Search results for: Association Rules Mining

Authors: Anchana Khemphila, Veera Boonjing

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In this study, the Multi-Layer Perceptron (MLP)with Back-Propagation learning algorithm are used to classify to effective diagnosis Parkinsons disease(PD).It-s a challenging problem for medical community.Typically characterized by tremor, PD occurs due to the loss of dopamine in the brains thalamic region that results in involuntary or oscillatory movement in the body. A feature selection algorithm along with biomedical test values to diagnose Parkinson disease.Clinical diagnosis is done mostly by doctor-s expertise and experience.But still cases are reported of wrong diagnosis and treatment. Patients are asked to take number of tests for diagnosis.In many cases,not all the tests contribute towards effective diagnosis of a disease.Our work is to classify the presence of Parkinson disease with reduced number of attributes.Original,22 attributes are involved in classify.We use Information Gain to determine the attributes which reduced the number of attributes which is need to be taken from patients.The Artificial neural networks is used to classify the diagnosis of patients.Twenty-Two attributes are reduced to sixteen attributes.The accuracy is in training data set is 82.051% and in the validation data set is 83.333%.

Keywords: Data mining, classification, Parkinson disease, artificial neural networks, feature selection, information gain.

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Authors: Brou K., Guéhi T., Konan A. G., Gbakayoro J. B., Gnakri D.

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Two types of crushing were applied to grains of red sorghum: manual crushing using a mortar and pestle of kitchen and mechanical crushing using a hammer mill. The flours obtained at the end of these various crushing were filtered and subdivided in different fractions according to the diameters of the mesh of the sieves (0.16mm; 0.25mm; 0.315mm; 0.4mm, and 0.63mm…). Some physical, chemical and nutritional traits of these flours were evaluated using Association of Official Analytical Chemists (AOAC). In vitro digestibility of these flours was also studied with freezing of flour 1% like substrate and α-amylase from B. licheniformis (E.C.3.2.1.1; Megazyme, Wicklow, Ireland). The results revealed that the batches of flours which have the finest diameters as 0.16mm; 0.25mm are the richest one in nutrients and are also the most digestible. Also mechanical crushing is the best mean to obtain significant amount of flours. In conclusion, the type of crushing and the size of the particles have an impact on the final concentration of some nutrients of the flours obtained. Indeed, the finest particles (0.16mm – 0.25mm 0.315mm) obtained after sifting of the flours are more nutritive and have a better digestibility than others size. So the finest particles could be advised for management of cereals namely the sorghum for the production of the infantile foods.

Keywords: Nutrients, digestibility, crush, flour, milling, granulometry.

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Authors: Su-Yan Tang, Wei Zhang, Shan Mei, Yi-Fan Zhu

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Network-Centric Air Defense Missile Systems (NCADMS) represents the superior development of the air defense missile systems and has been regarded as one of the major research issues in military domain at present. Due to lack of knowledge and experience on NCADMS, modeling and simulation becomes an effective approach to perform operational analysis, compared with those equation based ones. However, the complex dynamic interactions among entities and flexible architectures of NCADMS put forward new requirements and challenges to the simulation framework and models. ABS (Agent-Based Simulations) explicitly addresses modeling behaviors of heterogeneous individuals. Agents have capability to sense and understand things, make decisions, and act on the environment. They can also cooperate with others dynamically to perform the tasks assigned to them. ABS proves an effective approach to explore the new operational characteristics emerging in NCADMS. In this paper, based on the analysis of network-centric architecture and new cooperative engagement strategies for NCADMS, an agent-based simulation framework by expanding the simulation framework in the so-called System Effectiveness Analysis Simulation (SEAS) was designed. The simulation framework specifies components, relationships and interactions between them, the structure and behavior rules of an agent in NCADMS. Based on scenario simulations, information and decision superiority and operational advantages in NCADMS were analyzed; meanwhile some suggestions were provided for its future development.

Keywords: air defense missile systems, network-centric, agent-based simulation, simulation framework, information superiority, decision superiority, operational advantages

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Authors: Emari Hossien

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This study examined the underlying dimensions of brand equity in the chocolate industry. For this purpose, researchers developed a model to identify which factors are influential in building brand equity. The second purpose was to assess brand loyalty and brand images mediating effect between brand attitude, brand personality, brand association with brand equity. The study employed structural equation modeling to investigate the causal relationships between the dimensions of brand equity and brand equity itself. It specifically measured the way in which consumers’ perceptions of the dimensions of brand equity affected the overall brand equity evaluations. Data were collected from a sample of consumers of chocolate industry in Iran. The results of this empirical study indicate that brand loyalty and brand image are important components of brand equity in this industry. Moreover, the role of brand loyalty and brand image as mediating factors in the intention of brand equity are supported. The principal contribution of the present research is that it provides empirical evidence of the multidimensionality of consumer based brand equity, supporting Aaker´s and Keller´s conceptualization of brand equity. The present research also enriched brand equity building by incorporating the brand personality and brand image, as recommended by previous researchers. Moreover, creating the brand equity index in chocolate industry of Iran particularly is novel.

