Abstract: It has proved that nonlinear diffusion and bilateral
filtering (BF) have a closed connection. Early effort and contribution
are to find a generalized representation to link them by using adaptive
filtering. In this paper a new further relationship between nonlinear
diffusion and bilateral filtering is explored which pays more attention
to numerical calculus. We give a fresh idea that bilateral filtering can
be accelerated by multigrid (MG) scheme which likes the nonlinear
diffusion, and show that a bilateral filtering process with large kernel
size can be approximated by a nonlinear diffusion process based on
full multigrid (FMG) scheme.
Abstract: The national economy development affects the vehicle
ownership which ultimately increases fuel consumption. The rise of
the vehicle ownership is dominated by the increasing number of
motorcycles. This research aims to analyze and identify the
characteristics of fuel consumption, the city transportation system,
and to analyze the relationship and the effect of the city
transportation system on the fuel consumption. A multivariable
analysis is used in this study. The data analysis techniques include: a
Multivariate Multivariable Analysis by using the R software. More
than 84% of fuel on Java is consumed in metropolitan and large
cities. The city transportation system variables that strongly effect the
fuel consumption are population, public vehicles, private vehicles and
private bus. This method can be developed to control the fuel
consumption by considering the urban transport system and city
tipology. The effect can reducing subsidy on the fuel consumption,
increasing state economic.
Abstract: In recent years fuel cell vehicles are rapidly appearing
all over the globe. In less than 10 years, fuel cell vehicles have gone
from mere research novelties to operating prototypes and demonstration
models. At the same time, government and industry in development
countries have teamed up to invest billions of dollars in partnerships
intended to commercialize fuel cell vehicles within the early
years of the 21st century.
The purpose of this study is evaluation of model and performance
of fuel cell hybrid electric vehicle in different drive cycles. A fuel
cell system model developed in this work is a semi-experimental
model that allows users to use the theory and experimental relationships
in a fuel cell system. The model can be used as part of a complex
fuel cell vehicle model in advanced vehicle simulator (ADVISOR).
This work reveals that the fuel consumption and energy efficiency
vary in different drive cycles. Arising acceleration and speed in a
drive cycle leads to Fuel consumption increase. In addition, energy
losses in drive cycle relates to fuel cell system power request. Parasitic
power in different parts of fuel cell system will increase when
power request increases. Finally, most of energy losses in drive cycle
occur in fuel cell system because of producing a lot of energy by fuel
cell stack.
Abstract: Debates on residential satisfaction topic have been
vigorously discussed in family house setting. Nonetheless, less or
lack of attention was given to survey on student residential
satisfaction in the campus house setting. This study, however, tried to
fill in the gap by focusing more on the relationship between students-
socio-economic backgrounds and student residential satisfaction with
their on-campus student housing facilities. Two-stage cluster
sampling method was employed to classify the respondents. Then,
self-administered questionnaires were distributed face-to-face to the
students. In general, it was confirmed that the students- socioeconomic
backgrounds have significantly influence the students-
satisfaction with their on-campus student housing facilities. The main
influential factors were revealed as the economic status, sense of
sharing, and the ethnicity of roommates. Likewise, this study could
also provide some useful feedback for the universities administration
in order to improve their student housing facilities.
Abstract: Recent environmental turbulence including financial
crisis, intensified competitive forces, rapid technological change and
high market turbulence have dramatically changed the current
business climate. The managers firms have to plan and decide what
the best approaches that best fit their firms in order to pursue superior
performance. This research aims to examine the influence of strategic
reasoning and top level managers- individual characteristics on the
effectiveness of organizational improvisation and firm performance.
Given the lack of studies on these relationships in the previous
literature, there is significant contribution to the body of knowledge
as well as for managerial practices. 128 responses from top
management of technology-based companies in Malaysia were used
as a sample. Three hypotheses were examined and the findings
confirm that (a) there is no relationship between intuitive reasoning
and organizational improvisation but there is a link between rational
reasoning and organizational improvisation, (b) top level managers-
individual characteristics as a whole affect organizational
improvisation; and (c) organizational improvisation positively affects
firm performance. The theoretical and managerial implications were
discussed in the conclusions.
Abstract: Artificial neural networks (ANN) have the ability to model input-output relationships from processing raw data. This characteristic makes them invaluable in industry domains where such knowledge is scarce at best. In the recent decades, in order to overcome the black-box characteristic of ANNs, researchers have attempted to extract the knowledge embedded within ANNs in the form of rules that can be used in inference systems. This paper presents a new technique that is able to extract a small set of rules from a two-layer ANN. The extracted rules yield high classification accuracy when implemented within a fuzzy inference system. The technique targets industry domains that possess less complex problems for which no expert knowledge exists and for which a simpler solution is preferred to a complex one. The proposed technique is more efficient, simple, and applicable than most of the previously proposed techniques.
