Search results for: content based image retrieval system

Authors: R. AliMohammadzadeh, M. Haghir Chehreghani, A. Zarnani, M. Rahgozar

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Mining frequent tree patterns have many useful applications in XML mining, bioinformatics, network routing, etc. Most of the frequent subtree mining algorithms (i.e. FREQT, TreeMiner and CMTreeMiner) use anti-monotone property in the phase of candidate subtree generation. However, none of these algorithms have verified the correctness of this property in tree structured data. In this research it is shown that anti-monotonicity does not generally hold, when using weighed support in tree pattern discovery. As a result, tree mining algorithms that are based on this property would probably miss some of the valid frequent subtree patterns in a collection of trees. In this paper, we investigate the correctness of anti-monotone property for the problem of weighted frequent subtree mining. In addition we propose W3-Miner, a new algorithm for full extraction of frequent subtrees. The experimental results confirm that W3-Miner finds some frequent subtrees that the previously proposed algorithms are not able to discover.

Keywords: Semi-Structured Data Mining, Anti-Monotone Property, Trees.

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Authors: Vongsathorn Ngampuak, Yutachai Chookaew, Wipawee Dejtisakdi

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Dunaliella salina has great potential as a system for generating commercially valuable products, including beta-carotene, pharmaceuticals, and biofuels. Our goal is to improve this potential by enhancing growth rate and other properties of D. salina under optimal growth conditions. We used ethyl methane sulfonate (EMS) to generate random mutants in D. salina KU11, a strain classified in Thailand. In a preliminary experiment, we first treated D. salina cells with 0%, 0.8%, 1.0%, 1.2%, 1.44% and 1.66% EMS to generate a killing curve. After that, we randomly picked 30 candidates from approximately 300 isolated survivor colonies from the 1.44% EMS treatment (which permitted 30% survival) as an initial test of the mutant screen. Among the 30 survivor lines, we found that 2 strains (mutant #17 and #24) had significantly improved growth rates and cell number accumulation at stationary phase approximately up to 1.8 and 1.45 fold, respectively, 2 strains (mutant #6 and #23) had significantly decreased growth rates and cell number accumulation at stationary phase approximately down to 1.4 and 1.35 fold, respectively, while 26 of 30 lines had similar growth rates compared with the wild type control. We also analyzed cell size for each strain and found there was no significant difference comparing all mutants with the wild type. In addition, mutant #24 had shown an increase of biomass accumulation approximately 1.65 fold compared with the wild type strain on day 5 that was entering early stationary phase. From these preliminary results, it could be feasible to identify D. salina mutants with significant improved growth rate, cell accumulation and biomass production compared to the wild type for the further study; this makes it possible to improve this microorganism as a platform for biotechnology application.

Keywords: Dunaliella salina, mutant, ethyl methane sulfonate, growth rate, biomass.

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Authors: Omar Alshehri, Vic Lally

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This paper examined the attitudes of using social media tools to support learning at a university in Saudi Arabia. Moreover, it investigated the students’ current usage of these tools and examined the barriers they could face during the use of social media tools in the education process. Participants in this study were 42 university students. A web-based survey was used to collect data for this study. The results indicate that all of the students were familiar with social media and had used at least one type of social media for learning. It was found out that all students had very positive attitudes towards the use of social media and welcomed using these tools as a supplementary to the curriculum. However, the results indicated that the major barriers to using these tools in learning were distraction, opposing Islamic religious teachings, privacy issues, and cyberbullying. The study recommended that this study could be replicated at other Saudi universities to investigate factors and barriers that might affect Saudi students’ attitudes toward using social media to support learning.

Keywords: Saudi Arabia, social media, benefits of social media use, barriers to social media use, higher education.

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Authors: Jong Ho Hwang, Dae Hwan Kang, Young-IL Jeong

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Since hyaluronic acid (HA) receptor such as CD44 is over-expressed at sites of cancer cells, HA can be used as a targeting vehicles for anti-cancer drugs. The aim of this study is to synthesize block copolymer composed of hyaluronic acid and poly(ε-caprolactone) (HAPCL) and to fabricate polymeric micelles for anticancer drug targeting against CD44 receptor of tumor cells. Chemical composition of HAPCL was confirmed using 1H NMR spectroscopy. Doxorubicin (DOX) was incorporated into polymeric micelles of HAPCL. The diameters of HAPHS polymeric micelles were changed around 80nm and have spherical shapes. Targeting potential was investigated using CD44-overexpressing. When DOX-incorporated polymeric micelles was added to KB cells, they revealed strong red fluorescence color while blocking of CD44 receptor by pretreatment of free HA resulted in reduced intensity, indicating that HAPCL polymeric micelles have targetability against CD44 receptor.