Keywords: brand equity, brand personality, structural equationmodeling, Iran.

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Authors: S. Abdulsalam, A. D. I. Suleiman, N. M. Musa, M. Yusuf

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Environment free of pollutants should be the concern of every individual but with industrialization and urbanization it is difficult to achieve. In view of achieving a pollution limited environment at low cost, a study was conducted on the use of bioremediation technology to remediate hydrocarbons and three heavy metals namely; copper (Cu), zinc (Zn) and iron (Fe) from a typical petroleum refinery wastewater in a closed system. Physicochemical and microbiological characteristics on the wastewater sample revealed that it was polluted with the aforementioned pollutants. Isolation and identification of microorganisms present in the wastewater sample revealed the presence of Bacillus subtilis, Micrococcus luteus, Staphylococcus aureus and Staphylococcus epidermidis. Bioremediation experiments carried out on five batch reactors with different compositions but at same environmental conditions revealed that treatment T5 (boosted with the association of Bacillus subtilis, Micrococcus luteus) gave the best result in terms of oil and grease content removal (i.e. 67% in 63 days). In addition, these microorganisms were able of reducing the concentrations of heavy metals in the sample. Treatments T5, T3 (boosted with Bacillus subtilis only) and T4 (boosted with Micrococcus luteus only) gave optimum percentage uptakes of 65, 75 and 25 for Cu, Zn and Fe respectively.

Keywords: Boosted, bioremediation, closed system, aeration, uptake, wastewater.

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Authors: Wadii Boulila, Imed Riadh Farah, Karim Saheb Ettabaa, Basel Solaiman, Henda Ben Ghezala

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This paper investigates the problem of tracking spa¬tiotemporal changes of a satellite image through the use of Knowledge Discovery in Database (KDD). The purpose of this study is to help a given user effectively discover interesting knowledge and then build prediction and decision models. Unfortunately, the KDD process for spatiotemporal data is always marked by several types of imperfections. In our paper, we take these imperfections into consideration in order to provide more accurate decisions. To achieve this objective, different KDD methods are used to discover knowledge in satellite image databases. Each method presents a different point of view of spatiotemporal evolution of a query model (which represents an extracted object from a satellite image). In order to combine these methods, we use the evidence fusion theory which considerably improves the spatiotemporal knowledge discovery process and increases our belief in the spatiotemporal model change. Experimental results of satellite images representing the region of Auckland in New Zealand depict the improvement in the overall change detection as compared to using classical methods.

Keywords: Knowledge discovery in satellite databases, knowledge fusion, data imperfection, data mining, spatiotemporal change detection.

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Authors: M. Tohidi, J. Yang, C. Baniotopoulos

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Progressive collapse of buildings typically occurs  when abnormal loading conditions cause local damages, which leads  to a chain reaction of failure and ultimately catastrophic collapse. The  tie force (TF) method is one of the main design approaches for  progressive collapse. As the TF method is a simplified method, further  investigations on the reliability of the method is necessary. This study  aims to develop an improved TF method to design the cross wall  structures for progressive collapse. To this end, the pullout behavior of  strands in grout was firstly analyzed; and then, by considering the tie  force-slip relationship in the friction stage together with the catenary  action mechanism, a comprehensive analytical method was developed.  The reliability of this approach is verified by the experimental results  of concrete block pullout tests and full scale floor-to-floor joints tests  undertaken by Portland Cement Association (PCA). Discrepancies in  the tie force between the analytical results and codified specifications  have suggested the deficiency of TF method, hence an improved  model based on the analytical results has been proposed to address this  concern.

 

Keywords: Cross wall, progressive collapse, ties force method, catenary, analytical.

