Search results for: diagnostic analysis

Authors: Wisam H. Benamer, Ehab A. Elfallah, Mohamed A. Elshaari, Farag A. Elshaari

Abstract:

A challenge for laboratories is to provide bacterial identification and antibiotic sensitivity results within a short time. Hence, advancement in the required technology is desirable to improve timing, accuracy and quality. Even with the current advances in methods used for both phenotypic and genotypic identification of bacteria the need is there to develop method(s) that enhance the outcome of bacteriology laboratories in accuracy and time. The hypothesis introduced here is based on the assumption that the chromosome of any bacteria contains unique sequences that can be used for its identification and typing. The outcome of a pilot study designed to test this hypothesis is reported in this manuscript. Methods: The complete chromosome sequences of several bacterial species were downloaded to use as search targets for unique sequences. Visual basic and SQL server (2014) were used to generate a complete set of 18-base long primers, a process started with reverse translation of randomly chosen 6 amino acids to limit the number of the generated primers. In addition, the software used to scan the downloaded chromosomes using the generated primers for similarities was designed, and the resulting hits were classified according to the number of similar chromosomal sequences, i.e., unique or otherwise. Results: All primers that had identical/similar sequences in the selected genome sequence(s) were classified according to the number of hits in the chromosomes search. Those that were identical to a single site on a single bacterial chromosome were referred to as unique. On the other hand, most generated primers sequences were identical to multiple sites on a single or multiple chromosomes. Following scanning, the generated primers were classified based on ability to differentiate between medically important bacterial and the initial results looks promising. Conclusion: A simple strategy that started by generating primers was introduced; the primers were used to screen bacterial genomes for match. Primer(s) that were uniquely identical to specific DNA sequence on a specific bacterial chromosome were selected. The identified unique sequence can be used in different molecular diagnostic techniques, possibly to identify bacteria. In addition, a single primer that can identify multiple sites in a single chromosome can be exploited for region or genome identification. Although genomes sequences draft of isolates of organism DNA enable high throughput primer design using alignment strategy, and this enhances diagnostic performance in comparison to traditional molecular assays. In this method the generated primers can be used to identify an organism before the draft sequence is completed. In addition, the generated primers can be used to build a bank for easy access of the primers that can be used to identify bacteria.

Keywords: Bacteria chromosome, bacterial identification, sequence, primer generation.

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Authors: Lilac A. E. Al-Safadi

Abstract:

With the advance of multimedia and diagnostic images technologies, the number of radiographic images is increasing constantly. The medical field demands sophisticated systems for search and retrieval of the produced multimedia document. This paper presents an ongoing research that focuses on the semantic content of radiographic image documents to facilitate semantic-based radiographic image indexing and a retrieval system. The proposed model would divide a radiographic image document, based on its semantic content, and would be converted into a logical structure or a semantic structure. The logical structure represents the overall organization of information. The semantic structure, which is bound to logical structure, is composed of semantic objects with interrelationships in the various spaces in the radiographic image.

Keywords: Semantic Indexing, Content-Based Retrieval, Radiographic Images, Data Model

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Authors: H. Bouhamed, A. Rebai, T. Lecroq, M. Jaoua

Abstract:

The objective of our work is to develop a new approach for discovering knowledge from a large mass of data, the result of applying this approach will be an expert system that will serve as diagnostic tools of a phenomenon related to a huge information system. We first recall the general problem of learning Bayesian network structure from data and suggest a solution for optimizing the complexity by using organizational and optimization methods of data. Afterward we proposed a new heuristic of learning a Multi-Entities Bayesian Networks structures. We have applied our approach to biological facts concerning hereditary complex illnesses where the literatures in biology identify the responsible variables for those diseases. Finally we conclude on the limits arched by this work.

Keywords: Data-organization, data-optimization, automatic knowledge discovery, Multi-Entities Bayesian networks, score merging.

