Search results for: morphological derivations in sensorial patterns

Authors: Seyed Ali Mir Heydari, Mohsen Sayadiharikandeh

Abstract:

Static analysis of source code is used for auditing web applications to detect the vulnerabilities. In this paper, we propose a new algorithm to analyze the PHP source code for detecting LFI and RFI potential vulnerabilities. In our approach, we first define some patterns for finding some functions which have potential to be abused because of unhandled user inputs. More precisely, we use regular expression as a fast and simple method to define some patterns for detection of vulnerabilities. As inclusion functions could be also used in a safe way, there could occur many false positives (FP). The first cause of these FP-s could be that the function does not use a usersupplied variable as an argument. So, we extract a list of usersupplied variables to be used for detecting vulnerable lines of code. On the other side, as vulnerability could spread among the variables like by multi-level assignment, we also try to extract the hidden usersupplied variables. We use the resulted list to decrease the false positives of our method. Finally, as there exist some ways to prevent the vulnerability of inclusion functions, we define also some patterns to detect them and decrease our false positives.

Keywords: User-supplied Variables, hidden user-supplied variables, PHP vulnerabilities.

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Authors: Hanife Genc

Abstract:

This study was conducted to determine sex differentiation of laboratory reared Elm nymphalid (Nymphalis polychloros Linnaeus, 1758) by examining the morphological structure of pupal stage. Laboratory colony of elm nymphalid, reared on pear leaves, was used to set up experiments. It was performed with 5 replications having 8 pupae for each replication. Dorsal, ventral and lateral parts of external morphological structures of pupae were examined by Olympus SZX9 stereozoom microscope and photographed. When fully grown, mature larvae wander the highest part of the rearing cage and pupae were formed hanging by cremaster. After completing prepupa stage about 1.5±0.3 days, they all pupated. Pupal stage was completed at 24±1°C about 4.38±1.20 days. Pupal weights were 0.483±0.05 g in females and 0.392±0.08 g (n=40) in males respectively. Pupal emergence rate was 95%, with 22 females and 16 males. Examinations of ventral parts of 8th, 9th, and 10th abdominal segments revealed that anal opening were found at 10th abdominal segment in both sexes, 3 lumps were determined at 9th abdominal segments then the specific opening structure at 8th segment was only found on female pupae.

Keywords: Butterfly, Nymphalis polychloros, pupae, sex differentiation.

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Authors: M. Kiarna, S. Junjira, S. Casey, M. Nolwazi, M. S. Marcos, A. T. Tatiana, L. Cassandra

Abstract:

This paper details a rebrand design project developed for a non-profitable organization called Te Roopu Waiora (TRW), which is currently located in Auckland, Aotearoa New Zealand. This social enterprise is dedicated to supporting the Māori community living with sensorial, physical and intellectual disabilities (whānau hauā). As part of a year three bachelor design brief, the rebrand project enabled students to reflect on Kaupapa Māori principles and appropriately address the values of the organisation. As such, the methodology used a pragmatic paradigm approach and mixed methods design practices involving a human-centred design to problem solving. As result, the student project culminated in the development in a range of cohesive design artefacts, aiming to improve the rentability and perception of the brand with the audience and stakeholders.

Keywords: Design in Aotearoa New Zealand, Kaupapa Māori, branding, design education, human-centered design.

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Authors: Zhaoyu Chen

Abstract:

In this study, an attempt was made to find reasons why tourists go to particular attractions. Tourists may be either motivated by the attractions or simply make the choice to satisfy their needs and desires. Based on the attractions in Hong Kong, this research was conducted to explore the attraction-related concepts to discuss how the attraction system works. Due to the limited studies on exploring the attractiveness of attractions through tourist movement patterns, the study aims to evaluate such indicators to determine whether tourists are motivated by attractiveness or their own needs. The investigation is conducted through the comparison of different source markets - Mainland China, short haul markets (excluding Mainland China) and long haul markets. The latest finding of Departing Visitor Survey (DVS) implemented by the Hong Kong Tourism Board (HKTB) is employed for the analysis. Various tourist movement patterns are drawn from the practical data. The managerial implication to destination management organizations (DMOs) is suggested to better allocate attractions according to the needs of tourists.

Keywords: Attractions, attraction system, Hong Kong, tourist movement patterns.

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Authors: Simone C. F. Neves, Lúcio F. A. Campos, Ewaldo Santana, Ginalber L. O. Serra, Allan K. Barros

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We propose a method for discrimination and classification of ovarian with benign, malignant and normal tissue using independent component analysis and neural networks. The method was tested for a proteomic patters set from A database, and radial basis functions neural networks. The best performance was obtained with probabilistic neural networks, resulting I 99% success rate, with 98% of specificity e 100% of sensitivity.

Keywords: Cancer ovarian, Proteomic patterns in serum, independent component analysis and neural networks.

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Authors: U. Bottigli, R.Chiarucci, B. Golosio, G.L. Masala, P. Oliva, S.Stumbo, D.Cascio, F. Fauci, M. Glorioso, M. Iacomi, R. Magro, G. Raso

Abstract:

Purpose of this work is to develop an automatic classification system that could be useful for radiologists in the breast cancer investigation. The software has been designed in the framework of the MAGIC-5 collaboration. In an automatic classification system the suspicious regions with high probability to include a lesion are extracted from the image as regions of interest (ROIs). Each ROI is characterized by some features based generally on morphological lesion differences. A study in the space features representation is made and some classifiers are tested to distinguish the pathological regions from the healthy ones. The results provided in terms of sensitivity and specificity will be presented through the ROC (Receiver Operating Characteristic) curves. In particular the best performances are obtained with the Neural Networks in comparison with the K-Nearest Neighbours and the Support Vector Machine: The Radial Basis Function supply the best results with 0.89 ± 0.01 of area under ROC curve but similar results are obtained with the Probabilistic Neural Network and a Multi Layer Perceptron.

Keywords: Neural Networks, K-Nearest Neighbours, Support Vector Machine, Computer Aided Detection

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Authors: Jun Seok Kim, Cheong-Sool Park, Jun-Geol Baek, Sung-Shick Kim

Abstract:

Control chart pattern recognition is one of the most important tools to identify the process state in statistical process control. The abnormal process state could be classified by the recognition of unnatural patterns that arise from assignable causes. In this study, a wavelet based neural network approach is proposed for the recognition of control chart patterns that have various characteristics. The procedure of proposed control chart pattern recognizer comprises three stages. First, multi-resolution wavelet analysis is used to generate time-shape and time-frequency coefficients that have detail information about the patterns. Second, distance based features are extracted by a bi-directional Kohonen network to make reduced and robust information. Third, a back-propagation network classifier is trained by these features. The accuracy of the proposed method is shown by the performance evaluation with numerical results.

Keywords: Control chart pattern recognition, Multi-resolution wavelet analysis, Bi-directional Kohonen network, Back-propagation network, Feature extraction.

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Authors: Ho-Dae Chong, Jong-Kil Kim

Abstract:

Collaborative research has become more prevalent and important across disciplines because it stimulates innovation and interaction between scholars. Seeing as existing studies relatively disregarded the institutional conditions triggering collaborative research, this work aims to analyze the changing trend in collaborative work patterns among Korean social scientists. The focus of this research is the performance of social scientists who received research grants through the government’s Social Science Korea (SSK) program. Using quantitative statistical methods, collaborative research patterns in a total of 2,354 papers published under the umbrella of the SSK program in peer-reviewed scholarly journals from 2013 to 2016 were examined to identify changing trends and triggering factors in collaborative research. A notable finding is that the share of collaborative research is overwhelmingly higher than that of individual research. In particular, levels of collaborative research surpassed 70%, increasing much quicker compared to other research done in the social sciences. Additionally, the most common composition of collaborative research was for two or three researchers to conduct joint research as coauthors, and this proportion has also increased steadily. Finally, a strong association between international journals and co-authorship patterns was found for the papers published by SSK program researchers from 2013 to 2016. The SSK program can be seen as the driving force behind collaboration between social scientists. Its emphasis on competition through a merit-based financial support system along with a rigorous evaluation process seems to have influenced researchers to cooperate with those who have similar research interests.

Keywords: Co-authorship, collaboration, competition, cooperation, Social Science Korea, policy.

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Authors: F. J. Sowiński, M. Dziubiński

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In the study the influence of the physical-chemical properties of a liquid, the width of a channel gap and the superficial liquid and gas velocities on the patterns formed during two phase flows in vertical, narrow mini-channels was investigated. The research was performed in the channels of rectangular cross-section and of dimensions: 15 x 0.65 mm and 7.5 x 0.73 mm. The experimental data were compared with the published criteria of the transitions between the patterns of two-phase flows.

Keywords: Two-phase flow, flow regimes, mini-channel, viscosity.

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Authors: Ashwag O. Maghraby, Nida N. Khan, Hosnia A. Ahmed, Ghufran N. Brohi, Hind F. Assouli, Jawaher S. Melibari

Abstract:

The Arabic language is one of the most important languages. Learning it is so important for many people around the world because of its religious and economic importance and the real challenge lies in practicing it without grammatical or syntactical mistakes. This research focused on detecting and correcting the syntactic mistakes of Arabic syntax according to their position in the sentence and focused on two of the main syntactical rules in Arabic: Dual and Plural. It analyzes each sentence in the text, using Stanford CoreNLP morphological analyzer and machine-learning approach in order to detect the syntactical mistakes and then correct it. A prototype of the proposed system was implemented and evaluated. It uses support vector machine (SVM) algorithm to detect Arabic grammatical errors and correct them using the rule-based approach. The prototype system has a far accuracy 81%. In general, it shows a set of useful grammatical suggestions that the user may forget about while writing due to lack of familiarity with grammar or as a result of the speed of writing such as alerting the user when using a plural term to indicate one person.

Keywords: Arabic Language acquisition and learning, natural language processing, morphological analyzer, part-of-speech.

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Authors: Suwimon Saneewong Na Ayuttaya, Chainarong Chaktranond, Phadungsak Rattanadecho

Abstract:

This study numerically investigates the effects of Electrohydrodynamic on flow patterns and heat transfer enhancement within a cavity which is on the lower wall of channel. In this simulation, effects of using ground wire and ground plate on the flow patterns are compared. Moreover, the positions of electrode wire respecting with ground are tested in the range of angles θ = 0 - 180^o. High electrical voltage exposes to air is 20 kV. Bulk mean velocity and temperature of inlet air are controlled at 0.1 m/s and 60 ^OC, respectively. The result shows when electric field is applied, swirling flow is appeared in the channel. In addition, swirling flow patterns in the main flow of using ground plate are widely spreader than that of using ground wire. Moreover, direction of swirling flow also affects the flow pattern and heat transfer in a cavity. These cause the using ground wire to give the maximum temperature and heat transfer higher than using ground plate. Furthermore, when the angle is at θ = 60^o, high shear flow effect is obtained. This results show high strength of swirling flow and effective heat transfer enhancement.

Keywords: Swirling Flow, Heat Transfer, Electrohydrodynamic, Numerical Analysis.

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Authors: Hasmik P. Ter-Voskanyan

Abstract:

The account of genus Polygonum L. in "Flora of Armenia" was made more than five decades ago. After that many expeditions have been carried out in different regions of Armenia and a huge herbarium material has been collected. The genus included 5 sections with 20 species. Since then many authors accepted the sections as separate genera on the basis of anatomical, morphological, palynological and molecular data. According to the above mentioned it became clear, that the taxonomy of Armenian representatives of Polygonum s. l. also needs revision. New literature data and our investigations of live and herbarium material (ERE, LE) with specification of the morphological characters, distribution, ecology, flowering and fruiting terms brought us to conclusion, that genus Polygonum s. l. has to be split into 5 different genera (Aconogonon (Meisn.) Reichenb., Bistorta (L.) Scop., Fallopia Adans., Persicaria Mill., Polygonum L. s. s.). The number of species has been reduced to 16 species. For each genus new determination keys has been created. 

Keywords: Aconogonon (Meisn.) Reichenb., Bistorta (L.) Scop., Fallopia Adans., Persicaria Mill., Polygonum L. s. s., Flora of Armenia.

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Authors: Susana Matos, António Pinto, Conceição Castilho, Paula Reis Correia, António Cardoso Monteiro

Abstract:

Yogurts are prepared by fermenting milk with bacterial cultures consisting of a mixture of Streptococcus ssp. thermophilus and Lactobacillus delbrueckii ssp. bulgaricus. The main aim of this investigation was to develop a majority goat yogurt, with the addition of sheep milk in order to have a final product with good physicochemical quality properties and sensorial attributes. Four types of yogurts were prepared presenting the following proportion of goat and sheep milk respectively: C100 – 100%; C80 – 80%/20%; C60 – 60%/40%; C50 – 50%/50%. The goat milk was from the Serrana Jarmelista breed and the sheep milk from the Serra da Estrela breed. The inclusion of sheep milk improved attractiveness to consumers, and it also improved the nutritional value of the product, mainly the fatty acid and mineral contents. The C50 yogurt was preferred by 28% of the panellists, followed by the C100 with 16%  and the commercial cow yogurt was 40% of preferences.

Keywords: Goat, sheep, yogurt.

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Authors: Katalina Grigorova, Kaloyan Mironov

Abstract:

The paper focuses on the benefits of business process modeling. Although this discipline is developing for many years, there is still necessity of creating new opportunities to meet the ever increasing users’ needs. Because one of these needs is related to the conversion of business process models from one standard to another, the authors have developed a converter between BPMN and EPC standards using workflow patterns as intermediate tool. Nowadays there are too many systems for business process modeling. The variety of output formats is almost the same as the systems themselves. This diversity additionally hampers the conversion of the models. The presented study is aimed at discussing problems due to differences in the output formats of various modeling environments.

Keywords: Business process modeling, business process modeling standards, workflow patterns, converting models.

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Authors: Claudia Camargo, Enrique J. de la Vega, Jesús E. Olguín, Juan A. López, Sandra K. Enríquez

Abstract:

This study focuses on the application of sensory thermography, as a non-invasive method to evaluate the musculoskeletal injuries that industry workers performing Highly Repetitive Movements (HRM) may acquire. It was made at a wireless company having the target of analyze temperatures in worker’s wrists, elbows and shoulders in workstations during their activities, this thru sensorial thermography with the goal of detecting maximum temperatures (Tmax) that could indicate possible injuries. The tests were applied during 3 hours for only 2 workers that work in workstations where there’s been the highest index of injuries and accidents. We were made comparisons for each part of the body that were study for both because of the similitude between the activities of the workstations; they were requiring both an immediate evaluation. The Tmax was recorder during the test of the worker 2, in the left wrist, reaching a temperature of 35.088ºC and with a maximum increase of 1.856°C

Keywords: Highly Repetitive Movements (HRM), Maximum temperatures (Tmax), Worker.

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Authors: Jia-Rong Yeh, Tzu-Yu Lin, Jiann-Shing Shieh, Yun Chen

Abstract:

A mammal-s body can be seen as a blood vessel with complex tunnels. When heart pumps blood periodically, blood runs through blood vessels and rebounds from walls of blood vessels. Blood pressure signals can be measured with complex but periodic patterns. When an artery is clamped during a surgical operation, the spectrum of blood pressure signals will be different from that of normal situation. In this investigation, intestinal artery clamping operations were conducted to a pig for simulating the situation of intestinal blocking during a surgical operation. Similarity theory is a convenient and easy tool to prove that patterns of blood pressure signals of intestinal artery blocking and unblocking are surely different. And, the algorithm of Hilbert Huang Transform can be applied to extract the character parameters of blood pressure pattern. In conclusion, the patterns of blood pressure signals of two different situations, intestinal artery blocking and unblocking, can be distinguished by these character parameters defined in this paper.

Keywords: Blood pressure, spectrum, intestinal artery, similarity theory and Hilbert Huang Transform.

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Authors: Yuan-Hsiang Chang, Zhong-Xian Peng, Li-Der Jeng

Abstract:

Music has always been an integral part of human’s daily lives. But, for the most people, reading musical score and turning it into melody is not easy. This study aims to develop an Automatic music score recognition system using digital image processing, which can be used to read and analyze musical score images automatically. The technical approaches included: (1) staff region segmentation; (2) image preprocessing; (3) note recognition; and (4) accidental and rest recognition. Digital image processing techniques (e.g., horizontal /vertical projections, connected component labeling, morphological processing, template matching, etc.) were applied according to musical notes, accidents, and rests in staff notations. Preliminary results showed that our system could achieve detection and recognition rates of 96.3% and 91.7%, respectively. In conclusion, we presented an effective automated musical score recognition system that could be integrated in a system with a media player to play music/songs given input images of musical score. Ultimately, this system could also be incorporated in applications for mobile devices as a learning tool, such that a music player could learn to play music/songs.

Keywords: Connected component labeling, image processing, morphological processing, optical musical recognition.

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Authors: Affordability, Expenditure Patterns towards Sustainable Consumption in Malaysia

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Safe drinking water is needed for survival. Households have to pay the water bill monthly. However, lower income households are sometimes unable to afford the cost. This study examines water access and affordability among households in Malaysia and the determinants of water affordability using cross-sectional data and multiple regression. The paper expects that the bill for basic water consumption is inversely related to average income. This means that policy makers need to redesign the water tariff to improve the quality of life of lower income households.

Keywords: Affordability, households, income, water tariff.

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Authors: Giovanni Luca Masala

Abstract:

Pattern recognition is the research area of Artificial Intelligence that studies the operation and design of systems that recognize patterns in the data. Important application areas are image analysis, character recognition, fingerprint classification, speech analysis, DNA sequence identification, man and machine diagnostics, person identification and industrial inspection. The interest in improving the classification systems of data analysis is independent from the context of applications. In fact, in many studies it is often the case to have to recognize and to distinguish groups of various objects, which requires the need for valid instruments capable to perform this task. The objective of this article is to show several methodologies of Artificial Intelligence for data classification applied to biomedical patterns. In particular, this work deals with the realization of a Computer-Aided Detection system (CADe) that is able to assist the radiologist in identifying types of mammary tumor lesions. As an additional biomedical application of the classification systems, we present a study conducted on blood samples which shows how these methods may help to distinguish between carriers of Thalassemia (or Mediterranean Anaemia) and healthy subjects.

Keywords: Computer Aided Detection, mammary tumor, pattern recognition, dissimilarity

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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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Authors: H. W. Ker

Abstract:

Longitudinal data typically have the characteristics of changes over time, nonlinear growth patterns, between-subjects variability, and the within errors exhibiting heteroscedasticity and dependence. The data exploration is more complicated than that of cross-sectional data. The purpose of this paper is to organize/integrate of various visual-graphical techniques to explore longitudinal data. From the application of the proposed methods, investigators can answer the research questions include characterizing or describing the growth patterns at both group and individual level, identifying the time points where important changes occur and unusual subjects, selecting suitable statistical models, and suggesting possible within-error variance.

Keywords: Data exploration, exploratory analysis, HLMs/LMEs, longitudinal data, visual-graphical methods.

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Authors: O. Zimbili, W. Salim, M. Ndambuki

Abstract:

Construction and Demolition (C&D) wastes contribute the highest percentage of wastes worldwide (75%). Furthermore, ceramic materials contribute the highest percentage of wastes within the C&D wastes (54%). The current option for disposal of ceramic wastes is landfill. This is due to unavailability of standards, avoidance of risk, lack of knowledge and experience in using ceramic wastes in construction. The ability of ceramic wastes to act as a pozzolanic material in the production of cement has been effectively explored. The results proved that temperatures used in the manufacturing of these tiles (about 900⁰C) are sufficient to activate pozzolanic properties of clay. They also showed that, after optimization (11-14% substitution); the cement blend performs better, with no morphological difference between the cement blended with ceramic waste, and that blended with other pozzolanic materials. Sanitary ware and electrical insulator porcelain wastes are some wastes investigated for usage as aggregates in concrete production. When optimized, both produced good results, better than when natural aggregates are used. However, the research on ceramic wastes as partial substitute for fine aggregates or cement has not been overly exploited as the other areas. This review has been concluded with focus on investigating whether ceramic wall tile wastes used as partial substitute for cement and fine aggregates could prove to be beneficial since the two materials are the most high-priced during concrete production.

Keywords: Blended, morphological, pozzolanic properties, waste.

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Authors: P. Sengottuvelan, T. Gopalakrishnan

Abstract:

Web Usage Mining is the application of data mining techniques to find usage patterns from web log data, so as to grasp required patterns and serve the requirements of Web-based applications. User’s expertise on the internet may be improved by minimizing user’s web access latency. This may be done by predicting the future search page earlier and the same may be prefetched and cached. Therefore, to enhance the standard of web services, it is needed topic to research the user web navigation behavior. Analysis of user’s web navigation behavior is achieved through modeling web navigation history. We propose this technique which cluster’s the user sessions, based on the K-medoids technique.

Keywords: Clustering, K-medoids, Recommendation, User Session, