Search results for: Approaches to study

Authors: Sivapalan, S., Subramaniam, G., Clifford, M.J., Balbir Singh, M.S., Abdullah, A

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Higher education has an important role to play in advocating environmentalism. Given this responsibility, the goal of higher education should therefore be to develop graduates with the knowledge, skills and values related to environmentalism. However, research indicates that there is a lack of consciousness amongst graduates on the need to be more environmentally aware, especially when it comes to applying the appropriate knowledge and skills related to environmentalism. Although institutions of higher learning do include environmental parameters within their undergraduate and postgraduate academic programme structures, the environmental boundaries are usually confined to specific engineering majors within an engineering programme. This makes environmental knowledge, skills and values exclusive to certain quarters of the higher education system. The incorporation of environmental literacy within higher education institutions as a whole is of utmost pertinence if a nation-s human capital is to be nurtured to become change agents for the preservation of environment. This paper discusses approaches that can be adapted by institutions of higher learning to include environmental literacy within the graduate-s higher learning experience.

Keywords: Higher education, engineering education, environmental literacy, Malaysia.

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Authors: Jain-Shing Liu

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In this paper, we present a matrix game-theoretic cross-layer optimization formulation to maximize the network lifetime in wireless ad hoc networks with network coding. To this end, we introduce a cross-layer formulation of general NUM (network utility maximization) that accommodates routing, scheduling, and stream control from different layers in the coded networks. Specifically, for the scheduling problem and then the objective function involved, we develop a matrix game with the strategy sets of the players corresponding to hyperlinks and transmission modes, and design the payoffs specific to the lifetime. In particular, with the inherit merit that matrix game can be solved with linear programming, our cross-layer programming formulation can benefit from both game-based and NUM-based approaches at the same time by cooperating the programming model for the matrix game with that for the other layers in a consistent framework. Finally, our numerical example demonstrates its performance results on a well-known wireless butterfly network to verify the cross-layer optimization scheme.

Keywords: Cross-layer design, Lifetime maximization, Matrix game, Network coding

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Authors: Suyoto, Tri Prasetyaningrum

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At this paper, we will present the development of mobile application Social Guidance and Counseling (GC) that called “m-NingBK: Social GC”. The application is used for GC services that run on mobile devices. The application is designed specifically for Junior High School student. The methods are a combination of interactive multimedia approaches and educational psychology. Therefore, the design process is carried out three processes, which are digitizing of material social GC services, visualizing wisely and making interactive. This method is intended to make students not only hear and see but also "do" the virtual. There are five components used in multimedia applications "m-NingBK: Social GC" i.e. text, images / graphics, audio / sound, animation and video. Four menus provided by this application is the potential self, social, Expert System and about. The application is built using the Java programming language. This application was tested using a Smartphone with Android Operating System. Based on the test, people give rating: 16.7% excellent, 61.1% good, 19.4% adequate, and 2.8% poor.

Keywords: Expert Systems, Guidance and Counseling, mobile application, multimedia.

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Authors: Darwina Arshad, Paul Hughes

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Recent environmental turbulence including financial crisis, intensified competitive forces, rapid technological change and high market turbulence have dramatically changed the current business climate. The managers firms have to plan and decide what the best approaches that best fit their firms in order to pursue superior performance. This research aims to examine the influence of strategic reasoning and top level managers- individual characteristics on the effectiveness of organizational improvisation and firm performance. Given the lack of studies on these relationships in the previous literature, there is significant contribution to the body of knowledge as well as for managerial practices. 128 responses from top management of technology-based companies in Malaysia were used as a sample. Three hypotheses were examined and the findings confirm that (a) there is no relationship between intuitive reasoning and organizational improvisation but there is a link between rational reasoning and organizational improvisation, (b) top level managers- individual characteristics as a whole affect organizational improvisation; and (c) organizational improvisation positively affects firm performance. The theoretical and managerial implications were discussed in the conclusions.

Keywords: Organizational improvisation, strategic reasoning, firm performance.

