Search results for: Serial Analysis of Gene Expression
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 8980

Search results for: Serial Analysis of Gene Expression

8560 A Survey of the Applications of Sentiment Analysis

Authors: Pingping Lin, Xudong Luo

Abstract:

Natural language often conveys emotions of speakers. Therefore, sentiment analysis on what people say is prevalent in the field of natural language process and has great application value in many practical problems. Thus, to help people understand its application value, in this paper, we survey various applications of sentiment analysis, including the ones in online business and offline business as well as other types of its applications. In particular, we give some application examples in intelligent customer service systems in China. Besides, we compare the applications of sentiment analysis on Twitter, Weibo, Taobao and Facebook, and discuss some challenges. Finally, we point out the challenges faced in the applications of sentiment analysis and the work that is worth being studied in the future.

Keywords: Natural language processing, sentiment analysis, application, online comments.

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8559 Fine-Grained Sentiment Analysis: Recent Progress

Authors: Jie Liu, Xudong Luo, Pingping Lin, Yifan Fan

Abstract:

Facebook, Twitter, Weibo, and other social media and significant e-commerce sites generate a massive amount of online texts, which can be used to analyse people’s opinions or sentiments for better decision-making. So, sentiment analysis, especially the fine-grained sentiment analysis, is a very active research topic. In this paper, we survey various methods for fine-grained sentiment analysis, including traditional sentiment lexicon-based methods, ma-chine learning-based methods, and deep learning-based methods in aspect/target/attribute-based sentiment analysis tasks. Besides, we discuss their advantages and problems worthy of careful studies in the future.

Keywords: sentiment analysis, fine-grained, machine learning, deep learning

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8558 Marangoni Convection in a Fluid Layer with Internal Heat Generation

Authors: Norfifah Bachok, Norihan Md. Arifin

Abstract:

In this paper we use classical linear stability theory to investigate the effects of uniform internal heat generation on the onset of Marangoni convection in a horizontal layer of fluid heated from below. We use a analytical technique to obtain the close form analytical expression for the onset of Marangoni convection when the lower boundary is conducting with free-slip condition. We show that the effect of increasing the internal heat generation is always to destabilize the layer.

Keywords: Marangoni convection, heat generation, free-slip

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8557 A Survey of Sentiment Analysis Based on Deep Learning

Authors: Pingping Lin, Xudong Luo, Yifan Fan

Abstract:

Sentiment analysis is a very active research topic. Every day, Facebook, Twitter, Weibo, and other social media, as well as significant e-commerce websites, generate a massive amount of comments, which can be used to analyse peoples opinions or emotions. The existing methods for sentiment analysis are based mainly on sentiment dictionaries, machine learning, and deep learning. The first two kinds of methods rely on heavily sentiment dictionaries or large amounts of labelled data. The third one overcomes these two problems. So, in this paper, we focus on the third one. Specifically, we survey various sentiment analysis methods based on convolutional neural network, recurrent neural network, long short-term memory, deep neural network, deep belief network, and memory network. We compare their futures, advantages, and disadvantages. Also, we point out the main problems of these methods, which may be worthy of careful studies in the future. Finally, we also examine the application of deep learning in multimodal sentiment analysis and aspect-level sentiment analysis.

Keywords: Natural language processing, sentiment analysis, document analysis, multimodal sentiment analysis, deep learning.

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8556 Observations about the Principal Components Analysis and Data Clustering Techniques in the Study of Medical Data

Authors: Cristina G. Dascâlu, Corina Dima Cozma, Elena Carmen Cotrutz

Abstract:

The medical data statistical analysis often requires the using of some special techniques, because of the particularities of these data. The principal components analysis and the data clustering are two statistical methods for data mining very useful in the medical field, the first one as a method to decrease the number of studied parameters, and the second one as a method to analyze the connections between diagnosis and the data about the patient-s condition. In this paper we investigate the implications obtained from a specific data analysis technique: the data clustering preceded by a selection of the most relevant parameters, made using the principal components analysis. Our assumption was that, using the principal components analysis before data clustering - in order to select and to classify only the most relevant parameters – the accuracy of clustering is improved, but the practical results showed the opposite fact: the clustering accuracy decreases, with a percentage approximately equal with the percentage of information loss reported by the principal components analysis.

Keywords: Data clustering, medical data, principal components analysis.

