Abstract: Hydrogels are three-dimensional, hydrophilic,
polymeric networks composed of homopolymers or copolymers and
are insoluble in water due to the presence of chemical or physical
cross-links. When hydrogels come in contact with aqueous solutions,
they can effectively sorb and retain the dissolved substances,
depending on the nature of the monomeric units comprising the
hydrogel. For this reason, hydrogels have been proposed in several
studies as water purification agents. At the present work anionic
hydrogels bearing negatively charged –COO- groups were prepared
and investigated. These gels are based on sodium acrylate (ANa),
either homopolymerized (poly(sodiumacrylate), PANa) or
copolymerized (P(DMAM-co-ANa)) with N,N Dimethylacrylamide
(DMAM). The hydrogels were used to extract some model organic
dyes from water. It is found that cationic dyes are strongly sorbed and
retained by the hydrogels, while sorption of anionic dyes was
negligible. In all cases it was found that both maximum sorption
capacity and equilibrium binding constant varied from one dye to the
other depending on the chemical structure of the dye, the presence of
functional chemical groups and the hydrophobic-hydrophilic balance.
Finally, the nonionic hydrogel of the homopolymer poly(N,Ndimethylacrylamide),
PDMAM, was also used for reasons of
comparison.
Abstract: Spectrum handover is a significant topic in the
cognitive radio networks to assure an efficient data transmission in
the cognitive radio user’s communications. This paper proposes a
comparison between three spectrum handover models: VIKOR, SAW
and MEW. Four evaluation metrics are used. These metrics are,
accumulative average of failed handover, accumulative average of
handover performed, accumulative average of transmission
bandwidth and, accumulative average of the transmission delay. As a difference with related work, the performance of the three
spectrum handover models was validated with captured data of
spectrum occupancy in experiments performed at the GSM frequency
band (824 MHz - 849 MHz). These data represent the actual behavior
of the licensed users for this wireless frequency band. The results of the comparison show that VIKOR Algorithm
provides a 15.8% performance improvement compared to SAW
Algorithm and, it is 12.1% better than the MEW Algorithm.
Abstract: This paper develops a multiple channel assignment
model, which allows to take advantage of spectrum opportunities in
cognitive radio networks in the most efficient way. The developed
scheme allows making several assignments of available and
frequency adjacent channel, which require a bigger bandwidth, under
an equality environment. The hybrid assignment model it is made by
two algorithms, one that makes the ranking and selects available
frequency channels and the other one in charge of establishing the
Max-Min Fairness for not restrict the spectrum opportunities for all
the other secondary users, who also claim to make transmissions.
Measurements made were done for average bandwidth, average
delay, as well as fairness computation for several channel
assignments. Reached results were evaluated with experimental
spectrum occupational data from captured GSM frequency band. The
developed model shows evidence of improvement in spectrum
opportunity use and a wider average transmission bandwidth for each
secondary user, maintaining equality criteria in channel assignment.
Abstract: In the context of the handwriting recognition, we
propose an off line system for the recognition of the Arabic
handwritten words of the Algerian departments. The study is based
mainly on the evaluation of neural network performances, trained
with the gradient back propagation algorithm. The used parameters to
form the input vector of the neural network are extracted on the
binary images of the handwritten word by several methods. The
Distribution parameters, the centered moments of the different
projections of the different segments, the centered moments of the
word image coding according to the directions of Freeman, and the
Barr features applied binary image of the word and on its different
segments. The classification is achieved by a multi layers perceptron.
A detailed experiment is carried and satisfactory recognition results
are reported.
Abstract: In this paper, we present an optimization technique or
a learning algorithm using the hybrid architecture by combining the
most popular sequence recognition models such as Recurrent Neural
Networks (RNNs) and Hidden Markov models (HMMs). In order to
improve the sequence/pattern recognition/classification performance
by applying a hybrid/neural symbolic approach, a gradient descent
learning algorithm is developed using the Real Time Recurrent
Learning of Recurrent Neural Network for processing the knowledge
represented in trained Hidden Markov Models. The developed hybrid
algorithm is implemented on automata theory as a sample test beds
and the performance of the designed algorithm is demonstrated and
evaluated on learning the deterministic finite state automata.
