Abstract: Surface roughness (Ra) is one of the most important requirements in machining process. In order to obtain better surface roughness, the proper setting of cutting parameters is crucial before the process take place. This research presents the development of mathematical model for surface roughness prediction before milling process in order to evaluate the fitness of machining parameters; spindle speed, feed rate and depth of cut. 84 samples were run in this study by using FANUC CNC Milling α-Τ14ιE. Those samples were randomly divided into two data sets- the training sets (m=60) and testing sets(m=24). ANOVA analysis showed that at least one of the population regression coefficients was not zero. Multiple Regression Method was used to determine the correlation between a criterion variable and a combination of predictor variables. It was established that the surface roughness is most influenced by the feed rate. By using Multiple Regression Method equation, the average percentage deviation of the testing set was 9.8% and 9.7% for training data set. This showed that the statistical model could predict the surface roughness with about 90.2% accuracy of the testing data set and 90.3% accuracy of the training data set.
Abstract: On a such wide-area environment as a Grid, data
placement is an important aspect of distributed database systems. In
this paper, we address the problem of initial placement of database
no-replicated fragments in Grid architecture. We propose a graph
based approach that considers resource restrictions. The goal is to
optimize the use of computing, storage and communication
resources. The proposed approach is developed in two phases: in the
first phase, we perform fragment grouping using knowledge about
fragments dependency and, in the second phase, we determine an
efficient placement of the fragment groups on the Grid. We also
show, via experimental analysis that our approach gives solutions
that are close to being optimal for different databases and Grid
configurations.
Abstract: As the air traffic increases at a hub airport, some
flights cannot land or depart at their preferred target time. This event
happens because the airport runways become occupied to near their
capacity. It results in extra costs for both passengers and airlines
because of the loss of connecting flights or more waiting, more fuel
consumption, rescheduling crew members, etc. Hence, devising an
appropriate scheduling method that determines a suitable runway and
time for each flight in order to efficiently use the hub capacity and
minimize the related costs is of great importance. In this paper, we
present a mixed-integer zero-one model for scheduling a set of mixed
landing and departing flights (despite of most previous studies
considered only landings). According to the fact that the flight cost is
strongly affected by the level of airline, we consider different airline
categories in our model. This model presents a single objective
minimizing the total sum of three terms, namely 1) the weighted
deviation from targets, 2) the scheduled time of the last flight (i.e.,
makespan), and 3) the unbalancing the workload on runways. We
solve 10 simulated instances of different sizes up to 30 flights and 4
runways. Optimal solutions are obtained in a reasonable time, which
are satisfactory in comparison with the traditional rule, namely First-
Come-First-Serve (FCFS) that is far apart from optimality in most
cases.
Abstract: Because of the low maintenance and robustness induction motors have many applications in the industries. The speed control of induction motor is more important to achieve maximum torque and efficiency. Various speed control techniques like, Direct Torque Control, Sensorless Vector Control and Field Oriented Control are discussed in this paper. Soft computing technique – Fuzzy logic is applied in this paper for the speed control of induction motor to achieve maximum torque with minimum loss. The fuzzy logic controller is implemented using the Field Oriented Control technique as it provides better control of motor torque with high dynamic performance. The motor model is designed and membership functions are chosen according to the parameters of the motor model. The simulated design is tested using various tool boxes in MATLAB. The result concludes that the efficiency and reliability of the proposed speed controller is good.
Abstract: Within the new world order, the term “crisis" is nowadays familiar to companies. Organizations are experiencing conditions which are surprising, uncertain, often adverse and usually unstable. The companies, who grasp the importance of transformation within the information age, have felt the need to develop modern methods to achieve the ability to thrive despite severe shocks. Through strategically managing human resource and developing appropriate elements of human resource system, companies can be assured for resolving the crisis. In this paper the role of HR system on resolving crisis has been evaluated. To help accomplish this, an insight on previous strategic HRM literature and an introduction to the elements and relationship within HR systems has been presented. It also reviews different attitude around resilience in literature. It continues by reviewing three elements central to developing an organization-s capacity for crisis resolving and it will demonstrate how designing proper elements of HR system can lead the organizations to possess the ability for passing through crisis. Finally it will evaluate an Iranian Insurance organization in case of one of the three central elements (specific cognitive ability) and observe how successful they were on developing an effective HR system to be ready for facing crisis.
