Abstract: Recognizing human action from videos is an active
field of research in computer vision and pattern recognition. Human
activity recognition has many potential applications such as video
surveillance, human machine interaction, sport videos retrieval and
robot navigation. Actually, local descriptors and bag of visuals words
models achieve state-of-the-art performance for human action
recognition. The main challenge in features description is how to
represent efficiently the local motion information. Most of the
previous works focus on the extension of 2D local descriptors on 3D
ones to describe local information around every interest point. In this
paper, we propose a new spatio-temporal descriptor based on a spacetime
description of moving points. Our description is focused on an
Accordion representation of video which is well-suited to recognize
human action from 2D local descriptors without the need to 3D
extensions. We use the bag of words approach to represent videos.
We quantify 2D local descriptor describing both temporal and spatial
features with a good compromise between computational complexity
and action recognition rates. We have reached impressive results on
publicly available action data set
Abstract: Recent research has shown that milk proteins can
yield bioactive peptides with opioid, mineral binding,
cytomodulatory, antihypertensive, immunostimulating, antimicrobial
and antioxidative activity in the human body. Bioactive peptides are
encrypted in milk proteins and are only released by enzymatic
hydrolysis in vivo during gastrointestinal digestion, food processing
or by microbial enzymes in fermented products. At present
significant research is being undertaken on the health effects of
bioactive peptides. A variety of naturally formed bioactive peptides
have been found in fermented dairy products, such as yoghurt, sour
milk and cheese. In particular, antihypertensive peptides have been
identified in fermented milks, whey and ripened cheese. Some of
these peptides have been commercialized in the form of fermented
milks. Bioactive peptides have the potential to be used in the
formulation of health-enhancing nutraceuticals, and as potent drugs
with well defined pharmacological effects.
Abstract: For the purpose of finding the quotient structure of multiple algebras such as groups, Abelian groups and rings, we will state concepts of ( strong or weak ) equalities on multiple algebras, which will lead us to research on how ( strong or weak) are equalities defined on a multiple algebra over the quotients obtained from it. In order to find a quotient structure of multiple algebras such as groups, Abelian groups and loops, a part of this article has been allocated to the concepts of equalities (strong and weak) of the defined multiple functions on multiple algebras. This leads us to do research on how defined equalities (strong and weak) are made in the multiple algebra on its resulted quotient.
Abstract: This paper proposes a neural network weights and
topology optimization using genetic evolution and the
backpropagation training algorithm. The proposed crossover and
mutation operators aims to adapt the networks architectures and
weights during the evolution process. Through a specific inheritance
procedure, the weights are transmitted from the parents to their
offsprings, which allows re-exploitation of the already trained
networks and hence the acceleration of the global convergence of the
algorithm. In the preprocessing phase, a new feature extraction
method is proposed based on Legendre moments with the Maximum
entropy principle MEP as a selection criterion. This allows a global
search space reduction in the design of the networks. The proposed
method has been applied and tested on the well known MNIST
database of handwritten digits.
Abstract: Mobile ad hoc network is a collection of mobile
nodes communicating through wireless channels without any
existing network infrastructure or centralized administration.
Because of the limited transmission range of wireless network
interfaces, multiple "hops" may be needed to exchange data
across the network. Consequently, many routing algorithms
have come into existence to satisfy the needs of
communications in such networks. Researchers have
conducted many simulations comparing the performance of
these routing protocols under various conditions and
constraints. One question that arises is whether speed of nodes
affects the relative performance of routing protocols being
studied. This paper addresses the question by simulating two
routing protocols AODV and DSDV. Protocols were
simulated using the ns-2 and were compared in terms of
packet delivery fraction, normalized routing load and average
delay, while varying number of nodes, and speed.
