pareto chart: as it is represented the items under analysis in descending order of importance (value, frequency, etc) to prioritize analysis of the most important. -Ishikawa diagram: or cause and effect, or herringbone, used to identify causes of problems according to their nature. -Process Control Chart: main statistical tool of control processes.

-Stratification: used when there is suspected values for different origins of elements.

-Scatter diagram: appropriate to set behavior analysis of two quantitative variables considered simultaneously and evaluate their correlation. -Flow chart: provides a graphical representation of the interrelationship of all its activities, allowing a better visualization and understanding.

The following tools are also complementary in assisting quality management [START_REF] Carpinetti | Gestão da qualidade: conceitos e técnicas[END_REF].

-Brainstorming: is a group process in which individuals send free form of ideas, in large quantities, without criticism and in the shortest possible time. -5W1H or 5W2H: it is a tool to help structuring action plans from key issues ( What ?; Who ?; When ?; Where ?; Why ?; How ?). Although 5W2H adds the issue How much ?, emphasizing the cost of action. -5S:, a set of concepts and practices that are the main goals of the organization and rationalization of the work environment. The program refers to five Japanese words beginning with the letter S: seire, seiton, Seiso, Seiketsu and Shitsuke.

Knowledge

There are several levels of interaction that can arise within an organization for the development of knowledge that may be relevant in continuous improvement. The knowledge conversion model should be based on the interaction between the tactical knowledge and explicit [START_REF] Carpinetti | Gestão da qualidade: conceitos e técnicas[END_REF]. Tacit knowledge has a personal quality, subjective, the result of processing information, insights and technical abilities also that integrate the acquired knowledge, or know-how. Explicit knowledge refers to that transmitted into a formal language, systemic, onto a objectively from. Proposes a conversion model of knowledge where the integration of explicit knowledge and tacit knowledge complement each other, as shown in Figure 3 [START_REF] Nonaka | The knowledge-creating company: how Japanese companies create the dynamics of innovation[END_REF] . The knowledge spiral contemplates a successive process covering: a) Socialization: is the process which experiences are shared and tacit knowledge is socialized among individuals; b) Outsourcing: is the most important conversion model, because it allows the creation of new and explicit concepts through the tacit knowledge that normally are difficult to verbalize; c) Combination: This process is based on the exchange of explicit information and use paradigms of information technology; d) Internalization: is the mental absorption of the results of combinations checked in practice, or "learning by doing", returning to the beginning of tacit knowledge and the new working process at an advanced level of knowledge. While most share new mental models, tacit knowledge becomes part of the organizational culture, and by every successful internalisation, the cycle starts again, leading to improvement or innovation. Table 1 combines the main tools of quality and levels of knowledge, as well as its goals and objectives.

Existing tools and techniques in the management of knowledge and quality help define, analysis and measurement to solve problems.

Knowledge management is becoming an important integrator in organizations. Therefore, the implementation and use of systems such as ERP are the focus of studies that aim to address the effects on organizations under the technical and functional perspective [START_REF] Baskerville | Enterprise resource planning and organizational knowledge: patterns of convergence and divergence[END_REF].

Illustrative Case

An application of various ideas outlined in this work was done in an aluminum smelter company during the period of a year. This sets the presence of the action research methodology. Action research is a type of social research with empirical basis that is designed and carried out in close association with an action or resolution of a collective problem, which researchers and representative participants of the situation or problem are involved in cooperative mode or participatory [START_REF] Thiollent | Metodologia da pesquisa-ação[END_REF].

This work was carried out in an aluminum die casting company on the surroundings of São Paulo, which currently has 109 employees over three shifts. It was established by senior management should be prepared a medium-term action plan for the organization to become competitive stand out compared to its competitors. For this, to happen quality management methodologies and knowledge management were used in solving the problems. The main problem listed by managers was the high rate of noncompliance, Figure 4, caused by not having appropriate method on dealing some of the appointed internally problems and by the clients. As can be seen in Figure 4, the comparison between the 2013, with a total of twenty non-conformities and 2014, with a total of ten internal non-compliance where it is possible to see a fifty percent improvement after the implementations suggested by the tools of quality and knowledge management. Figure 5 shows shows the comparasion between 2013 and 2014 for external nonconformities. As can be seen in Figure 5, 2013 presented a total of eighteen nonconformities, and 2014, showed a total of seven external nonconformities cohere it is possible to see an improvement of sixty-one percent after the suggested tools implementations suggested by the tools of quality management and knowledge management.

Conclusion

Over the past few years organizations seek to develop methods to become increasingly competitive and stand out in the market in which they operate, but what is the gain that the implementation of knowledge and quality management tools can generate?

The research carried out in the company in question presented quantitative results and a substantial improvement in the quality, demonstrated by reducing the number of non-internal and external compliance.

The positive results were only possible after the interaction and the commitment of everyone in the organization, shared together the integration of management systems.

With this work we seek to offer a small contribution to organizations and emphasize the relationship of open tools for managing problems and improvements to the organization.

Fig. 1 .

 1 Fig.1. Model for knowledge management. Source: Adapted[START_REF] Neto | Administração com qualidade: conhecimentos necessários para a gestão moderna[END_REF]

Fig. 2 .

 2 Fig.2. Continuous improvement of the Quality Management System. Source:[START_REF]Associação Brasileira de Normas Técnicas[END_REF] and[9]

Fig. 3 .

 3 Fig.3. Knowledge Spiral. Source: Adapted[START_REF] Nonaka | The knowledge-creating company: how Japanese companies create the dynamics of innovation[END_REF]

Fig. 4 .

 4 Fig. 4. Control of non-conformities internal

Fig. 5 .

 5 Fig. 5. Control of no external compliance

Table 1 .

 1 Quality Tools and Levels of Knowledge

	Quality Tools	Homes	Level
	Cause and Effect Diagram	Identify the relationship between the result and all causes of a problem	Tacit
		Encourage the identification, measurement and
	Pareto chart	the priority of the most important problems of	Explicit
		a process
	Flowchart	Provides the sequences of process steps on easy veining	Explicit
	Letter Control	Monitor the variability and the problem of a pro-cess through charts explicit	Explicit
	Check Sheet	Enumerate the constant occurrences of a produc-tion process at a given time	Tacit
	Histogram	Monotoring identification the monitoring of vari-ables of a process	Explicit
	Diagram of Dispersion	Provide statistics of dependent and independent variables of a process	Explicit
		Detail the perceptions of a particular subject,
	Brainstorming	looking for different opinions from the collective	Tacit
		creativity
		Represent and unify the processes, on organizing
	5W2H	action plans and statement of Assistant methods	Tacit
		to indicators, to a management
	Stratification	Identify variables from different sources in order to avoid inconsistent analyzes	Tacit
		Collaborate in the behavioral modification of em-
	5S	ployees in order to have a sense of organization keeping the pleasant atmosphere and abolishing	Tacit
		waste


Minoro Jair

Nelio Dos Abe

Cristina Reis

Avelino De Oliveira

Palma

Pimenta

Jair M Abe
email: jairabe@uol.com.br

Nelio F Dos Reis

Cristina C De Oliveira

Avelino P Pimenta
email: appimenta@gmail.com

A Logical Framework for Imprecise and Conflicting Knowledge Representation for Multi-agent Systems

Keywords: multi-agent systems, conflicts in distributed systems, multiagents and logical representation, paraconsistente logics

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

Introduction

Multi-agent systems have emerged as one of the most important areas of research and development in information technology in the 1990s. Since the theme has received attention of specialists and nowadays a number of research topics has been considered such as cooperative distributed problem solving, mechanism design, auctions, game theory, multi-agent planning, negotiation protocols, multi-agent learning, conflict resolution, agent-oriented software engineering, including implementation languages and frameworks, E-business agents, novel computing paradigms (autonomic, grid, P2P, ubiquitous computing), among innumerous themes.

In this paper we are focused in the problem of conflict resolution among agents. For this task we need a suitable language for represent agent's communication and moreover inference rules to get interest results; in other words we need an underlying logical system to represent agent's interaction.

Agents' conflicts arise for different reasons, involve different concepts, and are dealt with in different ways, depending on the kind of agents and on the domain where they are considered.

For example,  incompleteness and uncertainty of the agents' knowledge or beliefs: in dynamic contexts, an agent may have more recent or more complete information than the others, and the differences in the agents' knowledge create knowledge conflicts;  limited or unavailable resources: not all agents have access to the same resources, thus resulting in resource conflicts;  differences in the agents' skills and points of view: autonomous and heterogeneous agents have different abilities, or even different preferences, which can cause conflicts if the agents' pieces of information are not comparable, if they come up with different answers to the same questions, or if they are strongly committed to their own preferences. Up till now, the focus has been much on how to avoid, solve or get rid of conflicts. However, recent research has shown that conflicts have positive effects in so far as they can generate original solutions and be a basis for a global enrichment of the knowledge within a multi-agent system. Since more and more concern is attached to agents' teamwork and agents' dialogue, conflicts naturally arise as a key issue to be dealt with, not only with application dedicated techniques, but also with more formal and generic tools.

