Abstract: Knowledge management (KM) is generally
considered to be a positive process in an organisation, facilitating
opportunities to achieve competitive advantage via better quality
information handling, compilation of expert know-how and rapid
response to fluctuations in the business environment. The KM
paradigm as portrayed in the literature informs the processes that can
increase intangible assets so that corporate knowledge is preserved.
However, in some instances, knowledge management exists in a
universe of dynamic tension among the conflicting needs to respect
privacy and intellectual property (IP), to guard against data theft, to
protect national security and to stay within the laws. While the
Knowledge Management literature focuses on the bright side of the
paradigm, there is also a different side in which knowledge is
distorted, suppressed or misappropriated due to personal or
organisational motives (the paradox). This paper describes the ethical
paradoxes that occur within the taxonomy and deontology of
knowledge management and suggests that recognising both the
promises and pitfalls of KM requires wisdom.
Abstract: It is believed that major account on language diversity must be taken in learning, and especially in learning using ICT. This paper-s objective is to exhibit language and communication barriers in learning, to approach the topic from socioculture and cognitivist perspectives, and to give exploratory solutions of handling such barriers. The review is mainly conducted by approaching the journal Computers & Education, but also an initially broad search was conducted. The results show that not much attention is paid on language and communication barriers in an immediate relation to learning using ICT. The results shows, inter alia, that language and communication barriers are caused because of not enough account is taken on both the individual-s background and the technology.
Abstract: Over the course of the past century, the global
automotive industry-s stance towards safety has evolved from one of
contempt to one nearing reverence. A suspension system that
provides safe handling and cornering capabilities can, with the help
of an efficient braking system, improve safety to a large extent. The
aim of this research is to propose a new automotive brake rotor
design and to compare it with automotive vented disk rotor. Static
structural and transient thermal analysis have been carried out on the
vented disk rotor and proposed rotor designs to evaluate and compare
their performance. Finite element analysis was employed for both
static structural and transient thermal analysis. Structural analysis
was carried out to study the stress and deformation pattern of the
rotors under extreme loads. Time varying temperature load was
applied on the rotors and the temperature distribution was analysed
considering cooling parameters (convection and radiation). This
dissertation illustrates the use of Finite Element Methods to examine
models, concluding with a comparative study of the proposed rotor
design and the conventional vented disk rotor for structural stability
and thermal efficiency.
Abstract: The genetic algorithm (GA) based solution techniques
are found suitable for optimization because of their ability of
simultaneous multidimensional search. Many GA-variants have been
tried in the past to solve optimal power flow (OPF), one of the
nonlinear problems of electric power system. The issues like
convergence speed and accuracy of the optimal solution obtained
after number of generations using GA techniques and handling
system constraints in OPF are subjects of discussion. The results
obtained for GA-Fuzzy OPF on various power systems have shown
faster convergence and lesser generation costs as compared to other
approaches. This paper presents an enhanced GA-Fuzzy OPF (EGAOPF)
using penalty factors to handle line flow constraints and load
bus voltage limits for both normal network and contingency case
with congestion. In addition to crossover and mutation rate
adaptation scheme that adapts crossover and mutation probabilities
for each generation based on fitness values of previous generations, a
block swap operator is also incorporated in proposed EGA-OPF. The
line flow limits and load bus voltage magnitude limits are handled by
incorporating line overflow and load voltage penalty factors
respectively in each chromosome fitness function. The effects of
different penalty factors settings are also analyzed under contingent
state.
Abstract: One of the major causes of voltage instability is the reactive power limit of the system. Improving the system's reactive power handling capacity via Flexible AC transmission System (FACTS) devices is a remedy for prevention of voltage instability and hence voltage collapse. In this paper, the effects of SVC and STATCOM in Static Voltage Stability Margin Enhancement will be studied. AC and DC representations of SVC and STATCOM are used in the continuation power flow process in static voltage stability study. The IEEE-14 bus system is simulated to test the increasing loadability. It is found that these controllers significantly increase the loadability margin of power systems.
Abstract: Cooperative visual modeling is more and more
necessary in our complicated world. A collaborative environment
which supports interactive operation and communication is required
to increase work efficiency. We present a collaborative visual
modeling framework which collaborative platform could be built on.
On this platform, cooperation and communication is available for
designers from different regions. This framework, which is different
from other collaborative frameworks, contains a uniform message
format, a message handling mechanism and other functions such as
message pretreatment and Role-Communication-Token Access
Control (RCTAC). We also show our implementation of this
framework called Orchestra Designer, which support BPLE
workflow modeling cooperatively online.