Keywords: Hyaluronic acid, CD44 receptor, biorecognizable nanoparticles, block copolymer.

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Authors: Jalil Z., Farooq M., Zafar H., Sabir M., Ashraf E.

Abstract:

Internet is largely composed of textual contents and a huge volume of digital contents gets floated over the Internet daily. The ease of information sharing and re-production has made it difficult to preserve author-s copyright. Digital watermarking came up as a solution for copyright protection of plain text problem after 1993. In this paper, we propose a zero text watermarking algorithm based on occurrence frequency of non-vowel ASCII characters and words for copyright protection of plain text. The embedding algorithm makes use of frequency non-vowel ASCII characters and words to generate a specialized author key. The extraction algorithm uses this key to extract watermark, hence identify the original copyright owner. Experimental results illustrate the effectiveness of the proposed algorithm on text encountering meaning preserving attacks performed by five independent attackers.

Keywords: Copyright protection, Digital watermarking, Document authentication, Information security, Watermark.

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Authors: Karin Hansson, Göran Cars, Mats Danielson, Love Ekenberg, Aron Larsson

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Within the realm of e-government, the development has moved towards testing new means for democratic decisionmaking, like e-panels, electronic discussion forums, and polls. Although such new developments seem promising, they are not problem-free, and the outcomes are seldom used in the subsequent formal political procedures. Nevertheless, process models offer promising potential when it comes to structuring and supporting transparency of decision processes in order to facilitate the integration of the public into decision-making procedures in a reasonable and manageable way. Based on real-life cases of urban planning processes in Sweden, we present an outline for an integrated framework for public decision making to: a) provide tools for citizens to organize discussion and create opinions; b) enable governments, authorities, and institutions to better analyse these opinions; and c) enable governments to account for this information in planning and societal decision making by employing a process model for structured public decision making.

Keywords: Negotiation games, Agenda setting, Multi-criteria decision analysis, Elicitation method.

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Authors: A. M. R. Mosalman Yazdi, B. A. R. Mosalman Yazdi

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In industry, on of the most important subjects is die and it's characteristics in which for cutting and forming different mechanical pieces, various punch and matrix metal die are used. whereas the common parts which form the main frame die are not often proportion with pieces and dies therefore using a part as socalled common part for frames in specified dimension ranges can decrease the time of designing, occupied space of warehouse and manufacturing costs. Parts in dies with getting uniform in their shape and dimension make common parts of dies. Common parts of punch and matrix metal die are as bolster, guide bush, guide pillar and shank. In this paper the common parts and effective parameters in selecting each of them as the primary information are studied, afterward for selection and design of mechanical parts an introduction and investigation based on the Mech. Desk. software is done hence with developing this software can standardize the metal common parts of punch and matrix. These studies will be so useful for designer in their designing and also using it has with very much advantage for manufactures of products in decreasing occupied spaces by dies.

Keywords: Die, Matrix, Punch, Standardize.

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Authors: Armando Cartenì, Ilaria Henke

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The perceived public transport quality is an important driver that influences both customer satisfaction and mobility choices. The competition among transport operators needs to improve the quality of the services and identify which attributes are perceived as relevant by passengers. Among the “traditional” public transport quality attributes there are, for example: travel and waiting time, regularity of the services, and ticket price. By contrast, there are some “non-conventional” attributes that could significantly influence customer satisfaction jointly with the “traditional” ones. Among these, the beauty/aesthetics of the transport terminals (e.g. rail station and bus terminal) is probably one of the most impacting on user perception. Starting from these considerations, the point stressed in this paper was if (and how munch) the travel experience of the overall travel (e.g. how long is the travel, how many transport modes must be used) influences the perception of the public transport quality. The aim of this paper was to investigate the weight of the terminal quality (e.g. aesthetic, comfort and service offered) within the overall travel experience. The case study was the extra-urban Italian bus network. The passengers of the major Italian terminal bus were interviewed and the analysis of the results shows that about the 75% of the travelers, are available to pay up to 30% more for the ticket price for having a high quality terminal. A travel experience effect was observed: the average perceived transport quality varies with the characteristic of the overall trip. The passengers that have a “long trip” (travel time greater than 2 hours) perceived as “low” the overall quality of the trip even if they pass through a high quality terminal. The opposite occurs for the “short trip” passengers. This means that if a traveler passes through a high quality station, the overall perception of that terminal could be significantly reduced if he is tired from a long trip. This result is important and if confirmed through other case studies, will allow to conclude that the “travel experience impact" must be considered as an explicit design variable for public transport services and planning.