Abstract: While to minimize the overall project cost is always
one of the objectives of construction managers, to obtain the
maximum economic return is definitely one the ultimate goals of the
project investors. As there is a trade-off relationship between the
project time and cost, and the project delivery time directly affects the
timing of economic recovery of an investment project, to provide a
method that can quantify the relationship between the project delivery
time and cost, and identify the optimal delivery time to maximize
economic return has always been the focus of researchers and
industrial practitioners. Using genetic algorithms, this study
introduces an optimization model that can quantify the relationship
between the project delivery time and cost and furthermore, determine
the optimal delivery time to maximize the economic return of the
project. The results provide objective quantification for accurately
evaluating the project delivery time and cost, and facilitate the
analysis of the economic return of a project.
Abstract: the article analyzes the national security as a scientific and practical problem, characterized by the state's political institutions to ensure effective action to maintain optimal conditions for the existence and development of the individual and society. National security, as a category of political science reflects the relationship between the security to the nation, including public relations and social consciousness, social institutions and their activities, ensuring the realization of national interests in a particular historical situation. In national security are three security levels: individual, society and state. Their role and place determined by the nature of social relations, political systems, the presence of internal and external threats. In terms of content in the concept of national security is taken to provide political, economic, military, environmental, information security and safety of the cultural development of the nation.
Abstract: The purpose of this paper is to examine the inter
relationships among various leadership branding constructs of
entrepreneurs in small and medium sized enterprises (SMEs). We
employ a quantitative structural equation modeling through a new
leadership branding engagement model comprises constructs of
leader-s or entrepreneur-s personality, branding practice and
customer engagement. The results confirm that there are significant
relationships between the three constructs and the major fit indices
indicate that the data fits the proposed model. The findings provide
insights and fill in the literature gaps on statistically validated
representation of leadership branding for SMEs across new economic
regions of Malaysia that may implicate other economic zones with
similar situations. This study extends the establishment of a
leadership branding engagement model with a new mechanism of
using leaders- personality as a predictor to branding practice and
customer engagement performance.
Abstract: Time-Cost Optimization "TCO" is one of the greatest challenges in construction project planning and control, since the optimization of either time or cost, would usually be at the expense of the other. Since there is a hidden trade-off relationship between project and cost, it might be difficult to predict whether the total cost would increase or decrease as a result of the schedule compression. Recently third dimension in trade-off analysis is taken into consideration that is quality of the projects. Few of the existing algorithms are applied in a case of construction project with threedimensional trade-off analysis, Time-Cost-Quality relationships. The objective of this paper is to presents the development of a practical software system; that named Automatic Multi-objective Typical Construction Resource Optimization System "AMTCROS". This system incorporates the basic concepts of Line Of Balance "LOB" and Critical Path Method "CPM" in a multi-objective Genetic Algorithms "GAs" model. The main objective of this system is to provide a practical support for typical construction planners who need to optimize resource utilization in order to minimize project cost and duration while maximizing its quality simultaneously. The application of these research developments in planning the typical construction projects holds a strong promise to: 1) Increase the efficiency of resource use in typical construction projects; 2) Reduce construction duration period; 3) Minimize construction cost (direct cost plus indirect cost); and 4) Improve the quality of newly construction projects. A general description of the proposed software for the Time-Cost-Quality Trade-Off "TCQTO" is presented. The main inputs and outputs of the proposed software are outlined. The main subroutines and the inference engine of this software are detailed. The complexity analysis of the software is discussed. In addition, the verification, and complexity of the proposed software are proved and tested using a real case study.
Abstract: The significance of environmental protection is wellknown in today's world. The execution of any program depends on sufficient knowledge and required familiarity with environment and its pollutants. Taking advantage of a systematic method, as a new science, in environmental planning can solve many problems. In this article, air pollution in Tehran and its relationship with health and population growth have been analyzed using dynamic systems. Firstly, by using casual loops, the relationship between the parameters effective on air pollution in Tehran were taken into consideration, then these casual loops were turned into flow diagrams [6], and finally, they were simulated using the software Vensim [16]in order to conclude what the effect of each parameter will be on air pollution in Tehran in the next 10 years, how changing of one or more parameters influences other parameters, and which parameter among all other parameters requires to be controlled more.
Abstract: Yogyakarta, as the capital city of Yogyakarta Province, has important roles in various sectors that require good provision of public transportation system. Ideally, a good transportation system should be able to accommodate the amount of travel demand. This research attempts to develop a trip generation model to predict the number of public transport passenger in Yogyakarta city. The model is built by using multiple linear regression analysis, which establishes relationship between trip number and socioeconomic attributes. The data consist of primary and secondary data. Primary data was collected by conducting household surveys which randomly selected. The resulted model is further applied to evaluate the existing TransJogja, a new Bus Rapid Transit system serves Yogyakarta and surrounding cities, shelters.