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Authors: Leong Lee, Cyriac Kandoth, Jennifer L. Leopold, Ronald L. Frank

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Protein 3D structure prediction has always been an important research area in bioinformatics. In particular, the prediction of secondary structure has been a well-studied research topic. Despite the recent breakthrough of combining multiple sequence alignment information and artificial intelligence algorithms to predict protein secondary structure, the Q3 accuracy of various computational prediction algorithms rarely has exceeded 75%. In a previous paper [1], this research team presented a rule-based method called RT-RICO (Relaxed Threshold Rule Induction from Coverings) to predict protein secondary structure. The average Q3 accuracy on the sample datasets using RT-RICO was 80.3%, an improvement over comparable computational methods. Although this demonstrated that RT-RICO might be a promising approach for predicting secondary structure, the algorithm-s computational complexity and program running time limited its use. Herein a parallelized implementation of a slightly modified RT-RICO approach is presented. This new version of the algorithm facilitated the testing of a much larger dataset of 396 protein domains [2]. Parallelized RTRICO achieved a Q3 score of 74.6%, which is higher than the consensus prediction accuracy of 72.9% that was achieved for the same test dataset by a combination of four secondary structure prediction methods [2].

Keywords: data mining, protein secondary structure prediction, parallelization.

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Authors: A. S. Lourens, B. Du Plooy

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Across the world, initiatives have been introduced to encourage women to enter into and remain in engineering fields. However, research has shown that many women leave engineering or suffer a loss of self-esteem and self-confidence compared to their male counterparts. To address this problem, a South African comprehensive university developed a self-leadership intervention pilot study in 2013, aimed at improving the self-efficacy of its female engineering students and increasing retention rates. This paper is a qualitative, descriptive, and interpretive study of the rationale and operational aspects of the Women in Engineering Leadership Association’s (WELA) self-leadership workshop. The objectives of this paper are to provide a framework for the design of a self-leadership workshop and to provide insight into the process of developing such a workshop specifically for women engineering students at a South African university. Finally, the paper proposes an evaluation process for the pilot workshop, which also provides a framework to improve future workshops. It is anticipated that the self-leadership development framework will be applicable to other higher education institutions wishing to improve women engineering student’s feelings of self-efficacy and therefore retention rates of women in engineering.

Keywords: Co-curricular interventions, Self-efficacy, Self-leadership, Women in Engineering.

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Authors: Javid Iqbal, Zhu Shifan

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The development in the construction of unconventional ships and the implementation of lightweight materials have shown a large impulse towards finite element (FE) method, making it a general tool for ship design. This paper briefly presents the modeling and analysis techniques of ship structures using FE method for complex boundary conditions which are difficult to analyze by existing Ship Classification Societies rules. During operation, all ships experience complex loading conditions. These loads are general categories into thermal loads, linear static, dynamic and non-linear loads. General strength of the ship structure is analyzed using static FE analysis. FE method is also suitable to consider the local loads generated by ballast tanks and cargo in addition to hydrostatic and hydrodynamic loads. Vibration analysis of a ship structure and its components can be performed using FE method which helps in obtaining the dynamic stability of the ship. FE method has developed better techniques for calculation of natural frequencies and different mode shapes of ship structure to avoid resonance both globally and locally. There is a lot of development towards the ideal design in ship industry over the past few years for solving complex engineering problems by employing the data stored in the FE model. This paper provides an overview of ship modeling methodology for FE analysis and its general application. Historical background, the basic concept of FE, advantages, and disadvantages of FE analysis are also reported along with examples related to hull strength and structural components.

Keywords: Dynamic analysis, finite element methods, ship structure, vibration analysis.

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Authors: Eric P. Jiang

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As the Internet continues to grow at a rapid pace as the primary medium for communications and commerce and as telecommunication networks and systems continue to expand their global reach, digital information has become the most popular and important information resource and our dependence upon the underlying cyber infrastructure has been increasing significantly. Unfortunately, as our dependency has grown, so has the threat to the cyber infrastructure from spammers, attackers and criminal enterprises. In this paper, we propose a new machine learning based network intrusion detection framework for cyber security. The detection process of the framework consists of two stages: model construction and intrusion detection. In the model construction stage, a semi-supervised machine learning algorithm is applied to a collected set of network audit data to generate a profile of normal network behavior and in the intrusion detection stage, input network events are analyzed and compared with the patterns gathered in the profile, and some of them are then flagged as anomalies should these events are sufficiently far from the expected normal behavior. The proposed framework is particularly applicable to the situations where there is only a small amount of labeled network training data available, which is very typical in real world network environments.

Keywords: classification, data analysis and mining, network intrusion detection, semi-supervised learning.