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8555 One-Class Support Vector Machine for Sentiment Analysis of Movie Review Documents

Authors: Chothmal, Basant Agarwal

Abstract:

Sentiment analysis means to classify a given review document into positive or negative polar document. Sentiment analysis research has been increased tremendously in recent times due to its large number of applications in the industry and academia. Sentiment analysis models can be used to determine the opinion of the user towards any entity or product. E-commerce companies can use sentiment analysis model to improve their products on the basis of users’ opinion. In this paper, we propose a new One-class Support Vector Machine (One-class SVM) based sentiment analysis model for movie review documents. In the proposed approach, we initially extract features from one class of documents, and further test the given documents with the one-class SVM model if a given new test document lies in the model or it is an outlier. Experimental results show the effectiveness of the proposed sentiment analysis model.

Keywords: Feature selection methods, Machine learning, NB, One-class SVM, Sentiment Analysis, Support Vector Machine.

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8554 Constraint Based Frequent Pattern Mining Technique for Solving GCS Problem

Authors: First G.M. Karthik, Second Ramachandra.V.Pujeri, Dr.

Abstract:

Generalized Center String (GCS) problem are generalized from Common Approximate Substring problem and Common substring problems. GCS are known to be NP-hard allowing the problems lies in the explosion of potential candidates. Finding longest center string without concerning the sequence that may not contain any motifs is not known in advance in any particular biological gene process. GCS solved by frequent pattern-mining techniques and known to be fixed parameter tractable based on the fixed input sequence length and symbol set size. Efficient method known as Bpriori algorithms can solve GCS with reasonable time/space complexities. Bpriori 2 and Bpriori 3-2 algorithm are been proposed of any length and any positions of all their instances in input sequences. In this paper, we reduced the time/space complexity of Bpriori algorithm by Constrained Based Frequent Pattern mining (CBFP) technique which integrates the idea of Constraint Based Mining and FP-tree mining. CBFP mining technique solves the GCS problem works for all center string of any length, but also for the positions of all their mutated copies of input sequence. CBFP mining technique construct TRIE like with FP tree to represent the mutated copies of center string of any length, along with constraints to restraint growth of the consensus tree. The complexity analysis for Constrained Based FP mining technique and Bpriori algorithm is done based on the worst case and average case approach. Algorithm's correctness compared with the Bpriori algorithm using artificial data is shown.

Keywords: Constraint Based Mining, FP tree, Data mining, GCS problem, CBFP mining technique.

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8553 Nitrification Efficiency and Community Structure of Municipal Activated Sewage Sludge

Authors: Oluyemi O. Awolusi, Abimbola M. Enitan, Sheena Kumari, Faizal Bux

Abstract:

Nitrification is essential to biological processes designed to remove ammonia and/or total nitrogen. It removes excess nitrogenous compound in wastewater which could be very toxic to the aquatic fauna or cause serious imbalance of such aquatic ecosystem. Efficient nitrification is linked to an in-depth knowledge of the structure and dynamics of the nitrifying community structure within the wastewater treatment systems. In this study, molecular technique was employed for characterizing the microbial structure of activated sludge [ammonia oxidizing bacteria (AOB) and nitrite oxidizing bacteria (NOB)] in a municipal wastewater treatment with intention of linking it to the plant efficiency. PCR based phylogenetic analysis was also carried out. The average operating and environmental parameters as well as specific nitrification rate of plant was investigated during the study. During the investigation the average temperature was 23±1.5oC. Other operational parameters such as mixed liquor suspended solids and chemical oxygen demand inversely correlated with ammonia removal. The dissolved oxygen level in the plant was constantly lower than the optimum (between 0.24 and 1.267 mg/l) during this study. The plant was treating wastewater with influent ammonia concentration of 31.69 and 24.47 mg/L. The influent flow rates (ML/Day) was 96.81 during period. The dominant nitrifiers include: Nitrosomonas spp. Nitrobacter spp. and Nitrospira spp. The AOB had correlation with nitrification efficiency and temperature. This study shows that the specific ammonia oxidizing rate and the specific nitrate formation rates can serve as good indicator of the plant overall nitrification performance.

Keywords: Ammonia monooxygenase α-subunit (amoA) gene, ammonia-oxidizing bacteria (AOB), nitrite-oxidizing bacteria (NOB), specific nitrification rate, PCR.