Paraconsistent, Paracomplete, and Non-alethic Logics

In what follows, we sketch the non-classical logics discussed in the paper, establishing some conventions and definitions. Let T be a theory whose underlying logic is L. T is called inconsistent when it contains theorems of the form A and A (the negation of A). If T is not inconsistent, it is called consistent. T is said to be trivial if all formulas of the language of T are also theorems of T. Otherwise, T is called non-trivial.

When L is classical logic (or one of several others, such as intuitionistic logic), T is inconsistent iff T is trivial. So, in trivial theories the extensions of the concepts of formula and theorem coincide. A paraconsistent logic is a logic that can be used as the basis for inconsistent but non-trivial theories. A theory is called paraconsistent if its underlying logic is a paraconsistent logic.

Issues such as those described above have been appreciated by many logicians. In 1910, the Russian logician Nikolaj A. Vasil'év (1880Vasil'év ( -1940) ) and the Polish logician Jan Lukasiewicz (1878-1956) independently glimpsed the possibility of developing such logics. Nevertheless, Stanislaw Jaskowski was in 1948 effectively the first logician to develop a paraconsistent system, at the propositional level. His system is known as 'discussive' (or discursive) propositional calculus'. Independently, some years later, the Brazilian logician Newton C.A. da Costa (1929-) constructed for the first time hierarchies of paraconsistent propositional calculi C i , 1  i   of paraconsistent first-order predicate calculi (with and without equality), of paraconsistent description calculi, and paraconsistent higher-order logics (systems NF i , 1  i  ). Another important class of non-classical logics are the paracomplete logics. A logical system is called paracomplete if it can function as the underlying logic of theories in which there are formulas such that these formulas and their negations are simultaneously false. Intuitionistic logic and several systems of many-valued logics are paracomplete in this sense (and the dual of intuitionistic logic, Brouwerian logic, is therefore paraconsistent).

As a consequence, paraconsistent theories do not satisfy the principle of noncontradiction, which can be stated as follows: of two contradictory propositions, i.e., one of which is the negation of the other, one must be false. And, paracomplete theories do not satisfy the principle of the excluded middle, formulated in the following form: of two contradictory propositions, one must be true.

Finally, logics which are simultaneously paraconsistent and paracomplete are called non-alethic logics.

A Logical Framework for Representing Impreciseness, Conflicts and Paracompleteness

We present, in this section, the multimodal predicate calculi M, based on annotated logics extensively studied by Abe [START_REF] Abe | Fundamentos da lógica anotada[END_REF], [START_REF] Akama | Many-valued and annotated modal logics[END_REF] and multimodal systems considered in [START_REF] Fagin | Reasoning about knowledge[END_REF].

The symbol  = <, , ~> indicates some finite lattice with operator called the lattice of truth-values. We use the symbol  to denote the ordering under which  is a complete lattice,  and ┬ to denote, respectively, the bottom element and the top element of . Also,  and  denote, respectively, the greatest lower bound and least upper bound operators with respect to subsets of . The operator ~:  will work as the "meaning" of the negation of the system M.

The language of M has the following primitive symbols: 1. Individual variables: a denumerable infinite set of variable symbols: x 1 , x 2 , ... 2. Logical connectives:  (negation),  (conjunction),  (disjunction), and  (implication). 3. For each n, zero or more n-ary function symbols (n is a natural number). 4. For each n  0, n-ary predicate symbols. 5. The equality symbol: = 6. Annotational constants: each member of  is called an annotational constant.

Modal operators:

[] 1 , [] 2 , ... , [] n , (n  1), [] G , [] C G , [] D G (
for every nonempty subset G of {1, ... , n}). 8. Quantifiers:  (for all) and  (there exists). 9. Auxiliary symbols: parentheses and comma.

A 0-ary function symbol is called a constant. We suppose that M possesses at least one predicate symbol.

We define the notion of term as usual. Given a predicate symbol p of arity n and n terms t 1 , ... , t n , a basic formula is an expression of the form p(t 1 , ... , t n ). An annotated atomic formula is an expression of the form p  (t 1 , ... , t n ), where  is an annotational constant. We introduce the general concept of (annotated) formula in the standard and[] D G A are also formulas [START_REF] Fagin | Reasoning about knowledge[END_REF].

way. For instance, if A is a formula, then [] 1 A, [] 2 A, ... , [] n A, [] G A, [] C G A,
Among several intuitive readings, an atomic annotated formula p  (t 1 , ... , t n ) can be read: it is believed that p(t 1 , ... , t n )'s truth-value is at least .

Definition 1 Let A and B be formulas. We put

A  B = Def. (A  B)  (B  A) and *A = Def. A  ((A  A)  (A  A)). The symbol '' is called biconditional and '*' is called strong negation.
Let A be a formula. Then:

 0 A = Def. A,  1 A = Def. A, and  k A = Def. ( k-1 A), (k  N, k > 0). Also, if   , ~0 = Def. , ~1 = Def. ~, and ~k = Def. ~(~k -1 ), (k  N, k > 0). If A is an atomic formula p  (t 1 , ... , t n ), then a formula of the form  k p  (t 1 , ... , t n ) (k  0) is called a hyper-literal.
A formula other than hyper-literals is called a complex formula.

The postulates (axiom schemata and primitive rules of inference) of M are the same of the logics Q [START_REF] Abe | Fundamentos da lógica anotada[END_REF] plus the following listed below [START_REF] Fagin | Reasoning about knowledge[END_REF], where A, B, and C are any formulas whatsoever, p(t 1 , ... , t n ) is a basic formula, and , ,  j are annotational constants.

M1

) [] i (A  B)  ([] i A  [] i B), i = 1, 2, ... , n M2) [] i A  [] i [] i A, i = 1, 2, ... , n M3) *[] i A  [] i *[] i A, i = 1,2, ... , n M4) [] i A  A, i = 1, 2, ... , n M5) A A i [] , i = 1, 2, ... , n M6) [] G A   iG [] i A M7) [] C G A  [] G (A  [] C G A) M8) [] D i} { A  [] i A, i = 1, 2, ... , n M9) [] D G A  [] D G ' A if G'  G M10) B A A B A B G G [] ) ( []    M11) x[] i A  [] i xA, i = 1, 2, ... , n M12) *(x = y)  [] i *(x = y), i = 1, 2, ... , n
M is an extension of the logic Q. As Q contains classical predicate logic, M contains classical modal logic S5, as well as the multimodal system studied in [START_REF] Fagin | Reasoning about knowledge[END_REF] in at least two directions. So, usual all valid schemes and rules of classical positive propositional logic are true. In particular, the deduction theorem is valid in M ant it contains intuitionistic positive logic.

Theorem 1 M is non-trivial. Now we introduce a semantical analysis by using Kripke models. Definition 2 A Kripke model for M (or M structure) is a set theoretical structure

K = [W, R 1 , R 2 , ... , R n , I]
where W is a nonempty set of elements called 'worlds'; R i (i = 1, 2, ... , n) is a binary relation on W such that it is an equivalence relation. I is an interpretation function with the usual properties with the exception that for each n-ary predicate symbol p we associate a function p I :W n  .

Given a Kripke model K for the language L of M, the diagram language L(K) is obtained as usual.

Definition 3 If A is a closed formula of M, and wW, we define the relation K,w ╟ A (K,w force A) by recursion on A:

1. If A is atomic of the form p  (t 1 , ... , t n ), then K,w ╟ A iff p I (K(t 1 ), ... ,K(t n ))  . 2. If A is of the form  k p  (t 1 , ... , t n ) (k  1), K,w ╟ A iff K,w ╟  k-1 p ~(t 1 , ... , t n ). 3. Let A and B formulas. Then, K,w ╟ (A  B) iff K,w ╟ A; K,w ╟ B; K,w ╟ (A  B) iff K,w ╟ A or K,w ╟ B; K,w ╟ (A  B) iff it is not the case that K,w ╟ A or K,w ╟ B; 4. If F is a complex formula, then K,w ╟ (F) iff it is not the case that K,w ╟ F. 5. If A is of the form (x)B, then K,w ╟ A iff K,w ╟ B x [i] for some i in L(K). 6. If A is of the form (x)B, then K,w ╟ A iff K,w ╟ B x [i] for all i in L(K). 7. If A is of the form [] i B then K,w ╟ A iff K,w' ╟ B for each w'  W such that wR i w', i = 1, 2, ... , n Definition 4 Let K = [W, R 1 , R 2 , ... , R n , I] be a Kripke structure for M. The Kripke structure K forces a formula A (in symbols, K ╟ A), if K,w ╟ A for each w  W. A formula A is called M-valid if for any M-structure K, K ╟ A. A formula A is called valid if it is M-
valid for all M structure. We symbolize this fact by ╟ A.