Abstract: Since the last decade, there has been a rapid growth in
digital multimedia, such as high-resolution media files and threedimentional
movies. Hence, there is a need for large digital storage
such as Hard Disk Drive (HDD). As such, users expect to have a
quieter HDD in their laptop. In this paper, a jury test has been
conducted on a group of 34 people where 17 of them are students
who are the potential consumer, and the remaining are engineers who
know the HDD. A total 13 HDD sound samples have been selected
from over hundred HDD noise recordings. These samples are
selected based on an agreed subjective feeling. The samples are
played to the participants using head acoustic playback system, which
enabled them to experience as similar as possible the same
environment as have been recorded. Analysis has been conducted and
the obtained results have indicated different group has different
perception over the noises. Two neural network-based acoustic
annoyance models are established based on back propagation neural
network. Four psychoacoustic metrics, loudness, sharpness,
roughness and fluctuation strength, are used as the input of the
model, and the subjective evaluation results are taken as the output.
The developed models are reasonably accurate in simulating both
training and test samples.
Abstract: The Radio Frequency Identification (RFID) technology
has a diverse base of applications, but it is also prone to security
threats. There are different types of security attacks which limit the
range of the RFID applications. For example, deploying the RFID
networks in insecure environments could make the RFID system
vulnerable to many types of attacks such as spoofing attack, location
traceability attack, physical attack and many more. Therefore, security
is often an important requirement for RFID systems. In this paper,
RFID mutual authentication protocol is implemented based on mobile
agent technology and timestamp, which are used to provide strong
authentication and integrity assurances to both the RFID readers and
their corresponding RFID tags. The integration of mobile agent
technology and timestamp provides promising results towards
achieving this goal and towards reducing the security threats in RFID
systems.
Abstract: In this paper, we present a comparative study of three
methods of 2D face recognition system such as: Iso-Geodesic Curves
(IGC), Geodesic Distance (GD) and Geodesic-Intensity Histogram
(GIH). These approaches are based on computing of geodesic
distance between points of facial surface and between facial curves.
In this study we represented the image at gray level as a 2D surface in
a 3D space, with the third coordinate proportional to the intensity
values of pixels. In the classifying step, we use: Neural Networks
(NN), K-Nearest Neighbor (KNN) and Support Vector Machines
(SVM). The images used in our experiments are from two wellknown
databases of face images ORL and YaleB. ORL data base was
used to evaluate the performance of methods under conditions where
the pose and sample size are varied, and the database YaleB was used
to examine the performance of the systems when the facial
expressions and lighting are varied.
Abstract: Health of a person plays a vital role in the collective
health of his community and hence the well-being of the society as a
whole. But, in today’s fast paced technology driven world, health
issues are increasingly being associated with human behaviors – their
lifestyle. Social networks have tremendous impact on the health
behavior of individuals. Many researchers have used social network
analysis to understand human behavior that implicates their social
and economic environments. It would be interesting to use a similar
analysis to understand human behaviors that have health
implications. This paper focuses on concepts of those behavioural
analyses that have health implications using social networks analysis
and provides possible algorithmic approaches. The results of these
approaches can be used by the governing authorities for rolling out
health plans, benefits and take preventive measures, while the
pharmaceutical companies can target specific markets, helping health
insurance companies to better model their insurance plans.
Abstract: The main issue in designing a wireless sensor network
(WSN) is the finding of a proper routing protocol that complies with
the several requirements of high reliability, short latency, scalability,
low power consumption, and many others. This paper proposes a
novel routing algorithm that complies with these design
requirements. The new routing protocol divides the WSN into several subnetworks
and each sub-network is divided into several clusters. This
division is designed to reduce the number of radio transmission and
hence decreases the power consumption. The network division may
be changed dynamically to adapt with the network changes and
allows the realization of the design requirements.
Abstract: Food supply chain is one of the most complex supply
chain networks due to its perishable nature and customer oriented
products, and food safety is the major concern for this industry. IT
system could help to minimize the production and consumption of
unsafe food by controlling and monitoring the entire system.
However, there have been many issues in adoption of IT system in
this industry specifically within SMEs sector. With this regard, this
study presents a novel approach to use IT and tractability systems in
the food supply chain, using application of RFID and central
database.
Abstract: This paper addresses the issue of resource allocation
in the emerging cognitive technology. Focusing the Quality of
Service (QoS) of Primary Users (PU), a novel method is proposed for
the resource allocation of Secondary Users (SU). In this paper, we
propose the unique Utility Function in the game theoretic model of
Cognitive Radio which can be maximized to increase the capacity of
the Cognitive Radio Network (CRN) and to minimize the
interference scenario. Utility function is formulated to cater the need
of PUs by observing Signal to Noise ratio. Existence of Nash
Equilibrium for the postulated game is established.