Abstract: Iris pattern is an important biological feature of human body; it becomes very hot topic in both research and practical applications. In this paper, an algorithm is proposed for iris recognition and a simple, efficient and fast method is introduced to extract a set of discriminatory features using first order gradient operator applied on grayscale images. The gradient based features are robust, up to certain extents, against the variations may occur in contrast or brightness of iris image samples; the variations are mostly occur due lightening differences and camera changes. At first, the iris region is located, after that it is remapped to a rectangular area of size 360x60 pixels. Also, a new method is proposed for detecting eyelash and eyelid points; it depends on making image statistical analysis, to mark the eyelash and eyelid as a noise points. In order to cover the features localization (variation), the rectangular iris image is partitioned into N overlapped sub-images (blocks); then from each block a set of different average directional gradient densities values is calculated to be used as texture features vector. The applied gradient operators are taken along the horizontal, vertical and diagonal directions. The low order norms of gradient components were used to establish the feature vector. Euclidean distance based classifier was used as a matching metric for determining the degree of similarity between the features vector extracted from the tested iris image and template features vectors stored in the database. Experimental tests were performed using 2639 iris images from CASIA V4-Interival database, the attained recognition accuracy has reached up to 99.92%.
Abstract: In recent years, there have been attempts to store
natural gas in adsorptive form. This is called adsorptive natural gas,
or ANG. The problem with this technology is the low sorption
capacity. The purpose is to achieve compressed natural gas (CNG)
capacity of 230 V/V. Further research is required to achieve such
target. Several research studies have been performed with this target;
through either the modification or development of new sorbents or
the optimization of the operation sorption process itself. In this work,
storage of methane on molecular sieves 5A and 13X was studied on
dry basis, and on wet basis to certain extent. The temperature and the
pressure dynamics were investigated. The results indicated that
regardless of the charge pressure, the time for the peak temperature
during the methane charge process is always the same. This can be
used as a characteristic of the adsorbent. The total achieved
deliveries using molecular sieves were much lower than that of
activated carbons; 53.0 V/V for the case of 13X molecular sieves and
43 V/V for the case of 5A molecular sieves, both at 2oC and 4 MPa
(580 psi). Investigation of charge pressure dynamic using wet
molecular sieves at 2oC and a mass ratio of 0.5, revealed slowness of
the process and unexpected behavior.
Abstract: The aim of this study is to determine the basic information and communication technology (ICT) skills that may be needed by students studying in the 8th grade of the primary education in their cooperative project works implemented via the Internet. Within the scope of the study, the curriculum used for European Computer Driving License (ECDL) and the curriculum used in Turkey are also compared in terms of the ability to use ICT, which is aimed to be provided to the students. The research population of the study, during which the pre test – post test control group experimental model was used, consisted of 40 students from three different schools. In the first stage of the study, the skills that might be needed by students for their cooperative project works implemented via the Internet were determined through examination of the completed Comenious, e – twinning and WorldLinks projects. In the second stage of the study, the curriculums of the Turkish Ministry of National Education (MEB) and ECDL were evaluated by seven different teachers in line with these skills. Also in this study the ECDL and MEB curriculums were compared in terms of capability to provide the skills to implement cooperative projects via the Internet. In line with the findings of the study, the skills that might be needed by students to implement cooperative projects via the Internet were outlined, and existence of a significant difference was established in favor of the ECDL curriculum upon comparison of both curriculums in accordance with this outline (U = 50,500; p
Abstract: CO2 miscible displacement is not feasible in many oil fields due to high reservoir temperature as higher pressure is required to achieve miscibility. The miscibility pressure is far higher than the formation fracture pressure making it impossible to have CO2 miscible displacement. However, by using oleophilic chemicals, minimum miscibility pressure (MMP) could be lowered. The main objective of this research is to find the best oleophilic chemical in MMP reduction using slim-tube test and Vanishing Interfacial Tension (VIT) The chemicals are selected based on the characteristics that it must be oil soluble, low water solubility, have 4 – 8 carbons, semi polar, economical, and safe for human operation. The families of chemicals chosen are carboxylic acid, alcohol, and ketone. The whole experiment would be conducted at 100°C and the best chemical is said to be effective when it is able to lower CO2-crude oil MMP the most. Findings of this research would have great impact to the oil and gas industry in reduction of operation cost for CO2EOR which is applicable to both onshore and offshore operation.