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Authors: Sarisa Pechpoothong

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The research is to minimize environmental damage pertinent to maritime activities about the operation of lighter boat anchorage and its tugboat. The guidance on upgrading current harbor service and infrastructure has been provided to Kho Sichang Municpality. This will involve a study of the maritime logistics of the water area under jurisdiction of the Sichang island Municipality and possible recommendations may involve charging taxes, regulations and fees. With implementing these recommendations will help in protection of the marine environment and in increasing operator functionality. Additionally, our recommendation is to generate a consistent revenue stream to the municipality. The action items contained in this research are feasible and effective, the success of these initiatives are heavily dependent upon successful promotion and enforcement. Promoting new rules and regulations effectively and peacefully can be done through theories and techniques used in the psychology of persuasion. In order to assure compliance with the regulations, the municipality must maintain stringent patrols and fines for violators. In order to become success, the Municipality must preserve a consistent, transparent and significant enforcement system. Considering potential opportunities outside of the current state of the municipality, the authors recommend that Koh Sichang be given additional jurisdiction to capture value from the master vessels, as well as to confront the more significant environmental challenges these vessels pose. Finally, the authors recommend that the Port of Koh Sichang Island obtain a free port status in order to increase economic viability and overall sustainability.

Keywords: Harbor, Garbage Collection Service, Environment, Off-shore port.

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Authors: Cheon Sik Min, Hyeong Wook Song, Sook Yeon Shim, Hoon Chang

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The purpose of this study was to analyze the correlation between permitted building areas and housing distribution ratios and their fluctuation, and test a distribution model during 3 successive governments in 5 cities including Bucheon in reference to the time series administrative data, and thereby, interpret the results of the analysis in association with the policies pursued by the successive governments to examine the structural fluctuation of permitted building areas and housing distribution ratios. In order to analyze the fluctuation of permitted building areas and housing distribution ratios during 3 successive governments and examine the cycles of the time series data, the spectral analysis was performed, and in order to analyze the correlation between permitted building areas and housing distribution ratios, the tabulation was performed to describe the correlations statistically, and in order to explain about differences of fluctuation distribution of permitted building areas and housing distribution ratios among 3 governments, the goodness of fit test was conducted.

Keywords: The Permitted Building Areas, Housing Distribution Ratios, the Structural Fluctuation.

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Authors: Marina Velikova, Hennie Daniels, Ad Feelders

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In many data mining applications, it is a priori known that the target function should satisfy certain constraints imposed by, for example, economic theory or a human-decision maker. In this paper we consider partially monotone prediction problems, where the target variable depends monotonically on some of the input variables but not on all. We propose a novel method to construct prediction models, where monotone dependences with respect to some of the input variables are preserved by virtue of construction. Our method belongs to the class of mixture models. The basic idea is to convolute monotone neural networks with weight (kernel) functions to make predictions. By using simulation and real case studies, we demonstrate the application of our method. To obtain sound assessment for the performance of our approach, we use standard neural networks with weight decay and partially monotone linear models as benchmark methods for comparison. The results show that our approach outperforms partially monotone linear models in terms of accuracy. Furthermore, the incorporation of partial monotonicity constraints not only leads to models that are in accordance with the decision maker's expertise, but also reduces considerably the model variance in comparison to standard neural networks with weight decay.

Keywords: mixture models, monotone neural networks, partially monotone models, partially monotone problems.

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Authors: William Xiu Shun Wong, Myungsu Lim, Yoonjin Hyun, Chen Liu, Seongi Choi, Dasom Kim, Kee-Young Kwahk, Namgyu Kim

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Recently, many users have begun to frequently share their opinions on diverse issues using various social media. Therefore, numerous governments have attempted to establish or improve national policies according to the public opinions captured from various social media. In this paper, we indicate several limitations of the traditional approaches to analyze public opinion on science and technology and provide an alternative methodology to overcome these limitations. First, we distinguish between the science and technology analysis phase and the social issue analysis phase to reflect the fact that public opinion can be formed only when a certain science and technology is applied to a specific social issue. Next, we successively apply a start list and a stop list to acquire clarified and interesting results. Finally, to identify the most appropriate documents that fit with a given subject, we develop a new logical filter concept that consists of not only mere keywords but also a logical relationship among the keywords. This study then analyzes the possibilities for the practical use of the proposed methodology thorough its application to discover core issues and public opinions from 1,700,886 documents comprising SNS, blogs, news, and discussions.

Keywords: Big data, social network analysis, text mining, topic modeling.

