Abstract: The advancement in wireless technology with the wide
use of mobile devices have drawn the attention of the research and
technological communities towards wireless environments, such as
Wireless Local Area Networks (WLANs), Wireless Wide Area
Networks (WWANs), and mobile systems and ad-hoc networks.
Unfortunately, wired and wireless networks are expressively different
in terms of link reliability, bandwidth, and time of propagation delay
and by adapting new solutions for these enhanced
telecommunications, superior quality, efficiency, and opportunities
will be provided where wireless communications were otherwise
unfeasible. Some researchers define 4G as a significant improvement
of 3G, where current cellular network’s issues will be solved and data
transfer will play a more significant role. For others, 4G unifies
cellular and wireless local area networks, and introduces new routing
techniques, efficient solutions for sharing dedicated frequency bands,
and an increased mobility and bandwidth capacity. This paper
discusses the possible solutions and enhancements probabilities that
proposed to improve the performance of Transmission Control
Protocol (TCP) over different wireless networks and also the paper
investigated each approach in term of advantages and disadvantages.
Abstract: Given a simple connected unweighted undirected graph G = (V (G), E(G)) with |V (G)| = n and |E(G)| = m, we present a new algorithm for the all-pairs shortest-path (APSP) problem. The running time of our algorithm is in O(n2 log n). This bound is an improvement over previous best known O(n2.376) time bound of Raimund Seidel (1995) for general graphs. The algorithm presented does not rely on fast matrix multiplication. Our algorithm with slight modifications, enables us to compute the APSP problem for unweighted directed graph in time O(n2 log n), improving a previous best known O(n2.575) time bound of Uri Zwick (2002).
Abstract: Turbine blade cooling is considered as the most
effective way of maintaining high operating temperature making use
of the available materials, and turbine systems with wet compression
have a potential for future power generation because of high efficiency
and high specific power with a relatively low cost. In this paper
performance analysis of wet-compression gas turbine cycle with
turbine blade cooling is carried out. The wet compression process is
analytically modeled based on non-equilibrium droplet evaporation.
Special attention is paid for the effects of pressure ratio and water
injection ratio on the important system variables such as ratio of
coolant fluid flow, fuel consumption, thermal efficiency and specific
power. Parametric studies show that wet compression leads to
insignificant improvement in thermal efficiency but significant
enhancement of specific power in gas turbine systems with turbine
blade cooling.
Abstract: The purpose of this study is to discuss the effect of the
intervention of exercise behavior change plan for high school students
on study subjects- social and psychological factors and exercise
stages. This research uses the transtheoretical model as the research
framework. One experiment group and one control group were used in
a quasi-experimental design research. The experimental group
accepted health-related physical fitness course and the traditional
course; the control group accepted traditional physical education
course. There is a significant difference before and after the
intervention in the experimental group. Karl-s test shows the
experimental group gained a better improvement than that in the
control group. The Analysis of Covariance had shown the exercise
stages (F=7.62, p
Abstract: In rail vehicles, air springs are very important isolating component, which guarantee good ride comfort for passengers during their trip. In the most new rail–vehicle models, developed by researchers, the thermo–dynamical effects of air springs are ignored and secondary suspension is modeled by simple springs and dampers. As the performance of suspension components have significant effects on rail–vehicle dynamics and ride comfort of passengers, a complete nonlinear thermo–dynamical air spring model, which is a combination of two different models, is introduced. Result from field test shows remarkable agreement between proposed model and experimental data. Effects of air suspension parameters on the system performances are investigated here and then these parameters are tuned to minimize Sperling ride comfort index during the trip. Results showed that by modification of air suspension parameters, passengers comfort is improved and ride comfort index is reduced about 10%.
