Abstract: One of the main processes of supply chain
management is supplier selection process which its accurate
implementation can dramatically increase company competitiveness.
In presented article model developed based on the features of
second tiers suppliers and four scenarios are predicted in order to
help the decision maker (DM) in making up his/her mind. In addition
two tiers of suppliers have been considered as a chain of suppliers.
Then the proposed approach is solved by a method combined of
concepts of fuzzy set theory (FST) and linear programming (LP)
which has been nourished by real data extracted from an engineering
design and supplying parts company. At the end results reveal the
high importance of considering second tier suppliers features as
criteria for selecting the best supplier.
Abstract: Business rules and data warehouse are concepts and
technologies that impact a wide variety of organizational tasks. In
general, each area has evolved independently, impacting application
development and decision-making. Generating knowledge from data
warehouse is a complex process. This paper outlines an approach to
ease import of information and knowledge from a data warehouse
star schema through an inference class of business rules. The paper
utilizes the Oracle database for illustrating the working of the
concepts. The star schema structure and the business rules are stored
within a relational database. The approach is explained through a
prototype in Oracle-s PL/SQL Server Pages.
Abstract: This paper describes a code clone visualization method, called FC graph, and the implementation issues. Code clone detection tools usually show the results in a textual representation. If the results are large, it makes a problem to software maintainers with understanding them. One of the approaches to overcome the situation is visualization of code clone detection results. A scatter plot is a popular approach to the visualization. However, it represents only one-to-one correspondence and it is difficult to find correspondence of code clones over multiple files. FC graph represents correspondence among files, code clones and packages in Java. All nodes in FC graph are positioned using force-directed graph layout, which is dynami- cally calculated to adjust the distances of nodes until stabilizing them. We applied FC graph to some open source programs and visualized the results. In the author’s experience, FC graph is helpful to grasp correspondence of code clones over multiple files and also code clones with in a file.
Abstract: The present work demonstrates the design and simulation of a fuzzy control of an air conditioning system at different pressures. The first order Sugeno fuzzy inference system is utilized to model the system and create the controller. In addition, an estimation of the heat transfer rate and water mass flow rate injection into or withdraw from the air conditioning system is determined by the fuzzy IF-THEN rules. The approach starts by generating the input/output data. Then, the subtractive clustering algorithm along with least square estimation (LSE) generates the fuzzy rules that describe the relationship between input/output data. The fuzzy rules are tuned by Adaptive Neuro-Fuzzy Inference System (ANFIS). The results show that when the pressure increases the amount of water flow rate and heat transfer rate decrease within the lower ranges of inlet dry bulb temperatures. On the other hand, and as pressure increases the amount of water flow rate and heat transfer rate increases within the higher ranges of inlet dry bulb temperatures. The inflection in the pressure effect trend occurs at lower temperatures as the inlet air humidity increases.
Abstract: Data stream analysis is the process of computing
various summaries and derived values from large amounts of data
which are continuously generated at a rapid rate. The nature of a
stream does not allow a revisit on each data element. Furthermore,
data processing must be fast to produce timely analysis results. These
requirements impose constraints on the design of the algorithms to
balance correctness against timely responses. Several techniques
have been proposed over the past few years to address these
challenges. These techniques can be categorized as either dataoriented
or task-oriented. The data-oriented approach analyzes a
subset of data or a smaller transformed representation, whereas taskoriented
scheme solves the problem directly via approximation
techniques. We propose a hybrid approach to tackle the data stream
analysis problem. The data stream has been both statistically
transformed to a smaller size and computationally approximated its
characteristics. We adopt a Monte Carlo method in the approximation
step. The data reduction has been performed horizontally and
vertically through our EMR sampling method. The proposed method
is analyzed by a series of experiments. We apply our algorithm on
clustering and classification tasks to evaluate the utility of our
approach.
