Abstract: One of the basic concepts in marketing is the concept
of meeting customers- needs. Since customer satisfaction is essential
for lasting survival and development of a business, screening and
observing customer satisfaction and recognizing its underlying
factors must be one of the key activities of every business.
The purpose of this study is to recognize the drivers that effect
customer satisfaction in a business-to-business situation in order to
improve marketing activities. We conducted a survey in which 93
business customers of a manufacturer of Diesel Generator in Iran
participated and they talked about their ideas and satisfaction of
supplier-s services related to its products. We developed the measures
for drivers of satisfaction first by as investigative research (by means
of feedback from executives and customers of sponsoring firm). Then
based on these measures, we created a mail survey, and asked the
respondents to explain their opinion about the sponsoring firm which
was a supplier of diesel generator and similar products. Furthermore,
the survey required the participants to mention their functional areas
and their company features.
In Conclusion we found that there are three drivers for customer
satisfaction, which are reliability, information about product, and
commercial features. Buyers/users from different functional areas
attribute different degree of importance to the last two drivers. For
instance, people from buying and management areas believe that
commercial features are more important than information about
products. But people in engineering, maintenance and production
areas believe that having information about products is more
important than commercial aspects. Marketing experts should
consider the attribute of customers regarding information about the
product and commercial features to improve market share.
Abstract: Recommender Systems act as personalized decision
guides, aiding users in decisions on matters related to personal taste.
Most previous research on Recommender Systems has focused on the
statistical accuracy of the algorithms driving the systems, with no
emphasis on the trustworthiness of the user. RS depends on
information provided by different users to gather its knowledge. We
believe, if a large group of users provide wrong information it will
not be possible for the RS to arrive in an accurate conclusion. The
system described in this paper introduce the concept of Testing the
knowledge of user to filter out these “bad users".
This paper emphasizes on the mechanism used to provide robust
and effective recommendation.
Abstract: We present a non standard Euclidean vehicle
routing problem adding a level of clustering, and we revisit the use
of self-organizing maps as a tool which naturally handles such
problems. We present how they can be used as a main operator
into an evolutionary algorithm to address two conflicting
objectives of route length and distance from customers to bus stops
minimization and to deal with capacity constraints. We apply the
approach to a real-life case of combined clustering and vehicle
routing for the transportation of the 780 employees of an
enterprise. Basing upon a geographic information system we
discuss the influence of road infrastructures on the solutions
generated.
Abstract: This paper presents dynamic voltage collapse prediction on an actual power system using support vector machines.
Dynamic voltage collapse prediction is first determined based on the PTSI calculated from information in dynamic simulation output. Simulations were carried out on a practical 87 bus test system by considering load increase as the contingency. The data collected from the time domain simulation is then used as input to the SVM in which support vector regression is used as a predictor to determine the
dynamic voltage collapse indices of the power system. To reduce training time and improve accuracy of the SVM, the Kernel function type and Kernel parameter are considered. To verify the
effectiveness of the proposed SVM method, its performance is compared with the multi layer perceptron neural network (MLPNN). Studies show that the SVM gives faster and more accurate results for dynamic voltage collapse prediction compared with the MLPNN.
Abstract: In this paper, a robust watermarking algorithm using
the wavelet transform and edge detection is presented. The efficiency
of an image watermarking technique depends on the preservation of
visually significant information. This is attained by embedding the
watermark transparently with the maximum possible strength. The
watermark embedding process is carried over the subband
coefficients that lie on edges, where distortions are less noticeable,
with a subband level dependent strength. Also, the watermark is
embedded to selected coefficients around edges, using a different
scale factor for watermark strength, that are captured by a
morphological dilation operation. The experimental evaluation of the
proposed method shows very good results in terms of robustness and
transparency to various attacks such as median filtering, Gaussian
noise, JPEG compression and geometrical transformations.