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Authors: Levan Nadareishvili, Roland Bakuradze, Barbara Kilosanidze, Nona Topuridze, Liana Sharashidze, Ineza Pavlenishvili

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Some regularities of formation of a new structural state of the thermoplastic polymers - gradually oriented (stretched) state (GOS) are discussed. Transition into GOS is realized by the graded oriented stretching - by action of inhomogeneous mechanical field on the isotropic linear polymers or by zone stretching that is implemented on a standard tensile-testing machine with using a specially designed zone stretching device (ZSD). Both technical approaches (especially zone stretching method) allows to manage the such quantitative parameters of gradually oriented polymers as a range of change in relative elongation/orientation degree, length of this change and profile (linear, hyperbolic, parabolic, logarithmic, etc.). The possibility of obtaining functionally graded materials (FGMs) by graded orientation method is briefly discussed. Uniaxial graded stretching method should be considered as an effective technological solution to create polymer materials with a predetermined gradient of physical properties.

Keywords: Controlled graded stretching, gradually oriented state, linear polymers, zone stretching device.

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Authors: Drago Jakovcevic, Mihovil Andelinovic, Igor Husak

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The aim of this paper is to explore the economic circumstances in which the selective credit policy, the least used instrument of four types of instruments on disposal to central banks, should be used. The most significant example includes the use of selective credit policies in response to the emergence of the global financial crisis by the FED. Specifics of the potential use of selective credit policies as the instigator of economic growth in Croatia, a small open economy, are determined by high euroization of financial system, fixed exchange rate and long-term trend growth of external debt that is related to the need to maintain high levels of foreign reserves. In such conditions, the classic forms of selective credit policies are unsuitable for the introduction. Several alternative approaches to implement selective credit policies are examined in this paper. Also, thorough analysis of distribution of selective monetary policy loans among economic sectors in Croatia is conducted in order to minimize the risk of investing funds and maximize the return, in order to influence the GDP growth.

Keywords: Global crisis, Selective credit policy, Small open economy.

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Authors: Ayelet Gur

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Background: In recent years we are witnessing a welcome trend in which more children/persons with disabilities are living at home with their families and within their communities. This trend is related to various policy innovations as the UN Convention on the Rights of People with Disabilities that reflect a shift from the medical-institutional model to a human rights approach. We also witness the emergence of family centered approaches that perceive the family and not just the individual with the disability as a worthy target of policy planning, implementation and evaluation efforts. The current investigation aims to explore economic, psychological and social factors among households of families of children or adults with intellectual disabilities in Israel and to present policy recommendation. Methods: A national sample of 301 households was recruited through the education and employment settings of persons with intellectual disability. The main caregiver of the person with the disability (a parent) was interviewed. Measurements included the income and expense surveys; assets and debts questionnaire; the questionnaire on resources and stress; the social involvement questionnaire and Personal Wellbeing Index. Results: Findings indicate significant gaps in financial circumstances between households of families of children with intellectual disabilities and households of the general Israeli society. Households of families of children with intellectual disabilities report lower income and higher expenditures and loans than the general society. They experience difficulties in saving and coping with unexpected expenses. Caregivers (the parents) experience high stress, low social participation, low financial support from family, friend and non-governmental organizations and decreased well-being. They are highly dependent on social security allowances which constituted 40% of the household's income. Conclusions: Households' dependency on social security allowances may seem contradictory to the encouragement of persons with intellectual disabilities to favor independent living in light of the human rights approach to disability. New policy should aim at reducing caregivers' stress and enhance their social participation and support, with special emphasis on families of lower socio-economic status. Finally, there is a need to continue monitoring the economic and psycho-social needs of households of families of children with intellectual disabilities and other developmental disabilities.

Keywords: Disability policy, family policy, intellectual and developmental disabilities, Israel, households study, parents of children with disabilities.