Theorem 2 Let K = [W, R 1 , R 2 , ... , R n , I] be a Kripke structure for M. Then 1. If A is an instance of a propositional tautology then, K ╟ A 2. If K ╟ A and K ╟ A  B, then K ╟ B 3. K ╟ [] i (A  B)  ([] i A  [] i B), i = 1, 2, ... , n 4. K ╟ [] i A  [] i [] i A, i = 1, 2, ... , n 5. K ╟ [] i A  A, i = 1, 2, ... , n 6. If K ╟ A then K ╟ [] i A, i = 1, 2, ... , n
Theorem 3 Let K be a Kripke model for M and F a complex formula. Then we have not simultaneously K,w ╟ F and K,w ╟ F.

Theorem 4 Let p(t 1 , ... , t n ) be a basic formula and , ,   . We have ╟ p  (t 1 , ... , t n ); ╟ p  (t 1 , ... , t n )  p  (t 1 , ... , t n ), if   ; ╟ p  (t 1 , ... , t n )  p  (t 1 , ... , t n )  p  (t 1 , ... , t n ), where  =    Theorem 5 Let A and B be arbitrary formulas and F a complex formula. Then:

╟ ((A  B)  ((A  *B)  *A)); ╟ (A  (*A  B)); ╟ (A  *A); ╟ (F  *F); ╟ A  **A; ╟ xA  x*A; ╟ (A  B)  *(*A  *B); ╟ A  x*A; ╟ xA  B  x(A  B); ╟ A  xB  x(A  B)
Corollary 5.1 In the same conditions of the preceding theorem, we have not simultaneously K ╟ ╖A and K ╟ A. The set of all formulas together with the connectives , , , and ╖ has all properties of the classical logic.

Theorem 6 There are Kripke models K such that for some hyper-literals A and B and some worlds w and w'  W, we have K,w ╟ A and K,w ╟ A and it is not the case that K,w' ╟ B.

Proof. Let W = {{a}} and R = {({a},{a})} (that is w = {a}) and p(t 1 , ... , t n ) and q(t' 1 , ... , t' n ) basic (closed) formulas such that I(p)  ┬ and I(q)  . As ┬  ┬, it follows that p ┬ (t 1 , ... , t n )  ┬. Also, ┬  ~┬. So, p I  ~┬. Therefore, K,w ╟ p ┬ (t 1 , ... , t n ) and K,w ╟ p ~┬(t 1 , ... , t n ). By condition 2 of Definition 4.2, it follows that K,w ╟  p ┬ (t 1 , ... , t n ). On the other hand, as it is false that   ┬; it follows that it is not the case that q I  ┬, and so, it is not the case that K,w ╟ q  (t' 1 , ... , t' n ).

Theorem 7 For some systems M there are Kripke models K such that for some hyper-literal formula A and some world w  W, we don't have K,w ╟ A nor K,w ╟ A.

Corollary 7.1 For some systems M there are Kripke models K such that for some hyper-literal formulas A and B, and some worlds w, w'  W, we have K,w ╟ A and K,w ╟ A and we don't have K,w ╟ B nor K,w ╟ B.

The earlier results show us that there are systems M such that we have "inconsistent" worlds, "paracomplete" worlds, or both. Now we present a strong version these results linking with paraconsistent, paracomplete, and non-alethic logics.

Definition 5 A Kripke model K is called paraconsistent if there are basic formulas p(t 1 , ... , t n ), q(t 1 , ... , t n ), and annotational constants ,    such that K,w ╟ p  (t 1 , ... , t n ), K,w ╟  p  (t 1 , ... , t n ), and it is not the case that K,w ╟ q  (t 1 , ... , t n ). Definition 6 A system M is called paraconsistent if there is a Kripke model K for M such that K is paraconsistent.

Theorem 8 M is a paraconsistent system iff # 2.

Proof. Define a structure K = [{w}, {(w, w)}, I] such that

      T I I p q
It is clear that p I  ┬, and so K ╟ p ┬ (t 1 , ... , t n ). Also, p I  ~┬, and, so K ╟ p ~┬(t 1 , ... , t n ), or K ╟ p ┬ (t 1 , ... , t n ). Also, it is not the case that q I (t 1 , ... , t n )  , so it is not the case that K,w ╟ q  (t 1 , ... , t n ) .

Definition 7 A Kripke model K is called paracomplete if there are a basic formula p(t 1 , ... , t n ) and an annotational constant    such that it is false that K,w ╟ p  (t 1 , ... , t n ) and it is false that K,w ╟ p  (t 1 , ... , t n ). A system M is called paracomplete if there is a Kripke models K for M such that K is paracomplete.

Definition 8 A Kripke model K is called non-alethic if K are both paraconsistent and paracomplete. A system M is called non-alethic if there is a Kripke model K for M such that K is non-alethic.

Theorem 9 If # 2, then there are systems M which are paracomplete and systems M' that are not paracomplete, #' 2.

Corollary 9.1 If # 2, then there are systems M which are non-alethic and systems M' that are not non-alethic, #' 2.

Theorem 10 Let U be a maximal non-trivial maximal (with respect to inclusion of sets) subset of the set of all formulas. Let A and B formulas whatsoever. Then if A is an axiom of M, then

A  U; A  B  U iff A  U and B  U ;A  B  U iff A  U or B  U; A  B  U iff A  U or B  U; If p  (t 1 , ... , t n )  U and p  (t 1 , ... , t n )  U, then p  (t 1 , ... , t n )  U, where  =   ;  k p  (t 1 , ... , t n )  U iff  k-1 p ~(t 1 , ... , t n )  U. If A and A  B  U, then B  U; A  U iff *A  U. Moreover A  U or *A  U. If A is a complex formula, A  U iff A  U. Moreover A  U or A  U. If A  U, then [] i A  U. Proof.

Concluding Remarks

It is quite interesting to observe the role of conflict within a multiagent system, i.e. how this system may evolve thanks to, despite, or because of conflicts. Such concept receives different 'interpretations' or characterizations depending on of the domain considered. Some considerations regarding to it  It is easier not to be in conflict than to be in conflict. The former may mean that the agents are not even interacting. The latter supposes that the agents are within the same context.  incompleteness and uncertainty of the agents' knowledge or beliefs: in dynamic contexts, an agent may have more recent or more complete information than the others, and the differences in the agents' knowledge create knowledge conflicts;  limited or unavailable resources: not all agents have access to the same resources, thus resulting in resource conflicts;  differences in the agents' skills and points of view: autonomous and heterogeneous agents have different abilities, or even different preferences, which can cause conflicts if the agents' pieces of information are not comparable, if they come up with different answers to the same questions, or if they are strongly committed to their own preferences.  When two agents (in this case, e.g. two robots) a conflict does not seem to be necessarily symmetric: conflict (a, b) does not imply conflict (b, a). When two robots roam in a 2D space for instance, the notion of spatial conflict appears only at the time when a robot attempts to move to the location of the other robot. But the latter does not see this conflict.  Are conflicts useful? The answer depends on the problem. To be useful, a conflict must be observed. For example, if an agent think about a solution and ask for two other agent's (experts) for an opinion and they have contradictory opinions, the former agent can decide, for instance, consult a third agent.  What we learn from a conflict depends on the situation. Learning is possible if agents are aware of the conflict.  Conflicts are positive in certain cases, e.g. they may create specific behaviours, create competition, or stimulate inference.

Up till now, the focus has been much on how to avoid, solve or get rid of conflicts. However, recent research has shown that conflicts have positive effects in so far as they can generate original solutions and be a basis for a global enrichment of the knowledge within a multiagent system. Thus this work is a contribution in this direction, showing, for instance that it is unnecessary to try to avoid conflicts; on the contrary with a logical knowledge representation of conflicts we can manage mathematically them and so it is possible to understand better the nature of them.