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8552 Estimating Enzyme Kinetic Parameters from Apparent KMs and Vmaxs

Authors: Simon Brown, Noorzaid Muhamad, David C Simcock

Abstract:

The kinetic properties of enzymes are often reported using the apparent KM and Vmax appropriate to the standard Michaelis-Menten enzyme. However, this model is inappropriate to enzymes that have more than one substrate or where the rate expression does not apply for other reasons. Consequently, it is desirable to have a means of estimating the appropriate kinetic parameters from the apparent values of KM and Vmax reported for each substrate. We provide a means of estimating the range within which the parameters should lie and apply the method to data for glutamate dehydrogenase from the nematode parasite of sheep Teladorsagia circumcincta.

Keywords: enzyme kinetics, glutamate dehydrogenase, intervalanalysis, parameter estimation.

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8551 Burden Sharing in Combating Terrorist Financing

Authors: M. Bogers, R. Beeres

Abstract:

This paper contributes to the literature concerning burden sharing. We provide a quantitative expression of the burden sharing behaviour of 174 states in the case of combating terrorist financing and address specific burden sharing issues in this context (i.e., weakest link; no substitutability). We conclude that advanced states have shown more effort to control terrorist financing than developing states. In this particular case, there is an incentive for advanced states to support developing states. Failing to do so will make the total financial system worse off.

Keywords: Burden sharing, combating terrorist financing, weakest link.

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8550 Reading and Teaching Poetry as Communicative Discourse: A Pragma-Linguistic Approach

Authors: Omnia Elkommos

Abstract:

Language is communication on several discourse levels. The target of teaching a language and the literature of a foreign language is to communicate a message. Reading, appreciating, analysing, and interpreting poetry as a sophisticated rhetorical expression of human thoughts, emotions, and philosophical messages is more feasible through the use of linguistic pragmatic tools from a communicative discourse perspective. The poet's intention, speech act, illocutionary act, and perlocutionary goal can be better understood when communicative situational context as well as linguistic discourse structure theories are employed. The use of linguistic theories in the teaching of poetry is, therefore, intrinsic to students' comprehension, interpretation, and appreciation of poetry of the different ages. It is the purpose of this study to show how both teachers as well as students can apply these linguistic theories and tools to dramatic poetic texts for an engaging, enlightening, and effective interpretation and appreciation of the language. Theories drawn from areas of pragmatics, discourse analysis, embedded discourse level, communicative situational context, and other linguistic approaches were applied to selected poetry texts from the different centuries. Further, in a simple statistical count of the number of poems with dialogic dramatic discourse with embedded two or three levels of discourse in different anthologies outweighs the number of descriptive poems with a one level of discourse, between the poet and the reader. Poetry is thus discourse on one, two, or three levels. It is, therefore, recommended that teachers and students in the area of ESL/EFL use the linguistics theories for a better understanding of poetry as communicative discourse. The practice of applying these linguistic theories in classrooms and in research will allow them to perceive the language and its linguistic, social, and cultural aspect. Texts will become live illocutionary acts with a perlocutionary acts goal rather than mere literary texts in anthologies.

Keywords: Coda, commissives, communicative situation, context of culture, context of reference, context of utterance, dialogue, directives, discourse analysis, dramatic discourse interaction, duologue, embedded discourse levels, language for communication, linguistic structures, literary texts, poetry, pragmatic theories, reader response, speech acts (macro/micro), stylistics, teaching literature, TEFL, terms of address, turn-taking.

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8549 Towards an Extended SQLf: Bipolar Query Language with Preferences

Authors: L. Ludovic, R. Daniel, S-E Tbahriti

Abstract:

Database management systems that integrate user preferences promise better solution for personalization, greater flexibility and higher quality of query responses. This paper presents a tentative work that studies and investigates approaches to express user preferences in queries. We sketch an extend capabilities of SQLf language that uses the fuzzy set theory in order to define the user preferences. For that, two essential points are considered: the first concerns the expression of user preferences in SQLf by so-called fuzzy commensurable predicates set. The second concerns the bipolar way in which these user preferences are expressed on mandatory and/or optional preferences.

Keywords: Flexible query language, relational database, userpreference.