Keywords: Transportation planning, sustainable mobility, decision support system, discrete choice model, design problem.

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Authors: Ekachai Phaisangittisagul, Rapeepol Chongprachawat

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Obtaining labeled data in supervised learning is often difficult and expensive, and thus the trained learning algorithm tends to be overfitting due to small number of training data. As a result, some researchers have focused on using unlabeled data which may not necessary to follow the same generative distribution as the labeled data to construct a high-level feature for improving performance on supervised learning tasks. In this paper, we investigate the impact of the relationship between unlabeled and labeled data for classification performance. Specifically, we will apply difference unlabeled data which have different degrees of relation to the labeled data for handwritten digit classification task based on MNIST dataset. Our experimental results show that the higher the degree of relation between unlabeled and labeled data, the better the classification performance. Although the unlabeled data that is completely from different generative distribution to the labeled data provides the lowest classification performance, we still achieve high classification performance. This leads to expanding the applicability of the supervised learning algorithms using unsupervised learning.

Keywords: Autoencoder, high-level feature, MNIST dataset, selftaught learning, supervised learning.

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Authors: Mohammad Irfan

Abstract:

The purpose of this paper is to investigate the relationship among the key macroeconomic variables and Islamic stock market in India. This study is based on the time series data of financial years 2009-2015 to explore the consistency of relationship between macroeconomic variables and Shariah Indices. The ADF (Augmented Dickey–Fuller Test Statistic) and PP (Phillips–Perron Test Statistic) tests are employed to check stationarity of the data. The study depicts the long run relationship between Shariah indices and macroeconomic variables by using the Johansen Co-integration test. BSE Shariah and Nifty Shariah have uni-direct Granger causality. The outcome of VECM is significantly confirming the applicability of best fitted model. Thus, Islamic stock indices are proficiently working for the development of Indian economy. It suggests that by keeping eyes on Islamic stock market which will be more interactive in the future with other macroeconomic variables.

Keywords: Indian shariah indices, macroeconomic variables, co-integration, Granger causality, Vector error correction model.

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Authors: Ritsuko Kawasaki (Aiba), Takeshi Hiromatsu

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Management is required to understand all information security risks within an organization, and to make decisions on which information security risks should be treated in what level by allocating how much amount of cost. However, such decision-making is not usually easy, because various measures for risk treatment must be selected with the suitable application levels. In addition, some measures may have objectives conflicting with each other. It also makes the selection difficult. Moreover, risks generally have trends and it also should be considered in risk treatment. Therefore, this paper provides the extension of the model proposed in the previous study. The original model supports the selection of measures by applying a combination of weighted average method and goal programming method for multi-objective analysis to find an optimal solution. The extended model includes the notion of weights to the risks, and the larger weight means the priority of the risk.

Keywords: Information security risk treatment, Selection of risk measures, Risk acceptanceand Multi-objective optimization.

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Authors: Chanin Yoopetch, Natcha Toemtemsab

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The purpose of this study was to explore the demographic differences of international tourists according to three main factors, including the value of time, shopping behavior and shopping motivation. The Chatuchak Weekend Market is known as one of the biggest weekend markets in the world. Too little academic studies had been conducted in this area of weekend market, despite its growth and continuous development. In general, both domestic visitors and international tourists are attracted to the perception of cheap and bargaining prices the weekend market. However, systematic research study can provide reliable understanding of the perception of the visitors. This study focused on the group of international tourists who visited the market and aimed to provide better insights based on the differences in their demographic factors. Findings indicated that several differences in value of time, shopping behavior, and shopping motivation were identified by gender, income and age. Research implications and directions for further studies were discussed.

Keywords: Value of Time, Shopping Behavior, Shopping Motivation, Chatuchak Weekend Market.