  Let us show only 3. In fact, if p  (t 1 , ... , t n )  U and p  (t 1 , ... , t n )  U, then p  (t 1 , ... , t n )  p  (t 1 , ... , t n )  U by 2. But it is an axiom p  (t 1 , ... ,t n )  p  (t 1 , ... , t n )  p  (t 1 , ... , t n ), where  =   . It follows that p  (t 1 , ... , t n )  p  (t 1 , ... , t n )  p  (t 1 , ... , t n )  U,and so p  (t 1 , ... , t n )  U, by 6.Given a set U of formulas, define U/[] i = {A[] i A  U}, i = 1, 2, ... , n. Let us consider the canonical structure K = [W, R i , I] where W = {UU is a maximal non-trivial set} and the interpretation function is as usual with the exception that given a n-ary predicate symbol p we associate the function p I :W n   defined by p I (t  1 , ... , t  n ) = def. { p  (t 1 , ... , t n )  U} (such function is well defined, so p  (t 1 , ... , t n )  U). Moreover, define R i = Def. {(U, U') U/[] i  U'}.Lemma 1 For all propositional variable p and if U is a maximal non-trivial set of formulas, we have p pI(t1, ... , tn) (t 1 , ... , t n )  U.Proof. It is a simple consequence of the previous theorem, item[START_REF] Cresswell | Logics and Languages[END_REF]. Theorem 11 For any formula A and for any non-trivial maximal set U, we have (K, U) ╟ A iff A  U. Proof. Let us suppose that A is p  (t 1 , ... , t n ) and (K, U) ╟ p  (t 1 , ... , t n ). It is clear by previous lemma that p pI(t1, ... , tn) (t 1 , ... , t n )  U. It follows also that p I (t  1 , ... , t  n )  . It is an axiom that p pI(t1, ... , tn) (t 1 , ... , t n )  p  (t 1 , ... , t n ). Thus, p  (t 1 , ... , t n )  U. Now, let us suppose that p  (t 1 , ... , t n )  U. By previous lemma, p pI(t1, ... , tn) (t 1 , ... , t n )  U. It follows that p I (t  1 , ... , t  n )  . Thus, by definition, (K, U) ╟ p  (t 1 , ... , t n ). By theorem 3.20,  k p  (t 1 , ... , t n )  U iff  k-1 p ~(t 1 , ... , t n )  U. Thus, by definition 3.4, (K, U) ╟  k p  (t 1 , ... , t n ) iff (K, U) ╟  k-1 p ~(t 1 , ... , t n ) . So, by induction on k the assertion is true for hyper-literals.The other cases, the proof is as in the classical case.

Corollary 11.1 A is a provable formula of M iff ╟ A


Papalardo Fabio
email: fabiopapalardo@gmail.com

F R De Carvalho

Sacomano B Jose

Production Planning in Intra-organizational Network -A Study under the point of view of Annotative Paraconsistent Logic

Keywords: Planning, Networks of Companies, Paraconsistent Logic

Competitiveness among enterprises, acting within global sustainability, has resorted to several types of administration in order to keep companies in the vanguard of the market. One of the most efficient types of administration is effective Planning, in such a way as to perform a task at the minimum time required and the lowest possible cost.Planning has become ever so complex, due to the innumerable demands from technology and market. A relevant aspect of Planning is that the sectors that influence it, whether productive or not, compound a chain of influences that will determine either success or failure of such Planning.One manner to tackle a network matrix analysis is by Para-consistent Logic, a mathematical model that does not follow Classic Logic.It was then possible to verify the efficacy of this model of Planning analysis, as a method to be used and studied and subsequently adopted and used.

Introduction

The globalization phenomenon has brought into the market ever more so the competitiveness among companies and countries, and, in order to maintain sustainable management, new administration models are necessary.

Innovative companies need agile action towards products and services in order to respond quickly and explore new conditions. This agile action, however, must be systematic [START_REF] Ernst | Agile requirements engineering via paraconsist reasoning -Journal homepage[END_REF].

At the industrial area, further to the development of new equipments and new technologies, the administration of Production Planning has become much more complex to face demands from market and new technologies.

One of the ways of analyzing this aspect is under the point of view of Networks of Companies; specifically, as far as Production Planning the analysis is done, an Intraorganizational Network.

Within an organization, and among organizations, there must be resource and knowledge channels, and these can be studied as a network [START_REF] Kajikawa | Multiscale analysis of interfirm networks in regional clusters[END_REF].

The study of resource channels can be analyzed in various manners, always keeping in mind that an intra-organizational network has its matrix aspect, as a company's sectors or departments do form among themselves a matrix network of interdependency.

Analysis resources, like Statistics, Matlab, Ucinet and others, have been studied for a wider vision of Production Planning.

In this work we shall introduce Annotative Paraconsistent Logic in order to visualize a scenery that presents all sectors involved in the industrial process, so to permit efficient Planning, as well as Control aspects to make sure that all planned requisites are kept during production.

2

Theoretic Foundation

Production Planning

The most important aspect of the context of development and maintenance of a control and planning production system perhaps is the continual change at the competition approach, and such changes should occur from the technological to the strategic and the legal areas [START_REF] Vollmann | Sistemas de planejamento e controle da produção[END_REF].

Along with technological development and a wide range of market strategies, as well as alterations of pertinent legislation due to globalization, Production Planning becoming ever more complex, as the number of variables increases systematically and some of these variables may be subject to alteration or even beyond assessment.

Independently of the type of manufacture or manufacturing system, Planning is an essential factor to the success of the task. Traditional systems, as ERP and others are no longer sufficient for a safe and effective planning. Various ERP projects draw into tangible and intangible developments, considerable in different areas, and to attain competitive advantages for organizations; nevertheless there are several histories of failures as companies use ERP [START_REF] Behboudi | Identifying and ranking the effective factors on selecting Enterprise Resource Planning (ERP) system using the combined Delphi and Shannon Entropy approach[END_REF].

Therefore, new thinking manners, new organizational formats and new logic reasoning must be implemented in order to keep a company competitive as it operates inside an ever changing universe.

Company Network

One way of planning and analyzing an organization is to look at it as it were a network, that is, where sectors or departments involved in the production process are seen as actors of this task.

The notion of network organization implies the need to rethink the limits of a sector separately, emphasizing the importance of the several types of relationship it has with other actors and institutions [START_REF] Mizruchi | Análise de redes sociais: avanços recentes e controvérsias atuais[END_REF].

The connection or influence that a sector or actor applies into another must be taken into consideration, so that it is possible a more global view of the process, instead of a static vision of each department by itself.

Obviously each sector receives and exerts different influence over another. The network study defines as central, the department or actor under scrutiny, and proceeds to identify how the other sectors receive and exert influence over it.

In this work, Planning is considered as central to a network, and the actors are: Sales; Product Project; Industrial Engineering or Processes; Production; Quality; Purchasing and Planning, the central agent.

The intensity of relationship between actors is called "density" and it shows the degree of influence of a sector over another. The assessment of density is important to quantify the network.

Networks inside an organization and between organizations must work as a channel of resources and knowledge. It has been found out that the proprieties of regional clustersshow marked differences, which intensify as the size of the network increases. It also became evident that companies connect themselves in different modules; thereforenetwork activity must focus on different modules, in order to support the development of networks [START_REF] Kajikawa | Multiscale analysis of interfirm networks in regional clusters[END_REF].

The network performance, as far as the flux of resources and knowledge, can be improved by adding connections inside an organization [START_REF] Przemysławrózewski | -Knowledge workers' collaborative learning behavior modeling in an organizational social network -Journal homepage[END_REF].

Meaningful role in these relationships is the strengthening of the links of experience and knowledge of the central. Added knowledge affects positively the company's competitiveness [START_REF] John Qi | CHIA-HAN YANG -Information technology and organizational learning in knowledge alliances and networks: Evidence from U.S. pharmaceutical industry[END_REF].

Paraconsitent Logic

In order to analyze an inter-organizational network company, we shall adopt a non classical logic, the so called paraconsistent logic.

Operations in models that tolerated the presence of inconsistencies are vital to uphold solutions of particular designs [START_REF] Ernst | Agile requirements engineering via paraconsist reasoning -Journal homepage[END_REF].

In annotated paraconsistent logic, one proposition A can be expressed by a matrix (µ;λ), where μ is the degree of belief A and λ is the degree of disbelief that is, A. Let us consider the maximum degree as one (1) and the minimum as zero (0). Therefore, a proposition A can be expressed by symbol "p", denoting uppA(1;0), that is, the grade of belief maximum and a grade of non belief minimum; on the other hand, the denial of A can be expressed by the symbol ¬ pA(0; 1), and reflects, by definition ¬ pA(0; 1) ↔ pA(1;0).

In paraconsistent logic may be evidence with degree of belief or disbelief different from the maximum (one), or the minimum (zero), i.e., there may be belief and disbelief in a proposition A.Placed in a Cartesian diagram, with the degree of belief in xaxis and the y-axis in disbelief, all the notes are a unit square (Fig. 1 left side), where are highlighted the extreme points and the point (0.6, 0.2). Importantly, the sum of two parameters μ and λ will not always be 1 (one) as common sense would indicate, since the degrees of belief and disbelief may be independent of each other, for example, a belief factor can be favorable to time execution of a task, and their degree of disbelief can be affected in relation to the delivery time from a vendor.

Therefore we can have extreme situations in which pA(0;0) or also pA(1;1). In the first case, there is no evidence of belief or non belief, that is, there are no available information and this extreme situation we call "undetermined". The other case we have evidence of maximum belief and, at the same time, evidence of maximum non belief, which we cal "inconsistent".The above extreme cases along with the concepts of classical logicin it we call pA(1;0) "Truthful", as the evidences of belief are maximum and non belief are minimum, and the negative of it pA(0;1) we call "False", as it denies the Truthful.One point may be closer or more distant from the extremes. It gives us a visual idea of the trend: Truthfulness, Falsity, Inconsistency or Indetermination. Of course the ideal is to have an affirmation the closest possible to the extreme point pA(1;0) -Truthful. So, is defined the "Degree of Certainty": it indicates where we are positioned in relation to the ideal pA(1;0). The degree of certainty is defined by the equation H = μ -λ. Graphically, the degree of certainty is expressed by a line in the graphic.