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8548 Removal of Basic Blue 3 from Aqueous Solution by Adsorption Onto Durio Ziberthinus

Authors: Siew-Teng

Abstract:

Durian husk (DH), a fruit waste, was studied for its ability to remove Basic blue 3 (BB3) from aqueous solutions. Batch kinetic studies were carried out to study the sorption characteristics under various experimental conditions. The optimum pH for the dye removal occurred in the pH range of 3-10. Sorption was found to be concentration and agitation dependent. The kinetics of dye sorption fitted a pseudo-second order rate expression. Both Langmuir and Freundlich models appeared to provide reasonable fittings for the sorption data of BB3 on durian husk. Maximum sorption capacity calculated from the Langmuir model is 49.50 mg g-1.

Keywords: Durian husk, Batch study, Sorption, Basic Blue 3

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8547 Detection of Tetracycline Resistance Genes in Lactococcus garvieae Strains Isolated from Rainbow Trout

Authors: M. Raissy, M. Shahrani

Abstract:

The present study was done to evaluate the presence of tetracycline resistance genes in Lactococcus garvieae isolated from cultured rainbow trout, West Iran. The isolates were examined for antimicrobial resistance using disc diffusion method. Of the 49 strains tested, 19 were resistant to tetracycline (38.7%), 32 to enrofloxacin (65.3%), 21 to erythromycin (42.8%), 20 to chloramphenicol and trimetoprim-sulfamethoxazole (40.8%). The strains were then characterized for their genotypic resistance profiles. The results revealed that all 49 isolates contained at least one of the tetracycline resistance genes. Tet (A) was found in 89.4% of tetracycline resistant isolates and the frequency of other gene were as follows: tet (E) 42.1%, tet (B) 47.3%, tet (D) 15.7%, tet (L) 26.3%, tet (K) 52.6%, tet (G) 36.8%, tet (34) 21%, tet (S) 63.1%, tet (C) 57.8%, tet (M) 73.6%, tet (O) 42.1%. The results revealed high levels of antibiotic resistance in L. garvieae strains which is a potential danger for trout culture as well as for public health.

Keywords: Lactococcus garvieae, rainbow trout, tetracycline resistance genes.

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8546 Sensitivity Analysis in Power Systems Reliability Evaluation

Authors: A.R Alesaadi, M. Nafar, A.H. Gheisari

Abstract:

In this paper sensitivity analysis is performed for reliability evaluation of power systems. When examining the reliability of a system, it is useful to recognize how results change as component parameters are varied. This knowledge helps engineers to understand the impact of poor data, and gives insight on how reliability can be improved. For these reasons, a sensitivity analysis can be performed. Finally, a real network was used for testing the presented method.

Keywords: sensitivity analysis, reliability evaluation, powersystems.

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8545 Prediction of MicroRNA-Target Gene by Machine Learning Algorithms in Lung Cancer Study

Authors: Nilubon Kurubanjerdjit, Nattakarn Iam-On, Ka-Lok Ng

Abstract:

MicroRNAs are small non-coding RNA found in many different species. They play crucial roles in cancer such as biological processes of apoptosis and proliferation. The identification of microRNA-target genes can be an essential first step towards to reveal the role of microRNA in various cancer types. In this paper, we predict miRNA-target genes for lung cancer by integrating prediction scores from miRanda and PITA algorithms used as a feature vector of miRNA-target interaction. Then, machine-learning algorithms were implemented for making a final prediction. The approach developed in this study should be of value for future studies into understanding the role of miRNAs in molecular mechanisms enabling lung cancer formation.

Keywords: MicroRNA, miRNAs, lung cancer, machine learning, Naïve Bayes, SVM.

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8544 Access Policy Specification for SCADA Networks

Authors: Rodrigo Chandia, Mauricio Papa

Abstract:

Efforts to secure supervisory control and data acquisition (SCADA) systems must be supported under the guidance of sound security policies and mechanisms to enforce them. Critical elements of the policy must be systematically translated into a format that can be used by policy enforcement components. Ideally, the goal is to ensure that the enforced policy is a close reflection of the specified policy. However, security controls commonly used to enforce policies in the IT environment were not designed to satisfy the specific needs of the SCADA environment. This paper presents a language, based on the well-known XACML framework, for the expression of authorization policies for SCADA systems.

Keywords: Access policy specification, process control systems, network security.

