Abstract: This study applies the sequential panel selection
method (SPSM) procedure proposed by Chortareas and Kapetanios
(2009) to investigate the time-series properties of energy
consumption in 50 US states from 1963 to 2009. SPSM involves the
classification of the entire panel into a group of stationary series and
a group of non-stationary series to identify how many and which
series in the panel are stationary processes. Empirical results obtained
through SPSM with the panel KSS unit root test developed by Ucar
and Omay (2009) combined with a Fourier function indicate that
energy consumption in all the 50 US states are stationary. The results
of this study have important policy implications for the 50 US states.
Abstract: The analysis of Acoustic Emission (AE) signal
generated from metal cutting processes has often approached
statistically. This is due to the stochastic nature of the emission
signal as a result of factors effecting the signal from its generation
through transmission and sensing. Different techniques are applied in
this manner, each of which is suitable for certain processes. In metal
cutting where the emission generated by the deformation process is
rather continuous, an appropriate method for analysing the AE signal
based on the root mean square (RMS) of the signal is often used and
is suitable for use with the conventional signal processing systems.
The aim of this paper is to set a strategy in tool failure detection in
turning processes via the statistic analysis of the AE generated from
the cutting zone. The strategy is based on the investigation of the
distribution moments of the AE signal at predetermined sampling.
The skews and kurtosis of these distributions are the key elements in
the detection. A normal (Gaussian) distribution has first been
suggested then this was eliminated due to insufficiency. The so
called Beta distribution was then considered, this has been used with
an assumed β density function and has given promising results with
regard to chipping and tool breakage detection.
Abstract: A new paradigm for software design and development models software by its business process, translates the model into a process execution language, and has it run by a supporting execution engine. This process-oriented paradigm promotes modeling of software by less technical users or business analysts as well as rapid development. Since business process models may be shared by different organizations and sometimes even by different business domains, it is interesting to apply a technique used in traditional software component technology to design reusable business processes. This paper discusses an approach to apply a technique for software component fabrication to the design of process-oriented software units, called process components. These process components result from decomposing a business process of a particular application domain into subprocesses with an aim that the process components can be reusable in different process-based software models. The approach is quantitative because the quality of process component design is measured from technical features of the process components. The approach is also strategic because the measured quality is determined against business-oriented component management goals. A software tool has been developed to measure how good a process component design is, according to the required managerial goals and comparing to other designs. We also discuss how we benefit from reusable process components.
Abstract: Through the course of this paper we define Business Case Management and its characteristics, and highlight its link to knowledge workers. Business Case Management combines knowledge and process effectively, supporting the ad hoc and unpredictable nature of cases, and coordinate a range of other technologies to appropriately support knowledge-intensive processes. We emphasize the growing importance of knowledge workers and the current poor support for knowledge work automation. We also discuss the challenges in supporting this kind of knowledge work and propose a novel approach to overcome these challenges.
Abstract: A traffic light gives security from traffic congestion,reducing the traffic jam, and organizing the traffic flow. Furthermore,increasing congestion level in public road networks is a growingproblem in many countries. Using Intelligent Transportation Systemsto provide emergency vehicles a green light at intersections canreduce driver confusion, reduce conflicts, and improve emergencyresponse times. Nowadays, the technology of wireless sensornetworks can solve many problems and can offer a good managementof the crossroad. In this paper, we develop a new approach based onthe technique of clustering and the graphical possibilistic fusionmodeling. So, the proposed model is elaborated in three phases. Thefirst one consists to decompose the environment into clusters,following by the fusion intra and inter clusters processes. Finally, wewill show some experimental results by simulation that proves theefficiency of our proposed approach.KeywordsTraffic light, Wireless sensor network, Controller,Possibilistic network/Bayesain network.
Abstract: System is using multiple processors for computing and information processing, is increasing rapidly speed operation of these systems compared with single processor systems, very significant impact on system performance is increased .important differences to yield a single multi-processor cpu, the scheduling policies, to reduce the implementation time of all processes. Notwithstanding the famous algorithms such as SPT, LPT, LSPT and RLPT for scheduling and there, but none led to the answer are not optimal.In this paper scheduling using genetic algorithms and innovative way to finish the whole process faster that we do and the result compared with three algorithms we mentioned.
Abstract: Air bending is one of the important metal forming
processes, because of its simplicity and large field application.