This is an example that we will use in our methodology. H = 0,7. Many combinations may result in H = 0,7, that is, pA(1;0,3) or pA(0,9;0,2) or pA(0,8;0,1) or pA(0,7;0) and many others.

For the analysis of this work will be considered the region of the unit square, defined by M ≥ 0.7, called certainly region (Fig. 1

Methodology

The present investigation involved structured interviews with specialists in the areas of Sales, Product Project, Fabrication Processes, Manufacturing, Quality, Purchasing and Planning. The company that was selected is an industry of capital goods, producer of drilling equipment and fluids pumping. Any product is usually "customized", and this is determinant that each product is manufactured just once. Consequently, Planning is essential for low cost and minimum production time, as there is no possibility of improving planning for next production. Interviews were conducted with specialists of managerial rank, one of each area, except the production, for which we interviewed two specialists. Such was necessary because this department is the most sensible to variations of the planning sector, and that is the reason to obtain two opinions of the production area. The criterion adopted for analysis is that each specialist answered questionsalways through a matrix (μ;λ) and added notes explaining reasons why he had indicated the degrees of belief or non belief. Data was organized in a table. The results indicated by specialists from the same area, in this case, the production, were considered through the disjunction criterion (V), where, p1(μ1; λ1)V p2(μ2; λ2)→ p1 or 2 (μmax; λmin). Results from specialists of different areas were considered through the conjunction criterion (˄), where, p1(μ1; λ1) ˄ p2(μ2; λ2)→ p1 or 2 (μmim; λmax) [START_REF] De | Tomadas de Decisão com Ferramentas da Lógica Paraconsistente Anotada[END_REF].

The minimum degree of certainty chosen for this work was H = 0,7. Observing the Figure 2 it appears that the area corresponding to the real area (or certain favorable), we verify that the area in the certainty zone is the area of a triangle 0,3 x 0,3/2 , that is a surface of 0,045; graphic total area is the surface of a square 1 x 1, or a surface of 1. The percentage of the certainty area as related to the total surface is 1 -(0,045 / 1) = 0,955 and the certainty is 95,5%, and this is a good number as far as planning is concerned. It is worthy to mention that for more restricted values above 0,7the costs for the functioning of the network can be very high.

The question brought up was: "How do you classify the condition of the analyzed item?"

The analyzed items were determined by all the consulted specialists through non structured interviews in order to determine the influences of each department over the Planning, considered as the center of the intra-organizational network in this study.

For a better assessment, each particular question was divided into three parts, each corresponding an interval of the degree of certainty: within the target 0,7 ≤H ≤ 1 (a); with relative degree of acceptance -0,7 ≤ H ≤ 0,7 (b); with no acceptance at all -1 ≤ H ≤ 0, Once completed the research, the marks determined by μ and λ were plotted on the graphic. The set of points permits a graphic idea of the network. The total influence of the 12 factors considered is indicated as the gravity center of the network; each point is a knot in a net and the gravity center is the resultant effect of the knots or the center of them [START_REF] De | Tomadas de Decisão com Ferramentas da Lógica Paraconsistente Anotada[END_REF].

To each knot was assigned the same importance; therefore there are no different values (weights) to add to a knot in order to calculate the gravity center. In case a knot exerts influence of a different weight over the gravity center, a weighted average must be calculated. In this case, the arithmetic mean was also calculated and it did coincide with the weighted average. Therefore, we come up with the global results and hence the present scenario for the sector of Planning.

Result and Discussion

After the research the results were found, and according to the disjunction criterion (V) among specialists of the same area -Production, we have p1prod(μ1; λ1) V p2prod(μ2; λ2) → p1ou 2 (μmax;λmin): The Center of Gravity, the total effect of the knots, or the center of gravity of the network, comes up as pplan(0,80; 0,25).

It was verified that the center of gravity is not in the region of the desired, as it is not on the region of certainty.

As the objective of Planning is to determine a scenario that makes sure that the task will be performed, individually each factor of lesser certainty was re-analyzed, in order to come up with the global result desired by Planning, that is, right on the area where H≥0,7.

The chosen factors were Training, KanBan, Quality System, SPC. These factors were chosen based on the notations and comments presented by the specialists when answering the questions.

The Training that had the matrix ptrain(0,8; 0,3), was based on eventual training programs, which, although not leading to a 100% certainty, can be effective as far as the workforce involved in Production. New matrix ptrain (0,9; 0). KanBan had a matrix pkan(0,7; 0,3); the system analyzed was in the installation process, it was only partially installed. As the installation experience was being positive, total installation was decided. New matrix pkan(1; 0).

The Quality System had a matrix pqual(0,8; 0,3); it was a system in the installation process; it was installed only partially. As the installation experience was positive; it was totally installed. New matrix pqual(1; 0). SPC which had a matrix pspc(0,8; 0,3) was also being installed, with the same characteristics of the two other items; total installation was decided. The factors chosen for modification in order to achieve the desired result were based on the criteria of lower investment to achieve a combination of μ and λ. In this work was done using the comparison of the most critical items.

New matrix pspc(1; 0). Other factors, for example, Equipments, also had a low matrix of certainty Pequip (0,7; 0,3): it was considered poorly updated; however a decision to bring it up to date would demand a considerable investment and a long installation periodthe decision was not to improve this item. Revised planning altered items:

Conclusion

Paraconsistent logic offers a tool for analysis, which, through the concept of interorganizational network, guides for attaining the desired scenario, even when some factors or premises are not ideal.

Even when the present scenario does not reach the desired objectives, a reevaluation may lead to changes, through the adjustment of a few items, thus obtaining a scenario within the expected indicators.

It is important to notice that the questions that were brought up are based on the control of premises, that is, planning is only well managed when the execution of its parameters are being controlled.

In the next paper, we will research the reanalysis of factors for the modification of anactual scenario, using paraconsistent logic and presenting it through a mathematical frame.

Still on this line of thought, we shall research how paraconsistent logic can be used for Production Control, and together with the present work, we intend to present Planning and Production Control according to this logic.

Fig. 1 .

 1 Fig. 1. Cartesian Diagram

  7 (c), as we can see in the following list of statements: SALES: -"Program Trends": Stable (a); Increase (b); Decrease (c) PROJECT PRODUCT: -"Benchmarking": Very Competitive (a); Somewhat Competitive (b); Hardly Competitive (c) / "Detailed Description": High Level Complexity (a); Medium Level Complexity (b); Low Level Complexity (c) PROCESSES: -"Method" and "Equipment": Modern and Up to Date (a); not so Modern (b); old (c) PRODUCTION: -"Lay Out": Functional (a); Not so Functional (b); Difficult to handle and operate (c) / "Training": Periodic Training Program (a); Eventual Training Program (b); No Training Program (c) / "Kan Ban": Installed (a); Installation in Progress (b); No Kan Ban (c) QUALITY: -"Quality System": Installed (a); Installation in Progress (b); No Quality System (c) / "Statistic Process Control": Installed (a); Installation in Progress (b); No Quality SPC (c) PURCHASING: -"Just in Time": Installed (a); Installation in Progress (b); No JIT (c) PLANNING PRODUCTION CONTROL: -"PPC": Agile -Quite efficient (a); medium (b); slow off poor performance (c)

Fig. 2 .Fig. 3 .

 23 Fig. 2. Results Disjunction Criteria

Fig. 4 .Fig. 5 .

 45 Fig. 4. Revised Planning


Marcelo K Shibuya
email: marcelo.shibuya@gmail.com

Irenilza De Näas
email: irenilza@gmail.com

Mario Mollo Neto
email: mariomollo@gmail.com

Irenilza De A Näas

Numeric Methodology for Determining the Volumetric Consumption of Hydrated Ethanol in Flex-Fuel Vehicles

Keywords: Ethanol, Flex-Fuel Vehicles, Fuel demand

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

Introduction

According to [START_REF]ANFAVEA -Associação Nacional dos Fabricantes de Veículos Automotores[END_REF], in 2014, 3.1 million light vehicles were licensed in Brazil. Out of these 3.1 million automobiles, 95% are equipped with the flex fuel technology and the remaining 5% are powered by gasoline or ethanol. It is found in current literature [START_REF] Bake | Explaining the experience curve: cost reductions of Brazilian ethanol from sugarcane[END_REF][START_REF] Nogueira | Biofuels in Brazil: Evolution, Achievements and Perspectives on Food Security[END_REF] that ethanol consumed by Brazilian vehicles may be anhydrous (mixed with gasoline in the proportion of 20 to 25%, depending on the availability and price of biofuel in the market) and the hydrated ethanol. The gasoline mixed with anhydrous ethanol is named by the [START_REF]Anuário Estatístico[END_REF] as gasoline type C.