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Authors: A. Rabin, G. Mazor, I. Ladizhenski, R. Z. Shneck

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The hardness and hardenability of AISI D2 cold work tool steel with conventional quenching (CQ), deep cryogenic quenching (DCQ) and rapid deep cryogenic quenching heat treatments caused by temporary porous coating based on magnesium sulfate was investigated. Each of the cooling processes was examined from the perspective of the full process efficiency, heat flux in the austenite-martensite transformation range followed by characterization of the temporary porous layer made of magnesium sulfate using confocal laser scanning microscopy (CLSM), surface and core hardness and hardenability using Vickers hardness technique. The results show that the cooling rate (CR) at the austenite-martensite transformation range has a high influence on the hardness of the studied steel.

Keywords: AISI D2, controllable cooling, magnesium sulfate coating, rapid cryogenic heat treatment, temporary porous layer.

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Authors: Semanur Soyyiğit Kaya, Ercan Eren

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Energy has a prominent role for development of nations. Countries which have energy resources also have strategic power in the international trade of energy since it is essential for all stages of production in the economy. Thus, it is important for countries to analyze the weaknesses and strength of the system. On the other side, international trade is one of the fields that are analyzed as a complex network via network analysis. Complex network is one of the tools to analyze complex systems with heterogeneous agents and interaction between them. A complex network consists of nodes and the interactions between these nodes. Total properties which emerge as a result of these interactions are distinct from the sum of small parts (more or less) in complex systems. Thus, standard approaches to international trade are superficial to analyze these systems. Network analysis provides a new approach to analyze international trade as a network. In this network, countries constitute nodes and trade relations (export or import) constitute edges. It becomes possible to analyze international trade network in terms of high degree indicators which are specific to complex networks such as connectivity, clustering, assortativity/disassortativity, centrality, etc. In this analysis, international trade of crude oil and coal which are types of fossil fuel has been analyzed from 2005 to 2014 via network analysis. First, it has been analyzed in terms of some topological parameters such as density, transitivity, clustering etc. Afterwards, fitness to Pareto distribution has been analyzed via Kolmogorov-Smirnov test. Finally, weighted HITS algorithm has been applied to the data as a centrality measure to determine the real prominence of countries in these trade networks. Weighted HITS algorithm is a strong tool to analyze the network by ranking countries with regards to prominence of their trade partners. We have calculated both an export centrality and an import centrality by applying w-HITS algorithm to the data. As a result, impacts of the trading countries have been presented in terms of high-degree indicators.

Keywords: Complex network approach, fossil fuel, international trade, network theory.

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Authors: Konstantin Movsovic, Emanuele Stomeo, Tatiana Kalganova

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The evolutionary design of electronic circuits, or evolvable hardware, is a discipline that allows the user to automatically obtain the desired circuit design. The circuit configuration is under the control of evolutionary algorithms. Several researchers have used evolvable hardware to design electrical circuits. Every time that one particular algorithm is selected to carry out the evolution, it is necessary that all its parameters, such as mutation rate, population size, selection mechanisms etc. are tuned in order to achieve the best results during the evolution process. This paper investigates the abilities of evolution strategy to evolve digital logic circuits based on programmable logic array structures when different mutation rates are used. Several mutation rates (fixed and variable) are analyzed and compared with each other to outline the most appropriate choice to be used during the evolution of combinational logic circuits. The experimental results outlined in this paper are important as they could be used by every researcher who might need to use the evolutionary algorithm to design digital logic circuits.

Keywords: Evolvable hardware, evolutionary algorithm, digitallogic circuit, mutation rate.

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Authors: Nur Atiqah Rochin Demong, Jie Lu, Farookh Khadeer Hussain

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Property investment in the real estate industry has a high risk due to the uncertainty factors that will affect the decisions made and high cost. Analytic hierarchy process has existed for some time in which referred to an expert-s opinion to measure the uncertainty of the risk factors for the risk analysis. Therefore, different level of experts- experiences will create different opinion and lead to the conflict among the experts in the field. The objective of this paper is to propose a new technique to measure the uncertainty of the risk factors based on multidimensional data model and data mining techniques as deterministic approach. The propose technique consist of a basic framework which includes four modules: user, technology, end-user access tools and applications. The property investment risk analysis defines as a micro level analysis as the features of the property will be considered in the analysis in this paper.

Keywords: Uncertainty factors, data mining, multidimensional data model, risk analysis.