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Authors: Omer Ishag Eldai, Ahmed Hassan M. H. Ali, S. Raviraja

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Web-based systems have become increasingly important due to the fact that the Internet and the World Wide Web have become ubiquitous, surpassing all other technological developments in our history. The Internet and especially companies websites has rapidly evolved in their scope and extent of use, from being a little more than fixed advertising material, i.e. a "web presences", which had no particular influence for the company's business, to being one of the most essential parts of the company's core business. Traditional software engineering approaches with process models such as, for example, CMM and Waterfall models, do not work very well since web system development differs from traditional development. The development differs in several ways, for example, there is a large gap between traditional software engineering designs and concepts and the low-level implementation model, many of the web based system development activities are business oriented (for example web application are sales-oriented, web application and intranets are content-oriented) and not engineering-oriented. This paper aims to introduce Increment Iterative extreme Programming (IIXP) methodology for developing web based systems. In difference to the other existence methodologies, this methodology is combination of different traditional and modern software engineering and web engineering principles.

Keywords: Web based systems, Web engineering.

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Authors: Rossitza M. Setchi, Qiao Tang

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Nowadays, ontologies are the only widely accepted paradigm for the management of sharable and reusable knowledge in a way that allows its automatic interpretation. They are collaboratively created across the Web and used to index, search and annotate documents. The vast majority of the ontology based approaches, however, focus on indexing texts at document level. Recently, with the advances in ontological engineering, it became clear that information indexing can largely benefit from the use of general purpose ontologies which aid the indexing of documents at word level. This paper presents a concept indexing algorithm, which adds ontology information to words and phrases and allows full text to be searched, browsed and analyzed at different levels of abstraction. This algorithm uses a general purpose ontology, OntoRo, and an ontologically tagged corpus, OntoCorp, both developed for the purpose of this research. OntoRo and OntoCorp are used in a two-stage supervised machine learning process aimed at generating ontology tagging rules. The first experimental tests show a tagging accuracy of 78.91% which is encouraging in terms of the further improvement of the algorithm.

Keywords: Concepts, indexing, machine learning, ontology, tagging.

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Authors: Banashree N. P., R. Vasanta

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Recognition of Indian languages scripts is challenging problems. In Optical Character Recognition [OCR], a character or symbol to be recognized can be machine printed or handwritten characters/numerals. There are several approaches that deal with problem of recognition of numerals/character depending on the type of feature extracted and different way of extracting them. This paper proposes a recognition scheme for handwritten Hindi (devnagiri) numerals; most admired one in Indian subcontinent. Our work focused on a technique in feature extraction i.e. global based approach using end-points information, which is extracted from images of isolated numerals. These feature vectors are fed to neuro-memetic model [18] that has been trained to recognize a Hindi numeral. The archetype of system has been tested on varieties of image of numerals. . In proposed scheme data sets are fed to neuro-memetic algorithm, which identifies the rule with highest fitness value of nearly 100 % & template associates with this rule is nothing but identified numerals. Experimentation result shows that recognition rate is 92-97 % compared to other models.

Keywords: OCR, Global Feature, End-Points, Neuro-Memetic model.

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Authors: Ahmed Elrewainy

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Mixing in the hyperspectral imaging occurs due to the low spatial resolutions of the used cameras. The existing pure materials “endmembers” in the scene share the spectra pixels with different amounts called “abundances”. Unmixing of the data cube is an important task to know the present endmembers in the cube for the analysis of these images. Unsupervised unmixing is done with no information about the given data cube. Sparsity is one of the recent approaches used in the source recovery or unmixing techniques. The l₁-norm optimization problem “basis pursuit” could be used as a sparsity-based approach to solve this unmixing problem where the endmembers is assumed to be sparse in an appropriate domain known as dictionary. This optimization problem is solved using proximal method “iterative thresholding”. The l₁-norm basis pursuit optimization problem as a sparsity-based unmixing technique was used to unmix real and synthetic hyperspectral data cubes.

Keywords: Basis pursuit, blind source separation, hyperspectral imaging, spectral unmixing, wavelets.