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8543 Feature Subset Selection approach based on Maximizing Margin of Support Vector Classifier

Authors: Khin May Win, Nan Sai Moon Kham

Abstract:

Identification of cancer genes that might anticipate the clinical behaviors from different types of cancer disease is challenging due to the huge number of genes and small number of patients samples. The new method is being proposed based on supervised learning of classification like support vector machines (SVMs).A new solution is described by the introduction of the Maximized Margin (MM) in the subset criterion, which permits to get near the least generalization error rate. In class prediction problem, gene selection is essential to improve the accuracy and to identify genes for cancer disease. The performance of the new method was evaluated with real-world data experiment. It can give the better accuracy for classification.

Keywords: Microarray data, feature selection, recursive featureelimination, support vector machines.

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8542 Fuzzy Optimization in Metabolic Systems

Authors: Feng-Sheng Wang, Wu-Hsiung Wu, Kai-Cheng Hsu

Abstract:

The optimization of biological systems, which is a branch of metabolic engineering, has generated a lot of industrial and academic interest for a long time. In the last decade, metabolic engineering approaches based on mathematical optimizations have been used extensively for the analysis and manipulation of metabolic networks. In practical optimization of metabolic reaction networks, designers have to manage the nature of uncertainty resulting from qualitative characters of metabolic reactions, e.g., the possibility of enzyme effects. A deterministic approach does not give an adequate representation for metabolic reaction networks with uncertain characters. Fuzzy optimization formulations can be applied to cope with this problem. A fuzzy multi-objective optimization problem can be introduced for finding the optimal engineering interventions on metabolic network systems considering the resilience phenomenon and cell viability constraints. The accuracy of optimization results depends heavily on the development of essential kinetic models of metabolic networks. Kinetic models can quantitatively capture the experimentally observed regulation data of metabolic systems and are often used to find the optimal manipulation of external inputs. To address the issues of optimizing the regulatory structure of metabolic networks, it is necessary to consider qualitative effects, e.g., the resilience phenomena and cell viability constraints. Combining the qualitative and quantitative descriptions for metabolic networks makes it possible to design a viable strain and accurately predict the maximum possible flux rates of desired products. Considering the resilience phenomena in metabolic networks can improve the predictions of gene intervention and maximum synthesis rates in metabolic engineering. Two case studies will present in the conference to illustrate the phenomena.

Keywords: Fuzzy multi-objective optimization problem, kinetic model, metabolic engineering.

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8541 Data and Spatial Analysis for Economy and Education of 28 E.U. Member-States for 2014

Authors: Alexiou Dimitra, Fragkaki Maria

Abstract:

The objective of the paper is the study of geographic, economic and educational variables and their contribution to determine the position of each member-state among the EU-28 countries based on the values of seven variables as given by Eurostat. The Data Analysis methods of Multiple Factorial Correspondence Analysis (MFCA) Principal Component Analysis and Factor Analysis have been used. The cross tabulation tables of data consist of the values of seven variables for the 28 countries for 2014. The data are manipulated using the CHIC Analysis V 1.1 software package. The results of this program using MFCA and Ascending Hierarchical Classification are given in arithmetic and graphical form. For comparison reasons with the same data the Factor procedure of Statistical package IBM SPSS 20 has been used. The numerical and graphical results presented with tables and graphs, demonstrate the agreement between the two methods. The most important result is the study of the relation between the 28 countries and the position of each country in groups or clouds, which are formed according to the values of the corresponding variables.

Keywords: Multiple factorial correspondence analysis, principal component analysis, factor analysis, E.U.-28 countries, statistical package IBM SPSS 20, CHIC Analysis V 1.1 Software, Eurostat.eu statistics.

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8540 The Establishment of Probabilistic Risk Assessment Analysis Methodology for Dry Storage Concrete Casks Using SAPHIRE 8

Authors: J. R. Wang, W. Y. Cheng, J. S. Yeh, S. W. Chen, Y. M. Ferng, J. H. Yang, W. S. Hsu, C. Shih

Abstract:

To understand the risk for dry storage concrete casks in the cask loading, transfer, and storage phase, the purpose of this research is to establish the probabilistic risk assessment (PRA) analysis methodology for dry storage concrete casks by using SAPHIRE 8 code. This analysis methodology is used to perform the study of Taiwan nuclear power plants (NPPs) dry storage system. The process of research has three steps. First, the data of the concrete casks and Taiwan NPPs are collected. Second, the PRA analysis methodology is developed by using SAPHIRE 8. Third, the PRA analysis is performed by using this methodology. According to the analysis results, the maximum risk is the multipurpose canister (MPC) drop case.