Abstract: Sorting appears the most attention among all computational tasks over the past years because sorted data is at the heart of many computations. Sorting is of additional importance to parallel computing because of its close relation to the task of routing data among processes, which is an essential part of many parallel algorithms. Many parallel sorting algorithms have been investigated for a variety of parallel computer architectures. In this paper, three parallel sorting algorithms have been implemented and compared in terms of their overall execution time. The algorithms implemented are the odd-even transposition sort, parallel merge sort and parallel rank sort. Cluster of Workstations or Windows Compute Cluster has been used to compare the algorithms implemented. The C# programming language is used to develop the sorting algorithms. The MPI (Message Passing Interface) library has been selected to establish the communication and synchronization between processors. The time complexity for each parallel sorting algorithm will also be mentioned and analyzed.
Abstract: The main mission of Ezilla is to provide a friendly
interface to access the virtual machine and quickly deploy the high
performance computing environment. Ezilla has been developed by
Pervasive Computing Team at National Center for High-performance
Computing (NCHC). Ezilla integrates the Cloud middleware,
virtualization technology, and Web-based Operating System (WebOS)
to form a virtual computer in distributed computing environment. In
order to upgrade the dataset and speedup, we proposed the sensor
observation system to deal with a huge amount of data in the
Cassandra database. The sensor observation system is based on the
Ezilla to store sensor raw data into distributed database. We adopt the
Ezilla Cloud service to create virtual machines and login into virtual
machine to deploy the sensor observation system. Integrating the
sensor observation system with Ezilla is to quickly deploy experiment
environment and access a huge amount of data with distributed
database that support the replication mechanism to protect the data
security.
Abstract: This paper presents Faults Forecasting System (FFS)
that utilizes statistical forecasting techniques in analyzing process
variables data in order to forecast faults occurrences. FFS is
proposing new idea in detecting faults. Current techniques used in
faults detection are based on analyzing the current status of the
system variables in order to check if the current status is fault or not.
FFS is using forecasting techniques to predict future timing for faults
before it happens. Proposed model is applying subset modeling
strategy and Bayesian approach in order to decrease dimensionality
of the process variables and improve faults forecasting accuracy. A
practical experiment, designed and implemented in Okayama
University, Japan, is implemented, and the comparison shows that
our proposed model is showing high forecasting accuracy and
BEFORE-TIME.
Abstract: Scatter behavior of fatigue life in die-cast AM60B
alloy was investigated. For comparison, those in rolled AM60B alloy
and die-cast A365-T5 aluminum alloy were also studied. Scatter
behavior of pore size was also investigated to discuss dominant
factors for fatigue life scatter in die-cast materials. Three-parameter
Weibull function was suitable to explain the scatter behavior of both
fatigue life and pore size. The scatter of fatigue life in die-cast
AM60B alloy was almost comparable to that in die-cast A365-T5
alloy, while it was significantly large compared to that in the rolled
AM60B alloy. Scatter behavior of pore size observed at fracture
nucleation site on the fracture surface was comparable to that
observed on the specimen cross-section and also to that of fatigue
life. Therefore, the dominant factor for large scatter of fatigue life in
die-cast alloys would be the large scatter of pore size. This
speculation was confirmed by the fracture mechanics fatigue life
prediction, where the pore observed at fatigue crack nucleation site
was assumed as the pre-existing crack.
Abstract: The draw solute separation process in Forward
Osmosis desalination was simulated in Aspen Plus chemical process
modeling software, to estimate the energy consumption and compare
it with other desalination processes, mainly the Reverse Osmosis
process which is currently most prevalent. The electrolytic chemistry
for the system was retrieved using the Elec – NRTL property method
in the Aspen Plus database. Electrical equivalent of energy required
in the Forward Osmosis desalination technique was estimated and
compared with the prevalent desalination techniques.