Abstract: The globalization of the Indian economy has thrown a great challenge to the Indian industries in respect of productivity, quality, cost, delivery etc. Achieving success• the global market has required fundamental shift in the way business is conducted and has dramatically affected virtually every aspect of process industry. The internal manufacturing process and supporting infrastructure should be such that it can compete successfully in global markets with better flexibility and delivery. The paper deals with a case study of a reputed process industry, some changes in the process has been suggested, which leads to reduction in labor cost and production cost.
Abstract: The paper applies a discourse analytical approach to investigate important concepts influencing the infrastructure planning process in the region of Scania in southern Sweden. Two discourses, one concerning regional development and one concerning sustainability are identified, discussed and contrasted. It is argued that the perceptions of problems and their suggested solutions related to transportation are based on specific ideas, in turn dependent on the importance given to certain concepts, such as regional enlargement, Scania as a transit region, the national environmental quality goals and regional attractiveness. These concepts, their underlying meaning structures and their relevance for the infrastructure planning process are analyzed. The handling of conflicting interests in the planning process, and the possible implications this may have is also discussed. The results indicate that the regional development discourse is dominant and although the solutions to the problems caused by transport are framed in similar ways in the two discourses a harmonization between conflicting goals is proving difficult to achieve.
Abstract: With the exponentially increasing demand for
wireless communications the capacity of current cellular systems will
soon become incapable of handling the growing traffic. Since radio
frequencies are diminishing natural resources, there seems to be a
fundamental barrier to further capacity increase. The solution can be
found in smart antenna systems.
Smart or adaptive antenna arrays consist of an array of antenna
elements with signal processing capability, that optimize the
radiation and reception of a desired signal, dynamically. Smart
antennas can place nulls in the direction of interferers via adaptive
updating of weights linked to each antenna element. They thus cancel
out most of the co-channel interference resulting in better quality of
reception and lower dropped calls. Smart antennas can also track the
user within a cell via direction of arrival algorithms. This implies that
they are more advantageous than other antenna systems. This paper
focuses on few issues about the smart antennas in mobile radio
networks.
Abstract: The present paper is oriented to problems of simulation of anticipatory systems, namely those that use simulation models for the aid of anticipation. A certain analogy between use of simulation and imagining will be applied to make the explication more comprehensible. The paper will be completed by notes of problems and by some existing applications. The problems consist in the fact that simulation of the mentioned anticipatory systems end is simulation of simulating systems, i.e. in computer models handling two or more modeled time axes that should be mapped to real time flow in a nondescent manner. Languages oriented to objects, processes and blocks can be used to surmount the problems.
Abstract: Heat pipes are two-phase heat transfer devices with
high effective thermal conductivity. Due to the high heat transport
capacity, heat exchanger with heat pipes has become much smaller
than traditional heat exchangers in handling high heat fluxes. With
the working fluid in a heat pipe, heat can be absorbed on the
evaporator region and transported to the condenser region where the
vapour condenses releasing the heat to the cooling media. Heat pipe
technology has found increasing applications in enhancing the
thermal performance of heat exchangers in microelectranics, energy
saving in HVAC systems for operating rooms,surgery centers, hotels,
cleanrooms etc, temperature regulation systems for the human body
and other industrial sectors. Development activity in heat pipe and
thermosyphon technology in asia in recent years is surveyed. Some
new results obtained in Australia and other countries are also
included.
Abstract: An integrated vehicle dynamics control system is developed in this paper by a combination of active front steering (AFS) and direct yaw-moment control (DYC) based on fuzzy logic control. The control system has a hierarchical structure consisting of two layers. A fuzzy logic controller is used in the upper layer (yaw rate controller) to keep the yaw rate in its desired value. The yaw rate error and its rate of change are applied to the upper controlling layer as inputs, where the direct yaw moment control signal and the steering angle correction of the front wheels are the outputs. In the lower layer (fuzzy integrator), a fuzzy logic controller is designed based on the working region of the lateral tire forces. Depending on the directions of the lateral forces at the front wheels, a switching function is activated to adjust the scaling factor of the fuzzy logic controller. Using a nonlinear seven degrees of freedom vehicle model, the simulation results illustrate considerable improvements which are achieved in vehicle handling through the integrated AFS/DYC control system in comparison with the individual AFS or DYC controllers.
Abstract: In this paper; we are interested principally in dynamic modelling of quadrotor while taking into account the high-order nonholonomic constraints in order to develop a new control scheme as well as the various physical phenomena, which can influence the dynamics of a flying structure. These permit us to introduce a new state-space representation. After, the use of Backstepping approach for the synthesis of tracking errors and Lyapunov functions, a sliding mode controller is developed in order to ensure Lyapunov stability, the handling of all system nonlinearities and desired tracking trajectories. Finally simulation results are also provided in order to illustrate the performances of the proposed controller.