Brazil is the world's largest producer of ethanol from sugar cane [START_REF] Martinez | Analysis of socio-economic impacts of sustainable sugarcane ethanol production by means of inter-organizational Input-Output analysis demonstrate of North-East of Brazil[END_REF], with the advantage that the climate is favorable for planting sugar cane. The biofuel production, concentrated in the Center-South region, favored the introduction and acceptance of the flex-fuel vehicles by consumers, and it is the region that has the largest fleet of automobiles. According to [START_REF] Du | Flex-fuel vehicle adoption and dynamics of ethanol prices: lessons from Brazil[END_REF], flex-fuel vehicles have been replacing vehicles that are supplied by a single type of fuel (only gasoline or ethanol), enabling owners to choose the fuel with lower price at the gas station pump. This characteristic of the flex-fuel vehicles brings a new scenario in fuel consumption by the fleet of light vehicles in Brazil, as well as difficulties to estimate the fuel volumes consumed by these vehicles.

In the current literature there are studies showing methods for determining future fuel consumption by using the correlation between the parity of prices between the two fuels and the fraction of hydrated ethanol relative to the total volume of fuel demanded by this fleet [START_REF]Avaliação do Comportamento dos Usuários de Veículos Flex-Fuel no Consumo de Combustíveis[END_REF][START_REF] Mma (ministério | Inventário Nacional de Emissões Atmosféricas por Veículos Automotores Rodoviários[END_REF][START_REF] Losekann | Difusão de Automóveis Flexíveis no Brasil: Sensibilidade ao Preço e Impactos na Emissão de CO 2[END_REF]. However, it lacks in information on the calculation method used to obtain the volume of hydrated ethanol and gasoline C consumed by flex fuel vehicles, based on the total amount of fuel consumed in a given period throughout the fleet.

This study aimed to develop a numerical calculation method for determining the fuel consumption by the flex-fuel vehicle fleet in Brazil. It is proposed to obtain the adequate volume of fuel consumed by the vehicle fleet of flex-fuel allowing studies to analyze the demand for behavior change due to the fuel price.

The evolution of vehicle fleet of flex-fuel and the fuel demand in Brazil

With the introduction of flex-fuel vehicles in Brazil in 2003, there was a significant change in the use of hydrated and anhydrous as propellant fuels. According to [START_REF] Freitas | Ethanol Demand under Flex-fuel Technology Regime in Brasil[END_REF] and [START_REF] Bndes | Bioetanol de cana-de-açúcar: energia para o desenvolvimento sustentável -Rio de Janeiro[END_REF], anhydrous ethanol is the most important additive in gasoline and the hydrated ethanol can be used as an alternative fuel in flex-fuel vehicles, capable of being supplied with gasoline C, hydrated ethanol or a mixture of both in any proportion.

Ethanol was introduced in the Brazilian energy matrix in 1975 through the Proalcool program (National Alcohol Program) whose objective was the large-scale production of fuels to replace fossil fuels used to supply the Brazilian fleet of vehicles [START_REF] Bndes | Bioetanol de cana-de-açúcar: energia para o desenvolvimento sustentável -Rio de Janeiro[END_REF][START_REF] Hira | Sugar Rush: Prospects for a Global Ethanol Market[END_REF][START_REF] Crago | Competitiveness of Brazilian sugarcane ethanol compared to US corn ethanol[END_REF][START_REF] Santos | Fuel Demand in Brazil in a Dynamic Panel Data Approach[END_REF]. The launch of the flex-fuel vehicles in 2003 gained rapid acceptance by the automobile owners by eliminating the risk of shortages, as it had happened to the owners of vehicles moved by ethanol in Proalcool time [START_REF] Stattman | Governing Biofuels in Brazil: a comparison of ethanol and biodiesel policy[END_REF]. Besides reducing the oil dependency, the use of ethanol for vehicle supply reduces the emission of particulate matter, carbon monoxide and minimizes problems in the ozone layer [START_REF] Neto | Is the Development of Brazilian Biofuel Network Sustainable[END_REF].

The fleet of light vehicles consists of passenger and light commercial automobiles. Light commercial vehicles are vans and pick-ups [START_REF]ANFAVEA -Associação Nacional dos Fabricantes de Veículos Automotores[END_REF]. As for supply, light vehicle fleet is composed of three types of engine, that is, with engines powered exclusively by gasoline C, ethanol, and flex-fuel. On the National Atmospheric Emissions Inventory of Road Vehicles, published by [START_REF] Mma (ministério | Inventário Nacional de Emissões Atmosféricas por Veículos Automotores Rodoviários[END_REF], it was estimated that the fuel demand of the light vehicle fleet can be estimated by the quantity of vehicles circulating in the fleet, the intensity of use and fuel efficiency. The equation 1 shows the relationship between these variables.

(

) 1
where C Vi : fuel demand for a given type of vehicle, Q Vi : number of vehicles that are effectively circulating in the given fleet, I Vi : use intensity for a given type of vehicle and R Vi : is the fuel efficiency for a given type of vehicle.

The Equation 2 and 3 show respectively, the mathematical functions for the fraction remaining vehicles of the fleet [START_REF] Mma (ministério | Inventário Nacional de Emissões Atmosféricas por Veículos Automotores Rodoviários[END_REF] and the average age of the vehicles fleet.

( ) ( ( ( ))) (2)
∑ ( ) ∑ (3)
where S(t): remaining vehicles of a given fleet, t: average age of the fleet, A n : mean age in a specific year, Vi: quantity of vehicles for a given type of fleet, Ai: age of the fleet in a given year.

Replacing gasoline with ethanol at the time of filling will only constitutes an advantage to the consumer if the ratio of the price of biofuel compared to the price of gasoline is less than 70% [START_REF] Freitas | Ethanol Demand under Flex-fuel Technology Regime in Brasil[END_REF] and [START_REF] Goldemberg | Brazilian sugarcane ethanol: lessons learned[END_REF]. This price relationship is related to the difference between the calorific values of these fuels. The [START_REF]Conversor de Unidades[END_REF] defines that a cubic meter of hydrated ethanol has 5,096 x 10 3 kcal and is equivalent to 3.59 oil barrels, and a cubic meter of gasoline C has 7,106 x 10 3 kcal and is equivalent to 5.42 oil barrels.

The figure 1 shows the fuel consumption and fleet evolution of light vehicles used in Brazil, comprehending the period from 2003 to 2013. Fig. 1: Fleet of light vehicles and fuel demand in (Source: [START_REF]ANFAVEA -Associação Nacional dos Fabricantes de Veículos Automotores[END_REF], [START_REF]Anuário Estatístico[END_REF], [START_REF] Mma (ministério | Inventário Nacional de Emissões Atmosféricas por Veículos Automotores Rodoviários[END_REF])

The increased consumption of fossil fuels and the reduction of biofuel demand from the year of 2009, showed in Figure 1, is considered as a phase of stagnation and halt of the sugarcane industry expansion in Brazil [START_REF] Nogueira | Biofuels in Brazil: Evolution, Achievements and Perspectives on Food Security[END_REF]; [START_REF]Avaliação do Comportamento dos Usuários de Veículos Flex-Fuel no Consumo de Combustíveis[END_REF]; [START_REF] Milanez | O déficit de produção de etanol no Brasil entre 2012 e 2015: determinantes, consequências e sugestões de política[END_REF]. The same authors add that the government intervention in gasoline prices since 2008, in order to combat inflation in the country, contributed to this phase of stagnation, making its marketed price lower than the oil barrel price.

From 2007 to 2013 (Figure 2), the annual production volumes of gasoline A (gasoline pure without additive), ethanol (including anhydrous and hydrated) and their respective imports indicate that, from the year of 2009 forward, there was an increase in the production and importation of gasoline A, to supply the rise in gasoline C demand by the light vehicle fleet. On the same graph, it is possible to perceive that, from the year of 2010, Brazil starts to import ethanol to supply the domestic demand. The use intensity of automotive light vehicles, including cars and light commercial is defined by [START_REF] Mma (ministério | Inventário Nacional de Emissões Atmosféricas por Veículos Automotores Rodoviários[END_REF]. The present study shows that the distance traveled by a light vehicle in one year varies according to its age. The equation 4 defines the mathematical function which expresses the use intensity.

( ) (4)
where is the use intensity in km/year and t is the age of the vehicle in year.

Methodology

The annual demand for hydrated ethanol and gasoline C were obtained from the data provided by the [START_REF]Anuário Estatístico[END_REF], and the annual quantities of licensed vehicles were obtained from [START_REF]ANFAVEA -Associação Nacional dos Fabricantes de Veículos Automotores[END_REF]. The study included the determination of the fuels used by flex-fuel vehicles in the period of 2006 to 2014.