Abstract: This paper deals with the design, development & implementation of a temperature sensor using zigbee. The main aim of the work undertaken in this paper is to sense the temperature and to display the result on the LCD using the zigbee technology. ZigBee operates in the industrial, scientific and medical (ISM) radio bands; 868 MHz in Europe, 915 MHz in the USA and 2.4 GHz in most jurisdictions worldwide. The technology is intended to be simpler and cheaper than other WPANs such as Bluetooth. The most capable ZigBee node type is said to require only about 10 % of the software of a typical Bluetooth or Wireless Internet node, while the simplest nodes are about 2 %. However, actual code sizes are much higher, more like 50 % of the Bluetooth code size. ZigBee chip vendors have announced 128-kilobyte devices. In this work undertaken in the design & development of the temperature sensor, it senses the temperature and after amplification is then fed to the micro controller, this is then connected to the zigbee module, which transmits the data and at the other end the zigbee reads the data and displays on to the LCD. The software developed is highly accurate and works at a very high speed. The method developed shows the effectiveness of the scheme employed.
Abstract: In wireless sensor network (WSN) the use of mobile
sink has been attracting more attention in recent times. Mobile sinks
are more effective means of balancing load, reducing hotspot
problem and elongating network lifetime. The sensor nodes in WSN
have limited power supply, computational capability and storage and
therefore for continuous data delivery reliability becomes high
priority in these networks. In this paper, we propose a Reliable
Energy-efficient Data Dissemination (REDD) scheme for WSNs with
multiple mobile sinks. In this strategy, sink first determines the
location of source and then directly communicates with the source
using geographical forwarding. Every forwarding node (FN) creates a
local zone comprising some sensor nodes that can act as
representative of FN when it fails. Analytical and simulation study
reveals significant improvement in energy conservation and reliable
data delivery in comparison to existing schemes.
Abstract: In the current research, we present an operation framework and protection mechanism to facilitate secure environment to protect mobile agents against tampering. The system depends on the presence of an authentication authority. The advantage of the proposed system is that security measures is an integral part of the design, thus common security retrofitting problems do not arise. This is due to the presence of AlGamal encryption mechanism to protect its confidential content and any collected data by the agent from the visited host . So that eavesdropping on information from the agent is no longer possible to reveal any confidential information. Also the inherent security constraints within the framework allow the system to operate as an intrusion detection system for any mobile agent environment. The mechanism is tested for most of the well known severe attacks against agents and networked systems. The scheme proved a promising performance that makes it very much recommended for the types of transactions that needs highly secure environments, e. g., business to business.
Abstract: Global Solar Radiation (H) for Dubai and Sharjah,
Latitude 25.25oN, Longitude 55oE and 25.29oN, Longitude 55oE
respectively have been studied using sunshine hour data (n) of the
areas using various methods. These calculated global solar radiation
values are then compared to the measured values presented by
NASA. Furthermore, the extraterrestrial (H0), diffuse (Hd) and beam
radiation (Hb) are also calculated. The diffuse radiation is calculated
using methods proposed by Page and Liu and Jordan (L-J). Diffuse
Radiation from the Page method is higher than the L-J method.
Moreover, the clearness index (KT) signifies a clear sky almost all
year round. Rainy days are hardly a few in a year and limited in the
months December to March. The temperature remains between 25oC
in winter to 44oC in summer and is desirable for thermal applications
of solar energy. From the estimated results, it appears that solar
radiation can be utilized very efficiently throughout the year for
photovoltaic and thermal applications.
Abstract: After allowing direct flights from Mainland China to
Taiwan, Chinese tourists increased according to Tourism
Bureaustatistics. There are from 0.19 to 2 million tourists from 2008 to
2011. Mainland China has become the main source of Taiwan
developing tourism industry. Taiwanese government should know
more about comments from Chinese tourists to Taiwan in order
toproperly market Taiwan tourism and enhance the overall quality of
tourism. In order to understand Chinese visitors’ comments, this study
adopts content analysis to analyze electronic word-of-mouth on Web.
This study collects 375 blog articles of Chinese tourists from
Ctrip.com as a database during 2009 to 2011. Through the qualitative
data analysis the traveling destination imagesis divided into seven
dimensions, such as senic spots, shopping, food and beverages,
accommodations, transportation, festivals and recreation activities.