Keywords: PRA, Dry storage, concrete cask, SAPHIRE.

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8539 Defect Modes in Multilayered Piezoelectric Structures

Authors: D. G. Piliposyan

Abstract:

Propagation of electro-elastic waves in a piezoelectric waveguide with finite stacks and a defect layer is studied using a modified transfer matrix method. The dispersion equation for a periodic structure consisting of unit cells made up from two piezoelectric materials with metallized interfaces is obtained. An analytical expression, for the transmission coefficient for a waveguide with finite stacks and a defect layer, that is found can be used to accurately detect and control the position of the passband within a stopband. The result can be instrumental in constructing a tunable waveguide made of layers of different or identical piezoelectric crystals and separated by metallized interfaces.

Keywords: Defect mode, Bloch waves, periodic phononic crystal, piezoelectric composite waveguide.

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8538 Research on the Predict Method of Random Vibration Cumulative Fatigue Damage Life Based on the Finite Element Analysis

Authors: Wang Chengcheng, Li Chuanri, Xu Fei, Guo Ying

Abstract:

Aiming at most of the aviation products are facing the problem of fatigue fracture in vibration environment, we makes use of the testing result of a bracket, analysis for the structure with ANSYS-Workbench, predict the life of the bracket by different ways, and compared with the testing result. With the research on analysis methods, make an organic combination of simulation analysis and testing, Not only ensure the accuracy of simulation analysis and life predict, but also make a dynamic supervision of product life process, promote the application of finite element simulation analysis in engineering practice.

Keywords: Random vibration, finite element simulation, fatigue, frequency domain.

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8537 Quantitative Analysis of PCA, ICA, LDA and SVM in Face Recognition

Authors: Liton Jude Rozario, Mohammad Reduanul Haque, Md. Ziarul Islam, Mohammad Shorif Uddin

Abstract:

Face recognition is a technique to automatically identify or verify individuals. It receives great attention in identification, authentication, security and many more applications. Diverse methods had been proposed for this purpose and also a lot of comparative studies were performed. However, researchers could not reach unified conclusion. In this paper, we are reporting an extensive quantitative accuracy analysis of four most widely used face recognition algorithms: Principal Component Analysis (PCA), Independent Component Analysis (ICA), Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM) using AT&T, Sheffield and Bangladeshi people face databases under diverse situations such as illumination, alignment and pose variations.

Keywords: PCA, ICA, LDA, SVM, face recognition, noise.

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8536 Generator of Hypotheses an Approach of Data Mining Based on Monotone Systems Theory

Authors: Rein Kuusik, Grete Lind

Abstract:

Generator of hypotheses is a new method for data mining. It makes possible to classify the source data automatically and produces a particular enumeration of patterns. Pattern is an expression (in a certain language) describing facts in a subset of facts. The goal is to describe the source data via patterns and/or IF...THEN rules. Used evaluation criteria are deterministic (not probabilistic). The search results are trees - form that is easy to comprehend and interpret. Generator of hypotheses uses very effective algorithm based on the theory of monotone systems (MS) named MONSA (MONotone System Algorithm).

Keywords: data mining, monotone systems, pattern, rule.

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8535 Containment/Penetration Analysis for the Protection of Aircraft Engine External Configuration and Nuclear Power Plant Structures

Authors: Dong Wook Lee, Adrian Mistreanu

Abstract:

The authors have studied a method for analyzing containment and penetration using an explicit nonlinear Finite Element Analysis. This method may be used in the stage of concept design for the protection of external configurations or components of aircraft engines and nuclear power plant structures. This paper consists of the modeling method, the results obtained from the method and the comparison of the results with those calculated from simple analytical method. It shows that the containment capability obtained by proposed method matches well with analytically calculated containment capability.

Keywords: Computer Aided Engineering, CAE, containment analysis, Finite Element Analysis, FEA, impact analysis, penetration analysis.