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Authors: Yu-Lin Liao, Ya-Fu Peng

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An adaptive dynamic cerebellar model articulation controller (DCMAC) neural network used for solving the prediction and identification problem is proposed in this paper. The proposed DCMAC has superior capability to the conventional cerebellar model articulation controller (CMAC) neural network in efficient learning mechanism, guaranteed system stability and dynamic response. The recurrent network is embedded in the DCMAC by adding feedback connections in the association memory space so that the DCMAC captures the dynamic response, where the feedback units act as memory elements. The dynamic gradient descent method is adopted to adjust DCMAC parameters on-line. Moreover, the analytical method based on a Lyapunov function is proposed to determine the learning-rates of DCMAC so that the variable optimal learning-rates are derived to achieve most rapid convergence of identifying error. Finally, the adaptive DCMAC is applied in two computer simulations. Simulation results show that accurate identifying response and superior dynamic performance can be obtained because of the powerful on-line learning capability of the proposed DCMAC.

Keywords: adaptive, cerebellar model articulation controller, CMAC, prediction, identification

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Authors: Zhanna Mingaleva, Irina Mirskikh

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Part IV of the Civil Code of the Russian Federation dedicated to legal regulation of Intellectual property rights came into force in 2008. It is a first attempt of codification in Intellectual property sphere in Russia. That is why a lot of new norms appeared. The main problem of the Russian Civil Code (part IV) is that many rules (norms of Law) contradict the norms of International Intellectual property Law (i.e. protection of inventions, creations, ideas, know-how, trade secrets, innovations). Intellectual property rights protect innovations and creations and reward innovative and creative activity. Intellectual property rights are international in character and in that respect they fit in rather well with the economic reality of the global economy. Inventors prefer not to take out a patent for inventions because it is a very difficult procedure, it takes a lot of time and is very expensive. That-s why they try to protect their inventions as ideas, know-how, confidential information. An idea is the main element of any object of Intellectual property (creation, invention, innovation, know-how, etc.). But ideas are not protected by Civil Code of Russian Federation. The aim of the paper is to reveal the main problems of legal regulation of Intellectual property in Russia and to suggest possible solutions. The authors of this paper have raised these essential issues through different activities. Through the panel survey, questionnaires which were spread among the participants of intellectual activities the main problems of implementation of innovations, protecting of the ideas and know-how were identified. The implementation of research results will help to solve economic and legal problems of innovations, transfer of innovations and intellectual property.1

Keywords: Innovation activities, intellectual property rights, know-how, patents, indicators of innovation activities

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Authors: A. Jamekhorshid, G. Karimi, I. Noshadi, A. Jahangiri

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Non-uniform current distribution in polymer electrolyte membrane fuel cells results in local over-heating, accelerated ageing, and lower power output than expected. This issue is very critical when fuel cell experiences water flooding. In this work, the performance of a PEM fuel cell is investigated under cathode flooding conditions. Two-dimensional partially flooded GDL models based on the conservation laws and electrochemical relations are proposed to study local current density distributions along flow fields over a wide range of cell operating conditions. The model results show a direct association between cathode inlet humidity increases and that of average current density but the system becomes more sensitive to flooding. The anode inlet relative humidity shows a similar effect. Operating the cell at higher temperatures would lead to higher average current densities and the chance of system being flooded is reduced. In addition, higher cathode stoichiometries prevent system flooding but the average current density remains almost constant. The higher anode stoichiometry leads to higher average current density and higher sensitivity to cathode flooding.

Keywords: Current distribution, Flooding, Hydrogen energysystem, PEM fuel cell.

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Authors: Awad A. Younis, Elise Stronberg, Shifa Noor

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Users’ susceptibility to malware attacks have been noticed in the past few years. Investigating the factors that make a user vulnerable to those attacks is critical because they can be utilized to set up proactive strategies such as awareness and education to mitigate the impacts of those attacks. Demographic, behavioral, and cultural vulnerabilities are the main factors that make users susceptible to malware attacks. It is challenging, however, to draw more general conclusions based on those factors due to the varieties in the type of users and different types of malware. Therefore, we conducted a systematic literature review (SLR) of the existing research for user susceptibility factors to malware attacks. The results showed that all demographic factors are consistently associated with malware infection regardless of the users' type except for age and gender. Besides, the association of culture and personality factors with malware infection is consistent in most of the selected studies and for all types of users. Moreover, malware infection varies based on age, geographic location, and host types. We propose that future studies should carefully take into consideration the type of users because different users may be exposed to different threats or targeted based on their user domains’ characteristics. Additionally, as different types of malware use different tactics to trick users, taking the malware types into consideration is important.