Abstract: Among various HLM techniques, the Multivariate Hierarchical Linear Model (MHLM) is desirable to use, particularly when multivariate criterion variables are collected and the covariance structure has information valuable for data analysis. In order to reflect prior information or to obtain stable results when the sample size and the number of groups are not sufficiently large, the Bayes method has often been employed in hierarchical data analysis. In these cases, although the Markov Chain Monte Carlo (MCMC) method is a rather powerful tool for parameter estimation, Procedures regarding MCMC have not been formulated for MHLM. For this reason, this research presents concrete procedures for parameter estimation through the use of the Gibbs samplers. Lastly, several future topics for the use of MCMC approach for HLM is discussed.
Abstract: Global environmental changes lead to increased frequency and scale of natural disaster, Taiwan is under the influence of global warming and extreme weather. Therefore, the vulnerability was increased and variability and complexity of disasters is relatively enhanced. The purpose of this study is to consider the source and magnitude of hazard characteristics on the tourism industry. Using modern risk management concepts, integration of related domestic and international basic research, this goes beyond the Taiwan typhoon disaster risk assessment model and evaluation of loss. This loss evaluation index system considers the impact of extreme weather, in particular heavy rain on the tourism industry in Taiwan. Consider the extreme climate of the compound impact of disaster for the tourism industry; we try to make multi-hazard risk assessment model, strategies and suggestions. Related risk analysis results are expected to provide government department, the tourism industry asset owners, insurance companies and banking include tourist disaster risk necessary information to help its tourism industry for effective natural disaster risk management.
Abstract: This article deals with the conceptual modeling under uncertainty. First, the division of information systems with their definition will be described, focusing on those where the construction of a conceptual model is suitable for the design of future information system database. Furthermore, the disadvantages of the traditional approach in creating a conceptual model and database design will be analyzed. A comprehensive methodology for the creation of a conceptual model based on analysis of client requirements and the selection of a suitable domain model is proposed here. This article presents the expert system used for the construction of a conceptual model and is a suitable tool for database designers to create a conceptual model.
Abstract: The aim of this paper is to provide a better
understanding of the implementation of Project Management
practices by UiTM contractors to ensure project success. A
questionnaire survey was administered to 120 UiTM contractors in
Malaysia. The purpose of this method was to gather information on
the contractors- project background and project management skills. It
was found that all of the contractors had basic knowledge and
understanding of project management skills. It is suggested that a
reasonable project plan and an appropriate organizational structure
are influential factors for project success. It is recommended that the
contractors need to have an effective program of work and up to date
information system are emphasized.
Abstract: An Ad hoc wireless network comprises of mobile
terminals linked and communicating with each other sans the aid of
traditional infrastructure. Optimized Link State Protocol (OLSR) is a
proactive routing protocol, in which routes are discovered/updated
continuously so that they are available when needed. Hello messages
generated by a node seeks information about its neighbor and if the
latter fails to respond to a specified number of hello messages
regulated by neighborhood hold time, the node is forced to assume
that the neighbor is not in range. This paper proposes to evaluate
OLSR routing protocol in a random mobility network having various
neighborhood hold time intervals. The throughput and delivery ratio
are also evaluated to learn about its efficiency for multimedia loads.
Abstract: The Ministry of Defense (MoD) spends hundreds of
millions of dollars on software to support its infrastructure, operate
its weapons and provide command, control, communications,
computing, intelligence, surveillance, and reconnaissance (C4ISR)
functions. These and other all new advanced systems have a common
critical component is information technology. Defense and
Aerospace environment is continuously striving to keep up with
increasingly sophisticated Information Technology (IT) in order to
remain effective in today-s dynamic and unpredictable threat
environment. This makes it one of the largest and fastest growing
expenses of Defense. Hundreds of millions of dollars spent a year on
IT projects. But, too many of those millions are wasted on costly
mistakes. Systems that do not work properly, new components that
are not compatible with old once, trendily new applications that do
not really satisfy defense needs or lost though poorly managed
contracts.