Abstract: In this paper we propose a Multiple Description Image Coding(MDIC) scheme to generate two compressed and balanced rates descriptions in the wavelet domain (Daubechies biorthogonal (9, 7) wavelet) using pairwise correlating transform optimal and application method for Generalized Multiple Description Coding (GMDC) to image coding in the wavelet domain. The GMDC produces statistically correlated streams such that lost streams can be estimated from the received data. Our performance test shown that the proposed method gives more improvement and good quality of the reconstructed image when the wavelet coefficients are normalized by Gaussian Scale Mixture (GSM) model then the Gaussian one ,.
Abstract: An attempt in this paper proposes a re-modification to
the minimum moment approach of resource leveling which is a modified minimum moment approach to the traditional method by
Harris. The method is based on critical path method. The new approach suggests the difference between the methods in the
selection criteria of activity which needs to be shifted for leveling resource histogram. In traditional method, the improvement factor
found first to select the activity for each possible day of shifting. In
modified method maximum value of the product of Resources Rate
and Free Float was found first and improvement factor is then
calculated for that activity which needs to be shifted. In the proposed
method the activity to be selected first for shifting is based on the largest value of resource rate. The process is repeated for all the
remaining activities for possible shifting to get updated histogram.
The proposed method significantly reduces the number of iterations
and is easier for manual computations.
Abstract: In this paper an analysis of blackouts in electric power
transmission systems is implemented using a model and studied in
simple networks with a regular topology. The proposed model
describes load demand and network improvements evolving on a
slow timescale as well as the fast dynamics of cascading overloads
and outages.
Abstract: Chemical and physical functionalization of multiwalled
carbon nanotubes (MWCNT) has been commonly practiced to
achieve better dispersion of carbon nanotubes (CNTs) in polymer
matrix. This work describes various functionalization methods (acidtreatment,
non-ionic surfactant treatment with TritonX-100),
fabrication of MWCNT/PP nanocomposites via melt blending and
characterization of mechanical properties. Microscopy analysis
(FESEM, TEM, XPS) showed effective purification of MWCNTs
under acid treatment, and better dispersion under both chemical and
physical functionalization techniques combined, in their respective
order. Tensile tests showed increase in tensile strength for the
nanocomposites that contain MWCNTs up to 2 wt%. A decrease in
tensile strength was seen in samples that contain 4 wt% of MWCNTs
for both raw and Triton X-100 functionalized, signifying MWCNT
degradation/rebundling at composition with higher content of
MWCNTs. For the acid-treated MWCNTs, however, the tensile
results showed slight improvement even at 4wt%, indicating effective
dispersion of MWCNTs.
Abstract: Detecting protein-protein interactions is a central problem in computational biology and aberrant such interactions may have implicated in a number of neurological disorders. As a result, the prediction of protein-protein interactions has recently received considerable attention from biologist around the globe. Computational tools that are capable of effectively identifying protein-protein interactions are much needed. In this paper, we propose a method to detect protein-protein interaction based on substring similarity measure. Two protein sequences may interact by the mean of the similarities of the substrings they contain. When applied on the currently available protein-protein interaction data for the yeast Saccharomyces cerevisiae, the proposed method delivered reasonable improvement over the existing ones.
Abstract: In the past decade, artificial neural networks (ANNs)
have been regarded as an instrument for problem-solving and
decision-making; indeed, they have already done with a substantial
efficiency and effectiveness improvement in industries and businesses.
In this paper, the Back-Propagation neural Networks (BPNs) will be
modulated to demonstrate the performance of the collaborative
forecasting (CF) function of a Collaborative Planning, Forecasting and
Replenishment (CPFR®) system. CPFR functions the balance between
the sufficient product supply and the necessary customer demand in a
Supply and Demand Chain (SDC). Several classical standard BPN will
be grouped, collaborated and exploited for the easy implementation of
the proposed modular ANN framework based on the topology of a
SDC. Each individual BPN is applied as a modular tool to perform the
task of forecasting SKUs (Stock-Keeping Units) levels that are
managed and supervised at a POS (point of sale), a wholesaler, and a
manufacturer in an SDC. The proposed modular BPN-based CF
system will be exemplified and experimentally verified using lots of
datasets of the simulated SDC. The experimental results showed that a
complex CF problem can be divided into a group of simpler
sub-problems based on the single independent trading partners
distributed over SDC, and its SKU forecasting accuracy was satisfied
when the system forecasted values compared to the original simulated
SDC data. The primary task of implementing an autonomous CF
involves the study of supervised ANN learning methodology which
aims at making “knowledgeable" decision for the best SKU sales plan
and stocks management.
