Abstract: Higher education institutions are increasingly opting to outsourcing methods in order to sustain themselves and this creates a gap of literature in terms of how they perceive the relationship. This research paper attempts to identify the behavioral and psychological factors that exist in the engagement thus providing valuable information to practicing and potential clients, and vendors. The determinants were gathered from previous literatures and analyzed to formulate the factors. This study adopts the case study and survey approaches in which interviews and questionnaires are deployed on employees of IT-related department in a Malaysian higher education institution.
Abstract: The precise form of tensorial transformations acting on a given collection of infinite matrices into another ; for such classical ideas connected with the summability field of double gai sequence spaces. In this paper the results are impose conditions on the tensor g so that it becomes a tensorial transformations from the metric space χ2 to the metric space C
Abstract: Stocking density is considered one of the important
factors affecting fish growth. But, information related to impact of
stocking density on growth performance of monosex tilapia population
under the ecological conditions of Gangetic plains in West Bengal,
India is limited. The aim of our study was to compare the growth
potential of monosex tilapia at various stocking densities and to
determine an ideal stocking density for culture of all-male monosex
fish. The males were isolated by examination of genital papilla region
and were stocked separately in 0.01 ha earthen ponds at different
stocking densities (5000, 10000, 15000, 20000, 25000 and 30000
fingerlings/ha). It was found that the highest weight, length, daily
weight gain, growth rate and protein content were observed for the
20000 fish/ha density class. Thus, culture of monosex tilapia at a
density of 20000 fish/ha can be considered ideal for augmented
production of the fish under Indian context.
Abstract: Array signal processing involves signal enumeration and source localization. Array signal processing is centered on the ability to fuse temporal and spatial information captured via sampling signals emitted from a number of sources at the sensors of an array in order to carry out a specific estimation task: source characteristics (mainly localization of the sources) and/or array characteristics (mainly array geometry) estimation. Array signal processing is a part of signal processing that uses sensors organized in patterns or arrays, to detect signals and to determine information about them. Beamforming is a general signal processing technique used to control the directionality of the reception or transmission of a signal. Using Beamforming we can direct the majority of signal energy we receive from a group of array. Multiple signal classification (MUSIC) is a highly popular eigenstructure-based estimation method of direction of arrival (DOA) with high resolution. This Paper enumerates the effect of missing sensors in DOA estimation. The accuracy of the MUSIC-based DOA estimation is degraded significantly both by the effects of the missing sensors among the receiving array elements and the unequal channel gain and phase errors of the receiver.
Abstract: Distance visualization of large datasets often takes the direction of remote viewing and zooming techniques of stored static images. However, the continuous increase in the size of datasets and visualization operation causes insufficient performance with traditional desktop computers. Additionally, the visualization techniques such as Isosurface depend on the available resources of the running machine and the size of datasets. Moreover, the continuous demand for powerful computing powers and continuous increase in the size of datasets results an urgent need for a grid computing infrastructure. However, some issues arise in current grid such as resources availability at the client machines which are not sufficient enough to process large datasets. On top of that, different output devices and different network bandwidth between the visualization pipeline components often result output suitable for one machine and not suitable for another. In this paper we investigate how the grid services could be used to support remote visualization of large datasets and to break the constraint of physical co-location of the resources by applying the grid computing technologies. We show our grid enabled architecture to visualize large medical datasets (circa 5 million polygons) for remote interactive visualization on modest resources clients.
Abstract: EPA (Ethernet for Plant Automation) resolves the nondeterministic problem of standard Ethernet and accomplishes real-time communication by means of micro-segment topology and deterministic scheduling mechanism. This paper studies the real-time performance of EPA periodic data transmission from theoretical and experimental perspective. By analyzing information transmission characteristics and EPA deterministic scheduling mechanism, 5 indicators including delivery time, time synchronization accuracy, data-sending time offset accuracy, utilization percentage of configured timeslice and non-RTE bandwidth that can be used to specify the real-time performance of EPA periodic data transmission are presented and investigated. On this basis, the test principles and test methods of the indicators are respectively studied and some formulas for real-time performance of EPA system are derived. Furthermore, an experiment platform is developed to test the indicators of EPA periodic data transmission in a micro-segment. According to the analysis and the experiment, the methods to improve the real-time performance of EPA periodic data transmission including optimizing network structure, studying self-adaptive adjustment method of timeslice and providing data-sending time offset accuracy for configuration are proposed.