Abstract: Recently, genetic algorithms (GA) and particle swarm optimization (PSO) technique have attracted considerable attention among various modern heuristic optimization techniques. Since the two approaches are supposed to find a solution to a given objective function but employ different strategies and computational effort, it is appropriate to compare their performance. This paper presents the application and performance comparison of PSO and GA optimization techniques, for Thyristor Controlled Series Compensator (TCSC)-based controller design. The design objective is to enhance the power system stability. The design problem of the FACTS-based controller is formulated as an optimization problem and both the PSO and GA optimization techniques are employed to search for optimal controller parameters. The performance of both optimization techniques in terms of computational time and convergence rate is compared. Further, the optimized controllers are tested on a weakly connected power system subjected to different disturbances, and their performance is compared with the conventional power system stabilizer (CPSS). The eigenvalue analysis and non-linear simulation results are presented and compared to show the effectiveness of both the techniques in designing a TCSC-based controller, to enhance power system stability.
Abstract: The job shop scheduling problem (JSSP) is a
notoriously difficult problem in combinatorial optimization. This
paper presents a hybrid artificial immune system for the JSSP with the
objective of minimizing makespan. The proposed approach combines
the artificial immune system, which has a powerful global exploration
capability, with the local search method, which can exploit the optimal
antibody. The antibody coding scheme is based on the operation based
representation. The decoding procedure limits the search space to the
set of full active schedules. In each generation, a local search heuristic
based on the neighborhood structure proposed by Nowicki and
Smutnicki is applied to improve the solutions. The approach is tested
on 43 benchmark problems taken from the literature and compared
with other approaches. The computation results validate the
effectiveness of the proposed algorithm.
Abstract: In this paper a combination approach of two heuristic-based algorithms: genetic algorithm and tabu search is proposed. It has been developed to obtain the least cost based on the split-pipe design of looped water distribution network. The proposed combination algorithm has been applied to solve the three well-known water distribution networks taken from the literature. The development of the combination of these two heuristic-based algorithms for optimization is aimed at enhancing their strengths and compensating their weaknesses. Tabu search is rather systematic and deterministic that uses adaptive memory in search process, while genetic algorithm is probabilistic and stochastic optimization technique in which the solution space is explored by generating candidate solutions. Split-pipe design may not be realistic in practice but in optimization purpose, optimal solutions are always achieved with split-pipe design. The solutions obtained in this study have proved that the least cost solutions obtained from the split-pipe design are always better than those obtained from the single pipe design. The results obtained from the combination approach show its ability and effectiveness to solve combinatorial optimization problems. The solutions obtained are very satisfactory and high quality in which the solutions of two networks are found to be the lowest-cost solutions yet presented in the literature. The concept of combination approach proposed in this study is expected to contribute some useful benefits in diverse problems.
Abstract: During last decades, developing multi-objective
evolutionary algorithms for optimization problems has found
considerable attention. Flexible job shop scheduling problem, as an
important scheduling optimization problem, has found this attention
too. However, most of the multi-objective algorithms that are
developed for this problem use nonprofessional approaches. In
another words, most of them combine their objectives and then solve
multi-objective problem through single objective approaches. Of
course, except some scarce researches that uses Pareto-based
algorithms. Therefore, in this paper, a new Pareto-based algorithm
called controlled elitism non-dominated sorting genetic algorithm
(CENSGA) is proposed for the multi-objective FJSP (MOFJSP). Our
considered objectives are makespan, critical machine work load, and
total work load of machines. The proposed algorithm is also
compared with one the best Pareto-based algorithms of the literature
on some multi-objective criteria, statistically.
Abstract: The search for factors that influence user behavior has remained an important theme for both the academic and practitioner Information Systems Communities. In this paper we examine relevant user behaviors in the phase after adoption and investigate two factors that are expected to influence such behaviors, namely User Involvement (UI) and Personal Innovativeness in IT (PIIT). We conduct a field study to examine how these factors influence postadoption behavior and how they are interrelated. Building on theoretical premises and prior empirical findings, we propose and test two alternative models of the relationship between these factors. Our results reveal that the best explanation of post-adoption behavior is provided by the model where UI and PIIT independently influence post-adoption behavior. Our findings have important implications for research and practice. To that end, we offer directions for future research.
