Abstract: Injection molding is a very complicated process to
monitor and control. With its high complexity and many process
parameters, the optimization of these systems is a very challenging
problem. To meet the requirements and costs demanded by the
market, there has been an intense development and research with the
aim to maintain the process under control. This paper outlines the
latest advances in necessary algorithms for plastic injection process
and monitoring, and also a flexible data acquisition system that
allows rapid implementation of complex algorithms to assess their
correct performance and can be integrated in the quality control
process. This is the main topic of this paper. Finally, to demonstrate
the performance achieved by this combination, a real case of use is
presented.
Abstract: Due to today-s fierce competition, companies have to
be proactive creators of the future by effectively developing
innovations. Especially radical innovations allow high profit margins
– but they also entail high risks. One possibility to realize radical
innovations and reduce the risk of failure is cross-industry innovation
(CII). CII brings together problems and solution ideas from different
industries. However, there is a lack of systematic ways towards CII.
Bridging this gap, the present paper provides a systematic approach
towards planned CII. Starting with the analysis of potentials, the
definition of promising search strategies is crucial. Subsequently,
identified solution ideas need to be assessed. For the most promising
ones, the adaption process has to be systematically planned –
regarding the risk affinity of a company. The introduced method is
explained on a project from the furniture industry.
Abstract: Much research into handwritten Thai character
recognition have been proposed, such as comparing heads of
characters, Fuzzy logic and structure trees, etc. This paper presents a
system of handwritten Thai character recognition, which is based on
the Ant-minor algorithm (data mining based on Ant colony
optimization). Zoning is initially used to determine each character.
Then three distinct features (also called attributes) of each character
in each zone are extracted. The attributes are Head zone, End point,
and Feature code. All attributes are used for construct the
classification rules by an Ant-miner algorithm in order to classify
112 Thai characters. For this experiment, the Ant-miner algorithm is
adapted, with a small change to increase the recognition rate. The
result of this experiment is a 97% recognition rate of the training set
(11200 characters) and 82.7% recognition rate of unseen data test
(22400 characters).
Abstract: The main objective of this paper is to contribute the
existing knowledge transfer and IT Outsourcing literature
specifically in the context of Malaysia by reviewing the current
practices of e-government IT outsourcing in Malaysia including the
issues and challenges faced by the public agencies in transferring the
knowledge during the engagement. This paper discusses various
factors and different theoretical model of knowledge transfer starting
from the traditional model to the recent model suggested by the
scholars. The present paper attempts to align organizational
knowledge from the knowledge-based view (KBV) and
organizational learning (OL) lens. This review could help shape the
direction of both future theoretical and empirical studies on inter-firm
knowledge transfer specifically on how KBV and OL perspectives
could play significant role in explaining the complex relationships
between the client and vendor in inter-firm knowledge transfer and
the role of organizational management information system and
Transactive Memory System (TMS) to facilitate the organizational
knowledge transferring process. Conclusion is drawn and further
research is suggested.
Abstract: Long term rainfall analysis and prediction is a
challenging task especially in the modern world where the impact of
global warming is creating complications in environmental issues.
These factors which are data intensive require high performance
computational modeling for accurate prediction. This research paper
describes a prototype which is designed and developed on grid
environment using a number of coupled software infrastructural
building blocks. This grid enabled system provides the demanding
computational power, efficiency, resources, user-friendly interface,
secured job submission and high throughput. The results obtained
using sequential execution and grid enabled execution shows that
computational performance has enhanced among 36% to 75%, for
decade of climate parameters. Large variation in performance can be
attributed to varying degree of computational resources available for
job execution.
Grid Computing enables the dynamic runtime selection, sharing
and aggregation of distributed and autonomous resources which plays
an important role not only in business, but also in scientific
implications and social surroundings. This research paper attempts to
explore the grid enabled computing capabilities on weather indices
from HOAPS data for climate impact modeling and change
detection.