Abstract: Predicting earnings management is vital for the capital
market participants, financial analysts and managers. The aim of this
research is attempting to respond to this query: Is there a significant
difference between the regression model and neural networks’
models in predicting earnings management, and which one leads to a
superior prediction of it? In approaching this question, a Linear
Regression (LR) model was compared with two neural networks
including Multi-Layer Perceptron (MLP), and Generalized
Regression Neural Network (GRNN). The population of this study
includes 94 listed companies in Tehran Stock Exchange (TSE)
market from 2003 to 2011. After the results of all models were
acquired, ANOVA was exerted to test the hypotheses. In general, the
summary of statistical results showed that the precision of GRNN did
not exhibit a significant difference in comparison with MLP. In
addition, the mean square error of the MLP and GRNN showed a
significant difference with the multi variable LR model. These
findings support the notion of nonlinear behavior of the earnings
management. Therefore, it is more appropriate for capital market
participants to analyze earnings management based upon neural
networks techniques, and not to adopt linear regression models.
Abstract: In recent years, new techniques for solving complex
problems in engineering are proposed. One of these techniques is
JPSO algorithm. With innovative changes in the nature of the jump
algorithm JPSO, it is possible to construct a graph-based solution
with a new algorithm called G-JPSO. In this paper, a new algorithm
to solve the optimal control problem Fletcher-Powell and optimal
control of pumps in water distribution network was evaluated.
Optimal control of pumps comprise of optimum timetable operation
(status on and off) for each of the pumps at the desired time interval.
Maximum number of status on and off for each pumps imposed to the
objective function as another constraint. To determine the optimal
operation of pumps, a model-based optimization-simulation
algorithm was developed based on G-JPSO and JPSO algorithms.
The proposed algorithm results were compared well with the ant
colony algorithm, genetic and JPSO results. This shows the
robustness of proposed algorithm in finding near optimum solutions
with reasonable computational cost.
Abstract: This paper proposes a novel heuristic algorithm that aims to determine the best size and location of distributed generators in unbalanced distribution networks. The proposed heuristic algorithm can deal with the planning cases where power loss is to be optimized without violating the system practical constraints. The distributed generation units in the proposed algorithm is modeled as voltage controlled node with the flexibility to be converted to constant power factor node in case of reactive power limit violation. The proposed algorithm is implemented in MATLAB and tested on the IEEE 37 -node feeder. The results obtained show the effectiveness of the proposed algorithm.
Abstract: Analyzing the relation networks between the hospital
buildings which have complex structure and distinctive spatial
relationships is quite difficult. The hospital buildings which require
specialty in spatial relationship solutions during design and selfinnovation
through the developing technology should survive and
keep giving service even after the disasters such as earthquakes. In
this study, a hospital building where the load-bearing system was
strengthened because of the insufficient earthquake performance and
the construction of an additional building was required to meet the
increasing need for space was discussed and a comparative spatial
evaluation of the hospital building was made with regard to its status
before the change and after the change. For this reason, spatial
organizations of the building before change and after the change were
analyzed by means of Space Syntax method and the effects of the
change on space organization parameters were searched by applying
an analytical procedure. Using Depthmap UCL software,
Connectivity, Visual Mean Depth, Beta and Visual Integration
analyses were conducted. Based on the data obtained after the
analyses, it was seen that the relationships between spaces of the
building increased after the change and the building has become more
explicit and understandable for the occupants. Furthermore, it was
determined according to findings of the analysis that the increase in
depth causes difficulty in perceiving the spaces and the changes
considering this problem generally ease spatial use.
Abstract: Evolution strategy (ES) is a well-known instance of evolutionary algorithms, and there have been many studies on ES. In this paper, the author proposes an extended ES for solving fuzzy-valued optimization problems. In the proposed ES, genotype values are not real numbers but fuzzy numbers. Evolutionary processes in the ES are extended so that it can handle genotype instances with fuzzy numbers. In this study, the proposed method is experimentally applied to the evolution of neural networks with fuzzy weights and biases. Results reveal that fuzzy neural networks evolved using the proposed ES with fuzzy genotype values can model hidden target fuzzy functions even though no training data are explicitly provided. Next, the proposed method is evaluated in terms of variations in specifying fuzzy numbers as genotype values. One of the mostly adopted fuzzy numbers is a symmetric triangular one that can be specified by its lower and upper bounds (LU) or its center and width (CW). Experimental results revealed that the LU model contributed better to the fuzzy ES than the CW model, which indicates that the LU model should be adopted in future applications of the proposed method.