Accuracy of analytical and empirical models reported for the analysis
of bending processes is governed by simplifying assumption and do
not consider the effect of dynamic parameters. Number of researches
is reported on the finite element analysis (FEA) of V-bending, Ubending,
and air V-bending processes. FEA of bending is found to be
very sensitive to many physical and numerical parameters. FE
models must be computationally efficient for practical use. Reported
work shows the 3D FEA of air bending process using Hyperform LSDYNA
and its comparison with, published 3D FEA results of air
bending in Ansys LS-DYNA and experimental results. Observing the
planer symmetry and based on the assumption of plane strain
condition, air bending problem was modeled in 2D with symmetric
boundary condition in width. Stress-strain results of 2D FEA were
compared with 3D FEA results and experiments. Simplification of
air bending problem from 3D to 2D resulted into tremendous
reduction in the solution time with only marginal effect on stressstrain
results. FE model simplification by studying the problem
symmetry is more efficient and practical approach for solution of
more complex large dimensions slow forming processes.
Abstract: Future astronomical projects on large space x-ray
imaging telescopes require novel substrates and technologies for the
construction of their reflecting mirrors. The mirrors must be
lightweight and precisely shaped to achieve large collecting area with
high angular resolution. The new materials and technologies must be
cost-effective. Currently, the most promising materials are glass or
silicon foils. We focused on precise shaping these foils by thermal
forming process. We studied free and forced slumping in the
temperature region of hot plastic deformation and compared the
shapes obtained by the different slumping processes. We measured
the shapes and the surface quality of the foils. In the experiments, we
varied both heat-treatment temperature and time following our
experiment design. The obtained data and relations we can use for
modeling and optimizing the thermal forming procedure.
Abstract: The design of distributed systems involves dividing the system into partitions (or components) and then allocating these partitions to physical nodes. There have been several techniques proposed for both the partitioning and allocation processes. These existing techniques suffer from a number of limitations including lack of support for replication. Replication is difficult to use effectively but has the potential to greatly improve the performance of a distributed system. This paper presents a new technique technique for allocating objects in order to improve performance in a distributed system that supports replication. The performance of the proposed technique is demonstrated and tested on an example system. The performance of the new technique is compared with the performance of an existing technique in order to demonstrate both the validity and superiority of the new technique when developing a distributed system that can utilise object replication.
Abstract: Most, if not all, public hospitals in Thailand have encountered a common problem regarding the increasing demand for medical services. The increasing number of patients causes so much strain on the hospital-s services, over-crowded, overloaded working hours, staff fatigue, medical error and long waiting time. This research studied the characteristics of operational processes of the medical care services at the medicine department in a large public university hospital. The research focuses on details regarding methods, procedures, processes, resources, and time management in overall processes. The simulation model is used as a tool to analyze the impact of various improvement strategies.
Abstract: IT consultants often take over an important role as an
interface between technological, organizational and managerial
structures. As a result, the services offered are in many cases
assigned to different disciplines which can cause a lack of
transparency on the market for consulting services. However, not all
consulting products are suitable for every company because of
different frameworks and business processes. In this context the
questions arises as to what consulting products are currently offered
and how they can be compared as well as how the market for IT
consulting services is structured on the supply side. The presented
study aims to shed light on the IT consulting market by giving an
overview of the current structure of the supply-side for IT consulting
services as well as proposing a categorization of the currently
available consulting services (consulting fields) in order to provide a
theoretical background for the empirical study. Apart from these
theoretical considerations, the empirical results of field surveys on
the Austrian IT consulting market are presented and analyzed.
Abstract: Regenerative Thermal Oxidizer (RTO) is one of the
best solutions for removal of Volatile Organic Compounds (VOC)
from industrial processes. In the RTO, VOC in a raw gas are usually
decomposed at 950-1300 K and the combustion heat of VOC is
recovered by regenerative heat exchangers charged with ceramic
honeycombs. The optimization of the treatment of VOC leads to the
reduction of fuel addition to VOC decomposition, the minimization of
CO2 emission and operating cost as well.
In the present work, the thermal efficiency of the RTO was
investigated experimentally in a pilot-scale RTO unit using toluene as
a typical representative of VOC. As a result, it was recognized that the
radiative heat transfer was dominant in the preheating process of a raw
gas when the gas flow rate was relatively low. Further, it was found
that a minimum heat exchanger volume to achieve self combustion of
toluene without additional heating of the RTO by fuel combustion was
dependent on both the flow rate of a raw gas and the concentration of
toluene. The thermal efficiency calculated from fuel consumption and
the decomposed toluene ratio, was found to have a maximum value of
0.95 at a raw gas mass flow rate of 1810 kg·h-1 and honeycombs height
of 1.5m.