Abstract: Flood zoning studies have become more efficient in
recent years because of the availability of advanced computational
facilities and use of Geographic Information Systems (GIS). In the
present study, flood inundated areas were mapped using GIS for the
Dikrong river basin of Arunachal Pradesh, India, corresponding to
different return periods (2, 5, 25, 50, and 100 years). Further, the developed inundation maps corresponding to 25, 50, and 100 year return period floods were compared to corresponding maps
developed by conventional methods as reported in the Brahmaputra Board Master Plan for Dikrong basin. It was found that, the average
deviation of modelled flood inundation areas from reported map
inundation areas is below 5% (4.52%). Therefore, it can be said that
the modelled flood inundation areas matched satisfactorily with
reported map inundation areas. Hence, GIS techniques were proved to be successful in extracting the flood inundation extent in a time and cost effective manner for the remotely located hilly basin of Dikrong, where conducting conventional surveys is very difficult.
Abstract: Performance appraisal of employee is important in
managing the human resource of an organization. With the change
towards knowledge-based capitalism, maintaining talented
knowledge workers is critical. However, management classification
of “outstanding", “poor" and “average" performance may not be an
easy decision. Besides that, superior might also tend to judge the
work performance of their subordinates informally and arbitrarily
especially without the existence of a system of appraisal. In this
paper, we propose a performance appraisal system using
multifactorial evaluation model in dealing with appraisal grades
which are often express vaguely in linguistic terms. The proposed
model is for evaluating staff performance based on specific
performance appraisal criteria. The project was collaboration with
one of the Information and Communication Technology company in
Malaysia with reference to its performance appraisal process.
Abstract: Recently, many web services to provide information for public transport are developed and released. They are optimized for mobile devices such a smartphone. We are also developing better path planning system for route buses and trains called “Bus-Net"[1]. However these systems only provide paths and related information before the user start moving. So we propose a context aware navigation to change the way to support public transport users. If we go to somewhere using many kinds of public transport, we have to know how to use them. In addition, public transport is dynamic system, and these have different characteristic by type. So we need information at real-time. Therefore we suggest the system that can support on user-s state. It has a variety of ways to help public transport users by each state, like turn-by-turn navigation. Context aware navigation will be able to reduce anxiety for using public transport.
Abstract: The right information at the right time influences the
enterprise and technical success. Sharing knowledge among members
of a big organization may be a complex activity. And as long as the
knowledge is not shared, can not be exploited by the organization.
There are some mechanisms which can originate knowledge sharing.
It is intended, in this paper, to trigger these mechanisms by using
semantic nets. Moreover, the intersection and overlapping of terms
and sub-terms, as well as their relationships will be described through
the mereology science for the whole knowledge sharing system. It is
proposed a knowledge system to supply to operators with the right
information about a specific process and possible risks, e.g. at the
assembly process, at the right time in an automated manufacturing
environment, such as at the automotive industry.
Abstract: The goal of data mining algorithms is to discover
useful information embedded in large databases. One of the most
important data mining problems is discovery of frequently occurring
patterns in sequential data. In a multidimensional sequence each
event depends on more than one dimension. The search space is quite
large and the serial algorithms are not scalable for very large
datasets. To address this, it is necessary to study scalable parallel
implementations of sequence mining algorithms.
In this paper, we present a model for multidimensional sequence
and describe a parallel algorithm based on data parallelism.
Simulation experiments show good load balancing and scalable and
acceptable speedup over different processors and problem sizes and
demonstrate that our approach can works efficiently in a real parallel
computing environment.
Abstract: In this article we present a change point detection algorithm based on the continuous wavelet transform. At the beginning of the article we describe a necessary transformation of a signal which has to be made for the purpose of change detection. Then case study related to iron ore sinter production which can be solved using our proposed technique is discussed. After that we describe a probabilistic algorithm which can be used to find changes using our transformed signal. It is shown that our algorithm works well with the presence of some noise and abnormal random bursts.
Abstract: The Economic factors are leading to the rise of
infrastructures provides software and computing facilities as a
service, known as cloud services or cloud computing. Cloud services
can provide efficiencies for application providers, both by limiting
up-front capital expenses, and by reducing the cost of ownership over
time. Such services are made available in a data center, using shared
commodity hardware for computation and storage. There is a varied
set of cloud services available today, including application services
(salesforce.com), storage services (Amazon S3), compute services
(Google App Engine, Amazon EC2) and data services (Amazon
SimpleDB, Microsoft SQL Server Data Services, Google-s Data
store). These services represent a variety of reformations of data
management architectures, and more are on the horizon.
Abstract: This paper presents a new approach for intelligent agent communication based on ontology for agent community. DARPA agent markup language (DAML) is used to build the community ontology. This paper extends the agent management specification by the foundation for intelligent physical agents (FIPA) to develop an agent role called community facilitator (CF) that manages community directory and community ontology. CF helps build agent community. Precise description of agent service in this community can thus be achieved. This facilitates agent communication. Furthermore, through ontology update, agents with different ontology are capable of communicating with each other. An example of advanced traveler information system is included to illustrate practicality of this approach.