Keywords: cybersecurity, malware, users, demographics, personality, culture, systematic literature review

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Authors: Dyah E. Herwindiati

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A clustering is process to identify a homogeneous groups of object called as cluster. Clustering is one interesting topic on data mining. A group or class behaves similarly characteristics. This paper discusses a robust clustering process for data images with two reduction dimension approaches; i.e. the two dimensional principal component analysis (2DPCA) and principal component analysis (PCA). A standard approach to overcome this problem is dimension reduction, which transforms a high-dimensional data into a lower-dimensional space with limited loss of information. One of the most common forms of dimensionality reduction is the principal components analysis (PCA). The 2DPCA is often called a variant of principal component (PCA), the image matrices were directly treated as 2D matrices; they do not need to be transformed into a vector so that the covariance matrix of image can be constructed directly using the original image matrices. The decomposed classical covariance matrix is very sensitive to outlying observations. The objective of paper is to compare the performance of robust minimizing vector variance (MVV) in the two dimensional projection PCA (2DPCA) and the PCA for clustering on an arbitrary data image when outliers are hiden in the data set. The simulation aspects of robustness and the illustration of clustering images are discussed in the end of paper

Keywords: Breakdown point, Consistency, 2DPCA, PCA, Outlier, Vector Variance

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Authors: Vakhtang Geladze, Nana Bolashvili, Tamazi Karalashvili, Nino Machavariani, Vajha Neidze, Nana Kvirkvelia, Tamar Chichinadze

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Deficiency of fresh water is a vital global problem today. It must be taken into consideration that in the nearest future fresh water crisis will become even more acute owing to the global climate warming and fast desertification processes in the world. Georgia has signed the association agreement with Euro Union last year where the priority spheres of cooperation are the management of water resources, development of trans-boundary approach to the problem and active participation in the “Euro Union water initiative” component of “the East Europe, Caucasus and the Central Asia”. Fresh water resources are the main natural wealth of Georgia. According to the average water layer height, Georgia is behind such European countries only as Norway, Switzerland and Austria. The annual average water provision of Georgia is 4-8 times higher than in its neighbor countries Armenia and Azerbaijan. Despite abundant water resources in Georgia, there is considerable discrepancy between their volume and use in some regions because of the uneven territorial distribution. In the East Georgia, water supply of the territory and population is four times less than in the West Georgia.

Keywords: GIS, sociological survey, water consumption, water resources.

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Authors: Radim Cajka, Pavlina Mateckova, Martina Janulikova, Marie Stara

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Use of a sliding joint is an effective method to decrease the stress in foundation structure where there is a horizontal deformation of subsoil (areas afflicted with underground mining) or horizontal deformation of a foundation structure (pre-stressed foundations, creep, shrinkage, temperature deformation). A convenient material for a sliding joint is a bitumen asphalt belt. Experiments for different types of bitumen belts were undertaken at the Faculty of Civil Engineering - VSB Technical University of Ostrava in 2008. This year an extension of the 2008 experiments is in progress and the shear resistance of a slide joint is being tested as a function of temperature in a temperature controlled room. In this paper experimental results of temperature dependant shear resistance are presented. The result of the experiments should be the sliding joint shear resistance as a function of deformation velocity and temperature. This relationship is used for numerical analysis of stress/strain relation between foundation structure and subsoil. Using a rheological slide joint could lead to a decrease of the reinforcement amount, and contribute to higher reliability of foundation structure and thus enable design of more durable and sustainable building structures.

Keywords: Pre-stressed foundations, sliding joint, soil-structure interaction, subsoil horizontal deformation.

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Authors: Ju-Young Kim, Tae-Heon Moon, Jung-Hun Cho

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Urban regeneration projects have been actively promoted in Korea. In particular, Jeonju Hanok Village is evaluated as one of representative cases in terms of utilizing local cultural heritage sits in the urban regeneration project. However, recently, there has been a growing concern in this area, due to the ‘gentrification’, caused by the excessive commercialization and surging tourists. This trend was changing land and building use and resulted in the loss of identity of the region. In this regard, this study analyzed the land use transformation between 2010 and 2016 to identify the commercialization trend in Jeonju Hanok Village. In addition, it conducted SNS big data analysis on Jeonju Hanok Village from February 14th, 2016 to March 31st, 2016 to identify visitors’ awareness of the village. The study results demonstrate that rapid commercialization was underway, unlikely the initial intention, so that planners and officials in city government should reconsider the project direction and rebuild deliberate management strategies. This study is meaningful in that it analyzed the land use transformation and SNS big data to identify the current situation in urban regeneration area. Furthermore, it is expected that the study results will contribute to the vitalization of regeneration area.

Keywords: Land use, SNS, text mining, urban regeneration.