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Authors: S. Qaedi, S. Seyedtabaii

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Non-Destructive evaluation of in-service power transformer condition is necessary for avoiding catastrophic failures. Dissolved Gas Analysis (DGA) is one of the important methods. Traditional, statistical and intelligent DGA approaches have been adopted for accurate classification of incipient fault sources. Unfortunately, there are not often enough faulty patterns required for sufficient training of intelligent systems. By bootstrapping the shortcoming is expected to be alleviated and algorithms with better classification success rates to be obtained. In this paper the performance of an artificial neural network, K-Nearest Neighbour and support vector machine methods using bootstrapped data are detailed and shown that while the success rate of the ANN algorithms improves remarkably, the outcome of the others do not benefit so much from the provided enlarged data space. For assessment, two databases are employed: IEC TC10 and a dataset collected from reported data in papers. High average test success rate well exhibits the remarkable outcome.

Keywords: Dissolved gas analysis, Transformer incipient fault, Artificial Neural Network, Support Vector Machine (SVM), KNearest Neighbor (KNN)

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Authors: Souhir Ben Amor, Heni Boubaker, Lotfi Belkacem

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This aims of this paper is to forecast the electricity spot prices. First, we focus on modeling the conditional mean of the series so we adopt a generalized fractional -factor Gegenbauer process (k-factor GARMA). Secondly, the residual from the -factor GARMA model has used as a proxy for the conditional variance; these residuals were predicted using two different approaches. In the first approach, a local linear wavelet neural network model (LLWNN) has developed to predict the conditional variance using the Back Propagation learning algorithms. In the second approach, the Gegenbauer generalized autoregressive conditional heteroscedasticity process (G-GARCH) has adopted, and the parameters of the k-factor GARMA-G-GARCH model has estimated using the wavelet methodology based on the discrete wavelet packet transform (DWPT) approach. The empirical results have shown that the k-factor GARMA-G-GARCH model outperform the hybrid k-factor GARMA-LLWNN model, and find it is more appropriate for forecasts.

Keywords: k-factor, GARMA, LLWNN, G-GARCH, electricity price, forecasting.

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Authors: M. Ovinis, D. Kerr, K. Bouazza-Marouf, M. Vloeberghs

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The use of anatomical landmarks as a basis for image to patient registration is appealing because the registration may be performed retrospectively. We have previously proposed the use of two anatomical soft tissue landmarks of the head, the canthus (corner of the eye) and the tragus (a small, pointed, cartilaginous flap of the ear), as a registration basis for an automated CT image to patient registration system, and described their localization in patient space using close range photogrammetry. In this paper, the automatic localization of these landmarks in CT images, based on their curvature saliency and using a rule based system that incorporates prior knowledge of their characteristics, is described. Existing approaches to landmark localization in CT images are predominantly semi-automatic and primarily for localizing internal landmarks. To validate our approach, the positions of the landmarks localized automatically and manually in near isotropic CT images of 102 patients were compared. The average difference was 1.2mm (std = 0.9mm, max = 4.5mm) for the medial canthus and 0.8mm (std = 0.6mm, max = 2.6mm) for the tragus. The medial canthus and tragus can be automatically localized in CT images, with performance comparable to manual localization, based on the approach presented.

Keywords: Anatomical Landmarks, CT, Localization.

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Authors: M.V Rajesh, Archana R, A Unnikrishnan, R Gopikakumari, Jeevamma Jacob

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The System Identification problem looks for a suitably parameterized model, representing a given process. The parameters of the model are adjusted to optimize a performance function based on error between the given process output and identified process output. The linear system identification field is well established with many classical approaches whereas most of those methods cannot be applied for nonlinear systems. The problem becomes tougher if the system is completely unknown with only the output time series is available. It has been reported that the capability of Artificial Neural Network to approximate all linear and nonlinear input-output maps makes it predominantly suitable for the identification of nonlinear systems, where only the output time series is available. [1][2][4][5]. The work reported here is an attempt to implement few of the well known algorithms in the context of modeling of nonlinear systems, and to make a performance comparison to establish the relative merits and demerits.

Keywords: Multilayer neural networks, Radial Basis Functions, Clustering algorithm, Back Propagation training, Extended Kalmanfiltering, Mean Square Error, Nonlinear Modeling, Cramer RaoLower Bound.