Abstract: This paper introduces an isolated and unique ancient language Burushaski, spoken in Hunza, Nagar, Yasin and parts of Gilgit in the Northern Areas of Pakistan. It explains the working mechanism of Multi Language Text Editor for Urdu and Burushaski. It is developed under the use of ISO/IEC 10646 Unicode standards for Urdu and Burushaski open-type fonts. It gives an ample opportunity to this regional ancient language to have a modern Information technology for its promotion and preservation. The main objective of this research paper is to help preserve the heritage of such rare languages and give smart way of automation. It also facilitates to those who are interested in undertaking research on Burushaski or keen to trace fonatic relationship between the national Urdu language and Burushaski. Since this editor covers both Burushaski and Urdu so it can play an important role to introduce Burusho linguistic culture to the world at large. Precisely, as a result of this research paper, Burushaski publication through IT means would be possible.
Abstract: Nowadays e-Learning is more popular, in Vietnam
especially. In e-learning, materials for studying are very important.
It is necessary to design the knowledge base systems and expert
systems which support for searching, querying, solving of
problems. The ontology, which was called Computational Object
Knowledge Base Ontology (COB-ONT), is a useful tool for
designing knowledge base systems in practice. In this paper, a
design method for knowledge base systems in education using
COKB-ONT will be presented. We also present the design of a
knowledge base system that supports studying knowledge and
solving problems in higher mathematics.
Abstract: The amount and heterogeneity of data in biomedical research, notably in interdisciplinary research, requires new methods for the collection, presentation and analysis of information. Important data from laboratory experiments as well as patient trials are available but come out of distributed resources. The Charite Medical School in Berlin has established together with the German Research Foundation (DFG) a new information service center for kidney diseases and transplantation (Open European Nephrology Science Centre - OpEN.SC). The system is based on a service-oriented architecture (SOA) with main and auxiliary modules arranged in four layers. To improve the reuse and efficient arrangement of the services the functionalities are described as business processes using the standardised Business Process Execution Language (BPEL).
Abstract: Academics and researchers are interested in the effects of social media on college students, with a specific focus on the most popular social media website; Facebook. Previous studied have found contradictory result on the relationship between Facebook usage and the student engagement with positive, detrimental and no significant relationships. However, these studies were limited to western higher education system. This paper fills a gap in the literature by using a sample (300) of Sri Lankan management undergraduates to examine the relationship between Facebook usage and student engagement. Student engagement was measured 35 item scale based on the National Survey of Student Engagement and Facebook usage by Facebook intensity scale. Descriptive statistics, path analysis and structural equation modeling were applied as statistical tools and techniques. Results indicate that student engagement scale was significantly negatively related with the Facebook usage with the influence from student engagement on Facebook usage.
Abstract: Nowadays, precipitation prediction is required for proper planning and management of water resources. Prediction with neural network models has received increasing interest in various research and application domains. However, it is difficult to determine the best neural network architecture for prediction since it is not immediately obvious how many input or hidden nodes are used in the model. In this paper, neural network model is used as a forecasting tool. The major aim is to evaluate a suitable neural network model for monthly precipitation mapping of Myanmar. Using 3-layerd neural network models, 100 cases are tested by changing the number of input and hidden nodes from 1 to 10 nodes, respectively, and only one outputnode used. The optimum model with the suitable number of nodes is selected in accordance with the minimum forecast error. In measuring network performance using Root Mean Square Error (RMSE), experimental results significantly show that 3 inputs-10 hiddens-1 output architecture model gives the best prediction result for monthly precipitation in Myanmar.
Abstract: This paper presents a narrative management system
for organizations to capture organization's tacit knowledge
through stories. The intention of capturing tacit knowledge is to
address the problem that comes with the mobility of workforce in
organisation. Storytelling in knowledge management context is
seen as a powerful management tool to communicate tacit
knowledge in organization. This narrative management system is
developed firstly to enable uploading of many types of knowledge
sharing stories, from general to work related-specific stories and
secondly, each video has comment functionality where knowledge
users can post comments to other knowledge users. The narrative
management system allows the stories to browse, search and view
by the users. In the system, stories are stored in a video repository.
Stories that were produced from this framework will improve
learning, knowledge transfer facilitation and tacit knowledge
quality in an organization.