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Authors: Domenico Chizzoniti, Monica Moscatelli, Letizia Cattani, Luca Preis

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A primary healthcare facility in developing countries should be a multifunctional space able to respond to different requirements: Flexibility, modularity, aggregation and reversibility. These basic features could be better satisfied if applied to an architectural artifact that complies with the typological, figurative and constructive aspects of the context in which it is located. Therefore, the purpose of this paper is to identify a procedure that can define the figurative aspects of the architectural structure of the health prototype for the marginal areas of developing countries through a critical approach. The application context is the rural areas of the Northeast of Bahia in Brazil. The prototype should be located in the rural district of Quingoma, in the municipality of Lauro de Freitas, a particular place where there is still a cultural fusion of black and indigenous populations. Based on the historical analysis of settlement strategies and architectural structures in spaces of public interest or collective use, this paper aims to provide a procedure able to identify the categories and rules underlying typological and figurative aspects, in order to detect significant and generalizable elements, as well as materials and constructive techniques typically adopted in the rural areas of Brazil. The object of this work is therefore not only the recovery of certain constructive approaches but also the development of a procedure that integrates the requirements of the primary healthcare prototype with its surrounding economic, social, cultural, settlement and figurative conditions.

Keywords: Architectural typology, Developing countries, Local construction techniques, Primary health care.

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Authors: Niousha Bagheri Khulenjani, Mohammad Saniee Abadeh

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Learning from very big datasets is a significant problem for most present data mining and machine learning algorithms. MicroRNA (miRNA) is one of the important big genomic and non-coding datasets presenting the genome sequences. In this paper, a hybrid method for the classification of the miRNA data is proposed. Due to the variety of cancers and high number of genes, analyzing the miRNA dataset has been a challenging problem for researchers. The number of features corresponding to the number of samples is high and the data suffer from being imbalanced. The feature selection method has been used to select features having more ability to distinguish classes and eliminating obscures features. Afterward, a Convolutional Neural Network (CNN) classifier for classification of cancer types is utilized, which employs a Genetic Algorithm to highlight optimized hyper-parameters of CNN. In order to make the process of classification by CNN faster, Graphics Processing Unit (GPU) is recommended for calculating the mathematic equation in a parallel way. The proposed method is tested on a real-world dataset with 8,129 patients, 29 different types of tumors, and 1,046 miRNA biomarkers, taken from The Cancer Genome Atlas (TCGA) database.

Keywords: Cancer classification, feature selection, deep learning, genetic algorithm.

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Authors: Ghada Badr, Arwa Alturki

Abstract:

The biological function of an RNA molecule depends on its structure. The objective of the alignment is finding the homology between two or more RNA secondary structures. Knowing the common functionalities between two RNA structures allows a better understanding and a discovery of other relationships between them. Besides, identifying non-coding RNAs -that is not translated into a protein- is a popular application in which RNA structural alignment is the first step A few methods for RNA structure-to-structure alignment have been developed. Most of these methods are partial structure-to-structure, sequence-to-structure, or structure-to-sequence alignment. Less attention is given in the literature to the use of efficient RNA structure representation and the structure-to-structure alignment methods are lacking. In this paper, we introduce an O(N2) Component-based Pairwise RNA Structure Alignment (CompPSA) algorithm, where structures are given as a component-based representation and where N is the maximum number of components in the two structures. The proposed algorithm compares the two RNA secondary structures based on their weighted component features rather than on their base-pair details. Extensive experiments are conducted illustrating the efficiency of the CompPSA algorithm when compared to other approaches and on different real and simulated datasets. The CompPSA algorithm shows an accurate similarity measure between components. The algorithm gives the flexibility for the user to align the two RNA structures based on their weighted features (position, full length, and/or stem length). Moreover, the algorithm proves scalability and efficiency in time and memory performance.

Keywords: Alignment, RNA secondary structure, pairwise, component-based, data mining.

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Authors: Isaac O. Asante, Yushi Jiang, Hailin Tao

Abstract:

Livestreaming marketing, the new electronic commerce element, has become an optional marketing channel following the COVID-19 pandemic, and many sellers are leveraging the features presented by livestreaming to increase sales. This study was conducted to measure real-time observable interactions between consumers and sellers. Based on the affordance theory, this study conceptualized constructs representing the interactive features and examined how they drive consumers’ purchase willingness during livestreaming sessions using 1238 datasets from Amazon Live, following the manual observation of transaction records. Using structural equation modeling, the ordinary least square regression suggests that live viewers, new followers, live chats, and likes positively affect purchase willingness. The Sobel and Monte Carlo tests show that new followers, live chats, and likes significantly mediate the relationship between live viewers and purchase willingness. The study presents a way of measuring interactions in livestreaming commerce and proposes a way to manually gather data on consumer behaviors in livestreaming platforms when the application programming interface (API) of such platforms does not support data mining algorithms.