This paper investigates and compiles the effective strategies that
aim to end exasperation with low returns and high cost of
Information Technology Acquisition for defense; it tries to show how
to maximize value while reducing time and expenditure.
Abstract: This paper describes an experience of research,
development and innovation applied in Industrial Naval at (Science
and Technology Corporation for the Development of Shipbuilding
Industry, Naval in Colombia (COTECMAR) particularly through
processes of research, innovation and technological development,
based on theoretical models related to organizational knowledge
management, technology management and management of human
talent and integration of technology platforms. It seeks ways to
facilitate the initial establishment of environments rich in
information, knowledge and content-supported collaborative
strategies on dynamic processes missionary, seeking further
development in the context of research, development and innovation
of the Naval Engineering in Colombia, making it a distinct basis for
the generation of knowledge assets from COTECMAR.
The integration of information and communication technologies,
supported on emerging technologies (mobile technologies, wireless,
digital content via PDA, and content delivery services on the Web 2.0
and Web 3.0) as a view of the strategic thrusts in any organization
facilitates the redefinition of processes for managing information and
knowledge, enabling the redesign of workflows, the adaptation of
new forms of organization - preferably in networking and support the
creation of symbolic-inside-knowledge promotes the development of
new skills, knowledge and attitudes of the knowledge worker
Abstract: Methods of clustering which were developed in the
data mining theory can be successfully applied to the investigation of
different kinds of dependencies between the conditions of
environment and human activities. It is known, that environmental
parameters such as temperature, relative humidity, atmospheric
pressure and illumination have significant effects on the human
mental performance. To investigate these parameters effect, data
mining technique of clustering using entropy and Information Gain
Ratio (IGR) K(Y/X) = (H(X)–H(Y/X))/H(Y) is used, where
H(Y)=-ΣPi ln(Pi). This technique allows adjusting the boundaries of
clusters. It is shown that the information gain ratio (IGR) grows
monotonically and simultaneously with degree of connectivity
between two variables. This approach has some preferences if
compared, for example, with correlation analysis due to relatively
smaller sensitivity to shape of functional dependencies. Variant of an
algorithm to implement the proposed method with some analysis of
above problem of environmental effects is also presented. It was
shown that proposed method converges with finite number of steps.
Abstract: The Requirements Abstraction Model (RAM) helps in managing abstraction in requirements by organizing them at four levels (product, feature, function and component). The RAM is adaptable and can be tailored to meet the needs of the various organizations. Because software requirements are an important source of information for developing high-level tests, organizations willing to adopt the RAM model need to know the suitability of the RAM requirements for developing high-level tests. To investigate this suitability, test cases from twenty randomly selected requirements were developed, analyzed and graded. Requirements were selected from the requirements document of a Course Management System, a web based software system that supports teachers and students in performing course related tasks. This paper describes the results of the requirements document analysis. The results show that requirements at lower levels in the RAM are suitable for developing executable tests whereas it is hard to develop from requirements at higher levels.
Abstract: The American Health Level Seven (HL7) Reference Information Model (RIM) consists of six back-bone classes that have different specialized attributes. Furthermore, for the purpose of enforcing the semantic expression, there are some specific mandatory vocabulary domains have been defined for representing the content values of some attributes. In the light of the fact that it is a duplicated effort on spending a lot of time and human cost to develop and modify Clinical Information Systems (CIS) for most hospitals due to the variety of workflows. This study attempts to design and develop sharing RIM-based components of the CIS for the different business processes. Therefore, the CIS contains data of a consistent format and type. The programmers can do transactions with the RIM-based clinical repository by the sharing RIM-based components. And when developing functions of the CIS, the sharing components also can be adopted in the system. These components not only satisfy physicians- needs in using a CIS but also reduce the time of developing new components of a system. All in all, this study provides a new viewpoint that integrating the data and functions with the business processes, it is an easy and flexible approach to build a new CIS.