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Authors: K. Soya, N. Mihara, D. Kuchar, M. Kubota, H. Matsuda, T. Fukuta

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The present work is concerned with sulfidation of Cu, Zn and Ni containing plating wastewater with CaS. The sulfidation experiments were carried out at a room temperature by adding solid CaS to simulated metal solution containing either single-metal of Ni, Zn and Cu, or Ni-Zn-Cu mixture. At first, the experiments were conducted without pH adjustment and it was found that the complete sulfidation of Zn and Ni was achieved at an equimolar ratio of CaS to a particular metal. However, in the case of Cu, a complete copper sulfidation was achieved at CaS to Cu molar ratio of about 2. In the case of the selective sulfidation, a simulated plating solution containing Cu, Zn and Ni at the concentration of 100 mg/dm3 was treated with CaS under various pH conditions. As a result, selective precipitation of metal sulfides was achieved by a sulfidation treatment at different pH values. Further, the precipitation agents of NaOH, Na2S and CaS were compared in terms of the average specific filtration resistance and compressibility coefficients of metal sulfide slurry. Consequently, based on the lowest filtration parameters of the produced metal sulfides, it was concluded that CaS was the most effective precipitation agent for separation and recovery of Cu, Zn and Ni.

Keywords: Calcium sulfide, Plating Wastewater, Filtrationcharacteristics, Heavy metals, Sulfidation.

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Authors: Amit Gil, Helman Stern, Yael Edan

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A cognitive collaborative reinforcement learning algorithm (CCRL) that incorporates an advisor into the learning process is developed to improve supervised learning. An autonomous learner is enabled with a self awareness cognitive skill to decide when to solicit instructions from the advisor. The learner can also assess the value of advice, and accept or reject it. The method is evaluated for robotic motion planning using simulation. Tests are conducted for advisors with skill levels from expert to novice. The CCRL algorithm and a combined method integrating its logic with Clouse-s Introspection Approach, outperformed a base-line fully autonomous learner, and demonstrated robust performance when dealing with various advisor skill levels, learning to accept advice received from an expert, while rejecting that of less skilled collaborators. Although the CCRL algorithm is based on RL, it fits other machine learning methods, since advisor-s actions are only added to the outer layer.

Keywords: Robot learning, human-robot collaboration, motion planning, reinforcement learning.

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Authors: Alicia Y. C. Tang, Rukaini Abdullah, Sharifuddin M. Zain, Noorsaadah A. Rahman

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This paper discusses the causal explanation capability of QRIOM, a tool aimed at supporting learning of organic chemistry reactions. The development of the tool is based on the hybrid use of Qualitative Reasoning (QR) technique and Qualitative Process Theory (QPT) ontology. Our simulation combines symbolic, qualitative description of relations with quantity analysis to generate causal graphs. The pedagogy embedded in the simulator is to both simulate and explain organic reactions. Qualitative reasoning through a causal chain will be presented to explain the overall changes made on the substrate; from initial substrate until the production of final outputs. Several uses of the QPT modeling constructs in supporting behavioral and causal explanation during run-time will also be demonstrated. Explaining organic reactions through causal graph trace can help improve the reasoning ability of learners in that their conceptual understanding of the subject is nurtured.

Keywords: Qualitative reasoning, causal graph, organicreactions, explanation, QPT, modeling constructs.

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Authors: Lai Yi-Hsiu

Abstract:

The present paper aims to examine the language processing of Chinese-speaking seniors with Alzheimer’s disease (AD) from the perspective of temporal cues. Twenty healthy adults, 17 healthy seniors, and 13 seniors with AD in Taiwan participated in this study to tell stories based on two sets of pictures. Nine temporal cues were fetched and analyzed. Oral productions in Mandarin Chinese were compared and discussed to examine to what extent and in what way these three groups of participants performed with significant differences. Results indicated that the age effects were significant in filled pauses. The dementia effects were significant in mean duration of pauses, empty pauses, filled pauses, lexical pauses, normalized mean duration of filled pauses and lexical pauses. The findings reported in the current paper help characterize the nature of language processing in seniors with or without AD, and contribute to the interactions between the AD neural mechanism and their temporal parameters.

Keywords: Language processing, Alzheimer’s disease, Mandarin Chinese, temporal cues.