Abstract: Bleeding in the digestive duct is an important diagnostic parameter for patients. Blood in the endoscopic image can be determined by investigating the color tone of blood due to the degree of oxygenation, under- or over- illumination, food debris and secretions, etc. However, we found that how to pre-process raw images obtained from the capsule detectors was very important. We applied various image process methods suitable for the capsule endoscopic image in order to remove noises and unbalanced sensitivities for the image pixels. The results showed that much improvement was achieved by additional pre-processing techniques on the algorithm of determining bleeding areas.
Abstract: Time series forecasting is an important and widely
popular topic in the research of system modeling. This paper
describes how to use the hybrid PSO-RLSE neuro-fuzzy learning
approach to the problem of time series forecasting. The PSO
algorithm is used to update the premise parameters of the
proposed prediction system, and the RLSE is used to update the
consequence parameters. Thanks to the hybrid learning (HL)
approach for the neuro-fuzzy system, the prediction performance
is excellent and the speed of learning convergence is much faster
than other compared approaches. In the experiments, we use the
well-known Mackey-Glass chaos time series. According to the
experimental results, the prediction performance and accuracy in
time series forecasting by the proposed approach is much better
than other compared approaches, as shown in Table IV. Excellent
prediction performance by the proposed approach has been
observed.
Abstract: One of the important tropical diseases is
Chikunkunya. This disease is transmitted between the human by the
insect-borne virus, of the genus Alphavirus. It occurs in Africa, Asia
and the Indian subcontinent. In Thailand, the incidences due to this
disease are increasing every year. In this study, the transmission of
this disease is studied through dynamical model analysis.
Abstract: With the development of technology, the growing
trend of fast and safe passenger transport, air pollution, traffic
congestion, increase in problems such as the increasing population
and the high cost of private vehicle usage made many cities around
the world with a population of more or less, start to build rail systems
as a means of urban transport in order to ensure the economic and
environmental sustainability and more efficient use of land in the
city. The implementation phase of rail systems costs much more than
other public transport systems. However, social and economic returns
in the long term made these systems the most popular investment tool
for planned and developing cities.
In our country, the purpose, goals and policies of transportation
plans are away from integrity, and the problems are not clearly
detected. Also, not defined and incomplete assessment of
transportation systems and insufficient financial analysis are the most
important cause of failure. Rail systems and other transportation
systems to be addressed as a whole is seen as the main factor in
increasing efficiency in applications that are not integrated yet in our
country to come to this point has led to the problem.
Abstract: Scheduling algorithms are used in operating systems
to optimize the usage of processors. One of the most efficient
algorithms for scheduling is Multi-Layer Feedback Queue (MLFQ)
algorithm which uses several queues with different quanta. The most
important weakness of this method is the inability to define the
optimized the number of the queues and quantum of each queue. This
weakness has been improved in IMLFQ scheduling algorithm.
Number of the queues and quantum of each queue affect the response
time directly. In this paper, we review the IMLFQ algorithm for
solving these problems and minimizing the response time. In this
algorithm Recurrent Neural Network has been utilized to find both
the number of queues and the optimized quantum of each queue.
Also in order to prevent any probable faults in processes' response
time computation, a new fault tolerant approach has been presented.
In this approach we use combinational software redundancy to
prevent the any probable faults. The experimental results show that
using the IMLFQ algorithm results in better response time in
comparison with other scheduling algorithms also by using fault
tolerant mechanism we improve IMLFQ performance.
Abstract: The recent advances in computational fluid dynamics
(CFD) can be useful in observing the detailed hemodynamics in
cerebral aneurysms for understanding not only their formation and
rupture but also for clinical evaluation and treatment. However,
important hemodynamic quantities are difficult to measure in vivo. In
the present study, an approximate model of normal middle cerebral
artery (MCA) along with two cases consisting broad and narrow
saccular aneurysms are analyzed. The models are generated in
ANSYS WORKBENCH and transient analysis is performed in
ANSYS-CFX. The results obtained are compared for three cases and
agree well with the available literature.