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8534 The Effects of Wood Ash on Ignition Point of Wood

Authors: Kenneth A. Ibe, Justina I. Mbonu, Godgift K. Umukoro

Abstract:

The effects of wood ash from five common tropical woods on the ignition point of four common tropical woods in Nigeria were investigated. The ash and moisture contents of the wood sawdust from Mahogany (Khaya ivorensis), Opepe (Sarcocephalus latifolius), Abura (Mitragyna ciliata), Rubber (Heavea brasilensis) and Poroporo (Sorghum bicolour) used, were determined using a furnace (Vecstar furnaces, model ECF2, serial no. f3077) and oven (Genlab laboratory oven, model MINO/040) respectively. The metal contents of the five wood sawdust ash samples were determined using a Perkin Elmer optima 3000 dv atomic absorption spectrometer while the ignition points were determined using Vecstar furnaces model ECF2. Poroporo had the highest ash content, 2.263g while rubber had the least, 0.710g. The results for the moisture content range from 2.971g to 0.903g. Magnesium metal had the highest concentration of all the metals, in all the wood ash samples; with mahogany ash having the highest concentration, 9.196ppm while rubber ash had the least concentration of magnesium metal, 2.196 ppm. The ignition point results showed that the wood ashes from mahogany and opepe increased the ignition points of the test wood samples, Danta (Nesogordonia papaverifera), Ekpaya, Akomu (Pycnanthus angolensis) and Oleku when coated on them while the ashes from poroporo, rubber and abura decreased the ignition points of the test wood samples when coated on them. However, Opepe saw dust ash decreased the ignition point in one of the test wood samples, suggesting that the metal content of the test wood sample was more than that of the Opepe saw dust ash. Therefore, Mahogany and Opepe saw dust ashes could be used in the surface treatment of wood to enhance their fire resistance or retardancy. However, the caution to be exercised in this application is that the metal content of the test wood samples should be evaluated as well.

Keywords: Ash, fire, ignition point, retardant, wood saw dust.

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8533 An Interview and PhotoVoice Exploration of Sexual Education Provision to Women with Physical Disability and Potential Experiences of Violence

Authors: D. Beckwith

Abstract:

This research explored sexual identity for women with physical disability, both congenital and acquired. It also explored whether exposure to violence or negative risk-taking had played a role in their intimate relationships. This phenomenological research used semi-structured interviews and photo elicitation with the researcher’s insider knowledge adding experiential substance and understanding to the discussion. Findings confirm sexuality for women with physical disability is marginalised and de-gendered making it less of a priority for professionals and policy makers and emphasising the need to more effectively support women with disability in relation to their sexuality, sexual expression and violence.

Keywords: Lived-experience, PhotoVoice, sexuality, violence.

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8532 Analysis of Aiming Performance for Games Using Mapping Method of Corneal Reflections Based on Two Different Light Sources

Authors: Yoshikazu Onuki, Itsuo Kumazawa

Abstract:

Fundamental motivation of this paper is how gaze estimation can be utilized effectively regarding an application to games. In games, precise estimation is not always important in aiming targets but an ability to move a cursor to an aiming target accurately is also significant. Incidentally, from a game producing point of view, a separate expression of a head movement and gaze movement sometimes becomes advantageous to expressing sense of presence. A case that panning a background image associated with a head movement and moving a cursor according to gaze movement can be a representative example. On the other hand, widely used technique of POG estimation is based on a relative position between a center of corneal reflection of infrared light sources and a center of pupil. However, a calculation of a center of pupil requires relatively complicated image processing, and therefore, a calculation delay is a concern, since to minimize a delay of inputting data is one of the most significant requirements in games. In this paper, a method to estimate a head movement by only using corneal reflections of two infrared light sources in different locations is proposed. Furthermore, a method to control a cursor using gaze movement as well as a head movement is proposed. By using game-like-applications, proposed methods are evaluated and, as a result, a similar performance to conventional methods is confirmed and an aiming control with lower computation power and stressless intuitive operation is obtained.

Keywords: Point-of-gaze, gaze estimation, head movement, corneal reflections, two infrared light sources, game.

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8531 Altered States of Consciousness in Narrative Cinema: Subjective Film Sound

Authors: Mladen Milicevic

Abstract:

In this paper subjective film sound will be addressed as it gets represented in narrative cinema. First, “meta-diegetic” sound will be briefly explained followed by transition to “oneiric” sound. The representation of oneiric sound refers to a situation where film characters are experiencing some sort of an altered state of consciousness. Looking at an antlered state of consciousness in terms of human brain processes will point out to the cinematic ways of expression, which “mimic” those processes. Using several examples for different films will illustrate these points.

Keywords: Oneiric, ASC (altered states of consciousness), film, sound.

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