Abstract: Safety of bus journey is a fundamental concern. Risk of injuries and fatalities is severe when bus superstructure fails during rollover accident. Adequate design and sufficient strength of bus superstructure can reduce the number of injuries and fatalities. This paper deals with structural analysis of bus superstructure undergoes rollover event. Several value of mass will be varied in multiple simulations. The purpose of this work is to analyze structural response of bus superstructure in terms of deformation, stress and strain under several loading and constraining conditions. A complete bus superstructure with forty four passenger-s capability was developed using finite element analysis software. Simulations have been conducted to observe the effect of total mass of bus on the strength of superstructure. These simulations are following United Nation Economic Commission of Europe regulation 66 which focuses on strength of large vehicle superstructure. Validation process had been done using simple box model experiment and results obtained are comparing with simulation results. Inputs data from validation process had been used in full scale simulation. Analyses suggested that, the failure of bus superstructure during rollover situation is basically dependent on the total mass of bus and on the strength of bus superstructure.
Abstract: Green Lean Total Quality Management (LTQM) Human Resource Management (HRM) System is a system comprises of HRM in Environmental Management System (EMS) practices which is integrated to TQM with Lean Manufacturing (LM) principles. HRM is essential especially in dealing with low motivation and less productive employees. The ultimate goal of this system is to focus on achieving total human resource development that is motivated and capable to optimize their creativity to be a part of Green and Lean TQM organization. A survey questionnaire was developed and distributed to 30 highly active automotive vendors in Malaysia and analyzed by Minitab v16 and SPSS v17. It was found out companies that are practicing Green LTQM HRM practices have generated more revenue and have RND capability. However, years of company establishment do not affect the openness of the company to adapt new initiatives that can help to improve the effectiveness of the operations. It was also found out the importance of training, communication and rewards for employees. The Green LTQM HRM practices framework model established in this study hopefully will give preliminary insight especially to companies that are still looking for system that can improve their productivity from managing human resource. This is preliminary study that combined 4 awards practices, ISO/TS16949, Toyota Production System SAEJ4000, MAJAICO Lean Production System and EMS focusing on highly active companies that have been involved in MAJAICO Program and Proton Vendor Development Program. Future study can be conducted to know the status at other industry as well as case study pertaining to this system.
Abstract: This paper presents recent work on the improvement
of the robotics vision based control strategy for underwater pipeline
tracking system. The study focuses on developing image processing
algorithms and a fuzzy inference system for the analysis of the
terrain. The main goal is to implement the supervisory fuzzy learning
control technique to reduce the errors on navigation decision due to
the pipeline occlusion problem. The system developed is capable of
interpreting underwater images containing occluded pipeline, seabed
and other unwanted noise. The algorithm proposed in previous work
does not explore the cooperation between fuzzy controllers,
knowledge and learnt data to improve the outputs for underwater
pipeline tracking. Computer simulations and prototype simulations
demonstrate the effectiveness of this approach. The system accuracy
level has also been discussed.
Abstract: With the rapid growth in business size, today's businesses orient towards electronic technologies. Amazon.com and e-bay.com are some of the major stakeholders in this regard. Unfortunately the enormous size and hugely unstructured data on the web, even for a single commodity, has become a cause of ambiguity for consumers. Extracting valuable information from such an everincreasing data is an extremely tedious task and is fast becoming critical towards the success of businesses. Web content mining can play a major role in solving these issues. It involves using efficient algorithmic techniques to search and retrieve the desired information from a seemingly impossible to search unstructured data on the Internet. Application of web content mining can be very encouraging in the areas of Customer Relations Modeling, billing records, logistics investigations, product cataloguing and quality management. In this paper we present a review of some very interesting, efficient yet implementable techniques from the field of web content mining and study their impact in the area specific to business user needs focusing both on the customer as well as the producer. The techniques we would be reviewing include, mining by developing a knowledge-base repository of the domain, iterative refinement of user queries for personalized search, using a graphbased approach for the development of a web-crawler and filtering information for personalized search using website captions. These techniques have been analyzed and compared on the basis of their execution time and relevance of the result they produced against a particular search.