Abstract: Controlled modification of appropriate sharpness for
nanotips is of paramount importance to develop novel materials and
functional devices at a nanometer resolution. Herein, we present a
reliable and unique strategy of laser irradiation enhanced
physicochemical etching to manufacture super sharp tungsten tips
with reproducible shape and dimension as well as high yields
(~80%). The corresponding morphology structure evolution of
tungsten tips and laser-tip interaction mechanisms were
systematically investigated and discussed using field emission
scanning electron microscope (SEM) and physical optics statistics
method with different fluences under 532 nm laser irradiation. This
work paves the way for exploring more accessible metallic tips
applications with tunable apex diameter and aspect ratio, and,
furthermore, facilitates the potential sharpening enhancement
technique for other materials used in a variety of nanoscale devices.
Abstract: The aim of study was to evaluate pressure distribution characteristics of the elastic textile bandages using two instrumental techniques: a prototype Instrument and a load Transference. The prototype instrument which simulates shape of real leg has pressure sensors which measure bandage pressure. Using this instrument, the results show that elastic textile bandages presents different pressure distribution characteristics and none produces a uniform distribution around lower limb.
The load transference test procedure is used to determine whether a relationship exists between elastic textile bandage structure and pressure distribution characteristics. The test procedure assesses degree of load, directly transferred through a textile when loads series are applied to bandaging surface. A range of weave fabrics was produced using needle weaving machine and a sewing technique. A textile bandage was developed with optimal characteristics far superior pressure distribution than other bandages. From results, we find that theoretical pressure is not consistent exactly with practical pressure. It is important in this study to make a practical application for specialized nurses in order to verify the results and draw useful conclusions for predicting the use of this type of elastic band.
Abstract: This research paper presents a framework on how to
build up malware dataset.Many researchers took longer time to
clean the dataset from any noise or to transform the dataset into a
format that can be used straight away for testing. Therefore, this
research is proposing a framework to help researchers to speed up
the malware dataset cleaningprocesses which later can be used for
testing. It is believed, an efficient malware dataset cleaning
processes, can improved the quality of the data, thus help to improve
the accuracy and the efficiency of the subsequent analysis. Apart
from that, an in-depth understanding of the malware taxonomy is
also important prior and during the dataset cleaning processes. A
new Trojan classification has been proposed to complement this
framework.This experiment has been conducted in a controlled lab
environment and using the dataset from VxHeavens dataset. This
framework is built based on the integration of static and dynamic
analyses, incident response method and knowledge database
discovery (KDD) processes.This framework can be used as the basis
guideline for malware researchers in building malware dataset.
Abstract: Since the 1990s the American furniture industry faces
a transition period. Manufacturers, one of its most important actors
made its entrance into the retail industry. This shift has had deep
consequences not only for the American furniture industry as a
whole, but also for other international furniture industries, especially
the Chinese. The present work aims to analyze this actor based on the
distinction provided by the Global Commodity Chain Theory. It
stresses its characteristics, structure, operational way and importance
for both the U.S. and the Chinese furniture industries.
Abstract: There are many issues that affect modeling and designing real-time databases. One of those issues is maintaining consistency between the actual state of the real-time object of the external environment and its images as reflected by all its replicas distributed over multiple nodes. The need to improve the scalability is another important issue. In this paper, we present a general framework to design a replicated real-time database for small to medium scale systems and maintain all timing constrains. In order to extend the idea for modeling a large scale database, we present a general outline that consider improving the scalability by using an existing static segmentation algorithm applied on the whole database, with the intent to lower the degree of replication, enables segments to have individual degrees of replication with the purpose of avoiding excessive resource usage, which all together contribute in solving the scalability problem for DRTDBS.