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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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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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Authors: F. Bakiri, T. Rexha, A. Mitre

Abstract:

The aim of our study was to compare knowledge of regarding HPV and cervical cancer in female student of 18 to 26 years old, with or without sexual intercourse. We conducted a questionnaire survey of the students (N=568), in Faculty of Natural Sciences, Tirana, Albania. Sexually experienced students were more likely to have heard of risk factors such as multiple sex partners, sexual intercourse before age 18, having contracted any sexually transmitted diseases, having genital warts, smoking cigarettes, use of oral contraceptive, poor diet or nutrition and using tampons. No significant sexually experience differences were observed in knowledge of the way of transmission of the virus associated with cervical cancer knowledge, the virus associated with cervical cancer knowledge, the prevention of cervical cancer knowledge. On the other hand strong significant sexually experience differences were observed in knowledge of the diagnostic way of cervical cancer and what HPV can cause knowledge.

Keywords: Risk factors, HPV, Cervical cancer, Albanian students.

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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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Authors: Marios Poulos, Eirini Maliagani, Minas Paschopoulos, George Bokos

Abstract:

The purpose of my research proposal is to demonstrate that there is a relationship between EEG and endometrial cancer. The above relationship is based on an Aristotelian Syllogism; since it is known that the 14-3-3 protein is related to the electrical activity of the brain via control of the flow of Na+ and K+ ions and since it is also known that many types of cancer are associated with 14-3-3 protein, it is possible that there is a relationship between EEG and cancer. This research will be carried out by well-defined diagnostic indicators, obtained via the EEG, using signal processing procedures and pattern recognition tools such as neural networks in order to recognize the endometrial cancer type. The current research shall compare the findings from EEG and hysteroscopy performed on women of a wide age range. Moreover, this practice could be expanded to other types of cancer. The implementation of this methodology will be completed with the creation of an ontology. This ontology shall define the concepts existing in this research-s domain and the relationships between them. It will represent the types of relationships between hysteroscopy and EEG findings.

Keywords: Bioinformatics, Protein 14-3-3, EEG, Endometrial cancer, Ontology.

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Authors: Asif Mansoor, Nasiruddin Khan, Noreen Jamil

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In this communication a quantitative modeling approach is applied to construct model for the exchange of gases from open sewer channel to the atmosphere. The data for the exchange of gases of the open sewer channel for the year January 1979 to December 2006 is utilized for the construction of the model. The study reveals that stream flow of the open sewer channel exchanges the toxic gases continuously with time varying scale. We find that the quantitative modeling approach is more parsimonious model for these exchanges. The usual diagnostic tests are applied for the model adequacy. This model is beneficial for planner and managerial bodies for the improvement of implemented policies to overcome future environmental problems.

Keywords: Open sewer channel, Industrial waste, Municipalwaste, Gases exchange, Atmosphere, Stochastic models, Diagnosticschecks.

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Authors: R. Krishnamoorthy, N. Amudhavalli, M.K. Sivakkolunthu

Abstract:

X-ray mammography is the most effective method for the early detection of breast diseases. However, the typical diagnostic signs such as microcalcifications and masses are difficult to detect because mammograms are of low-contrast and noisy. In this paper, a new algorithm for image denoising and enhancement in Orthogonal Polynomials Transformation (OPT) is proposed for radiologists to screen mammograms. In this method, a set of OPT edge coefficients are scaled to a new set by a scale factor called OPT scale factor. The new set of coefficients is then inverse transformed resulting in contrast improved image. Applications of the proposed method to mammograms with subtle lesions are shown. To validate the effectiveness of the proposed method, we compare the results to those obtained by the Histogram Equalization (HE) and the Unsharp Masking (UM) methods. Our preliminary results strongly suggest that the proposed method offers considerably improved enhancement capability over the HE and UM methods.

Keywords: mammograms, image enhancement, orthogonalpolynomials, contrast improvement

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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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Authors: Mohammed Saleem Tariq

Abstract:

The enthusiasm for gluten avoidance in a growing market is met by improvements in sensitive detection methods for analysing gluten content. Paradoxically, manufacturers employ no such systems in the production process but continue to market their product as gluten free, a significant risk posed to an undetermined coeliac population. This paper resonates with an immunological response that causes gastrointestinal scarring and villous atrophy with the conventional description of personal injury. This thesis divulges into evaluating potential inadequacies of gluten labelling laws which not only present a diagnostic challenge for general practitioners in the UK but it also exposes a less than adequate form of available legal protection to those who suffer adverse reactions as a result of gluten digestion. Central to this discussion is whether a claim brought in misrepresentation, negligence and/or under the Consumer Protection Act 1987 could be sustained. An interesting comparison is then made with the legal regimes of neighboring jurisdictions furthering the theme of a legally un-catered for gluten kingdom.

Keywords: Coeliac, litigation, misrepresentation, negligence.

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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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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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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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Authors: Dong Hoon Lim

Abstract:

A series of microarray experiments produces observations of differential expression for thousands of genes across multiple conditions. Principal component analysis(PCA) has been widely used in multivariate data analysis to reduce the dimensionality of the data in order to simplify subsequent analysis and allow for summarization of the data in a parsimonious manner. PCA, which can be implemented via a singular value decomposition(SVD), is useful for analysis of microarray data. For application of PCA using SVD we use the DNA microarray data for the small round blue cell tumors(SRBCT) of childhood by Khan et al.(2001). To decide the number of components which account for sufficient amount of information we draw scree plot. Biplot, a graphic display associated with PCA, reveals important features that exhibit relationship between variables and also the relationship of variables with observations.

Keywords: Principal component analysis, singular value decomposition, microarray data, SRBCT

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Authors: Farzad Yavari, Hamid Chegini, Saeed Lotfi

Abstract:

This paper reviews the comparison of Resin Rich (RR) and Vacuum Pressure Impregnation (VPI) insulation system qualities for stator bar of rotating electrical machines. Voltage endurance and tangent delta are two diagnostic tests to determine the quality of insulation systems. The paper describes the trend of dissipation factor while performing voltage endurance test for different stator bar samples made with RR and VPI insulation system methods. Some samples were made with the same strands and insulation thickness but with different main wall material to prove the influence of insulation system methods on stator bar quality. Also, some of the samples were subjected to voltage at the temperature of their insulation class, and their dissipation factor changes were measured and studied.

Keywords: Vacuum pressure impregnation, resin rich, insulation, stator bar, dissipation factor, voltage endurance.

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Authors: Marwa I. Shabayek, Ola A. Said, Hanan A. Attaia, Heba A. Awida

Abstract:

Bladder carcinoma is an important worldwide health problem. Both cystoscopy and urine cytology used in detecting bladder cancer suffer from drawbacks where cystoscopy is an invasive method and urine cytology shows low sensitivity in low grade tumors. This study validates easier and less time-consuming techniques to evaluate the value of combined use of angiogenin and clusterin in comparison and combination with voided urine cytology in the detection of bladder cancer patients. This study includes malignant (bladder cancer patients, n= 50), benign (n=20) and healthy (n=20) groups. The studied groups were subjected to cystoscopic examination, detection of bilharzial antibodies, urine cytology, and estimation of urinary angiogenin and clusterin by ELISA. The overall sensitivity and specificity were 66% and 75% for angiogenin, 70% and 82.5% for clusterin and 46% and 80% for voided urine cytology. Combined sensitivity of angiogenin and clusterin with urine cytology increased from 82 to 88%. 

Keywords: Angiogenin, Bladder Cancer, Clusterin, Cytology.

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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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Authors: Suken Nayak, Aditya Kambli, Bharati Ingale, Gauri Shukla

Abstract:

The technological concepts such as wireless hospital and portable cardiac telemetry system require the development of physiological signal acquisition devices to be easily integrated into the hospital database. In this paper we present the low cost, portable wireless ECG acquisition hardware that transmits ECG signals to a dedicated computer.The front end of the system obtains and processes incoming signals, which are then transmitted via a microcontroller and wireless Bluetooth module. A monitoring purpose Bluetooth based end user application integrated with patient database management module is developed for the computers. The system will act as a continuous event recorder, which can be used to follow up patients who have been resuscitatedfrom cardiac arrest, ventricular tachycardia but also for diagnostic purposes for patients with arrhythmia symptoms. In addition, cardiac information can be saved into the patient-s database of the hospital.

Keywords: ECG, Bluetooth communication, monitoring application, patient database

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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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Authors: P.Cordero, R.Poler, R.Sanchis

Abstract:

The environmental impacts caused by the current production and consumption models, together with the impact that the current economic crisis, bring necessary changes in the European industry toward new business models based on sustainability issues that could allow them to innovate and improve their competitiveness. This paper analyzes the key environmental issues and the current and future market trends in one of the most important industrial sectors in Spain, the furniture sector. It also proposes new decision support tools -diagnostic kit, roadmap and guidelines- to guide companies to implement sustainability criteria into their organizations, including eco-design strategies and other economical and social strategies in accordance with the sustainability definition, and other available tools such as eco-labels, environmental management systems, etc., and to use and combine them to obtain the results the company expects to help improve its competitiveness.

Keywords: Furniture sector, eco-design, sustainability, economical crisis, market trends, roadmap

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Authors: Simon B. N. Thompson

Abstract:

Retinoblastoma is a rare type of childhood genetic cancer that affects children worldwide. The diagnosis is often missed due to lack of education and difficulty in presentation of the tumor. Frequently, the tumor on the retina is noticed by photography when the red-eye flash, commonly seen in normal eyes, is not produced. Instead, a yellow or white colored patch is seen or the child has a noticeable strabismus. Early detection can be life-saving though often results in removal of the affected eye. Remaining functioning in the healthy eye when the child is young has resulted in super-vision and high or above-average intelligence. Technological advancement of cameras has helped in early detection. Brain imaging has also made possible early detection of neurological diseases and, together with the monitoring of cortisol levels and yawning frequency, promises to be the next new early diagnostic tool for the detection of neurological diseases where cortisol insufficiency is particularly salient, such as multiple sclerosis and Cushing’s disease.

Keywords: Cortisol, Neurological Disease, Retinoblastoma, Thompson Cortisol Hypothesis, Yawning.

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Authors: J. R. Wang, H. C. Chen, C. Shih, S. W. Chen, J. H. Yang, Y. Chiang

Abstract:

In this study, we focus on the establishment of the analysis model for Maanshan PWR nuclear power plant (NPP) by using RADTRAD and SNAP codes with the FSAR, manuals, and other data. In order to evaluate the cumulative dose at the Exclusion Area Boundary (EAB) and Low Population Zone (LPZ) outer boundary, Maanshan NPP RADTRAD/SNAP model was used to perform the analysis of the DBA LOCA case. The analysis results of RADTRAD were similar to FSAR data. These analysis results were lower than the failure criteria of 10 CFR 100.11 (a total radiation dose to the whole body, 250 mSv; a total radiation dose to the thyroid from iodine exposure, 3000 mSv).

Keywords: RADionuclide, transport, removal, and dose estimation, RADTRAD, symbolic nuclear analysis package, SNAP, dose, PWR.

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Authors: Tawakal Hasnain Baluch, Adnan Masood, Javaid Iqbal, Umer Izhar, Umar Shahbaz Khan

Abstract:

This paper will provide the kinematic and dynamic analysis of a lower limb exoskeleton. The forward and inverse kinematics of proposed exoskeleton is performed using Denevit and Hartenberg method. The torques required for the actuators will be calculated using Lagrangian formulation technique. This research can be used to design the control of the proposed exoskeleton.

Keywords: Dynamic Analysis, Exoskeleton, Kinematic Analysis, Lower Limb, Rehabilitation Robotics

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Authors: K. Paisal

Abstract:

The purposes of this research were (1) to create a learning activity for constructivism, (2) study the Mathematical Analysis courses learning achievement, and (3) study students’ attitude toward the learning activity for constructivism. The samples in this study were divided into 2 parts including 3 Mathematical Analysis courses instructors of Suan Sunandha Rajabhat University who provided basic information and attended the seminar and 17 Mathematical Analysis courses students who were studying in the academic and engaging in the learning activity for constructivism. The research instruments were lesson plans constructivism, subjective Mathematical Analysis courses achievement test with reliability index of 0.8119, and an attitude test concerning the students’ attitude toward the Mathematical Analysis courses learning activity for constructivism. The result of the research show that the efficiency of the Mathematical Analysis courses learning activity for constructivism is 73.05/72.16, which is more than expected criteria of 70/70. The research additionally find that the average score of learning achievement of students who engaged in the learning activities for constructivism are equal to 70% and the students’ attitude toward the learning activity for constructivism are at the medium level.

Keywords: Constructivism, learning management, Mathematical Analysis courses.

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Authors: J. Grira, Y. Bédard, S. Roche

Abstract:

The aim of this research is to design a collaborative framework that integrates risk analysis activities into the geospatial database design (GDD) process. Risk analysis is rarely undertaken iteratively as part of the present GDD methods in conformance to requirement engineering (RE) guidelines and risk standards. Accordingly, when risk analysis is performed during the GDD, some foreseeable risks may be overlooked and not reach the output specifications especially when user intentions are not systematically collected. This may lead to ill-defined requirements and ultimately in higher risks of geospatial data misuse. The adopted approach consists of 1) reviewing risk analysis process within the scope of RE and GDD, 2) analyzing the challenges of risk analysis within the context of GDD, and 3) presenting the components of a risk-based collaborative framework that improves the collection of the intended/forbidden usages of the data and helps geo-IT experts to discover implicit requirements and risks.

Keywords: Collaborative risk analysis, intention of use, Geospatial database design, Geospatial data misuse.

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Authors: Jae-Neung Lee, Sung-Bum Pan, Keun-Chang Kwak

Abstract:

This paper describes an analysis of Yacht Simulator international trends and also explains about Yacht. The results are summarized as follows. Attached to the cockpit are sensors that feed -back information on rudder angle, boat heel angle and mainsheet tension to the computer. Energy expenditure of the sailor measure indirectly using expired gas analysis for the measurement of VO2 and VCO2. At sea course configurations and wind conditions can be preset to suit any level of sailor from complete beginner to advanced sailor.

Keywords: Trends Analysis, Yacht Simulator, Sailing.

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Authors: Ameur Abdelkader, Abed Bouarfa Hafida

Abstract:

Since its inception, predictive analysis has revolutionized the IT industry through its robustness and decision-making facilities. It involves the application of a set of data processing techniques and algorithms in order to create predictive models. Its principle is based on finding relationships between explanatory variables and the predicted variables. Past occurrences are exploited to predict and to derive the unknown outcome. With the advent of big data, many studies have suggested the use of predictive analytics in order to process and analyze big data. Nevertheless, they have been curbed by the limits of classical methods of predictive analysis in case of a large amount of data. In fact, because of their volumes, their nature (semi or unstructured) and their variety, it is impossible to analyze efficiently big data via classical methods of predictive analysis. The authors attribute this weakness to the fact that predictive analysis algorithms do not allow the parallelization and distribution of calculation. In this paper, we propose to extend the predictive analysis algorithm, Classification And Regression Trees (CART), in order to adapt it for big data analysis. The major changes of this algorithm are presented and then a version of the extended algorithm is defined in order to make it applicable for a huge quantity of data.

Keywords: Predictive analysis, big data, predictive analysis algorithms. CART algorithm.

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Authors: D. Hişam, S. İkizoğlu

Abstract:

Identifying the problem behind balance disorder is one of the most interesting topics in medical literature. This study has considerably enhanced the development of artificial intelligence (AI) algorithms applying multiple machine learning (ML) models to sensory data on gait collected from humans to classify between normal people and those suffering from Vestibular System (VS) problems. Although AI is widely utilized as a diagnostic tool in medicine, AI models have not been used to perform feature extraction and identify VS disorders through training on raw data. In this study, three ML models, the Random Forest Classifier (RF), Extreme Gradient Boosting (XGB), and K-Nearest Neighbor (KNN), have been trained to detect VS disorder, and the performance comparison of the algorithms has been made using accuracy, recall, precision, and f1-score. With an accuracy of 95.28 %, Random Forest (RF) Classifier was the most accurate model.

Keywords: Vestibular disorder, machine learning, random forest classifier, k-nearest neighbor, extreme gradient boosting.

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