Abstract: Cognizant of the fact that enterprise systems involve
organizational change and their implementation is over shadowed by a
high failure rate, it is argued that there is the need to focus attention on
employees- perceptions of such organizational change when
explaining adoption behavior of enterprise systems. For this purpose,
the research incorporates a conceptual constructo fattitude toward
change that captures views about the need for organizational change.
Centered on this conceptual construct, the research model includes
beliefs regarding the system and behavioral intention as its
consequences, and the personal characteristics of organizational
commitment and perceived personal competence as its antecedents.
Structural equation analysis using LISREL provides significant
support for the proposed relationships. Theoretical and practical
implications are discussed along with limitations.
Abstract: Considering toxicity of heavy metals and their
accumulation in domestic wastes, immobilization of lead and
cadmium is envisaged inside glass-ceramics. We particularly
focused this work on calcium-rich phases embedded in a
glassy matrix.
Glass-ceramics were synthesized from glasses doped with
12 wt% and 16 wt% of PbO or CdO. They were observed and
analyzed by Electron MicroProbe Analysis (EMPA) and
Analytical Scanning Electron Microscopy (ASEM). Structural
characterization of the samples was performed by powder XRay
Diffraction.
Diopside crystals of CaMgSi2O6 composition are shown to
incorporate significant amounts of cadmium (up to 9 wt% of
CdO). Two new crystalline phases are observed with very
high Cd or Pb contents: about 40 wt% CdO for the cadmiumrich
phase and near 60 wt% PbO for the lead-rich phase. We
present complete chemical and structural characterization of
these phases. They represent a promising way for the
immobilization of toxic elements like Cd or Pb since glass
ceramics are known to propose a “double barrier" protection
(metal-rich crystals embedded in a glass matrix) against metal
release in the environment.
Abstract: In today's day and age, one of the important topics in
information security is authentication. There are several alternatives
to text-based authentication of which includes Graphical Password
(GP) or Graphical User Authentication (GUA). These methods stems
from the fact that humans recognized and remembers images better
than alphanumerical text characters. This paper will focus on the
security aspect of GP algorithms and what most researchers have
been working on trying to define these security features and
attributes. The goal of this study is to develop a fuzzy decision model
that allows automatic selection of available GP algorithms by taking
into considerations the subjective judgments of the decision makers
who are more than 50 postgraduate students of computer science. The
approach that is being proposed is based on the Fuzzy Analytic
Hierarchy Process (FAHP) which determines the criteria weight as a
linear formula.
Abstract: The exploration of this paper will focus on the Cshaped
transition curve. This curve is designed by using the concept
of circle to circle where one circle lies inside other. The degree of
smoothness employed is curvature continuity. The function used in
designing the C-curve is Bézier-like cubic function. This function has
a low degree, flexible for the interactive design of curves and
surfaces and has a shape parameter. The shape parameter is used to
control the C-shape curve. Once the C-shaped curve design is
completed, this curve will be applied to design spur gear tooth. After
the tooth design procedure is finished, the design will be analyzed by
using Finite Element Analysis (FEA). This analysis is used to find
out the applicability of the tooth design and the gear material that
chosen. In this research, Cast Iron 4.5 % Carbon, ASTM A-48 is
selected as a gear material.
Abstract: Palestinian cities face the challenges of land scarcity,
high population growth rates, rapid urbanization, uneven
development and territorial fragmentation. Due to geopolitical
constrains and the absence of an effective Palestinian planning
institution, urban development in Palestinian cities has not followed
any discernable planning scheme. This has led to a number of
internal contradictions in the structure of cities, and adversely
affected land use, the provision of urban services, and the quality of
the living environment.
This paper explores these challenges, and the potential that exists
for introducing a more sustainable urban development pattern in
Palestinian cities. It assesses alternative development approaches
with a particular focus on sustainable development, promoting ecodevelopment
imperatives, limiting random urbanization, and meeting
present and future challenges, including fulfilling the needs of the
people and conserving the scarce land and limited natural resources.
This paper concludes by offering conceptual proposals and guidelines
for promoting sustainable physical development in Palestinian cities.
Abstract: Bonding has become a routine procedure in several
dental specialties – from prosthodontics to conservative dentistry and
even orthodontics. In many of these fields it is important to be able to
investigate the bonded interfaces to assess their quality. All currently
employed investigative methods are invasive, meaning that samples
are destroyed in the testing procedure and cannot be used again. We
have investigated the interface between human enamel and bonded
ceramic brackets non-invasively, introducing a combination of new
investigative methods – optical coherence tomography (OCT),
fluorescence OCT and confocal microscopy (CM). Brackets were
conventionally bonded on conditioned buccal surfaces of teeth. The
bonding was assessed using these methods. Three dimensional
reconstructions of the detected material defects were developed using
manual and semi-automatic segmentation. The results clearly prove
that OCT, fluorescence OCT and CM are useful in orthodontic
bonding investigations.
Abstract: EDF (Early Deadline First) algorithm is a very important scheduling algorithm for real- time systems . The EDF algorithm assigns priorities to each job according to their absolute deadlines and has good performance when the real-time system is not overloaded. When the real-time system is overloaded, many misdeadlines will be produced. But these misdeadlines are not uniformly distributed, which usually focus on some tasks. In this paper, we present an adaptive fuzzy control scheduling based on EDF algorithm. The improved algorithm can have a rectangular distribution of misdeadline ratios among all real-time tasks when the system is overloaded. To evaluate the effectiveness of the improved algorithm, we have done extensive simulation studies. The simulation results show that the new algorithm is superior to the old algorithm.
Abstract: Human identification at a distance has recently gained
growing interest from computer vision researchers. Gait recognition
aims essentially to address this problem by identifying people based
on the way they walk [1]. Gait recognition has 3 steps. The first step
is preprocessing, the second step is feature extraction and the third
one is classification. This paper focuses on the classification step that
is essential to increase the CCR (Correct Classification Rate).
Multilayer Perceptron (MLP) is used in this work. Neural Networks
imitate the human brain to perform intelligent tasks [3].They can
represent complicated relationships between input and output and
acquire knowledge about these relationships directly from the data
[2]. In this paper we apply MLP NN for 11 views in our database and
compare the CCR values for these views. Experiments are performed
with the NLPR databases, and the effectiveness of the proposed
method for gait recognition is demonstrated.
Abstract: Mining sequential patterns from large customer transaction databases has been recognized as a key research topic in database systems. However, the previous works more focused on mining sequential patterns at a single concept level. In this study, we introduced concept hierarchies into this problem and present several algorithms for discovering multiple-level sequential patterns based on the hierarchies. An experiment was conducted to assess the performance of the proposed algorithms. The performances of the algorithms were measured by the relative time spent on completing the mining tasks on two different datasets. The experimental results showed that the performance depends on the characteristics of the datasets and the pre-defined threshold of minimal support for each level of the concept hierarchy. Based on the experimental results, some suggestions were also given for how to select appropriate algorithm for a certain datasets.
Abstract: Magnetic Nanoparticles (MNPs) have great potential
to overcome many of the shortcomings of the present diagnostic and
therapeutic approaches used in cancer diagnosis and treatment. This
Literature review discusses the use of Magnetic Nanoparticles
focusing mainly on Iron oxide based MNPs in cancer imaging using
MRI.
Abstract: In recent years, scanning probe atomic force
microscopy SPM AFM has gained acceptance over a wide spectrum
of research and science applications. Most fields focuses on physical,
chemical, biological while less attention is devoted to manufacturing
and machining aspects. The purpose of the current study is to assess
the possible implementation of the SPM AFM features and its
NanoScope software in general machining applications with special
attention to the tribological aspects of cutting tool. The surface
morphology of coated and uncoated as-received carbide inserts is
examined, analyzed, and characterized through the determination of
the appropriate scanning setting, the suitable data type imaging
techniques and the most representative data analysis parameters
using the MultiMode SPM AFM in contact mode. The NanoScope
operating software is used to capture realtime three data types
images: “Height", “Deflection" and “Friction". Three scan sizes are
independently performed: 2, 6, and 12 μm with a 2.5 μm vertical
range (Z). Offline mode analysis includes the determination of three
functional topographical parameters: surface “Roughness", power
spectral density “PSD" and “Section". The 12 μm scan size in
association with “Height" imaging is found efficient to capture every
tiny features and tribological aspects of the examined surface. Also,
“Friction" analysis is found to produce a comprehensive explanation
about the lateral characteristics of the scanned surface. Configuration
of many surface defects and drawbacks has been precisely detected
and analyzed.