Abstract: The objective of this research was to study factors,
which were affected on surface roughness in high speed milling of
hardened tool steel. Material used in the experiment was tool steel JIS
SKD 61 that hardened on 60 ±2 HRC. Full factorial experimental
design was conducted on 3 factors and 3 levels (3
3
designs) with 2
replications. Factors were consisted of cutting speed, feed rate, and
depth of cut. The results showed that influenced factor affected to
surface roughness was cutting speed, feed rate and depth of cut which
showed statistical significant. Higher cutting speed would cause on
better surface quality. On the other hand, higher feed rate would cause
on poorer surface quality. Interaction of factor was found that cutting
speed and depth of cut were significantly to surface quality. The
interaction of high cutting speed associated with low depth of cut
affected to better surface quality than low cutting speed and high depth
of cut.
Abstract: The trends of design and development of information systems have undergone a variety of ongoing phases and stages. These variations have been evolved due to brisk changes in user requirements and business needs. To meet these requirements and needs, a flexible and agile business solution was required to come up with the latest business trends and styles. Another obstacle in agility of information systems was typically different treatment of same diseases of two patients: business processes and information services. After the emergence of information technology, the business processes and information systems have become counterparts. But these two business halves have been treated under totally different standards. There is need to streamline the boundaries of these both pillars that are equally sharing information system's burdens and liabilities. In last decade, the object orientation has evolved into one of the major solutions for modern business needs and now, SOA is the solution to shift business on ranks of electronic platform. BPM is another modern business solution that assists to regularize optimization of business processes. This paper discusses how object orientation can be conformed to incorporate or embed SOA in BPM for improved information systems.
Abstract: The aim of this study is to point out whether personalization of mathematical word problems could affect student achievement or not. The research was applied on two-grades students at spring semester 2008-2009. Before the treatment, students personal data were taken and given to the computer. During the treatment, paper-based personalized problems and paper-based non personalized problems were prepared by computer as the same problems and then these problems were given to students. At the end of the treatment, students- opinion was taken. As a result of this research, it was found out that there were no significant differences between learners through personalized or non-personalized materials, and also there were no significant differences between gender through personalized and non-personalized problems. However, opinion of students was highly positive through the personalized problems.
Abstract: The purpose of this article is to analyze economic and
political tendencies of development of integration processes with
different developing level and speed on the Eurasian space, by considering two organizations at the region – Eurasian Economic
Community and Shanghai Cooperation Organization, by considering the interests of participations in organizations of Russia and China as
a global powers and Kazakhstan as a leader among the Central Asian
countries. This article investigates what certain goals Eurasian
countries (especially Russia, Kazakhstan and China) are waiting from integration within the SCO and the EurAsEC, linking the process
with the theories of regional integration. After European debt crisis it is more topically to research the integration within the specific
region's conditions.
Abstract: Knowledge sharing in general and the contextual
access to knowledge in particular, still represent a key challenge in
the knowledge management framework. Researchers on semantic
web and human machine interface study techniques to enhance this
access. For instance, in semantic web, the information retrieval is
based on domain ontology. In human machine interface, keeping
track of user's activity provides some elements of the context that can
guide the access to information. We suggest an approach based on
these two key guidelines, whilst avoiding some of their weaknesses.
The approach permits a representation of both the context and the
design rationale of a project for an efficient access to knowledge. In
fact, the method consists of an information retrieval environment
that, in the one hand, can infer knowledge, modeled as a semantic
network, and on the other hand, is based on the context and the
objectives of a specific activity (the design). The environment we
defined can also be used to gather similar project elements in order to
build classifications of tasks, problems, arguments, etc. produced in a
company. These classifications can show the evolution of design
strategies in the company.
Abstract: This Classifying Bird Sounds (chip notes) project-s
purpose is to reduce the unwanted noise from recorded bird sound
chip notes, design a scheme to detect differences and similarities
between recorded chip notes, and classify bird sound chip notes. The
technologies of determining the similarities of sound waves have
been used in communication, sound engineering and wireless sound
applications for many years. Our research is focused on the similarity
of chip notes, which are the sounds from different birds. The program
we use is generated by Microsoft Cµ.