Abstract: Collaborative planning, forecasting and
replenishment (CPFR) coordinates the various supply chain
management activities including production and purchase planning,
demand forecasting and inventory replenishment between supply
chain trading partners. This study proposes a systematic way of
analyzing CPFR supporting factors using fuzzy cognitive map
(FCM) approach. FCMs have proven particularly useful for solving
problems in which a number of decision variables and
uncontrollable variables are causally interrelated. Hence the FCMs
of CPFR are created to show the relationships between the factors
that influence on effective implementation of CPFR in the supply
chain.
Abstract: Studies in economics domain tried to reveal the correlation between stock markets. Since the globalization era, interdependence between stock markets becomes more obvious. The Dynamic Interaction Network (DIN) algorithm, which was inspired by a Gene Regulatory Network (GRN) extraction method in the bioinformatics field, is applied to reveal important and complex dynamic relationship between stock markets. We use the data of the stock market indices from eight countries around the world in this study. Our results conclude that DIN is able to reveal and model patterns of dynamic interaction from the observed variables (i.e. stock market indices). Furthermore, it is also found that the extracted network models can be utilized to predict movement of the stock market indices with a considerably good accuracy.
Abstract: The research was designed to examine the relationship
between the development of muscle fatigue and the effect it has on
sport performance, specifically during maximal voluntary
contraction. This kind of this investigation using simultaneous
electrophysiological and mechanical recordings, based on advanced
mathematical processing, allows us to get parameters, and indexes in
a short time, and finally, the mapping to use for the thorough
investigation of the muscle contraction force, respectively the
phenomenon of local muscle fatigue, both for athletes and other
subjects.
Abstract: Generalization is one of the most challenging issues
of Learning Classifier Systems. This feature depends on the
representation method which the system used. Considering the
proposed representation schemes for Learning Classifier System, it
can be concluded that many of them are designed to describe the
shape of the region which the environmental states belong and the
other relations of the environmental state with that region was
ignored. In this paper, we propose a new representation scheme
which is designed to show various relationships between the
environmental state and the region that is specified with a particular
classifier.
Abstract: Business Process Reengineering (BPR) is an essential tool before an information system project implementation. Enterprise Resource Planning (ERP) projects definitely require the standardization and fixation of business processes from customer order to shipment. Therefore, ERP implementations are well proven to be coupled with BPR, although the extend and timing of BPR with respect to ERP implementation differ. This study aims at analyzing the effects of BPR on ERP implementation success. Basing on two Turkish ERP implementations in pharmaceutical sector, a comparative study is performed. One of the ERP implementations took place after a BPR implementation, whereas the other implementation was without a prior BPR application. Both implementations have been realized with the same consultant team, the case with prior BPR implementation going live first. The results of the case study reveal that if business processes are not optimized and improved before an ERP implementation, ERP live system would face with disharmony problems of processes and processes automated by ERP. This suggests a definite precedence relationship between BPR and ERP applications
Abstract: The technique of k-anonymization has been proposed to obfuscate private data through associating it with at least k identities. This paper investigates the basic tabular structures that
underline the notion of k-anonymization using cell suppression.
These structures are studied under idealized conditions to identify the
essential features of the k-anonymization notion. We optimize data kanonymization
through requiring a minimum number of anonymized
values that are balanced over all columns and rows. We study the
relationship between the sizes of the anonymized tables, the value k, and the number of attributes. This study has a theoretical value through contributing to develop a mathematical foundation of the kanonymization
concept. Its practical significance is still to be
investigated.
Abstract: Accurate software cost estimates are critical to both
developers and customers. They can be used for generating request
for proposals, contract negotiations, scheduling, monitoring and
control. The exact relationship between the attributes of the effort
estimation is difficult to establish. A neural network is good at
discovering relationships and pattern in the data. So, in this paper a
comparative analysis among existing Halstead Model, Walston-Felix
Model, Bailey-Basili Model, Doty Model and Neural Network
Based Model is performed. Neural Network has outperformed the
other considered models. Hence, we proposed Neural Network
system as a soft computing approach to model the effort estimation
of the software systems.
Abstract: The main purpose of this study is to analyze climbers
involved in motivation and risk perception and analysis of the
predictive ability of the risk perception "mountaineering" involved in
motivation. This study used questionnaires, to have to climb the
3000m high mountain in Taiwan climbers object to carry out an
investigation in order to non-random sampling, a total of 231 valid
questionnaires were. After statistical analysis, the study found that: 1.
Climbers the highest climbers involved in motivation "to enjoy the
natural beauty of the fun. 2 climbers for climbers "risk perception" the
highest: the natural environment of risk. 3. Climbers “seeking
adventure stimulate", “competence achievement" motivation highly
predictive of risk perception. Based on these findings, this study not
only practices the recommendations of the outdoor leisure industry,
and also related research proposals for future researchers.