Keywords: Livestreaming marketing, live chats, live viewers, likes, new followers, purchase willingness.

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Authors: I. M. Sujaul, M. A. Sobahan, A. A. Edriyana, F. M. Yahaya, R. M. Yunus

Abstract:

This study was carried out to investigate the adverse effect of industrial wastewater on surface water quality in Gebeng industrial estate, Pahang, Malaysia. Surface water was collected from six sampling stations. Physicochemical parameters were characterized based on in-situ and ex-situ analysis according to standard methods by American Public Health Association (APHA). Selected heavy metals were determined by using Inductively Coupled Plasma Mass Spectrometry (ICP MS). The results revealed that the concentration of heavy metals such as Pb, Cu, Cd, Cr and Hg were high in samples. The results also showed that the value of Pb and Hg were higher in the wet season in comparison to dry season. According to Malaysia National Water Quality Standard (NWQS) and Water Quality Index (WQI) all the sampling station were categorized as class IV (highly polluted). The present study revealed that the adverse effects of careless disposal of wastes and directly discharge of effluents affected on surface water quality. Therefore, the authorities should implement the laws to ensure the proper practices of wastewater management for environmental sustainability around the study area.

Keywords: Gebeng, heavy metals, waste water, water quality index.

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Authors: Golnaz Rezai, Zainalabidin Mohamed, Mad Nasir Shamsudin

Abstract:

The Malaysian government is promoting entrepreneurship development skills amongst farmers through informal courses. These courses will concentrate on teaching managerial skills as inevitable means for small farms to succeed by making farmers more creative and innovative. Therefore it is important to assess the effect of informal agri-entrepreneurial training in developing entrepreneurship among the farmers in Malaysia. Seven hundred and ninety six farmers (796) farmers were interviewed via structured questionnaire to define their opinion on whether the current informal educational and training establishments are sufficient to teach and develop entrepreneurial skills. Factor analysis and logic regression analysis were used to determine the motivating factors and predict their impact on the development of entrepreneurial skills. The result from the factor analysis led us to investigate the association between these factors and farmers- opinions about the development of entrepreneurial skills and traits through participating in informal entrepreneurship training or education. The outcome has shown us that the importance of informal training to promote entrepreneurship among farmers is crucial. The training should be intensified to encourage farmers to not only focus on the modern technologies but also on the fundamental changes in their attitude towards agriculture as a business. DOA: KMO: Kaiser- Meyer- Olkin Test MOA: Ministry of Agriculture NMP: Ninth Malaysia Plan NAP: Third National Agricultural Policy (2000-2010)

Keywords: Entrepreneurial skills, farmers, informal education, Malaysia

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Authors: Tang Mui Joo, Chan Eang Teng

Abstract:

The use of social media has become more defined. It has been widely used for the purpose of business. More marketers are now using social media as tools to enhance their businesses. Whereas on the other hand, there are more and more people spending their time through mobile apps to be engaged in the social media sites like YouTube, Facebook, Twitter and others. Social media has even become common in Public Relations (PR). It has become number one platform for creating and sharing content. In view to this, social media has changed the rules in PR where it brings new challenges and opportunities to the profession. Although corporate websites, chat-rooms, email customer response facilities and electronic news release distribution are now viewed as standard aspects of PR practice, many PR practitioners are still struggling with the impact of new media though the implementation of social media is potentially reducing the cost of communication. It is to the point that PR practitioners are not fully embracing new media, they are ill-equipped to do so and they have a fear of the technology. Somehow that social media has become a new style of communication that is characterized by conversation and community. It has become a platform that allows individuals to interact with one another and build relationship among each other. Therefore, in the use of business world, consumers are able to interact with those companies that have joined any social media. Based on their experiences with social networking site interactions, they are also exposed to personal interaction while communicating. This paper is to study the impact of social media to PR. This paper discovers the potential changes of PR practices in a developing country like Malaysia. Eventually the study reflects on how PR practitioners are actually using social media in the country. This paper is based on two theories in its development of this research foundation. Media Ecology Theory is to support the impact and changes to PR. Social Penetration Theory is to reflect on how the use of social media is among PRs. This research is using survey with PR practitioners in its data collection. The results have shown that PR professionals value social media more than they actually use it and the way of organizations communicate had been changed due to the transformation of social media.

Keywords: New media, social media, PR.

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