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: The main problems of data centric and open source
project are large number of developers and changes of core
framework. Model-View-Control (MVC) design pattern significantly
improved the development and adjustments of complex projects.
Entity framework as a Model layer in MVC architecture has
simplified communication with the database. How often are the new
technologies used and whether they have potentials for designing
more efficient Enterprise Resource Planning (ERP) system that will
be more suited to accountants?
Abstract: This paper studies dynamic stability of homogeneous
beams with piezoelectric layers subjected to periodic axial
compressive load that is simply supported at both ends lies on a
continuous elastic foundation. The displacement field of beam is
assumed based on Bernoulli-Euler beam theory. Applying the
Hamilton's principle, the governing dynamic equation is established.
The influences of applied voltage, foundation coefficient and
piezoelectric thickness on the unstable regions are presented. To
investigate the accuracy of the present analysis, a compression study
is carried out with a known data.
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: Lectins have a good scope in current clinical
microbiology research. In the present study evaluated the
antimicrobial activities of a D-galactose binding lectin (PnL) was
purified from the annelid, Perinereis nuntia (polychaeta) by affinity
chromatography. The molecular mass of the lectin was determined to
be 32 kDa as a single polypeptide by SDS-PAGE under both reducing
and non-reducing conditions. The hemagglutinating activity of the
PnL showed against trypsinized and glutaraldehyde-fixed human
erythrocytes was specifically inhibited by D-Gal, GalNAc,
Galβ1-4Glc and Galα1-6Glc. PnL was evaluated for in vitro
antibacterial screening studies against 11 gram-positive and
gram-negative microorganisms. From the screening results, it was
revealed that PnL exhibited significant antibacterial activity against
gram-positive bacteria. Bacillus megaterium showed the highest
growth inhibition by the lectin (250 μg/disc). However, PnL did not
inhibit the growth of gram-negative bacteria such as Vibrio cholerae
and Pseudomonas sp. PnL was also examined for in vitro antifungal
activity against six fungal phytopathogens. PnL (100 μg/mL) inhibited
the mycelial growth of Alternaria alternata (24.4%). These results
indicate that future findings of lectin applications obtained from
annelids may be of importance to life sciences.
Abstract: This paper presents the research agenda that has been proposed to develop an integrated model to explain technology adoption of SMEs in Malaysia. SMEs form over 90% of all business entities in Malaysia and they have been contributing to the development of the nation. Technology adoption has been a thorn issue among SMEs as they require big outlay which might not be available to the SMEs. Although resource has been an issue among SMEs they cannot lie low and ignore the technological advancements that are taking place at a rapid pace. With that in mind this paper proposes a model to explain the technology adoption issue among SMEs.
Abstract: In this study, the ability of Aspergillus niger and
Penicillium simplicissimum to extract heavy metals from a spent
refinery catalyst was investigated. For the first step, a spent
processing catalyst from one of the oil refineries in Iran was
physically and chemically characterized. Aspergillus niger and
Penicillium simplicissimum were used to mobilize Al/Co/Mo/Ni from
hazardous spent catalysts. The fungi were adapted to the mixture of
metals at 100-800 mg L-1 with increments in concentration of 100 mg
L-1. Bioleaching experiments were carried out in batch cultures. To
investigate the production of organic acids in sucrose medium,
analyses of the culture medium by HPLC were performed at specific
time intervals after inoculation. The results obtained from Inductive
coupled plasma-optical emission spectrometry (ICP-OES) showed
that after the one-step bioleaching process using Aspergillus niger,
maximum removal efficiencies of 27%, 66%, 62% and 38% were
achieved for Al, Co, Mo and Ni, respectively. However, the highest
removal efficiencies using Penicillium simplicissimum were of 32%,
67%, 65% and 38% for Al, Co, Mo and Ni, respectively
Abstract: Chatter vibration has been a troublesome problem for a
machine tool toward the high precision and high speed machining.
Essentially, the machining performance is determined by the dynamic
characteristics of the machine tool structure and dynamics of cutting
process. Therefore the dynamic vibration behavior of spindle tool
system greatly determines the performance of machine tool. The
purpose of this study is to investigate the influences of the machine
frame structure on the dynamic frequency of spindle tool unit through
finite element modeling approach. To this end, a realistic finite
element model of the vertical milling system was created by
incorporated the spindle-bearing model into the spindle head stock of
the machine frame. Using this model, the dynamic characteristics of
the milling machines with different structural designs of spindle head
stock and identical spindle tool unit were demonstrated. The results of
the finite element modeling reveal that the spindle tool unit behaves
more compliant when the excited frequency approaches the natural
mode of the spindle tool; while the spindle tool show a higher dynamic
stiffness at lower frequency that may be initiated by the structural
mode of milling head. Under this condition, it is concluded that the
structural configuration of spindle head stock associated with the
vertical column of milling machine plays an important role in
determining the machining dynamics of the spindle unit.
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: In this paper a class of analog algorithms based on the
concept of Cellular Neural Network (CNN) is applied in some
processing operations of some important medical images, namely
retina images, for detecting various symptoms connected with
diabetic retinopathy. Some specific processing tasks like
morphological operations, linear filtering and thresholding are
proposed, the corresponding template values are given and
simulations on real retina images are provided.
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: The bromination of five selected pharmaceuticals
(metoprolol, naproxen, amoxicillin, hydrochlorotiazide and
phenacetin) in ultrapure water and in three water matrices (a
groundwater, a surface water from a public reservoir and a secondary
effluent from a WWTP) was investigated. The apparent rate
constants for the bromination reaction were determined as a function
of the pH, and the sequence obtained for the reaction rate was
amoxicillin > naproxen >> hydrochlorotiazide ≈ phenacetin ≈
metoprolol. The proposal of a kinetic mechanism, which specifies the
dissociation of bromine and each pharmaceutical according to their
pKa values and the pH allowed the determination of the intrinsic rate
constants for every elementary reaction. The influence of the main
operating conditions (pH, initial bromine dose, and the water matrix)
on the degradation of pharmaceuticals was established. In addition,
the presence of bromide in chlorination experiments was
investigated. The presence of bromide in wastewaters and drinking
waters in the range of 10 to several hundred μg L-1 accelerated
slightly the oxidation of the selected pharmaceuticals during chorine
disinfection.
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: Stirred tanks have applications in many chemical
processes where mixing is important for the overall performance of
the system. In present work 5%v of the tank is filled by solid particles
with diameter of 700 m that Rushton Turbine and Propeller impeller
is used for stirring. An Eulerian-Eulerian Multi Fluid Model coupled
and for modeling rotating of impeller, moving reference frame
(MRF) technique was used and standard-k- model was selected for
turbulency. Flow field, radial velocity and axial distribution of solid
for both of impellers was investigation and comparison. Comparisons
of simulation results between Rushton Turbine and propeller impeller
shows that final quality of solid-liquid slurry in different rotating
speed for propeller impeller is better than the Rushton Turbine.
Abstract: The Programmable Logic Controller (PLC) plays a
vital role in automation and process control. Grafcet is used for
representing the control logic, and traditional programming
languages are used for describing the pure algorithms. Grafcet is used
for dividing the process to be automated in elementary sequences that
can be easily implemented. Each sequence represent a step that has
associated actions programmed using textual or graphical languages
after case. The programming task is simplified by using a set of
subroutines that are used in several steps. The paper presents an
example of implementation for a punching machine for sheets and
plates. The use the graphical languages the programming of a
complex sequential process is a necessary solution. The state of
Grafcet can be used for debugging and malfunction determination.
The use of the method combined with a set of knowledge acquisition
for process application reduces the downtime of the machine and
improve the productivity.
Abstract: In the era of great competition, understanding and satisfying
customers- requirements are the critical tasks for a company
to make a profits. Customer relationship management (CRM) thus
becomes an important business issue at present. With the help of
the data mining techniques, the manager can explore and analyze
from a large quantity of data to discover meaningful patterns and
rules. Among all methods, well-known association rule is most
commonly seen. This paper is based on Apriori algorithm and uses
genetic algorithms combining a data mining method to discover fuzzy
classification rules. The mined results can be applied in CRM to
help decision marker make correct business decisions for marketing
strategies.
Abstract: Empirical insights into the implementation of logistics competencies at the top management level are scarce. This paper addresses this issue with an explorative approach which is based on a dataset of 872 observations in the years 2000, 2004 and 2008 using quantitative content analysis from annual reports of the 500 publicly listed firms with the highest global research and development expenditures according to the British Department for Business Innovation and Skills. We find that logistics competencies are more pronounced in Asian companies than in their European or American counterparts. On an industrial level the results are quite mixed. Using partial point-biserial correlations we show that logistics competencies are positively related to financial performance.
Abstract: In this paper, we have developed an explicit analytical
drain current model comprising surface channel potential and
threshold voltage in order to explain the advantages of the proposed
Gate Stack Double Diffusion (GSDD) MOSFET design over the
conventional MOSFET with the same geometric specifications that
allow us to use the benefits of the incorporation of the high-k layer
between the oxide layer and gate metal aspect on the immunity of the
proposed design against the self-heating effects. In order to show the
efficiency of our proposed structure, we propose the simulation of the
power chopper circuit. The use of the proposed structure to design a
power chopper circuit has showed that the (GSDD) MOSFET can
improve the working of the circuit in terms of power dissipation and
self-heating effect immunity. The results so obtained are in close
proximity with the 2D simulated results thus confirming the validity
of the proposed model.
Abstract: The concept of flexible manufacturing is highly
appealing in gaining a competitive edge in the market by quickly
adapting to the changing customer needs. Scheduling jobs on flexible
manufacturing systems (FMSs) is a challenging task of managing the
available flexibility on the shop floor to react to the dynamics of the
environment in real-time. In this paper, an agent-oriented scheduling
framework that can be integrated with a real or a simulated FMS is
proposed. This framework works in stochastic environments with a
dynamic model of job arrival. It supports a hierarchical cooperative
scheduling that builds on the available flexibility of the shop floor.
Testing the framework on a model of a real FMS showed the
capability of the proposed approach to overcome the drawbacks of
the conventional approaches and maintain a near optimal solution
despite the dynamics of the operational environment.