Abstract: The wireless link can be unreliable in realistic wireless
sensor networks (WSNs). Energy efficient and reliable data
forwarding is important because each node has limited resources.
Therefore, we must suggest an optimal solution that considers using
the information of the node-s characteristics. Previous routing
protocols were unsuited to realistic asymmetric WSNs. In this paper,
we propose a Protocol that considers Both sides of Link-quality and
Energy (PBLE), an optimal routing protocol that balances modified
link-quality, distance and energy. Additionally, we propose a node
scheduling method. PBLE achieves a longer lifetime than previous
routing protocols and is more energy-efficient. PBLE uses energy,
local information and both sides of PRR in a 1-hop distance. We
explain how to send data packets to the destination node using the
node's information. Simulation shows PBLE improves delivery rate
and network lifetime compared to previous schemes. Moreover, we
show the improvement in various WSN environments.
Abstract: Rapid advancement in computing technology brings
computers and humans to be seamlessly integrated in future. The
emergence of smartphone has driven computing era towards
ubiquitous and pervasive computing. Recognizing human activity has
garnered a lot of interest and has raised significant researches-
concerns in identifying contextual information useful to human
activity recognition. Not only unobtrusive to users in daily life,
smartphone has embedded built-in sensors that capable to sense
contextual information of its users supported with wide range
capability of network connections. In this paper, we will discuss the
classification algorithms used in smartphone-based human activity.
Existing technologies pertaining to smartphone-based researches in
human activity recognition will be highlighted and discussed. Our
paper will also present our findings and opinions to formulate
improvement ideas in current researches- trends. Understanding
research trends will enable researchers to have clearer research
direction and common vision on latest smartphone-based human
activity recognition area.
Abstract: A concern that researchers usually face in different
applications of Artificial Neural Network (ANN) is determination of
the size of effective domain in time series. In this paper, trial and
error method was used on groundwater depth time series to determine
the size of effective domain in the series in an observation well in
Union County, New Jersey, U.S. different domains of 20, 40, 60, 80,
100, and 120 preceding day were examined and the 80 days was
considered as effective length of the domain. Data sets in different
domains were fed to a Feed Forward Back Propagation ANN with
one hidden layer and the groundwater depths were forecasted. Root
Mean Square Error (RMSE) and the correlation factor (R2) of
estimated and observed groundwater depths for all domains were
determined. In general, groundwater depth forecast improved, as
evidenced by lower RMSEs and higher R2s, when the domain length
increased from 20 to 120. However, 80 days was selected as the
effective domain because the improvement was less than 1% beyond
that. Forecasted ground water depths utilizing measured daily data
(set #1) and data averaged over the effective domain (set #2) were
compared. It was postulated that more accurate nature of measured
daily data was the reason for a better forecast with lower RMSE
(0.1027 m compared to 0.255 m) in set #1. However, the size of input
data in this set was 80 times the size of input data in set #2; a factor
that may increase the computational effort unpredictably. It was
concluded that 80 daily data may be successfully utilized to lower the
size of input data sets considerably, while maintaining the effective
information in the data set.
Abstract: Ensemble learning algorithms such as AdaBoost and
Bagging have been in active research and shown improvements in
classification results for several benchmarking data sets with mainly
decision trees as their base classifiers. In this paper we experiment to
apply these Meta learning techniques with classifiers such as random
forests, neural networks and support vector machines. The data sets
are from MAGIC, a Cherenkov telescope experiment. The task is to
classify gamma signals from overwhelmingly hadron and muon
signals representing a rare class classification problem. We compare
the individual classifiers with their ensemble counterparts and
discuss the results. WEKA a wonderful tool for machine learning has
been used for making the experiments.