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Authors: M.Stella, M. Russo, D. Begušić

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Ability of accurate and reliable location estimation in indoor environment is the key issue in developing great number of context aware applications and Location Based Services (LBS). Today, the most viable solution for localization is the Received Signal Strength (RSS) fingerprinting based approach using wireless local area network (WLAN). This paper presents two RSS fingerprinting based approaches – first we employ widely used WLAN based positioning as a reference system and then investigate the possibility of using GSM signals for positioning. To compare them, we developed a positioning system in real world environment, where realistic RSS measurements were collected. Multi-Layer Perceptron (MLP) neural network was used as the approximation function that maps RSS fingerprints and locations. Experimental results indicate advantage of WLAN based approach in the sense of lower localization error compared to GSM based approach, but GSM signal coverage by far outreaches WLAN coverage and for some LBS services requiring less precise accuracy our results indicate that GSM positioning can also be a viable solution.

Keywords: Indoor positioning, WLAN, GSM, RSS, location fingerprints, neural network.

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Authors: Sareh Rajabi, Taha Anjamrooz, Salwa Bheiry

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Sustainability of construction projects is an important issue to be addressed since the sector will continue to be developed in the coming years, especially in developing countries. Thus, it is significant to discover approaches and solutions for improving sustainability. Currently, the construction industry is the largest consumer of natural resources. This is the same in other countries in the Gulf region, and the United Arab Emirates (UAE) has limited natural resources such as water, electricity, etc. Recently, the UAE has taken several actions in order to implement sustainable initiatives within its construction industry. Within the industry, the contractors’ role is significant in promoting sustainable development by taking the responsibility to minimize their negative impacts on the environment and society, and maximize their economic distribution. In this research, sustainability will be studied as an important key to bring competitive advantages to contracting organizations. The contractors should understand the need to improve their sustainable performance in order to expand their business competitiveness. Competitiveness at the construction project level refers to a contractor’s ability to compete for a project. There is less focus on how to improve contractors’ competitiveness by implementing sustainable construction practices. Based on an inclusive literature review on the relationship between sustainability performance and business competitiveness, this research will conduct a study of sustainable practice in the construction industry and the relationship between sustainability performance and business competitiveness in order to develop a framework for evaluating how contractors can improve their competitiveness in terms of more efficient processes, enhancements in productivity, and lower costs of compliance in order to reduce the initial project cost and obtain market opportunities in the UAE. The research findings will provide a framework that can be a useful guideline for contractors to develop their sustainability policy, strategy and practice for meeting the increased requirements for sustainable development in construction.

Keywords: Sustainable construction practice, sustainability, competitiveness, construction industry, contractors.

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Authors: Martin Skutil, Klára Havlíčková, Renata Matějíčková

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The paper is the first output of a larger research project conducted at the Faculty of Education of the University of Hradec Králové, which deals with an improved understanding of teachers' work in the subject of National History and Geography. Partial findings focusing on the use of didactic material resources in teaching are presented in this phase. With the regard to promotion of independent activity of students within learner based education, material equipment of schools with didactic aids is becoming increasingly important. This paper is based on qualitative research, where the possibilities and mainly the reasons for use of material didactic resources in teaching were investigated through semi-structured interviews. Attention was focused on ways of working with different teaching aids and their implementation in the educational process. It turns out that teachers accept current constructivist and humanistic approaches to education associated with the requirement to prepare students for life in an information society, and accordingly they adjust their teaching.

Keywords: Primary education, National History and Geography, didactic material resources, qualitative research.

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Authors: M. Sadeghi, H. Pezeshk, R. Tusserkani, A. Sharifi Zarchi, A. Malekpour, M. Foroughmand, S. Goliaei, M. Totonchi, N. Ansari–Pour

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The role and relative importance of intrinsic and extrinsic factors in the development of complex diseases such as cancer still remains a controversial issue. Determining the amount of variation explained by these factors needs experimental data and statistical models. These models are nevertheless based on the occurrence and accumulation of random mutational events during stem cell division, thus rendering cancer development a stochastic outcome. We demonstrate that not only individual genome sequencing is uninformative in determining cancer risk, but also assigning a unique genome sequence to any given individual (healthy or affected) is not meaningful. Current whole-genome sequencing approaches are therefore unlikely to realize the promise of personalized medicine. In conclusion, since genome sequence differs from cell to cell and changes over time, it seems that determining the risk factor of complex diseases based on genome sequence is somewhat unrealistic, and therefore, the resulting data are likely to be inherently uninformative.

