Search results for: Association language features
1992 Secure Image Retrieval Based On Orthogonal Decomposition under Cloud Environment
Authors: Yanyan Xu, Lizhi Xiong, Zhengquan Xu, Li Jiang
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In order to protect data privacy, image with sensitive or private information needs to be encrypted before being outsourced to the cloud. However, this causes difficulties in image retrieval and data management. A secure image retrieval method based on orthogonal decomposition is proposed in the paper. The image is divided into two different components, for which encryption and feature extraction are executed separately. As a result, cloud server can extract features from an encrypted image directly and compare them with the features of the queried images, so that the user can thus obtain the image. Different from other methods, the proposed method has no special requirements to encryption algorithms. Experimental results prove that the proposed method can achieve better security and better retrieval precision.
Keywords: Secure image retrieval, secure search, orthogonal decomposition, secure cloud computing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21141991 Natural Language News Generation from Big Data
Authors: Bastian Haarmann, Lukas Sikorski
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In this paper, we introduce an NLG application for the automatic creation of ready-to-publish texts from big data. The resulting fully automatic generated news stories have a high resemblance to the style in which the human writer would draw up such a story. Topics include soccer games, stock exchange market reports, and weather forecasts. Each generated text is unique. Readyto-publish stories written by a computer application can help humans to quickly grasp the outcomes of big data analyses, save timeconsuming pre-formulations for journalists and cater to rather small audiences by offering stories that would otherwise not exist.
Keywords: Big data, natural language generation, publishing, robotic journalism.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16871990 A Neuron Model of Facial Recognition and Detection of an Authorized Entity Using Machine Learning System
Authors: J. K. Adedeji, M. O. Oyekanmi
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This paper has critically examined the use of Machine Learning procedures in curbing unauthorized access into valuable areas of an organization. The use of passwords, pin codes, user’s identification in recent times has been partially successful in curbing crimes involving identities, hence the need for the design of a system which incorporates biometric characteristics such as DNA and pattern recognition of variations in facial expressions. The facial model used is the OpenCV library which is based on the use of certain physiological features, the Raspberry Pi 3 module is used to compile the OpenCV library, which extracts and stores the detected faces into the datasets directory through the use of camera. The model is trained with 50 epoch run in the database and recognized by the Local Binary Pattern Histogram (LBPH) recognizer contained in the OpenCV. The training algorithm used by the neural network is back propagation coded using python algorithmic language with 200 epoch runs to identify specific resemblance in the exclusive OR (XOR) output neurons. The research however confirmed that physiological parameters are better effective measures to curb crimes relating to identities.
Keywords: Biometric characters, facial recognition, neural network, OpenCV.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6951989 The Different Ways to Describe Regular Languages by Using Finite Automata and the Changing Algorithm Implementation
Authors: Abdulmajid Mukhtar Afat
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This paper aims at introducing finite automata theory, the different ways to describe regular languages and create a program to implement the subset construction algorithms to convert nondeterministic finite automata (NFA) to deterministic finite automata (DFA). This program is written in c++ programming language. The program reads FA 5tuples from text file and then classifies it into either DFA or NFA. For DFA, the program will read the string w and decide whether it is acceptable or not. If accepted, the program will save the tracking path and point it out. On the other hand, when the automation is NFA, the program will change the Automation to DFA so that it is easy to track and it can decide whether the w exists in the regular language or not.
Keywords: Finite Automata, subset construction DFA, NFA.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19861988 Spurious Crests in Second-Order Waves
Authors: M. A. Tayfun
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Occurrences of spurious crests on the troughs of large, relatively steep second-order Stokes waves are anomalous and not an inherent characteristic of real waves. Here, the effects of such occurrences on the statistics described by the standard second-order stochastic model are examined theoretically and by way of simulations. Theoretical results and simulations indicate that when spurious occurrences are sufficiently large, the standard model leads to physically unrealistic surface features and inaccuracies in the statistics of various surface features, in particular, the troughs and thus zero-crossing heights of large waves. Whereas inaccuracies can be fairly noticeable for long-crested waves in both deep and shallower depths, they tend to become relatively insignificant in directional waves.Keywords: Large waves, non-linear effects, simulation, spectra, spurious crests, Stokes waves, wave breaking, wave statistics.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13141987 BIDENS: Iterative Density Based Biclustering Algorithm With Application to Gene Expression Analysis
Authors: Mohamed A. Mahfouz, M. A. Ismail
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Biclustering is a very useful data mining technique for identifying patterns where different genes are co-related based on a subset of conditions in gene expression analysis. Association rules mining is an efficient approach to achieve biclustering as in BIMODULE algorithm but it is sensitive to the value given to its input parameters and the discretization procedure used in the preprocessing step, also when noise is present, classical association rules miners discover multiple small fragments of the true bicluster, but miss the true bicluster itself. This paper formally presents a generalized noise tolerant bicluster model, termed as μBicluster. An iterative algorithm termed as BIDENS based on the proposed model is introduced that can discover a set of k possibly overlapping biclusters simultaneously. Our model uses a more flexible method to partition the dimensions to preserve meaningful and significant biclusters. The proposed algorithm allows discovering biclusters that hard to be discovered by BIMODULE. Experimental study on yeast, human gene expression data and several artificial datasets shows that our algorithm offers substantial improvements over several previously proposed biclustering algorithms.Keywords: Machine learning, biclustering, bi-dimensional clustering, gene expression analysis, data mining.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19631986 Investigating the Influence of L2 Motivational Self-System on Willingness to Communicate in English: A Study of Chinese Non-English Major Students in EFL Classrooms
Authors: Wanghongshu Zhou
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This study aims to explore the relationship between the second language motivational self-system (L2MSS) and the willingness to communicate (WTC) among Chinese non-English major students in order to provide pedagogical implications for English as a Foreign Language (EFL) classrooms in Chinese universities. By employing a mixed methods approach, we involved 103 Chinese non-English major students from a typical university in China, conducted questionnaire survey to measure their levels of L2WTC and L2MSS level, and then analyzed the correlation between the two above mentioned variables. Semi-structured interviews were conducted with eight participants to provide a deeper understanding and explanation of the questionnaire data. Findings show that 1) Chinese non-English major students’ ideal L2 self and L2 learning experience could positively predict their L2 WTC in EFL class; 2) Chinese non-English major students’ ought-to L2 self might have no significant impact on their L2 WTC in EFL class; and 3) self-confidence might be another main factor that will influence Chinese non-English major students’ L2 WTC in EFL class. These findings might shed light on the second language acquisition field and provide pedagogical recommendations for pre-service as well as in-service EFL teachers.
Keywords: Chinese non-English major students, L2 Motivation, L2 willingness to communicate, self-confidence.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1651985 The Association of Vitamin B₁₂ with Body Weight-and Fat-Based Indices in Childhood Obesity
Authors: Mustafa M. Donma, Orkide Donma
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Vitamin deficiencies are common in obese individuals. Particularly, the status of vitamin B12 and its association with vitamin B9 (folate) and vitamin D is under investigation in recent time. Vitamin B12 is closely related to many vital processes in the body. In clinical studies, its involvement in fat metabolism draws attention from the obesity point of view. Obesity, in its advanced stages and in combination with metabolic syndrome (MetS) findings, may be a life-threatening health problem. Pediatric obesity is particularly important, because it may be a predictor of the severe chronic diseases during adulthood period of the child. Due to its role in fat metabolism, vitamin B12 deficiency may disrupt metabolic pathways of the lipid and energy metabolisms in the body. The association of low B12 levels with obesity degree may be an interesting topic to be investigated. Obesity indices may be helpful at this point. Weight- and fat-based indices are available. Of them, body mass index (BMI) is in the first group. Fat mass index (FMI), fat-free mass index (FFMI) and diagnostic obesity notation model assessment-II (D2I) index lie in the latter group. The aim of this study is to clarify possible associations between vitamin B12 status and obesity indices in pediatric population. The study comprises a total of 122 children. 32 children were included in the normal-body mass index (N-BMI) group. 46 and 44 children constitute groups with morbid obese children without MetS and with MetS, respectively. Informed consent forms and the approval of the institutional ethics committee were obtained. Tables prepared for obesity classification by World Health Organization were used. MetS criteria were defined. Anthropometric and blood pressure measurements were taken. BMI, FMI, FFMI, D2I were calculated. Routine laboratory tests were performed. Vitamin B9, B12, D concentrations were determined. Statistical evaluation of the study data was performed. Vitamin B9 and vitamin D levels were reduced in MetS group compared to children with N-BMI (p > 0.05). Significantly lower values were observed in vitamin B12 concentrations of MetS group (p < 0.01). Upon evaluation of blood pressure as well as triglyceride levels, there exist significant increases in morbid obese children. Significantly decreased concentrations of high-density lipoprotein cholesterol were observed. All of the obesity indices and insulin resistance index exhibit increasing tendency with the severity of obesity. Inverse correlations were calculated between vitamin D and insulin resistance index as well as vitamin B12 and D2I in morbid obese groups. In conclusion, a fat-based index, D2I, was the most prominent body index, which shows strong correlation with vitamin B12 concentrations in the late stage of obesity in children. A negative correlation between these two parameters was a confirmative finding related to the association between vitamin B12 and obesity degree.
Keywords: Body mass index, children, D2I index, fat mass index, obesity.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7091984 A New Computational Tool for Noise Prediction of Rotating Surfaces (FACT)
Authors: Ana Vieira, Fernando Lau, João Pedro Mortágua, Luís Cruz, Rui Santos
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The air transport impact on environment is more than ever a limitative obstacle to the aeronautical industry continuous growth. Over the last decades, considerable effort has been carried out in order to obtain quieter aircraft solutions, whether by changing the original design or investigating more silent maneuvers. The noise propagated by rotating surfaces is one of the most important sources of annoyance, being present in most aerial vehicles. Bearing this is mind, CEIIA developed a new computational chain for noise prediction with in-house software tools to obtain solutions in relatively short time without using excessive computer resources. This work is based on the new acoustic tool, which aims to predict the rotor noise generated during steady and maneuvering flight, making use of the flexibility of the C language and the advantages of GPU programming in terms of velocity. The acoustic tool is based in the Formulation 1A of Farassat, capable of predicting two important types of noise: the loading and thickness noise. The present work describes the most important features of the acoustic tool, presenting its most relevant results and framework analyses for helicopters and UAV quadrotors.
Keywords: Rotor noise, acoustic tool, GPU Programming, UAV noise.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20581983 Poli4SDG: An Application for Environmental Crises Management and Gender Support
Authors: Angelica S. Valeriani, Lorenzo Biasiolo
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In recent years, the scale of the impact of climate change and its related side effects has become ever more massive and devastating. Sustainable Development Goals (SDGs), promoted by United Nations, aim to front issues related to climate change, among others. In particular, the project CROWD4SDG focuses on a bunch of SDGs, since it promotes environmental activities and climate-related issues. In this context, we developed a prototype of an application, under advanced development considering web design, that focuses on SDG 13 (SDG on climate action) by providing users with useful instruments to face environmental crises and climate-related disasters. Our prototype is thought and structured for both web and mobile development. The main goal of the application, POLI4SDG, is to help users to get through emergency services. To this extent, an organized overview and classification prove to be very effective and helpful to people in need. A careful analysis of data related to environmental crises prompted us to integrate the user contribution, i.e. exploiting a core principle of Citizen Science, into the realization of a public catalog, available for consulting and organized according to typology and specific features. In addition, gender equality and opportunity features are considered in the prototype, in order to allow women, often the most vulnerable category, to have direct support. The overall description of the application functionalities is detailed. Moreover, implementation features and properties of the prototype are discussed.
Keywords: Crowdsourcing, social media, SDG, climate change, natural disasters, gender equality.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6931982 Association between Job Satisfaction, Motivation and Five Factors of Organizational Citizenship Behavior
Authors: K. Mushtaq, M. Umar
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The research aims to study the association between job satisfaction, motivation and the five factors of organizational citizenship behavior (i.e. Altruism, Conscientiousness, Sportsmanship, Courtesy and Civic virtue) among Public Sector Employees in Pakistan. In this research Structure Equation Modeling with confirmatory factor analysis was used to test the relationship between two independent and five dependent variables. Data was collected through questionnaire survey from 152 Public Servants Working in Gujrat District-Pakistan in different capacities. Stratified Random Sampling Technique was used to conduct this survey. The results of the study indicate that five factors of OCB have positive significant relation with both motivation and job satisfaction except the relationship of Civic Virtue with Motivation. The research findings implicate that factors other than motivation and job satisfaction may also affect OCB. Likewise, all the five factors of OCB may not be present in all populations. Thus, Managers must concentrate on increasing motivation and job satisfaction to increase OCB. Furthermore, the present research gives a direction to future researchers to use more independent variables (e.g. Culture, leadership, workplace environment, various job attitudes, types of motivation, etc.) on different types of populations with larger sample size in order to find the reasons behind insignificant relationship of civic virtue with Motivation in the research in hand and to generalize the tested model.Keywords: Five Factors of Organizational Citizenship Behavior (OCB), Motivation, Job Satisfaction, Public Sector Employees in Pakistan.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 31671981 Metaphor in Terminology: Visualization as a Way to Term Perception
Authors: Jeļena Tretjakova
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Metaphor has recently gained extensive interest most probably due to developments in cognitive sciences and the study of language as the reflection of humans- world perception. Metaphor is no longer reckoned as solely literary expressive means. Nowadays it is studied in a whole number of discourses, such as politics, law, medicine, sports, etc. with the purpose of the analysis and determining its role. The scientific language is not an exception. It might seem that metaphor cannot suit it; we would dare to draw a hypothesis that metaphor has indeed found its stable place in terminology. In comprehension of metaphorically represented terms the stage of visualization plays a significant role. We proceeded on the assumption that this stage is the main in provision of better term comprehension and would try to exemplify it with metaphoricallyoriented terms.
Keywords: Comprehension, metaphor, terminology, visualization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18721980 Part of Speech Tagging Using Statistical Approach for Nepali Text
Authors: Archit Yajnik
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Part of Speech Tagging has always been a challenging task in the era of Natural Language Processing. This article presents POS tagging for Nepali text using Hidden Markov Model and Viterbi algorithm. From the Nepali text, annotated corpus training and testing data set are randomly separated. Both methods are employed on the data sets. Viterbi algorithm is found to be computationally faster and accurate as compared to HMM. The accuracy of 95.43% is achieved using Viterbi algorithm. Error analysis where the mismatches took place is elaborately discussed.Keywords: Hidden Markov model, Viterbi algorithm, POS tagging, natural language processing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17081979 Research on Self-Perceptions of Pre-Service Turkish Language Teachers in Turkey with Regard to Problem Solving Skills
Authors: Canan Aslan
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The aim of this research is to determine how preservice Turkish teachers perceive themselves in terms of problem solving skills. Students attending Department of Turkish Language Teaching of Gazi University Education Faculty in 2005-2006 academic year constitute the study group (n= 270) of this research in which survey model was utilized. Data were obtained by Problem Solving Inventory developed by Heppner & Peterson and Personal Information Form. Within the settings of this research, Cronbach Alpha reliability coefficient of the scale was found as .87. Besides, reliability coefficient obtained by split-half technique which splits odd and even numbered items of the scale was found as r=.81 (Split- Half Reliability). The findings of the research revealed that preservice Turkish teachers were sufficiently qualified on the subject of problem solving skills and statistical significance was found in favor of male candidates in terms of “gender" variable. According to the “grade" variable, statistical significance was found in favor of 4th graders.
Keywords: Problem Solving, problem solving skills, PreserviceTurkish Language Teachers.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13581978 Segmentation Free Nastalique Urdu OCR
Authors: Sobia T. Javed, Sarmad Hussain, Ameera Maqbool, Samia Asloob, Sehrish Jamil, Huma Moin
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The electronically available Urdu data is in image form which is very difficult to process. Printed Urdu data is the root cause of problem. So for the rapid progress of Urdu language we need an OCR systems, which can help us to make Urdu data available for the common person. Research has been carried out for years to automata Arabic and Urdu script. But the biggest hurdle in the development of Urdu OCR is the challenge to recognize Nastalique Script which is taken as standard for writing Urdu language. Nastalique script is written diagonally with no fixed baseline which makes the script somewhat complex. Overlap is present not only in characters but in the ligatures as well. This paper proposes a method which allows successful recognition of Nastalique Script.Keywords: HMM, Image processing, Optical CharacterRecognition, Urdu OCR.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21591977 Resolving Dependency Ambiguity of Subordinate Clauses using Support Vector Machines
Authors: Sang-Soo Kim, Seong-Bae Park, Sang-Jo Lee
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In this paper, we propose a method of resolving dependency ambiguities of Korean subordinate clauses based on Support Vector Machines (SVMs). Dependency analysis of clauses is well known to be one of the most difficult tasks in parsing sentences, especially in Korean. In order to solve this problem, we assume that the dependency relation of Korean subordinate clauses is the dependency relation among verb phrase, verb and endings in the clauses. As a result, this problem is represented as a binary classification task. In order to apply SVMs to this problem, we selected two kinds of features: static and dynamic features. The experimental results on STEP2000 corpus show that our system achieves the accuracy of 73.5%.Keywords: Dependency analysis, subordinate clauses, binaryclassification, support vector machines.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15971976 The Use of Project to Enhance Writing Skill
Authors: Duangkamol Thitivesa, Abigail Melad Essien
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This paper explores the use of project work in a content-based instruction in a Rajabhat University, a teacher college, where student teachers are instructed to perform teaching roles mainly in basic education level. Its aim is to link theory to practice, and to help language teachers maximize the full potential of project work for genuine communication and give real meaning to writing activity. Two research questions are formulated to guide this study: a) What is the academic achievement of the students- writing skill against the 70% attainment target after the use of project to enhance the skill? and b) To what degree is the development of the students- writing skills during the course of project to enhance the skill? The sample of the study comprised of 38 fourth-year English major students. The data was collected by means of achievement test, student writing works, and project diary. The scores in the summative achievement test were analyzed by mean score, standard deviation, and t-test. Project diary serves as students- record of the language acquired during the project. List of structures and vocabulary noted in the diary has shown students- ability to attend to, recognize, and focus on meaningful patterns of language forms.Keywords: EFL classroom, Project-Based Learning, project work, writing skill.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 33251975 Classification of Potential Biomarkers in Breast Cancer Using Artificial Intelligence Algorithms and Anthropometric Datasets
Authors: Aref Aasi, Sahar Ebrahimi Bajgani, Erfan Aasi
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Breast cancer (BC) continues to be the most frequent cancer in females and causes the highest number of cancer-related deaths in women worldwide. Inspired by recent advances in studying the relationship between different patient attributes and features and the disease, in this paper, we have tried to investigate the different classification methods for better diagnosis of BC in the early stages. In this regard, datasets from the University Hospital Centre of Coimbra were chosen, and different machine learning (ML)-based and neural network (NN) classifiers have been studied. For this purpose, we have selected favorable features among the nine provided attributes from the clinical dataset by using a random forest algorithm. This dataset consists of both healthy controls and BC patients, and it was noted that glucose, BMI, resistin, and age have the most importance, respectively. Moreover, we have analyzed these features with various ML-based classifier methods, including Decision Tree (DT), K-Nearest Neighbors (KNN), eXtreme Gradient Boosting (XGBoost), Logistic Regression (LR), Naive Bayes (NB), and Support Vector Machine (SVM) along with NN-based Multi-Layer Perceptron (MLP) classifier. The results revealed that among different techniques, the SVM and MLP classifiers have the most accuracy, with amounts of 96% and 92%, respectively. These results divulged that the adopted procedure could be used effectively for the classification of cancer cells, and also it encourages further experimental investigations with more collected data for other types of cancers.
Keywords: Breast cancer, health diagnosis, Machine Learning, biomarker classification, Neural Network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3201974 Standard Deviation of Mean and Variance of Rows and Columns of Images for CBIR
Authors: H. B. Kekre, Kavita Patil
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This paper describes a novel and effective approach to content-based image retrieval (CBIR) that represents each image in the database by a vector of feature values called “Standard deviation of mean vectors of color distribution of rows and columns of images for CBIR". In many areas of commerce, government, academia, and hospitals, large collections of digital images are being created. This paper describes the approach that uses contents as feature vector for retrieval of similar images. There are several classes of features that are used to specify queries: colour, texture, shape, spatial layout. Colour features are often easily obtained directly from the pixel intensities. In this paper feature extraction is done for the texture descriptor that is 'variance' and 'Variance of Variances'. First standard deviation of each row and column mean is calculated for R, G, and B planes. These six values are obtained for one image which acts as a feature vector. Secondly we calculate variance of the row and column of R, G and B planes of an image. Then six standard deviations of these variance sequences are calculated to form a feature vector of dimension six. We applied our approach to a database of 300 BMP images. We have determined the capability of automatic indexing by analyzing image content: color and texture as features and by applying a similarity measure Euclidean distance.
Keywords: Standard deviation Image retrieval, color distribution, Variance, Variance of Variance, Euclidean distance.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 37461973 Aspect Oriented Software Architecture
Authors: Pradip Peter Dey, Ronald F. Gonzales, Gordon W. Romney, Mohammad Amin, Bhaskar Raj Sinha
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Natural language processing systems pose a unique challenge for software architectural design as system complexity has increased continually and systems cannot be easily constructed from loosely coupled modules. Lexical, syntactic, semantic, and pragmatic aspects of linguistic information are tightly coupled in a manner that requires separation of concerns in a special way in design, implementation and maintenance. An aspect oriented software architecture is proposed in this paper after critically reviewing relevant architectural issues. For the purpose of this paper, the syntactic aspect is characterized by an augmented context-free grammar. The semantic aspect is composed of multiple perspectives including denotational, operational, axiomatic and case frame approaches. Case frame semantics matured in India from deep thematic analysis. It is argued that lexical, syntactic, semantic and pragmatic aspects work together in a mutually dependent way and their synergy is best represented in the aspect oriented approach. The software architecture is presented with an augmented Unified Modeling Language.Keywords: Language engineering, parsing, software design, user experience.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17431972 An Improved Fast Search Method Using Histogram Features for DNA Sequence Database
Authors: Qiu Chen, Feifei Lee, Koji Kotani, Tadahiro Ohmi
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In this paper, we propose an efficient hierarchical DNA sequence search method to improve the search speed while the accuracy is being kept constant. For a given query DNA sequence, firstly, a fast local search method using histogram features is used as a filtering mechanism before scanning the sequences in the database. An overlapping processing is newly added to improve the robustness of the algorithm. A large number of DNA sequences with low similarity will be excluded for latter searching. The Smith-Waterman algorithm is then applied to each remainder sequences. Experimental results using GenBank sequence data show the proposed method combining histogram information and Smith-Waterman algorithm is more efficient for DNA sequence search.Keywords: Fast search, DNA sequence, Histogram feature, Smith-Waterman algorithm, Local search
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13291971 Dynamic Features Selection for Heart Disease Classification
Authors: Walid MOUDANI
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The healthcare environment is generally perceived as being information rich yet knowledge poor. However, there is a lack of effective analysis tools to discover hidden relationships and trends in data. In fact, valuable knowledge can be discovered from application of data mining techniques in healthcare system. In this study, a proficient methodology for the extraction of significant patterns from the Coronary Heart Disease warehouses for heart attack prediction, which unfortunately continues to be a leading cause of mortality in the whole world, has been presented. For this purpose, we propose to enumerate dynamically the optimal subsets of the reduced features of high interest by using rough sets technique associated to dynamic programming. Therefore, we propose to validate the classification using Random Forest (RF) decision tree to identify the risky heart disease cases. This work is based on a large amount of data collected from several clinical institutions based on the medical profile of patient. Moreover, the experts- knowledge in this field has been taken into consideration in order to define the disease, its risk factors, and to establish significant knowledge relationships among the medical factors. A computer-aided system is developed for this purpose based on a population of 525 adults. The performance of the proposed model is analyzed and evaluated based on set of benchmark techniques applied in this classification problem.Keywords: Multi-Classifier Decisions Tree, Features Reduction, Dynamic Programming, Rough Sets.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25321970 Object-Oriented Programming for Modeling and Simulation of Systems in Physiology
Authors: J. Fernandez de Canete
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Object-oriented modeling is spreading in current simulation of physiological systems through the use of the individual components of the model and its interconnections to define the underlying dynamic equations. In this paper we describe the use of both the SIMSCAPE and MODELICA simulation environments in the object-oriented modeling of the closed loop cardiovascular system. The performance of the controlled system was analyzed by simulation in light of the existing hypothesis and validation tests previously performed with physiological data. The described approach represents a valuable tool in the teaching of physiology for graduate medical students.
Keywords: Object-Oriented Modeling, SIMSCAPE Simulation Language, MODELICA Simulation Language, Cardiovascular System.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 28621969 Thai Prosody Problems with First Year Students
Authors: Jiraporn Adchariyaprasit
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Thai language is difficult in all four language skills, especially reading. The first year students may have different abilities in reading, so a teacher is required to find out a student’s reading level so that the teacher can help and support them till they can develop and resolve each problem themselves. This research is aimed to study the prosody problem among Thai students and will be focused on first year Thai students in the second semester. A total of 58 students were involved in this study. Four obstacles were found: 1. Interpretation from what they read and write 2. Incorrectness Pronunciation of Prosody 3. Incorrectness in Rhythm of the Poem 4. Incorrectness of the Thai Poem Pronunciation
Keywords: Interpretation, Pronunciation, Prosody, Reading.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16451968 Describing Learning Features of Reusable Resources: A Proposal
Authors: Serena Alvino, Paola Forcheri, Maria Grazia Ierardi, Luigi Sarti
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One of the main advantages of the LO paradigm is to allow the availability of good quality, shareable learning material through the Web. The effectiveness of the retrieval process requires a formal description of the resources (metadata) that closely fits the user-s search criteria; in spite of the huge international efforts in this field, educational metadata schemata often fail to fulfil this requirement. This work aims to improve the situation, by the definition of a metadata model capturing specific didactic features of shareable learning resources. It classifies LOs into “teacher-oriented" and “student-oriented" categories, in order to describe the role a LO is to play when it is integrated into the educational process. This article describes the model and a first experimental validation process that has been carried out in a controlled environment.Keywords: Learning object, pedagogical metadata, experimental validation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15451967 Support Vector Machine for Persian Font Recognition
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In this paper we examine the use of global texture analysis based approaches for the purpose of Persian font recognition in machine-printed document images. Most existing methods for font recognition make use of local typographical features and connected component analysis. However derivation of such features is not an easy task. Gabor filters are appropriate tools for texture analysis and are motivated by human visual system. Here we consider document images as textures and use Gabor filter responses for identifying the fonts. The method is content independent and involves no local feature analysis. Two different classifiers Weighted Euclidean Distance and SVM are used for the purpose of classification. Experiments on seven different type faces and four font styles show average accuracy of 85% with WED and 82% with SVM classifier over typefacesKeywords: Persian font recognition, support vector machine, gabor filter.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17091966 Improving Subjective Bias Detection Using Bidirectional Encoder Representations from Transformers and Bidirectional Long Short-Term Memory
Authors: Ebipatei Victoria Tunyan, T. A. Cao, Cheol Young Ock
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Detecting subjectively biased statements is a vital task. This is because this kind of bias, when present in the text or other forms of information dissemination media such as news, social media, scientific texts, and encyclopedias, can weaken trust in the information and stir conflicts amongst consumers. Subjective bias detection is also critical for many Natural Language Processing (NLP) tasks like sentiment analysis, opinion identification, and bias neutralization. Having a system that can adequately detect subjectivity in text will boost research in the above-mentioned areas significantly. It can also come in handy for platforms like Wikipedia, where the use of neutral language is of importance. The goal of this work is to identify the subjectively biased language in text on a sentence level. With machine learning, we can solve complex AI problems, making it a good fit for the problem of subjective bias detection. A key step in this approach is to train a classifier based on BERT (Bidirectional Encoder Representations from Transformers) as upstream model. BERT by itself can be used as a classifier; however, in this study, we use BERT as data preprocessor as well as an embedding generator for a Bi-LSTM (Bidirectional Long Short-Term Memory) network incorporated with attention mechanism. This approach produces a deeper and better classifier. We evaluate the effectiveness of our model using the Wiki Neutrality Corpus (WNC), which was compiled from Wikipedia edits that removed various biased instances from sentences as a benchmark dataset, with which we also compare our model to existing approaches. Experimental analysis indicates an improved performance, as our model achieved state-of-the-art accuracy in detecting subjective bias. This study focuses on the English language, but the model can be fine-tuned to accommodate other languages.
Keywords: Subjective bias detection, machine learning, BERT–BiLSTM–Attention, text classification, natural language processing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8301965 Morpho-Phonological Modelling in Natural Language Processing
Authors: Eleni Galiotou, Angela Ralli
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In this paper we propose a computational model for the representation and processing of morpho-phonological phenomena in a natural language, like Modern Greek. We aim at a unified treatment of inflection, compounding, and word-internal phonological changes, in a model that is used for both analysis and generation. After discussing certain difficulties cuase by well-known finitestate approaches, such as Koskenniemi-s two-level model [7] when applied to a computational treatment of compounding, we argue that a morphology-based model provides a more adequate account of word-internal phenomena. Contrary to the finite state approaches that cannot handle hierarchical word constituency in a satisfactory way, we propose a unification-based word grammar, as the nucleus of our strategy, which takes into consideration word representations that are based on affixation and [stem stem] or [stem word] compounds. In our formalism, feature-passing operations are formulated with the use of the unification device, and phonological rules modeling the correspondence between lexical and surface forms apply at morpheme boundaries. In the paper, examples from Modern Greek illustrate our approach. Morpheme structures, stress, and morphologically conditioned phoneme changes are analyzed and generated in a principled way.
Keywords: Morpho-Phonology, Natural Language Processing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21291964 A Visual Control Flow Language and Its Termination Properties
Authors: László Lengyel, Tihamér Levendovszky, Hassan Charaf
Abstract:
This paper presents the visual control flow support of Visual Modeling and Transformation System (VMTS), which facilitates composing complex model transformations out of simple transformation steps and executing them. The VMTS Visual Control Flow Language (VCFL) uses stereotyped activity diagrams to specify control flow structures and OCL constraints to choose between different control flow branches. This work discusses the termination properties of VCFL and provides an algorithm to support the termination analysis of VCFL transformations.
Keywords: Control Flow, Metamodel-Based Visual Model Transformation, OCL, Termination Properties, UML.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20661963 Multi-Level Air Quality Classification in China Using Information Gain and Support Vector Machine
Authors: Bingchun Liu, Pei-Chann Chang, Natasha Huang, Dun Li
Abstract:
Machine Learning and Data Mining are the two important tools for extracting useful information and knowledge from large datasets. In machine learning, classification is a wildly used technique to predict qualitative variables and is generally preferred over regression from an operational point of view. Due to the enormous increase in air pollution in various countries especially China, Air Quality Classification has become one of the most important topics in air quality research and modelling. This study aims at introducing a hybrid classification model based on information theory and Support Vector Machine (SVM) using the air quality data of four cities in China namely Beijing, Guangzhou, Shanghai and Tianjin from Jan 1, 2014 to April 30, 2016. China's Ministry of Environmental Protection has classified the daily air quality into 6 levels namely Serious Pollution, Severe Pollution, Moderate Pollution, Light Pollution, Good and Excellent based on their respective Air Quality Index (AQI) values. Using the information theory, information gain (IG) is calculated and feature selection is done for both categorical features and continuous numeric features. Then SVM Machine Learning algorithm is implemented on the selected features with cross-validation. The final evaluation reveals that the IG and SVM hybrid model performs better than SVM (alone), Artificial Neural Network (ANN) and K-Nearest Neighbours (KNN) models in terms of accuracy as well as complexity.
Keywords: Machine learning, air quality classification, air quality index, information gain, support vector machine, cross-validation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 948