Abstract: As seen in literature, about 70% of the improvement initiatives fail, and a significant number do not even get started. This paper analyses the problem of failing initiatives on Software Process Improvement (SPI), and proposes good practices supported by motivational tools that can help minimizing failures. It elaborates on the hypothesis that human factors are poorly addressed by deployers, especially because implementation guides usually emphasize only technical factors. This research was conducted with SPI deployers and analyses 32 SPI initiatives. The results indicate that although human factors are not commonly highlighted in guidelines, the successful initiatives usually address human factors implicitly. This research shows that practices based on human factors indeed perform a crucial role on successful implantations of SPI, proposes change management as a theoretical framework to introduce those practices in the SPI context and suggests some motivational tools based on SPI deployers experience to support it.
Abstract: Aluminothermic rail welding was from the beginning
a great success because its low price even in 1895 in Germany. This
method is now, widely used all over the world for the railways
construction, maintenance and modernization. Instructions give you
guidelines for preparing papers for conferences or journals.
After 1989, the welding needs of the potentials beneficiaries
(Romanian Railways, Urban Transportation Companies) keep raise
because of the railways maintenance and modernization necessity.
The main materials that determine the Thermit (T) composition
result from manufacturing scraps all over the country. This can help
the environment by consuming these scraps.
The Romanian need for alumino-thermic welding is now by 11300
per year, and in a favourable economical environment, this amount
can reach 30000 units.
This paper tries to show the effect of two types of modifiers
introduced in the T composition on the structure and properties of an
alumino-thermic welding.
Abstract: This research investigates the suitability of fuel oil in
improving gypseous soil. A detailed laboratory tests were carried-out
on two soils (soil I with 51.6% gypsum content, and soil II with
26.55%), where the two soils were obtained from Al-Therthar site
(Al-Anbar Province-Iraq).
This study examines the improvement of soil properties using the
gypsum material which is locally available with low cost to minimize
the effect of moisture on these soils by using the fuel oil. This study
was conducted on two models of the soil gypsum, from the Tharthar
area. The first model was sandy soil with Gypsum content of (51.6%)
and the second is clayey soil and the content of Gypsum is (26.55%).
The program included tests measuring the permeability and
compressibility of the soil and their collapse properties. The shear
strength of the soil and the amounts of weight loss of fuel oil due to
drying had been found. These tests have been conducted on the
treated and untreated soils to observe the effect of soil treatment on
the engineering properties when mixed with varying degrees of fuel
oil with the equivalent of the water content.
The results showed that fuel oil is a good material to modify the
basic properties of the gypseous soil of collapsibility and
permeability, which are the main problems of this soil and retained
the soil by an appropriate amount of the cohesion suitable for
carrying the loads from the structure.
Abstract: This paper presents the result of three senior capstone
projects at the Department of Computer Engineering, Prince of
Songkla University, Thailand. These projects focus on developing an
examination management system for the Faculty of Engineering in
order to manage the examination both the examination room
assignments and the examination proctor assignments in each room.
The current version of the software is a web-based application. The
developed software allows the examination proctors to select their
scheduled time online while each subject is assigned to each available
examination room according to its type and the room capacity. The
developed system is evaluated using real data by prospective users of
the system. Several suggestions for further improvements are given
by the testers. Even though the features of the developed software are
not superior, the developing process can be a case study for a projectbased
teaching style. Furthermore, the process of developing this
software can show several issues in developing an educational
support application.
Abstract: In this paper, we present a novel objective nonreference performance assessment algorithm for image fusion. It takes into account local measurements to estimate how well the important information in the source images is represented by the fused image. The metric is based on the Universal Image Quality Index and uses the similarity between blocks of pixels in the input images and the fused image as the weighting factors for the metrics. Experimental results confirm that the values of the proposed metrics correlate well with the subjective quality of the fused images, giving a significant improvement over standard measures based on mean squared error and mutual information.