Keywords: Cancer risk, extrinsic factors, genome sequencing, intrinsic factors.

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Authors: Ming Wen, Nasim Nezamoddini

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Sophisticated numerical simulations like finite element analysis (FEA) involve a complicated process from model setup to post-processing tasks that require replication of time-consuming steps. Utilizing FEA automation program simplifies the complexity of the involved steps while minimizing human errors in analysis set up, calculations, and results processing. One of the main challenges in designing FEA automation programs is to identify user requirements and link them to possible design alternatives. This paper presents a decision-making framework to design a Python based FEA automation program for modal analysis, frequency response analysis, and random vibration fatigue (RVF) analysis procedures. Analytical hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) are applied to evaluate design alternatives considering the feedback received from experts and program users.

Keywords: FEA, random vibration fatigue, process automation, AHP, TOPSIS, multiple-criteria decision-making, MCDM.

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Authors: Dewan Md. Farid, Nouria Harbi, Emna Bahri, Mohammad Zahidur Rahman, Chowdhury Mofizur Rahman

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Recently, information security has become a key issue in information technology as the number of computer security breaches are exposed to an increasing number of security threats. A variety of intrusion detection systems (IDS) have been employed for protecting computers and networks from malicious network-based or host-based attacks by using traditional statistical methods to new data mining approaches in last decades. However, today's commercially available intrusion detection systems are signature-based that are not capable of detecting unknown attacks. In this paper, we present a new learning algorithm for anomaly based network intrusion detection system using decision tree algorithm that distinguishes attacks from normal behaviors and identifies different types of intrusions. Experimental results on the KDD99 benchmark network intrusion detection dataset demonstrate that the proposed learning algorithm achieved 98% detection rate (DR) in comparison with other existing methods.

Keywords: Detection rate, decision tree, intrusion detectionsystem, network security.

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Authors: Levent Basayigit, Sinan Demir, Yusuf Ucar, Burhan Kara

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Many research projects require accurate delineation of the different land cover type of the agricultural area. Especially it is critically important for the definition of specific plants like cannabis. However, the complexity of vegetation stands structure, abundant vegetation species, and the smooth transition between different seconder section stages make vegetation classification difficult when using traditional approaches such as the maximum likelihood classifier. Most of the time, classification distinguishes only between trees/annual or grain. It has been difficult to accurately determine the cannabis mixed with other plants. In this paper, a mixed distribution models approach is applied to classify pure and mix cannabis parcels using Worldview-2 imagery in the Lakes region of Turkey. Five different land use types (i.e. sunflower, maize, bare soil, and cannabis) were identified in the image. A constrained Gaussian mixture discriminant analysis (GMDA) was used to unmix the image. In the study, 255 reflectance ratios derived from spectral signatures of seven bands (Blue-Green-Yellow-Red-Rededge-NIR1-NIR2) were randomly arranged as 80% for training and 20% for test data. Gaussian mixed distribution model approach is proved to be an effective and convenient way to combine very high spatial resolution imagery for distinguishing cannabis vegetation. Based on the overall accuracies of the classification, the Gaussian mixed distribution model was found to be very successful to achieve image classification tasks. This approach is sensitive to capture the illegal cannabis planting areas in the large plain. This approach can also be used for monitoring and determination with spectral reflections in illegal cannabis planting areas.

Keywords: Gaussian mixture discriminant analysis, spectral mixture model, World View-2, land parcels.

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Authors: A. Ghaffari, A. Meghdari, D. Naderi, S. Eslami

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In this paper an algorithm based on the adaptive neuro-fuzzy controller is provided to enhance the tipover stability of mobile manipulators when they are subjected to predefined trajectories for the end-effector and the vehicle. The controller creates proper configurations for the manipulator to prevent the robot from being overturned. The optimal configuration and thus the most favorable control are obtained through soft computing approaches including a combination of genetic algorithm, neural networks, and fuzzy logic. The proposed algorithm, in this paper, is that a look-up table is designed by employing the obtained values from the genetic algorithm in order to minimize the performance index and by using this data base, rule bases are designed for the ANFIS controller and will be exerted on the actuators to enhance the tipover stability of the mobile manipulator. A numerical example is presented to demonstrate the effectiveness of the proposed algorithm.

Keywords: Mobile Manipulator, Tipover Stability Enhancement, Adaptive Neuro-Fuzzy Inference Controller System, Soft Computing.

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Authors: A. Smagina, A. Lindemanis

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In the time of globalisation, growing uncertainty, ambiguity and change, traditional way of doing business are no longer sufficient and it is important to consider non-conventional methods and approaches to release creativity and facilitate innovation and growth. Thus, creative industries, as a natural source of creativity and innovation, draw particular attention. This paper explores feasibility of building creative partnerships between creative industries and business and brings attention to mutual benefits derived from such partnerships. Design/approach - This paper is a theoretical exploration of projects, practices and research findings addressing collaboration between creative industries and business. Thus, it concerns creative industries, arts, business and its representatives in order to define requirements for creative partnerships to work and succeed. Findings – Current practices in engaging into arts-business partnerships are still very few, although most of creative partnerships proved to be highly valuable and mutually beneficial. Certain conditions shall be provided in order to benefit from arts-business creative synergy. Originality/value- By integrating different sources of literature, this article provides a base for conducting empirical research in several dimensions within arts-business partnerships.

Keywords: Arts, artists, business, creative industries, partnership

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Authors: Behnam Mehrkian, Arash Bahar, Ali Chaibakhsh

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Magneto-rheological (MR) fluid damper is a semiactive control device that has recently received more attention by the vibration control community. But inherent hysteretic and highly nonlinear dynamics of MR fluid damper is one of the challenging aspects to employ its unique characteristics. The combination of artificial neural network (ANN) and fuzzy logic system (FLS) have been used to imitate more precisely the behavior of this device. However, the derivative-based nature of adaptive networks causes some deficiencies. Therefore, in this paper, a novel approach that employ genetic algorithm, as a free-derivative algorithm, to enhance the capability of fuzzy systems, is proposed. The proposed method used to model MR damper. The results will be compared with adaptive neuro-fuzzy inference system (ANFIS) model, which is one of the well-known approaches in soft computing framework, and two best parametric models of MR damper. Data are generated based on benchmark program by applying a number of famous earthquake records.

Keywords: Benchmark program, earthquake record filtering, fuzzy logic, genetic algorithm, MR damper.

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Authors: Qin Wei

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There has been an increased number of immigrants arriving in Canada and a concurrent rise in the number of immigrant youth suffering from drug abuse. Immigrant youths’ drug abuse has become a significant social and public health concern for researchers. This paper explores the nature of immigrant youths’ drug abuse by examining the factors influencing the onset of substance misuse, the barriers that discourage youth to seek out treatment, and how to resolve addictions amidst immigrant youth. Findings demonstrate that diminished parental supervision, acculturation challenges, peer conformity, discrimination, and ethnic marginalization are all significant factors influencing youth to use drugs as an outlet for their pain, while culturally incompetent care and fear of family and culture-based addiction stigma act as barriers discouraging youth from seeking out addiction support. To resolve addiction challenges amidst immigrant youth, future research should focus on promoting and implementing culturally sensitive practices and psychoeducational initiatives into immigrant communities and within public health policies.

Keywords: Approaches, barriers, drug abuse, Canada, immigrant youth.

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Authors: Ashish Payal, C. S. Rai, B. V. R. Reddy

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With the increasing use and application of Wireless Sensor Networks (WSN), need has arisen to explore them in more effective and efficient manner. An important area which can bring efficiency to WSNs is the localization process, which refers to the estimation of the position of wireless sensor nodes in an ad hoc network setting, in reference to a coordinate system that may be internal or external to the network. In this paper, we have done comparison and analysed Sigmoidal Feedforward Artificial Neural Networks (SFFANNs) and Radial Basis Function (RBF) networks for developing localization framework in WSNs. The presented work utilizes the Received Signal Strength Indicator (RSSI), measured by static node on 100 x 100 m² grid from three anchor nodes. The comprehensive evaluation of these approaches is done using MATLAB software. The simulation results effectively demonstrate that FFANNs based sensor motes will show better localization accuracy as compared to RBF.

Keywords: Localization, wireless sensor networks, artificial neural network, radial basis function, multi-layer perceptron, backpropagation, RSSI.

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Authors: Magdalena Naplavova, Tomas Ludik, Petr Hruza, Frantisek Bozek

Abstract:

The use of IT equipment has become a part of every day. However, each device that is part of cyberspace should be secured against unauthorized use. It is very important to know the basics of these security devices, but also the basics of safe conduct their owners. This information should be part of every curriculum computer science education in primary and secondary schools. Therefore, the work focuses on the education of pupils in primary and secondary schools on the Internet. Analysis of the current state describes approaches to the education of pupils in security issues on the Internet. The paper presents a questionnaire-based survey which was carried out in the Czech Republic, whose task was to ascertain the level of opinion pupils in primary and secondary schools on the issue of communication in social networks. The research showed that awareness of socio-pathological phenomena on the Internet environment is very low. Based on the results it was proposed appropriate ways of teaching to this issue and its inclusion a proposal of curriculum for primary and secondary schools.

Keywords: Cyberspace, educational system, general awareness, information security, questionnaire, socio-pathological phenomena.

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Authors: Yanling Li, Linying Ji, Zita Oravecz, Timothy R. Brick, Michael D. Hunter, Sy-Miin Chow

Abstract:

Assessing several individuals intensively over time yields intensive longitudinal data (ILD). Even though ILD provide rich information, they also bring other data analytic challenges. One of these is the increased occurrence of missingness with increased study length, possibly under non-ignorable missingness scenarios. Multiple imputation (MI) handles missing data by creating several imputed data sets, and pooling the estimation results across imputed data sets to yield final estimates for inferential purposes. In this article, we introduce dynr.mi(), a function in the R package, Dynamic Modeling in R (dynr). The package dynr provides a suite of fast and accessible functions for estimating and visualizing the results from fitting linear and nonlinear dynamic systems models in discrete as well as continuous time. By integrating the estimation functions in dynr and the MI procedures available from the R package, Multivariate Imputation by Chained Equations (MICE), the dynr.mi() routine is designed to handle possibly non-ignorable missingness in the dependent variables and/or covariates in a user-specified dynamic systems model via MI, with convergence diagnostic check. We utilized dynr.mi() to examine, in the context of a vector autoregressive model, the relationships among individuals’ ambulatory physiological measures, and self-report affect valence and arousal. The results from MI were compared to those from listwise deletion of entries with missingness in the covariates. When we determined the number of iterations based on the convergence diagnostics available from dynr.mi(), differences in the statistical significance of the covariate parameters were observed between the listwise deletion and MI approaches. These results underscore the importance of considering diagnostic information in the implementation of MI procedures.

Keywords: Dynamic modeling, missing data, multiple imputation, physiological measures.

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Authors: Kelemewerk Destalem, Jungjae Cho, Jaeseong Lee, Ju H. Park, Joonhyuk Yoo

Abstract:

Background subtraction and temporal difference are often used for moving object detection in video. Both approaches are computationally simple and easy to be deployed in real-time image processing. However, while the background subtraction is highly sensitive to dynamic background and illumination changes, the temporal difference approach is poor at extracting relevant pixels of the moving object and at detecting the stopped or slowly moving objects in the scene. In this paper, we propose a simple moving object detection scheme based on adaptive background subtraction and temporal difference exploiting dynamic background updates. The proposed technique consists of histogram equalization, a linear combination of background and temporal difference, followed by the novel frame-based and pixel-based background updating techniques. Finally, morphological operations are applied to the output images. Experimental results show that the proposed algorithm can solve the drawbacks of both background subtraction and temporal difference methods and can provide better performance than that of each method.

Keywords: Background subtraction, background updating, real time and lightweight algorithm, temporal difference.

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