Abstract: Trust management and Reputation models are
becoming integral part of Internet based applications such as CSCW,
E-commerce and Grid Computing. Also the trust dimension is a
significant social structure and key to social relations within a
collaborative community. Collaborative Decision Making (CDM) is
a difficult task in the context of distributed environment (information
across different geographical locations) and multidisciplinary
decisions are involved such as Virtual Organization (VO). To aid
team decision making in VO, Decision Support System and social
network analysis approaches are integrated. In such situations social
learning helps an organization in terms of relationship, team
formation, partner selection etc. In this paper we focus on trust
learning. Trust learning is an important activity in terms of
information exchange, negotiation, collaboration and trust
assessment for cooperation among virtual team members. In this
paper we have proposed a reinforcement learning which enhances the
trust decision making capability of interacting agents during
collaboration in problem solving activity. Trust computational model
with learning that we present is adapted for best alternate selection of
new project in the organization. We verify our model in a multi-agent
simulation where the agents in the community learn to identify
trustworthy members, inconsistent behavior and conflicting behavior
of agents.
Abstract: The main objective of this paper is to analyse the influence of preparation and control of orders on performance. The focused activities explored in this research are: procurement, production and distribution. These changes in performance were obtained through improvement of the supply chain. It is proved using all the company activities that it is possible to increase de efficiency and do services in an adequate way, placing the products in the market efficiently. For that, it was explored the importance of the supply chain, with privilege to the practical environment and the quantification of the obtained results.
Abstract: Recent theorizations on the cognitive process of moral
judgment have focused on the role of intuitions and emotions, marking
a departure from previous emphasis on conscious, step-by-step
reasoning. My study investigated how being in a disgusted mood state
affects moral judgment.
Participants were induced to enter a disgusted mood state through
listening to disgusting sounds and reading disgusting descriptions.
Results shows that they, when compared to control who have not been
induced to feel disgust, are more likely to endorse actions that are
emotionally aversive but maximizes utilitarian return
The result is analyzed using the 'emotion-as-information' approach
to decision making. The result is consistent with the view that
emotions play an important role in determining moral judgment.
Abstract: Work stress causes the organizational work-life
imbalance of employees. Because of this imbalance, workers perform
with lower effort to finish assignments and thus an organization will
experience reduced productivity. In order to investigate the problem
of an organizational work-life imbalance, this qualitative case study
focuses on an organizational work-life imbalance among Thai
software developers in a German-owned company in Chiang Mai,
Thailand. In terms of knowledge management, fishbone diagram is
useful analysis tool to investigate the root causes of an organizational
work-life imbalance systematically in focus-group discussions.
Furthermore, fishbone diagram shows the relationship between
causes and effects clearly. It was found that an organizational worklife
imbalance among Thai software developers is influenced by
management team, work environment, and information tools used in
the company over time.
Abstract: Logistics is part of the supply chain processes that plans, implements, and controls the efficient and effective forward and reverse flow and storage of goods, services, and related information between the point of origin and the point of consumption in order to meet customer requirements. This research aims to investigate the current status and future direction of the use of Information Technology (IT) for logistics, focusing on Supply Chain Management (SCM) and E-Commerce adoption in Johor. Therefore, this research stresses on the type of technology being adopted, factors, benefits and barriers affecting the innovation in SCM and ECommerce technology adoption among Logistics Service Providers (LSP). A mailed questionnaire survey was conducted to collect data from 265 logistics companies in Johor. The research revealed that SCM technology adoption among LSP was higher as they had adopted SCM technology in various business processes while they perceived a high level of benefits from SCM adoption. Obviously, ECommerce technology adoption among LSP is relatively low.