Abstract: Modern information and communication technologies
offer a variety of support options for the efficient handling of
customer relationships. CRM systems have been developed, which
are designed to support the processes in the areas of marketing, sales
and service. Along with technological progress, CRM systems are
constantly changing, i.e. the systems are continually enhanced by
new functions. However, not all functions are suitable for every
company because of different frameworks and business processes. In
this context the question arises whether or not CRM systems are
widely used in Austrian companies and which business processes are
most frequently supported by CRM systems. This paper aims to shed
light on the popularity of CRM systems in Austrian companies in
general and the use of different functions to support their daily
business. First of all, the paper provides a theoretical overview of the
structure of modern CRM systems and proposes a categorization of
currently available software functionality for collaborative,
operational and analytical CRM processes, which provides the
theoretical background for the empirical study. Apart from these
theoretical considerations, the paper presents the empirical results of
a field survey on the use of CRM systems in Austrian companies and
analyzes its findings.
Abstract: The presence of cold air with the convergent
topography of the Lut valley over the valley-s sloping terrain can
generate Low Level Jets (LLJ). Moreover, the valley-parallel
pressure gradients and northerly LLJ are produced as a result of the
large-scale processes. In the numerical study the regional MM5
model was run leading to achieve an appropriate dynamical analysis
of flows in the region for summer and winter. The results of this
study show the presence of summer synoptical systems cause the
formation of north-south pressure gradients in the valley which could
be led to the blowing of winds with the velocity more than 14 ms-1
and vulnerable dust and wind storms lasting more than 120 days.
Whereas the presence of cold air masses in the region in winter,
cause the average speed of LLJs decrease. In this time downslope
flows are noticeable in creating the night LLJs.
Abstract: The effects of global warming on India vary from the
submergence of low-lying islands and coastal lands to the melting of
glaciers in the Indian Himalayas, threatening the volumetric flow rate
of many of the most important rivers of India and South Asia. In
India, such effects are projected to impact millions of lives. As a
result of ongoing climate change, the climate of India has become
increasingly volatile over the past several decades; this trend is
expected to continue.
Climate change is one of the most important global environmental
challenges, with implications for food production, water supply,
health, energy, etc. Addressing climate change requires a good
scientific understanding as well as coordinated action at national and
global level. The climate change issue is part of the larger challenge
of sustainable development. As a result, climate policies can be more
effective when consistently embedded within broader strategies
designed to make national and regional development paths more
sustainable. The impact of climate variability and change, climate
policy responses, and associated socio-economic development will
affect the ability of countries to achieve sustainable development
goals.
A very well calibrated Soil and Water Assessment Tool (R2 =
0.9968, NSE = 0.91) was exercised over the Khatra sub basin of the
Kangsabati River watershed in Bankura district of West Bengal,
India, in order to evaluate projected parameters for agricultural
activities. Evapotranspiration, Transmission Losses, Potential
Evapotranspiration and Lateral Flow to reach are evaluated from the
years 2041-2050 in order to generate a picture for sustainable
development of the river basin and its inhabitants.
India has a significant stake in scientific advancement as well as
an international understanding to promote mitigation and adaptation.
This requires improved scientific understanding, capacity building,
networking and broad consultation processes. This paper is a
commitment towards the planning, management and development of
the water resources of the Kangsabati River by presenting detailed
future scenarios of the Kangsabati river basin, Khatra sub basin, over
the mentioned time period.
India-s economy and societal infrastructures are finely tuned to the
remarkable stability of the Indian monsoon, with the consequence
that vulnerability to small changes in monsoon rainfall is very high.
In 2002 the monsoon rains failed during July, causing profound loss
of agricultural production with a drop of over 3% in India-s GDP.
Neither the prolonged break in the monsoon nor the seasonal rainfall
deficit was predicted. While the general features of monsoon
variability and change are fairly well-documented, the causal
mechanisms and the role of regional ecosystems in modulating the
changes are still not clear. Current climate models are very poor at
modelling the Asian monsoon: this is a challenging and critical
region where the ocean, atmosphere, land surface and mountains all
interact. The impact of climate change on regional ecosystems is
likewise unknown. The potential for the monsoon to become more
volatile has major implications for India itself and for economies
worldwide. Knowledge of future variability of the monsoon system,
particularly in the context of global climate change, is of great
concern for regional water and food security.