Abstract: The aim of this study was to investigate the
environmental conservation behavior of the Applied Health Science
students of Suranaree University of Technology, a green and clean
university. The sample group was 184 Applied Health Science
students (medical, nursing, and public health). A questionnaire was
used to collect information.
The result of the study found that the students had more negative
than positive behaviors towards energy, water, and forest
conservation. This result can be used as basic information for
designing long-term behavior modification activities or research
projects on environmental conservation. Thus Applied Health
Science students will be encouraged to be conscious and also be a
good example of environmental conservation behavior.
Abstract: Web-based technologies have created numerous
opportunities for electronic word-of-mouth (eWOM) communication.
There are many factors that affect customer adoption and decisionmaking
process. However, only a few researches focus on some
factors such as the membership time of forum and propensity to trust.
Using a discrete-time event simulation to simulate a diffusion model
along with a consumer decision model, the study shows the effect of
each factor on adoption of opinions on on-line discussion forum. The
purpose of this study is to examine the effect of factor affecting
information adoption and decision making process. The model is
constructed to test quantitative aspects of each factor. The simulation
study shows the membership time and the propensity to trust has an
effect on information adoption and purchasing decision. The result of
simulation shows that the longer the membership time in the
communities and the higher propensity to trust could lead to the
higher demand rates because consumers find it easier and faster to
trust the person in the community and then adopt the eWOM. Other
implications for both researchers and practitioners are provided.
Abstract: This research work is aimed at speech recognition
using scaly neural networks. A small vocabulary of 11 words were
established first, these words are “word, file, open, print, exit, edit,
cut, copy, paste, doc1, doc2". These chosen words involved with
executing some computer functions such as opening a file, print
certain text document, cutting, copying, pasting, editing and exit.
It introduced to the computer then subjected to feature extraction
process using LPC (linear prediction coefficients). These features are
used as input to an artificial neural network in speaker dependent
mode. Half of the words are used for training the artificial neural
network and the other half are used for testing the system; those are
used for information retrieval.
The system components are consist of three parts, speech
processing and feature extraction, training and testing by using neural
networks and information retrieval.
The retrieve process proved to be 79.5-88% successful, which is
quite acceptable, considering the variation to surrounding, state of
the person, and the microphone type.
Abstract: Researchers have been applying tional intelligence (AI/CI) methods to computer games. In this research field, further researchesare required to compare AI/CI
methods with respect to each game application. In th
our experimental result on the comparison of three evolutionary algorithms – evolution strategy, genetic algorithm, and their hybrid
applied to evolving controller agents for the CIG 2007 Simulated Car Racing competition. Our experimental result shows that, premature
convergence of solutions was observed in the case of ES, and GA outperformed ES in the last half of generations. Besides, a hybrid
which uses GA first and ES next evolved the best solution among the whole solutions being generated. This result shows the ability of GA in
globally searching promising areas in the early stage and the ability of ES in locally searching the focused area (fine-tuning solutions).
Abstract: A ten-year grazing study was conducted at the
Agriculture and Agri-Food Canada Brandon Research Centre in
Manitoba to study the effect of alfalfa inclusion and fertilizer (N, P,
K, and S) addition on economics and efficiency of non-renewable
energy use in meadow brome grass-based pasture systems for beef
production. Fertilizing grass-only or alfalfa-grass pastures to full soil
test recommendations improved pasture productivity, but did not
improve profitability compared to unfertilized pastures. Fertilizing
grass-only pastures resulted in the highest net loss of any pasture
management strategy in this study. Adding alfalfa at the time of
seeding, with no added fertilizer, was economically the best pasture
improvement strategy in this study. Because of moisture limitations,
adding commercial fertilizer to full soil test recommendations is
probably not economically justifiable in most years, especially with
the rising cost of fertilizer. Improving grass-only pastures by adding
fertilizer and/or alfalfa required additional non-renewable energy
inputs; however, the additional energy required for unfertilized
alfalfa-grass pastures was minimal compared to the fertilized
pastures. Of the four pasture management strategies, adding alfalfa
to grass pastures without adding fertilizer had the highest efficiency
of energy use. Based on energy use and economic performance, the
unfertilized alfalfa-grass pasture was the most efficient and
sustainable pasture system.