Abstract: The Portuguese footwear industry had in the last five years a remarkable performance in the exportation values, the trade balance and others economic indicators. After a long period of difficulties and with a strong reduction of companies and employees since 1994 until 2009, the Portuguese footwear industry changed the strategy and is now a success case between the international players of footwear. Only the Italian industry sells footwear with a higher value than the Portuguese and the distance between them is decreasing year by year. This paper analyses how the Portuguese footwear companies innovate and make innovation, according the classification proposed by the Oslo Manual. Also, analyses the strategy follow in the innovation process and shows the linkage between the type of innovation and the strategy of innovation. The research methodology was qualitative and the strategy for data collection was the case study. The qualitative data will be analyzed with the MAXQDA software. The economic results of the footwear companies studied shows differences between all of them and these differences are related with the innovation strategy adopted. The companies focused in product and marketing innovation, oriented to their target market, have higher ratios “turnover per worker” than the companies focused in process innovation. However, all the footwear companies in this “low-tech” industry create value and contribute to a positive foreign trade of 1.310 million euros in 2013. The growth strategies implemented has the participation of the sectorial organizations in several innovative projects. And it’s obvious that cooperation between all of them is a critical element to the performance achieved by the companies and the innovation observed. The Portuguese footwear sector has in the last years an excellent performance (economic results, exportation values, trade balance, brands and international image) and his performance is strongly related with the strategy in innovation followed, the type of innovation and the networks in the cluster. A simplified model, called “Ace of Diamonds”, is proposed by the authors and explains the way how this performance was reached by the seven companies that participate in the study (two of them are the leaders in the setor), and if this model can be used in others traditional and “low-tech” industries.
Abstract: The Gezi Park protests of 2013 have significantly changed the Turkish agenda and its effects have been felt historically. The protests, which rapidly spread throughout the country, were triggered by the proposal to recreate the Ottoman Army Barracks to function as a shopping mall on Gezi Park located in Istanbul’s Taksim neighbourhood despite the oppositions of several NGOs and when trees were cut in the park for this purpose. Once the news that the construction vehicles entered the park on May 27 spread on social media, activists moved into the park to stop the demolition, against whom the police used disproportioned force. With this police intervention and the then prime-minister Tayyip Erdoğan's insistent statements about the construction plans, the protests turned into anti- government demonstrations, which then spread to the rest of the country, mainly in big cities like Ankara and Izmir. According to the Ministry of Internal Affairs’ June 23rd reports, 2.5 million people joined the demonstrations in 79 provinces, that is all of them, except for the provinces of Bayburt and Bingöl, while even more people shared their opinions via social networks. As a result of these events, 8 civilians and 2 security personnel lost their lives, namely police chief Mustafa Sarı, police officer Ahmet Küçükdağ, citizens Mehmet Ayvalıtaş, Abdullah Cömert, Ethem Sarısülük, Ali İsmail Korkmaz, Ahmet Atakan, Berkin Elvan, Burak Can Karamanoğlu, Mehmet İstif, and Elif Çermik, and 8163 more were injured. Besides being a turning point in Turkish history, the Gezi Park protests also had broad repercussions in both in Turkish and in global media, which focused on Turkey throughout the events. Our study conducts content analysis of three Turkish reporting newspapers with varying ideological standpoints, Hürriyet, Cumhuriyet ve Yeni Şafak, in order to reveal their basic approach to news casting in context of the Gezi Park protests. Headlines, news segments, and news content relating to the Gezi protests were treated and analysed for this purpose. The aim of this study is to understand the social effects of the Gezi Park protests through media samples with varying political attitudes towards news casting.
Abstract: A Mobile Adhoc Network (MANET) is a collection of mobile nodes that communicate with each other with wireless links and without pre-existing communication infrastructure. Routing is an important issue which impacts network performance. As MANETs lack central administration and prior organization, their security concerns are different from those of conventional networks. Wireless links make MANETs susceptible to attacks. This study proposes a new trust mechanism to mitigate wormhole attack in MANETs. Different optimization techniques find available optimal path from source to destination. This study extends trust and reputation to an improved link quality and channel utilization based Adhoc Ondemand Multipath Distance Vector (AOMDV). Differential Evolution (DE) is used for optimization.