Abstract: This paper presents a supervised clustering algorithm,
namely Grid-Based Supervised Clustering (GBSC), which is able to
identify clusters of any shapes and sizes without presuming any
canonical form for data distribution. The GBSC needs no prespecified
number of clusters, is insensitive to the order of the input
data objects, and is capable of handling outliers. Built on the
combination of grid-based clustering and density-based clustering,
under the assistance of the downward closure property of density
used in bottom-up subspace clustering, the GBSC can notably reduce
its search space to avoid the memory confinement situation during its
execution. On two-dimension synthetic datasets, the GBSC can
identify clusters with different shapes and sizes correctly. The GBSC
also outperforms other five supervised clustering algorithms when
the experiments are performed on some UCI datasets.
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: Stock portfolio selection is a classic problem in finance,
and it involves deciding how to allocate an institution-s or an individual-s
wealth to a number of stocks, with certain investment objectives
(return and risk). In this paper, we adopt the classical Markowitz
mean-variance model and consider an additional common realistic
constraint, namely, the cardinality constraint. Thus, stock portfolio
optimization becomes a mixed-integer quadratic programming problem
and it is difficult to be solved by exact optimization algorithms.
Chemical Reaction Optimization (CRO), which mimics the molecular
interactions in a chemical reaction process, is a population-based
metaheuristic method. Two different types of CRO, named canonical
CRO and Super Molecule-based CRO (S-CRO), are proposed to solve
the stock portfolio selection problem. We test both canonical CRO
and S-CRO on a benchmark and compare their performance under
two criteria: Markowitz efficient frontier (Pareto frontier) and Sharpe
ratio. Computational experiments suggest that S-CRO is promising
in handling the stock portfolio optimization problem.
Abstract: Variable Structure Control (VSC) is one of the most useful tools handling the practical system with uncertainties and disturbances. Up to now, unfortunately, not enough studies on the input-saturated system with linear-growth-bound disturbances via VSC have been presented. Therefore, this paper proposes an asymp¬totic stability condition for the system via VSC. The designed VSC controller consists of two control parts. The linear control part plays a role in stabilizing the system, and simultaneously, the nonlinear control part in rejecting the linear-growth-bound disturbances perfectly. All conditions derived in this paper are expressed with Linear Matrices Inequalities (LMIs), which can be easily solved with an LMI toolbox in MATLAB.
Abstract: An effort to develop a unit commitment approach
capable of handling large power systems consisting of both thermal
and hydro generating units offers a large profitable return. In order to
be feasible, the method to be developed must be flexible, efficient
and reliable. In this paper, various proposed methods have been
described along with their strengths and weaknesses. As all of these
methods have some sort of weaknesses, a comprehensive algorithm
that combines the strengths of different methods and overcomes each
other-s weaknesses would be a suitable approach for solving
industry-grade unit commitment problem.
Abstract: Trust management is one of the drawbacks in Peer-to-Peer (P2P) system. Lack of centralized control makes it difficult to control the behavior of the peers. Reputation system is one approach to provide trust assessment in P2P system. In this paper, we use fuzzy logic to model trust in a P2P environment. Our trust model combines first-hand (direct experience) and second-hand (reputation)information to allow peers to represent and reason with uncertainty regarding other peers' trustworthiness. Fuzzy logic can help in handling the imprecise nature and uncertainty of trust. Linguistic labels are used to enable peers assign a trust level intuitively. Our fuzzy trust model is flexible such that inference rules are used to weight first-hand and second-hand accordingly.
Abstract: Automated discovery of Rule is, due to its applicability, one of the most fundamental and important method in KDD. It has been an active research area in the recent past. Hierarchical representation allows us to easily manage the complexity of knowledge, to view the knowledge at different levels of details, and to focus our attention on the interesting aspects only. One of such efficient and easy to understand systems is Hierarchical Production rule (HPRs) system. A HPR, a standard production rule augmented with generality and specificity information, is of the following form: Decision If < condition> Generality Specificity . HPRs systems are capable of handling taxonomical structures inherent in the knowledge about the real world. This paper focuses on the issue of mining Quantified rules with crisp hierarchical structure using Genetic Programming (GP) approach to knowledge discovery. The post-processing scheme presented in this work uses Quantified production rules as initial individuals of GP and discovers hierarchical structure. In proposed approach rules are quantified by using Dempster Shafer theory. Suitable genetic operators are proposed for the suggested encoding. Based on the Subsumption Matrix(SM), an appropriate fitness function is suggested. Finally, Quantified Hierarchical Production Rules (HPRs) are generated from the discovered hierarchy, using Dempster Shafer theory. Experimental results are presented to demonstrate the performance of the proposed algorithm.