Abstract: Emerging adulthood, between the ages of 18 and 25, as a new developmental stage extending from adolescence to young adulthood. According to Arnett [2004], there are experiments related to identity in three basic fields which are love, work and view of the world in emerging adulthood. When the literature related to identity is examined, it is seen that identity has been studied more with adolescent, and studies were concentrated on the relationship of identity with many demographic variables neglecting important variables such as marital status, parental status and SES. Thus, the main aim of this study is to determine whether identity statuses differenciate with marital status, parental status and SES. A total of 700 emerging adults participated in this study, and the mean age was 22,45 years [SD = 3.76]. The sample was made up of 347 female and 353 male. All participants in the study were students from colleges. Student responses to the Extended Version of the Objective Measure of Ego Identity Status [EOM-EIS-2] used to classify students into one of the four identity statuses. SPSS 15.00 program wasa used to analyse data. Percentage, frequency and X2 analysis were used in the analysis of data. When the findings of the study is viewed as a whole, the most frequently observed identity status in the group is found to be moratorium. Also, identity statuses differenciate with marital status, parental status and SES. Findings were discussed in the context of emerging adulthood.
Abstract: In many sensor network applications, sensor nodes are deployed in open environments, and hence are vulnerable to physical attacks, potentially compromising the node's cryptographic keys. False sensing report can be injected through compromised nodes, which can lead to not only false alarms but also the depletion of limited energy resource in battery powered networks. Ye et al. proposed a statistical en-route filtering scheme (SEF) to detect such false reports during the forwarding process. In this scheme, the choice of a security threshold value is important since it trades off detection power and overhead. In this paper, we propose a fuzzy logic for determining a security threshold value in the SEF based sensor networks. The fuzzy logic determines a security threshold by considering the number of partitions in a global key pool, the number of compromised partitions, and the energy level of nodes. The fuzzy based threshold value can conserve energy, while it provides sufficient detection power.
Abstract: The recent development of Information and Communication Technology (ICT) enables new ways of "democratic" decision-making such as a page-ranking system, which estimates the importance of a web page based on indirect trust on that page shared by diverse group of unorganized individuals. These kinds of "democracy" have not been acclaimed yet in the world of real politics. On the other hand, a large amount of data about personal relations including trust, norms of reciprocity, and networks of civic engagement has been accumulated in a computer-readable form by computer systems (e.g., social networking systems). We can use these relations as a new type of social capital to construct a new democratic decision-making system based on a delegation network. In this paper, we propose an effective decision-making support system, which is based on empowering someone's vote whom you trust. For this purpose, we propose two new techniques: the first is for estimating entire vote distribution from a small number of votes, and the second is for estimating active voter choice to promote voting using a delegation network. We show that these techniques could increase the voting ratio and credibility of the whole decision by agent-based simulations.
Abstract: Increasing concerns over climate change have limited
the liberal usage of available energy technology options. India faces
a formidable challenge to meet its energy needs and provide adequate
energy of desired quality in various forms to users in sustainable
manner at reasonable costs. In this paper, work carried out with an
objective to study the role of various energy technology options
under different scenarios namely base line scenario, high nuclear
scenario, high renewable scenario, low growth and high growth rate
scenario. The study has been carried out using Model for Energy
Supply Strategy Alternatives and their General Environmental
Impacts (MESSAGE) model which evaluates the alternative energy
supply strategies with user defined constraints on fuel availability,
environmental regulations etc. The projected electricity demand, at
the end of study period i.e. 2035 is 500490 MWYr. The model
predicted the share of the demand by Thermal: 428170 MWYr,
Hydro: 40320 MWYr, Nuclear: 14000 MWYr, Wind: 18000 MWYr
in the base line scenario. Coal remains the dominant fuel for
production of electricity during the study period. However, the
import dependency of coal increased during the study period. In
baseline scenario the cumulative carbon dioxide emissions upto 2035
are about 11,000 million tones of CO2. In the scenario of high nuclear
capacity the carbon dioxide emissions reduced by 10 % when nuclear
energy share increased to 9 % compared to 3 % in baseline scenario.
Similarly aggressive use of renewables reduces 4 % of carbon
dioxide emissions.