Abstract: Image Compression using Artificial Neural Networks
is a topic where research is being carried out in various directions
towards achieving a generalized and economical network.
Feedforward Networks using Back propagation Algorithm adopting
the method of steepest descent for error minimization is popular and
widely adopted and is directly applied to image compression.
Various research works are directed towards achieving quick
convergence of the network without loss of quality of the restored
image. In general the images used for compression are of different
types like dark image, high intensity image etc. When these images
are compressed using Back-propagation Network, it takes longer
time to converge. The reason for this is, the given image may
contain a number of distinct gray levels with narrow difference with
their neighborhood pixels. If the gray levels of the pixels in an image
and their neighbors are mapped in such a way that the difference in
the gray levels of the neighbors with the pixel is minimum, then
compression ratio as well as the convergence of the network can be
improved. To achieve this, a Cumulative distribution function is
estimated for the image and it is used to map the image pixels. When
the mapped image pixels are used, the Back-propagation Neural
Network yields high compression ratio as well as it converges
quickly.
Abstract: It well recognized that one feature that makes a
successful company is its ability to successfully align its business goals with its information communication technologies platform.
Enterprise Resource Planning (ERP) systems contribute to achieve better performance by integrating various business functions and
providing support for information flows. However, the technological
systems complexity is known to prevent the business users to exploit in an efficient way the Enterprise Resource Planning Systems (ERP).
This paper aims to investigate the role of training in improving the
usage of ERP systems. To this end, we have designed an instrument
survey to employees of a Norwegian multinational global provider of
technology solutions. Based on the analysis of collected data, we have delineated a training model that could be high relevance for
both researchers and practitioners as a step towards a better
understanding of ERP system implementation.
Abstract: Urban disaster risks and vulnerabilities are great problems for Turkey. The annual loss of life and property through disaster in the world-s major metropolitan areas is increasing. Urban concentrations of the poor and less-informed in environmentally fragile locations suffer the impact of disaster disproportionately. Gecekondu (squatter) developments will compound the inherent risks associated with high-density environments, in appropriate technologies, and inadequate infrastructure. On the other hand, there are many geological disadvantages such as sitting on top of active tectonic plate boundaries, and why having avalanche, flood, and landslide and drought prone areas in Turkey. However, this natural formation is inevitable; the only way to survive in such a harsh geography is to be aware of importance of these natural events and to take political and physical measures. The main aim of this research is to bring up the magnitude of natural hazard risks in Izmir built-up zone, not being taken into consideration adequately. Because the dimensions of the peril are not taken seriously enough, the natural hazard risks, which are commonly well known, are not considered important or they are being forgotten after some time passes. Within this research, the magnitude of natural hazard risks for Izmir is being presented in the scope of concrete and local researches over Izmir risky areas.
Abstract: Despite the recent surge of research in control of
worm propagation, currently, there is no effective defense system
against such cyber attacks. We first design a distributed detection
architecture called Detection via Distributed Blackholes (DDBH).
Our novel detection mechanism could be implemented via virtual
honeypots or honeynets. Simulation results show that a worm can be
detected with virtual honeypots on only 3% of the nodes. Moreover,
the worm is detected when less than 1.5% of the nodes are infected.
We then develop two control strategies: (1) optimal dynamic trafficblocking,
for which we determine the condition that guarantees
minimum number of removed nodes when the worm is contained and
(2) predictive dynamic traffic-blocking–a realistic deployment of
the optimal strategy on scale-free graphs. The predictive dynamic
traffic-blocking, coupled with the DDBH, ensures that more than
40% of the network is unaffected by the propagation at the time
when the worm is contained.