The volumes of hydrated ethanol and gasoline C were convertes into a single unit of calorific value, choosing the for this, the Barrel of Oil Equivalent (BOE). Thus, with the same power measurement unit in volume of the fuels, it was possibility to perform the mathematical operations of both fuels, without the conversions needs.

The annual volumes of gasoline C and hydrated ethanol demanded by the vehicles were calculated by converting the annual volumes of gasoline C and hydrated ethanol in BOE volumes. The total consumption (Ct) of fuels can be expressed by Equation 5.

( ) ( ) (5)
The volumes of fuels supplied by the fleet (Gasoline C or hydrated ethanol) can be further expressed by Equations 6, 7, 8 and 9:

( ) ( ) (6)
( ) ( ) (7
( ) ( ) (8)
where C t : total fuel consumption in a given period; C t(E) ; total ethanol consumption in a given period; C t(G) : total gasoline C consumption in a given period; 4, Equation 9is obtained:

( ) (10)
Considering that the volumes of fuel were expressed in the same unit of energy, it can be considered that the income data in kilometers per unit of BOE for the vehicles powered with gasoline, ethanol and flex-fuel are similar. Thus, it can be defined that the volumes of fuel demanded by the vehicles in the fleet (Equation 10) is proportional to the amount of fleet vehicles multiplied by its respective use intensity. The volumes of gasoline C and hydrated ethanol consumed by the light vehicle fleet were obtained with the aid of a calculation spreadsheet (Excel).

Results and discussion

Figure 3 shows that from the year of 2011 on the flex-fuel vehicles have become most of vehicle fleet, as reported by [START_REF] Du | Flex-fuel vehicle adoption and dynamics of ethanol prices: lessons from Brazil[END_REF]. A significant increase in the consumption of gasoline C by the flex-fuel vehicles was noticed (Figure 5). The volume increased from 2.074 million cubic meters in 2006 to 28.787 million cubic meters in 2014. It is also seen an increase in hydrated ethanol consumption by flex-fuel vehicles between 2006 and 2009, and a demand reduction from 2010. These results suggest that the owners of flex-fuel vehicles began to prefer the fossil fuel, against the use of biofuel. These numbers desagrees with other findings [3; 7; 19] which had determined that 2009 was the beginning of stagnating of the sugarcane industry in Brazil, with the consequences the interruption of the expansion of ethanol plnts and the reduction of the biofuel supply. The percentage of gasoline C consumed volume in relation to the total amount of fuel consumed by flex-fuel vehicles had definite change in the fuel demand, such as the increased gasoline C consumption, from 36.7% in 2006 to 69.8% in 2014 (Figure 6). started their operations. It is a negative balance compared to the amount of flex-fuel vehicles, most of the Brazilian light vehicle fleet, released by [START_REF] Milanez | O déficit de produção de etanol no Brasil entre 2012 e 2015: determinantes, consequências e sugestões de política[END_REF], which enhance the biofuel demand. The second consequence is, if gasoline C consumption rate is maintained at levels similar to the period 2011-2014 (Figure 6), it might cause a growing need to import this fuel, as disclosed by [START_REF]Anuário Estatístico[END_REF]. Finally, another factor that should not be ignored is the ecologic benefits brought by the use of biofuels, such as the reduction of particulate matter, greenhouse gases including carbon monoxide [START_REF] Neto | Is the Development of Brazilian Biofuel Network Sustainable[END_REF]. The maintenance of these high rates gasoline C use by the flex-fuel vehicles can minimize these benefits and worsen air quality of Brazilian cities

Conclusion

Using the numeric methodology proposed in this study, it was possible to estimate the annual volumes of gasoline C and hydrated ethanol consumed by the flexfuel vehicle fleet in Brazil. The study covered the period from 2006 to 2014 and allowed to identify changes in the demand for fuels used by flex-fuel vehicles. With the volumes of fuels obtained, the demand (in percentage) curve for gasoline C was determined, where it was possible to identify the change in consumption of the fuel from 2010 forward.

Although there are several causes related to the crisis established in the sugar cane industry, and the consequent change in the fuel demand, it is important to point out that the lack of an energy policy in Brazil may have been their primary factor for the controversial success in the use of flex-fuel vehicles. Maintainning the demand for hydrated ethanol within the same levels of the period of 2006-2010, would bring various benefits to Brazil, such as the return of the Brazilian sugarcane sector growth, job growth in the supply chain, the reduction of oil dependency and finally, the improvement of air quality due to the replacement of fossil fuel by biodiesel. The numeric calculation methodology reported in this study could be used to determine the hydrated ethanol consumption mathematical function on the basis of price parity between hydrated ethanol and gasoline C.

The mathematical function could be used to predict the fuel demand for the light vehicle fleet, allowing it to anticipate the volumes to be consumed, and the make production planning and infrastructure necessary for the supply of such products in the Brazilian fuel market.

Fig. 2 :

 2 Fig. 2: gasoline A and ethanol production and importation Graph (Source: [4])

  C VG : total consumption of gasoline C by the fleet of vehicles moved by gasoline; C VD : total consumption of hydrated ethanol by the fleet of vehicles moved by ethanol; C VF : total consumption of fuel (gasoline C e hydrated ethanol) by the flex fuel vehicles; C VF(gas) : gasoline fuel consumption by the fleet of flex-fuel vehicles and C VF(ethanol) : total ethanol fuel consumption by the fleet of flex-fuel vehicles. By substituting Equation 1 on Equation

Fig. 3 :Fig. 4 :

 34 Fig. 3: Variation of the vehicle fleet in circulation in Brazil.

Fig. 6 :

 6 Fig. 6: Percentage of gasoline C consumed by the flex fuel vehicles


Samuel Dos Santos

Oduvaldo Vendrametto
email: oduvaldov@uol.com.br

Miguel León González
email: miguel.leon@uol.com.br

Creusa Fernandes Correia

Samuel Dereste
email: samuel_dereste@yahoo.com.br

Santos

Profile of Building Information Modeling -BIM -Tools Maturity in Brazilian Civil Construction Scenery

Keywords: BIM, CAD, Profile, Maturity

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

Introduction

Building Information Modelling (BIM) has different definitions, with wide aspects considered by experts. It can be defined as the process of generating, storing, managing, exchanging, and sharing information from building process, in an interoperable and reusable way, with the use of a computer generated model to simulate the planning, design, construction and operational phases of a project [START_REF] Eardie | BIM Implementation throughout the UK construction project lifecycle: an analysis in Automation in Construction[END_REF]. The BIM -Building Information Modeling -tools are gaining, worldwide, great importance despite all this qualities for project development in AEC -Architecture, Engineering and Construction -Area. This tool has conceptual differences when compared with other software and permits a project development more efficient [START_REF] Porwal | Building Information Modeling (BIM) partnering framework for public construction projects in Automation in Construction[END_REF].

An analysis of the project development history since 1950 shows that the advent of CAD -Computer Aided Design -tools remains the transfer to the computer information that was handmade manipulated. Besides, with software and computer popularization starts a process of evolution that changed the type of information manipulated.

Besides all work integration possibilities of BIM tools nowadays, the construction industry worldwide still exhibits a low maturity in BIM use, since no significant changes in the traditional business model accompany the introduction of new tools [START_REF] Porwal | Building Information Modeling (BIM) partnering framework for public construction projects in Automation in Construction[END_REF]. The purpose of this study was to evaluate the degree of BIM maturity implementation in Brazil´s context, to find the differences of BIM software utilization under different projects. The strategy was based on a technical review focused on periodical papers as well as a study developed with 16 BIM expert´s projects in Brazil.

This paper is organized into sections as follows: introduction, technical review, case study, discussion and, finally, results and references.

-Technical review

General Definition

The Building Information Modelling (BIM) can be understood like an IT approach that involves applying and maintaining an integral digital representation of the building information, considering different phases of the project lifecycle, working like a data repository. The common data changed in this environment is geometric data, non-geometric data (parameters), and this information is joined in a virtual reality ambience, that allows research, collaboration, improve data integrity, intelligent documentation, retrieving of building data. All these characteristics allow a high quality process project, thorough an enhanced performance analysis, as well as multidisciplinary planning, verification and coordination [START_REF] Gu | Understanding and facilitating BIM adoption in the AEC industry in Automation in Construction[END_REF] This project model allows reducing design mistakes and increases productivity of construction industry because is being used not only one software, but a family of tools that, in an integrated way, results in an integrated model that have, inside, all the different projects steps and the different types of information joined in the same model. Such, BIM provides an emerging new paradigm for project development and construction management to architecture, engineering and construction industry [START_REF] Miettinen | Beyond the BIM Utopia: Approaches to the development and implementation of Building Information Modeling in Automation in Construction[END_REF].