Finally, this study proposes some practical managerial implication to
know both positive and negative images of the seven dimensions from
Chinese tourists, providing marketing strategies and suggestions to
traveling agency industry.
Abstract: In this paper, the modelling and design of artificial neural network architecture for load forecasting purposes is investigated. The primary pre-requisite for power system planning is to arrive at realistic estimates of future demand of power, which is known as Load Forecasting. Short Term Load Forecasting (STLF) helps in determining the economic, reliable and secure operating strategies for power system. The dependence of load on several factors makes the load forecasting a very challenging job. An over estimation of the load may cause premature investment and unnecessary blocking of the capital where as under estimation of load may result in shortage of equipment and circuits. It is always better to plan the system for the load slightly higher than expected one so that no exigency may arise. In this paper, a load-forecasting model is proposed using a multilayer neural network with an appropriately modified back propagation learning algorithm. Once the neural network model is designed and trained, it can forecast the load of the power system 24 hours ahead on daily basis and can also forecast the cumulative load on daily basis. The real load data that is used for the Artificial Neural Network training was taken from LDC, Gujarat Electricity Board, Jambuva, Gujarat, India. The results show that the load forecasting of the ANN model follows the actual load pattern more accurately throughout the forecasted period.
Abstract: This paper is concerned with motion recognition based fuzzy WP(Wavelet Packet) feature extraction approach from Vicon physical data sets. For this purpose, we use an efficient fuzzy mutual-information-based WP transform for feature extraction. This method estimates the required mutual information using a novel approach based on fuzzy membership function. The physical action data set includes 10 normal and 10 aggressive physical actions that measure the human activity. The data have been collected from 10 subjects using the Vicon 3D tracker. The experiments consist of running, seating, and walking as physical activity motion among various activities. The experimental results revealed that the presented feature extraction approach showed good recognition performance.
Abstract: The process of constructing a scale measuring the attitudes of youth toward violence on televisions is reported. A 30-item draft attitude scale was applied to a working group of 232 students attending the Faculty of Educational Sciences at Ankara University between the years 2005-2006. To introduce the construct validity and dimensionality of the scale, exploratory and confirmatory factor analysis was applied to the data. Results of the exploratory factor analysis showed that the scale had three factors that accounted for 58,44% (22,46% for the first, 22,15% for the second and 13,83% for the third factor) of the common variance. It is determined that the first factor considered issues related individual effects of violence on televisions, the second factor concerned issues related social effects of violence on televisions and the third factor concerned issues related violence on television programs. Results of the confirmatory factor analysis showed that all the items under each factor are fitting the concerning factors structure. An alpha reliability of 0,90 was estimated for the whole scale. It is concluded that the scale is valid and reliable.
Abstract: The control of commutation of switched reluctance
(SR) motor has nominally depended on a physical position detector.
The physical rotor position sensor limits robustness and increases
size and inertia of the SR drive system. The paper describes a method
to overcome these limitations by using magnetization characteristics
of the motor to indicate rotor and stator teeth overlap status. The
method is using active current probing pulses of same magnitude that
is used to simulate flux linkage in the winding being probed. A
microprocessor is used for processing magnetization data to deduce
rotor-stator teeth overlap status and hence rotor position. However,
the back-of-core saturation and mutual coupling introduces overlap
detection errors, hence that of commutation control. This paper
presents the concept of the detection scheme and the effects of backof
core saturation.
Abstract: Within the framework of a method of the information
theory it is offered statistics and probabilistic model for definition of
cause-and-effect relations in the coupled multicomponent
subsystems. The quantitative parameter which is defined through
conditional and unconditional entropy functions is introduced. The
method is applied to the analysis of the experimental data on
dynamics of change of the chemical elements composition of plants
organs (roots, reproductive organs, leafs and stems). Experiment is
directed on studying of temporal processes of primary soil formation
and their connection with redistribution dynamics of chemical
elements in plant organs. This statistics and probabilistic model
allows also quantitatively and unambiguously to specify the
directions of the information streams on plant organs.