Abstract: Data Structures and Algorithms is a module in most
Computer Science or Information Technology curricula. It is one of
the modules most students identify as being difficult. This paper
demonstrates how programming a solution for Sudoku can make
abstract concepts more concrete. The paper relates concepts of a
typical Data Structures and Algorithms module to a step by step
solution for Sudoku in a human type as opposed to a computer
oriented solution.
Abstract: Background noise is particularly damaging to speech
intelligibility for people with hearing loss especially for sensorineural
loss patients. Several investigations on speech intelligibility have
demonstrated sensorineural loss patients need 5-15 dB higher SNR
than the normal hearing subjects. This paper describes Discrete
Cosine Transform Power Normalized Least Mean Square algorithm
to improve the SNR and to reduce the convergence rate of the LMS
for Sensory neural loss patients. Since it requires only real arithmetic,
it establishes the faster convergence rate as compare to time domain
LMS and also this transformation improves the eigenvalue
distribution of the input autocorrelation matrix of the LMS filter.
The DCT has good ortho-normal, separable, and energy compaction
property. Although the DCT does not separate frequencies, it is a
powerful signal decorrelator. It is a real valued function and thus
can be effectively used in real-time operation. The advantages of
DCT-LMS as compared to standard LMS algorithm are shown via
SNR and eigenvalue ratio computations. . Exploiting the symmetry
of the basis functions, the DCT transform matrix [AN] can be
factored into a series of ±1 butterflies and rotation angles. This
factorization results in one of the fastest DCT implementation. There
are different ways to obtain factorizations. This work uses the fast
factored DCT algorithm developed by Chen and company. The
computer simulations results show superior convergence
characteristics of the proposed algorithm by improving the SNR at
least 10 dB for input SNR less than and equal to 0 dB, faster
convergence speed and better time and frequency characteristics.
Abstract: In this paper, using a model transformation approach a system of linear delay differential equations (DDEs) with multiple delays is converted to a non-delayed initial value problem. The variational iteration method (VIM) is then applied to obtain the approximate analytical solutions. Numerical results are given for several examples involving scalar and second order systems. Comparisons with the classical fourth-order Runge-Kutta method (RK4) verify that this method is very effective and convenient.
Abstract: The rapid growth of e-Commerce services is
significantly observed in the past decade. However, the method to
verify the authenticated users still widely depends on numeric
approaches. A new search on other verification methods suitable for
online e-Commerce is an interesting issue. In this paper, a new online
signature-verification method using angular transformation is
presented. Delay shifts existing in online signatures are estimated by
the estimation method relying on angle representation. In the
proposed signature-verification algorithm, all components of input
signature are extracted by considering the discontinuous break points
on the stream of angular values. Then the estimated delay shift is
captured by comparing with the selected reference signature and the
error matching can be computed as a main feature used for verifying
process. The threshold offsets are calculated by two types of error
characteristics of the signature verification problem, False Rejection
Rate (FRR) and False Acceptance Rate (FAR). The level of these two
error rates depends on the decision threshold chosen whose value is
such as to realize the Equal Error Rate (EER; FAR = FRR). The
experimental results show that through the simple programming,
employed on Internet for demonstrating e-Commerce services, the
proposed method can provide 95.39% correct verifications and 7%
better than DP matching based signature-verification method. In
addition, the signature verification with extracting components
provides more reliable results than using a whole decision making.
Abstract: It is difficult to judge ripeness by outward
characteristics such as size or external color. In this paper a nondestructive
method was studied to determine watermelon (Crimson
Sweet) quality. Responses of samples to excitation vibrations were
detected using laser Doppler vibrometry (LDV) technology. Phase
shift between input and output vibrations were extracted overall
frequency range. First and second were derived using frequency
response spectrums. After nondestructive tests, watermelons were
sensory evaluated. So the samples were graded in a range of ripeness
based on overall acceptability (total desired traits consumers).
Regression models were developed to predict quality using obtained
results and sample mass. The determination coefficients of the
calibration and cross validation models were 0.89 and 0.71
respectively. This study demonstrated feasibility of information
which is derived vibration response curves for predicting fruit
quality. The vibration response of watermelon using the LDV method
is measured without direct contact; it is accurate and timely, which
could result in significant advantage for classifying watermelons
based on consumer opinions.
Abstract: The emergence of networked information and communication has transformed the accessibility and delivery of scholarly information and fundamentally impacted on the processes of research and scholarly communication. The purpose of this study is to investigate disciplinary differences in the use of networked information for research and scholarly communication at Sultan Qaboos University, Oman. This study has produced quantitative data about how and why academics within different disciplines utilize networked information that is made available either internally through the university library, or externally through networked services accessed by the Internet. The results indicate some significant differences between the attitudes and practice of academics in the science disciplines when compared to those from the social sciences and humanities. While respondents from science disciplines show overall longer and more frequent use of networked information, respondents from humanities and social sciences indicated more positive attitudes and a greater degree of satisfaction toward library networked services.