The potential of productivity increased by BIM implementation express one consider modification in civil construction production projects. Besides the BIM definition, the need and possibility of project development in integrated and interoperable platforms was yet recognized already in the 1970s. BIM systems can be seen as an evolution of CAD systems through intelligence and interoperable increasing information [START_REF] Miettinen | Beyond the BIM Utopia: Approaches to the development and implementation of Building Information Modeling in Automation in Construction[END_REF].

When a business implement BIM solutions, there are a substantial impact through all stages of project and construction process. There is an expand of stakeholder collaboration through different steps of project development. However, is necessary a change in business processes, and not only a simple promotion technology. BIM implementation can affect all the processes, and cannot be treated only as a software change [START_REF] Eardie | BIM Implementation throughout the UK construction project lifecycle: an analysis in Automation in Construction[END_REF].

At final, with BIM implementation, is possible to have a more accurate way of working, as a reduction of waste/loses (materials, resources, hour-work, etc). Besides, the 3 dimensional work allows the development of a better project. Instead, it needs the generation of models in extranet/internet, what makes necessary the utilization of security protocols for information management [START_REF] Eardie | BIM Implementation throughout the UK construction project lifecycle: an analysis in Automation in Construction[END_REF].

BIM Maturity

The BIM implementation will not occur at the same way in all kind of business. BIM adopters will need to go through a managed process of changing, starting with the internal organization through external suppliers and clients. BIS -Department of Business Innovations and Skills -UK, developed a maturity model defining the levels from 0 through 3 (fig. 1) to understand software implementation in construction industry. Worldwide, great part of the market is still working with Level 1 processes, and the best in class are experiencing significant benefits in Level 2 [START_REF] Porwal | Building Information Modeling (BIM) partnering framework for public construction projects in Automation in Construction[END_REF]. According BIS, the BIM evolution can be divided into 4 levels. The level 0 consists in the first CAD applications for project development worldwide. The focus of these applications was bi-dimensional objects, and remains the transfer of handmade projects to computer in all areas, like aeronautics, mechanical and civil construction. The level 1 consists in the first efforts of make bi and tri-dimensional integrated objects, but the objects of this level are difficult to be integrated because they are still vectorized, like CAD previous tools [START_REF] Porwal | Building Information Modeling (BIM) partnering framework for public construction projects in Automation in Construction[END_REF].

In the sequence, the level 2 consists in the utilization of BIM first applications. However, the utilization in this phase are still modelling, without integration. At last, the level 3 consists in the application of BIM in an integrated manner, with the project development with different tools.

Others models were developed to understand the BIM implementation. Model Progression Specifications for BIM has been adopted by the American Institute of Architects to address the phase outcomes, milestones, and deliverables, and the idea of assigning tasks on a best person basis. The core was the level of detailing, which describes the steps of the BIM element logical progress. The levels of details ranged from the lowest level (100) of conceptual approximation to the highest level of representational precision (500) (fig. 2.) [START_REF] Porwal | Building Information Modeling (BIM) partnering framework for public construction projects in Automation in Construction[END_REF].

BIM Implementation Stages and Definitions

The evolution of BIM tools can be linked with the type of information manipulated in that phase. According [START_REF] Calvert | Why we care about BIM[END_REF], it can be defined by: Table 1. -BIM stages and definitions. Adapted from [START_REF] Calvert | Why we care about BIM[END_REF].

Stage Definition

2D

First CAD applications drawings. Use of lines, arcs, and geometric vectors.

3D

First tri-dimensional objects, with some parameters like construction materials.

4D

Models with time-production information. Possibility of production planning using just-in-time solutions.

5D

Models with cost-estimation. Each element of the building model has a cost associated with it. It's allows for detailed analysis to be done regarding budgets. 6D Sustainability analysis variables of building projects. LEED -Leadership in Energy and Environmental Design -performance. 7D

As-Built. Fundamental part to accurate Facilities Management. Maintenance planning.

The BIM implementation in industry requires the adjustment of variables of working (cooperation between pairs, suppliers), hardware, operators (designers, engineers, architects, collaborators) and client demands. Worldwide, it had not a uniform implementation, where different solutions divide same partners, and it is a great challenge for BIM implementation. To understand these variables in Brazilian Civil Construction scenery, is necessary evaluate the market behavior.

Level of

Model Progression Specifications (AIA)*

Case Study

Description

To understand the degree of BIM maturity implementation in Brazil, there was made an analysis of works presented by BIM experts of Brazil at "Autodesk University Brazil" in the years 2013 and 2014. In this event, the most important offices shows their BIM experiences developed in Brazil, what made the event one thermometer of how the companies are leading with this technology, and how is the level of BIM software integration in the country.

Sampling

Sixteen companies was analyzed by their case studies showed on lectures. There was 6.25% of small companies, 56.25% of medium companies and 37.5% of large companies. The business line of the companies were: 37.5% of companies develop architecture projects and infrastructure works, 18.75% of the companies works with control and planning production, and 6.25% with Building Systems (HVAC).

-BIS Data analysis and classification

Second [START_REF] Porwal | Building Information Modeling (BIM) partnering framework for public construction projects in Automation in Construction[END_REF], the BIS made one classification based on levels to define de degree of maturity of BIM tools implementation. The BIS classification consider the scale showed at table 2. Analyzing the projects and materials available by enterprises, no ones were classified in Levels 0 and 1. About level 2, 37.5% of the companies were classified in this level because they are using BIM solutions only for modeling, without integration between different instances. So 62.5 % were classified in Level 3 because they were using BIM solutions in a superior instance.

Table 2. Level Definitions by BIS [2]

Fig. 5. BIS Classification Results

A problem resultant of this classification is the generalization made by BIS of how kind of works are being developed inside Level 3, that consider advanced one enterprise that develop projects at high BIM instances.

-Category Data Analysis

To resolve this problem, there was made another analysis dividing the BIM implementation into seven categories, named CAT-01, CAT-02, CAT-03, CAT-04, CAT-05, CAT-06 e CAT-07. The characteristic of each one are listed at table 3. The objective was understand the differences between BIM implementations in the different enterprises, to know the particularities of each one.

Discussion

The BIM implementation inside a company can get different results depending of the context. BIS classification can indicate the degree of BIM evolution inside a company. The results, according this classification, demonstrated that no enterprises are Level 0 or Level 1, and 37,5% are Level and 62,5% are Level 3. These results indicates that great part of companies are implementing BIM tools into an advanced way.

However, the data analysis of Category Classification could shows that no enterprises are using only 2D and 3D solutions, but BIM for modeling (31,25%), BIM for Structural Analysis (6,25%), Building Systems (37,5%) and Infrastructure Projects (25%). No enterprises are using BIM for thermal and acoustic projects evaluation.

Another important aspect is the low rate of enterprises (37,5%) using BIM in an integrated way. The great BIM challenge is the possibility of project development in a collaborative job. If the offices in Brazil are not implementing software integration in large scale, the BIM systems values are not full and contributes to a low evolution of the tool in the country.

Conclusions

BIM tools were a great change on project development. The study shown that, besides difficulties, the companies are implementing the tool. Considering the BIS classification, the companies are using the BIM tools into an advanced way, signaling that software implementation is accompanying the world context.

Besides, the Category Analysis showed a low application of structural analysis with BIM tools (6,25 %), and a great force in Modeling (31,25%), HVAC (37,5%) and Infrastructure (25%). The Category Analysis also showed that great part of the companies (62,5%) use BIM tools without instances integration. Companies did not mention the thermal and acoustic analysis.

To professionals, the BIM implementation in AEC industry means a better kind of tool for project development, with could permit the collaborative work, with is very interesting in our actual scenery, where the deadlines are short and changes need to be done in a fastest way. A collaborative work also permits project development without disciplines incompatibilities, contributing for a more efficiency project.

Besides, for Building and Facilities Managers, the growing of projects developed with BIM tools creates an opportunity for a better work, where all information is joined at same model, allowing a better maintenance of all building systems, saving energy and water, becoming ecological the building lifecycle.

The challenges of BIM implementation in Brazil are many, and, the BIM integration with interoperability data can be, in the long run, a way of better project development processes in Brazil context.

Fig. 1 .

 1 Fig. 1.-BIM maturity implementation[START_REF] Porwal | Building Information Modeling (BIM) partnering framework for public construction projects in Automation in Construction[END_REF]

Fig. 2 .

 2 Fig.2. -Model Progress Specifications. Adapted from[START_REF] Porwal | Building Information Modeling (BIM) partnering framework for public construction projects in Automation in Construction[END_REF]

Fig. 3 .

 3 Fig. 3. -Company Profile Fig. 4 -Business Line

Fig. 6 .

 6 Fig. 6. Category Classification Results

Table 3 .

 3 -Category BIM classification

Acknowledgment

The authors would like to thank CAPES (Coordenação de aperfeiçoamento de pessoal de nível superior) and Paulista University (UNIP) for the financial support to develop this work.