The major findings of this paper were that of all the chosen
projected parameters, transmission losses, soil water content,
potential evapotranspiration, evapotranspiration and lateral flow to
reach, display an increasing trend over the time period of years 2041-
2050.
Abstract: Most neural network (NN) models of human category learning use a gradient-based learning method, which assumes that locally-optimal changes are made to model parameters on each learning trial. This method tends to under predict variability in individual-level cognitive processes. In addition many recent models of human category learning have been criticized for not being able to replicate rapid changes in categorization accuracy and attention processes observed in empirical studies. In this paper we introduce stochastic learning algorithms for NN models of human category learning and show that use of the algorithms can result in (a) rapid changes in accuracy and attention allocation, and (b) different learning trajectories and more realistic variability at the individual-level.
Abstract: This article presents a detailed analysis and comparative
performance evaluation of model reference adaptive control systems.
In contrast to classical control theory, adaptive control methods allow
to deal with time-variant processes. Inspired by the works [1] and
[2], two methods based on the MIT rule and Lyapunov rule are
applied to a linear first order system. The system is simulated and
it is investigated how changes to the adaptation gain affect the
system performance. Furthermore, variations in the reference model
parameters, that is changing the desired closed-loop behaviour are
examinded.
Abstract: In the semiconductor manufacturing process, large
amounts of data are collected from various sensors of multiple
facilities. The collected data from sensors have several different characteristics
due to variables such as types of products, former processes
and recipes. In general, Statistical Quality Control (SQC) methods
assume the normality of the data to detect out-of-control states of
processes. Although the collected data have different characteristics,
using the data as inputs of SQC will increase variations of data,
require wide control limits, and decrease performance to detect outof-
control. Therefore, it is necessary to separate similar data groups
from mixed data for more accurate process control. In the paper,
we propose a regression tree using split algorithm based on Pearson
distribution to handle non-normal distribution in parametric method.
The regression tree finds similar properties of data from different
variables. The experiments using real semiconductor manufacturing
process data show improved performance in fault detecting ability.
Abstract: In Supply Chain Management (SCM), strengthening partnerships with suppliers is a significant factor for enhancing competitiveness. Hence, firms increasingly emphasize supplier evaluation processes. Supplier evaluation systems are basically developed in terms of criteria such as quality, cost, delivery, and flexibility. Because there are many variables to be analyzed, this process becomes hard to execute and needs expertise. On this account, this study aims to develop an expert system on supplier evaluation process by designing Artificial Neural Network (ANN) that is supported with Data Envelopment Analysis (DEA). The methods are applied on the data of 24 suppliers, which have longterm relationships with a medium sized company from German Iron and Steel Industry. The data of suppliers consists of variables such as material quality (MQ), discount of amount (DOA), discount of cash (DOC), payment term (PT), delivery time (DT) and annual revenue (AR). Meanwhile, the efficiency that is generated by using DEA is added to the supplier evaluation system in order to use them as system outputs.
Abstract: Lipases are enzymes particularly amenable for
immobilization by entrapment methods, as they can work equally
well in aqueous or non-conventional media and long-time stability of
enzyme activity and enantioselectivity is needed to elaborate more
efficient bioprocesses. The improvement of Pseudomonas
fluorescens (Amano AK) lipase characteristics was investigated by
optimizing the immobilization procedure in hybrid organic-inorganic
matrices using ionic liquids as additives. Ionic liquids containing a
more hydrophobic alkyl group in the cationic moiety are beneficial
for the activity of immobilized lipase. Silanes with alkyl- or aryl
nonhydrolizable groups used as precursors in combination with
tetramethoxysilane could generate composites with higher
enantioselectivity compared to the native enzyme in acylation
reactions of secondary alcohols. The optimal effect on both activity
and enantioselectivity was achieved for the composite made from
octyltrimethoxysilane and tetramethoxysilane at 1:1 molar ratio (60%
increase of total activity following immobilization and enantiomeric
ratio of 30). Ionic liquids also demonstrated valuable properties as
reaction media for the studied reactions, comparable with the usual
organic solvent, hexane.