Abstract: This research studied about green logistics and the
expected benefit that organization gotten when adapted to green
logistics also the organization concerned about the important activity
in green logistics to apply in implementation from study was found
that the benefit of green logistics that organization was gotten by
logistics management which was the increased efficiency process of
management the product from producer to customer all of reduce
production cost, increased value added save energy and prevented
environment together
From study was found that the organization had green logistics to
apply in logistics activities in supply chain since downstream till
upstream to prevent environment as follow 1). Purchasing process,
trade facilitation enhance such as linking of information technology
during business to business (B2B business). 2). Productions process
improved by business logistics improvement 3). Warehouse
management process such as recycled packaging, moving goods in to
warehouse, transportation goods and inside receiving and delivery
products plan.
Abstract: In this paper, we proposed a novel receiver algorithm
for coherent underwater acoustic communications. The proposed
receiver is composed of three parts: (1) Doppler tracking and
correction, (2) Time reversal channel estimation and combining, and
(3) Joint iterative equalization and decoding (JIED). To reduce
computational complexity and optimize the equalization algorithm,
Time reversal (TR) channel estimation and combining is adopted to
simplify multi-channel adaptive decision feedback equalizer (ADFE)
into single channel ADFE without reducing the system performance.
Simultaneously, the turbo theory is adopted to form joint iterative
ADFE and convolutional decoder (JIED). In JIED scheme, the ADFE
and decoder exchange soft information in an iterative manner, which
can enhance the equalizer performance using decoding gain. The
simulation results show that the proposed algorithm can reduce
computational complexity and improve the performance of equalizer.
Therefore, the performance of coherent underwater acoustic
communications can be improved greatly.
Abstract: The equivalence class subset algorithm is a powerful
tool for solving a wide variety of constraint satisfaction problems and
is based on the use of a decision function which has a very high but
not perfect accuracy. Perfect accuracy is not required in the decision
function as even a suboptimal solution contains valuable information
that can be used to help find an optimal solution. In the hardest
problems, the decision function can break down leading to a
suboptimal solution where there are more equivalence classes than
are necessary and which can be viewed as a mixture of good decision
and bad decisions. By choosing a subset of the decisions made in
reaching a suboptimal solution an iterative technique can lead to an
optimal solution, using series of steadily improved suboptimal
solutions. The goal is to reach an optimal solution as quickly as
possible. Various techniques for choosing the decision subset are
evaluated.
Abstract: We introduce a novel approach to measuring how
humans learn based on techniques from information theory and
apply it to the oriental game of Go. We show that the total amount
of information observable in human strategies, called the strategic
information, remains constant for populations of players of differing
skill levels for well studied patterns of play. This is despite the very
large amount of knowledge required to progress from the recreational
players at one end of our spectrum to the very best and most
experienced players in the world at the other and is in contrast to
the idea that having more knowledge might imply more 'certainty'
in what move to play next. We show this is true for very local
up to medium sized board patterns, across a variety of different
moves using 80,000 game records. Consequences for theoretical and
practical AI are outlined.
Abstract: Multi-Agent Systems (MAS) emerged in the pursuit to improve our standard of living, and hence can manifest complex human behaviors such as communication, decision making, negotiation and self-organization. The Social Network Services (SNSs) have attracted millions of users, many of whom have integrated these sites into their daily practices. The domains of MAS and SNS have lots of similarities such as architecture, features and functions. Exploring social network users- behavior through multiagent model is therefore our research focus, in order to generate more accurate and meaningful information to SNS users. An application of MAS is the e-Auction and e-Rental services of the Universiti Cyber AgenT(UniCAT), a Social Network for students in Universiti Tunku Abdul Rahman (UTAR), Kampar, Malaysia, built around the Belief- Desire-Intention (BDI) model. However, in spite of the various advantages of the BDI model, it has also been discovered to have some shortcomings. This paper therefore proposes a multi-agent framework utilizing a modified BDI model- Belief-Desire-Intention in Dynamic and Uncertain Situations (BDIDUS), using UniCAT system as a case study.