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Authors: Adrian O’Hagan, Robert McLoughlin

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Considerable focus in the world of insurance risk quantification is placed on modeling loss values from lines of business (LOBs) that possess upper tail dependence. Copulas such as the Joe, Gumbel and Student-t copula may be used for this purpose. The copula structure imparts a desired level of tail dependence on the joint distribution of claims from the different LOBs. Alternatively, practitioners may possess historical or simulated data that already exhibit upper tail dependence, through the impact of catastrophe events such as hurricanes or earthquakes. In these circumstances, it is not desirable to induce additional upper tail dependence when modeling the joint distribution of the loss values from the individual LOBs. Instead, it is of interest to accurately assess the degree of tail dependence already present in the data. The empirical copula and its associated upper tail dependence coefficient are presented in this paper as robust, efficient means of achieving this goal.

Keywords: Empirical copula, extreme events, insurance loss reserving, upper tail dependence coefficient.

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Authors: Ming-Hsiung Wu, Yu-Hsi Yuan

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The aim of the research is to understand whether the accuracy of customer detection of employee emotional labor strategy would influence the overall service satisfaction. From path analysis, it was found that employee-s positive emotions positively influenced service quality. Service quality in turn influenced Customer detection of employee emotional deep action strategy and Customer detection of employee emotional surface action strategy. Lastly, Customer detection of employee emotional deep action strategy and Customer detection of employee emotional surface action strategy positively influenced service satisfaction. Based on the analysis results, suggestions are proposed to provide reference for human resource management and use in relative fields.

Keywords: Emotional labor, Emotional deep action strategy, Emotional surface action strategy, Service satisfaction

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Authors: Do-Hwan Kim, Roberto Leon

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Probabilistic characteristics of seismic responses of the Partially Restrained connection rotation (PRCR) and panel zone deformation (PZD) installed in older steel moment frames were investigated in accordance with statistical inference in decision-making process. The 4, 6 and 8 story older steel moment frames with clip angle and T-stub connections were designed and analyzed using 2%/50yrs ground motions in four cities of the Mid-America earthquake region. The probability density function and cumulative distribution function of PRCR and PZD were determined by the goodness-of-fit tests based on probabilistic parameters measured from the results of the nonlinear time-history analyses. The obtained probabilistic parameters and distributions can be used to find out what performance level mainly PR connections and panel zones satisfy and how many PR connections and panel zones experience a serious damage under the Mid-America ground motions.

Keywords: Mid-America earthquake, Panel zone, PR connection, Probabilistic characteristics, seismic performance

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Authors: Hyun-Woo Cho

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The early diagnostic decision making in industrial processes is absolutely necessary to produce high quality final products. It helps to provide early warning for a special event in a process, and finding its assignable cause can be obtained. This work presents a hybrid diagnostic schmes for batch processes. Nonlinear representation of raw process data is combined with classification tree techniques. The nonlinear kernel-based dimension reduction is executed for nonlinear classification decision boundaries for fault classes. In order to enhance diagnosis performance for batch processes, filtering of the data is performed to get rid of the irrelevant information of the process data. For the diagnosis performance of several representation, filtering, and future observation estimation methods, four diagnostic schemes are evaluated. In this work, the performance of the presented diagnosis schemes is demonstrated using batch process data.

Keywords: Diagnostics, batch process, nonlinear representation, data filtering, multivariate statistical approach

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Authors: Ronit Chakraborty, Sugata Banerji

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There has been a marked increase in the reported prevalence of Autism Spectrum Disorder (ASD) among children in the US over the past two decades. This research has analyzed the growth in state-level ASD prevalence against 45 different potentially explanatory factors including socio-economic, demographic, healthcare, public policy and political factors. The goal was to understand if these factors have adequate predictive power in modeling the differential growth in ASD prevalence across various states, and, if they do, which factors are the most influential. The key findings of this study include (1) there is a confirmation that the chosen feature set has considerable power in predicting the growth in ASD prevalence, (2) the most influential predictive factors are identified, (3) given the nature of the most influential predictive variables, an indication that a considerable portion of the reported ASD prevalence differentials across states could be attributable to over and under diagnosis, and (4) Florida is identified as a key outlier state pointing to a potential under-diagnosis of ASD.

Keywords: Autism Spectrum Disorder, ASD, clustering, Machine Learning, predictive modeling.

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Authors: Bachir Chemani, Halima Chemani

Abstract:

This paper studies the application of a variety of sawdust materials in the production of lightweight insulating bricks. First, the mineralogical and chemical composition of clays was determined. Next, ceramic bricks were fabricated with different quantities of materials (3–6 and 9 wt. % for sawdust, 65 wt. % for grey clay, 24–27 and 30 wt. % for yellow clay and 2 wt% of tuff). These bricks were fired at 800 and 950 °C. The effect of adding this sawdust on the technological behaviour of the brick was assessed by drying and firing shrinkage, water absorption, porosity, bulk density and compressive strength. The results have shown that the optimum sintering temperature is 950 °C. Below this temperature, at 950 °C, increased open porosity was observed, which decreased the compressive strength of the bricks. Based on the results obtained, the optimum amounts of waste were 9 wt. % sawdust of eucalyptus, 24 wt. % shaping moisture and 1.6 particle size diameter. These percentages produced bricks whose mechanical properties were suitable for use as secondary raw materials in ceramic brick production.

Keywords: Clay brick, Porosity, Sawdust.

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Authors: S. Hosseini, M. Ahmadi Najafabadi, M. Akhlaghi

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The health of the journal bearings is very important in preventing unforeseen breakdowns in rotary machines, and poor lubrication is one of the most important factors for producing the bearing failures. Hydrodynamic lubrication (HL), mixed lubrication (ML), and boundary lubrication (BL) are three regimes of a journal bearing lubrication. This paper uses acoustic emission (AE) measurement technique to correlate features of the AE signals to the three lubrication regimes. The transitions from HL to ML based on operating factors such as rotating speed, load, inlet oil pressure by time domain and time-frequency domain signal analysis techniques are detected, and then metal-to-metal contacts between sliding surfaces of the journal and bearing are identified. It is found that there is a significant difference between theoretical and experimental operating values that are obtained for defining the lubrication regions.

Keywords: Acoustic emission technique, pressure fed journal bearing, time and frequency signal analysis, metal-to-metal contact.

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Authors: Chartree Sithananun, Teekayu Limchamroon, Tanawat Limwathanagura, Thanyarat Singhanart

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The objective of this paper is to present the development of the frame of Chulalongkorn University team in TSAE Auto Challenge Student Formula and Student Formula SAE Competition of Japan. Chulalongkorn University's SAE team, has established since year 2003, joined many competitions since year 2006 and became the leading team in Thailand. Through these 5 years, space frame was the most selected and developed year by year through six frame designs. In this paper, the discussions on the conceptual design of these frames are introduced, focusing on the mass and torsional stiffness improvement. The torsional stiffness test was performed on the real used frames and the results are compared. It can be seen that the 2010-2011 frame is firstly designed based on the analysis and experiment that considered the required mass and torsional stiffness. From the torsional stiffness results, it can be concluded that the frames were developed including the decreasing of mass and the increasing torsional stiffness by applying many techniques.

Keywords: SAE Student Formula, Space Frame, Torsional Stiffness

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Authors: Wen Liu

Abstract:

With the rapid progress of modern cities, the railway construction must be developing quickly in China.As a typical high-density country, shopping center on the subway should be one important factor during the process of urban development. The paper discusses the influence of the layout of shopping center on the subway, and put it in the time and space’s axis of Shanghai urban development. We usethe digital technology to establish the database of relevant information. And then get the change role about shopping center on subway in Shanghaiby the Kernel density estimate.The result shows the development of shopping center on subway has a relationship with local economic strength, population size, policysupport, and city construction. And the suburbanization trend of shopping center would be increasingly significant.By this case research, we could see the Kernel density estimate is an efficient analysis method on the spatial layout. It could reveal the characters of layout form of shopping center on subway in essence. And it can also be applied to the other research of space form.

Keywords: Shanghai, Shopping center on the subway, Layout form, The Kernel density estimate.

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Authors: Çiğdem Bakır, Mecit Yüzkat

Abstract:

With the increasing emphasis on water quality worldwide, the search for and expanding the market for new and intelligent monitoring systems has increased. The current method is the laboratory process, where samples are taken from bodies of water, and tests are carried out in laboratories. This method is time-consuming, a waste of manpower and uneconomical. To solve this problem, we used machine learning methods to detect water pollution in our study. We created decision trees with the Orange3 software used in the study and tried to determine all the factors that cause water pollution. An automatic prediction model based on water quality was developed by taking many model inputs such as water temperature, pH, transparency, conductivity, dissolved oxygen, and ammonia nitrogen with machine learning methods. The proposed approach consists of three stages: Preprocessing of the data used, feature detection and classification. We tried to determine the success of our study with different accuracy metrics and the results were presented comparatively. In addition, we achieved approximately 98% success with the decision tree.

Keywords: Decision tree, water quality, water pollution, machine learning.

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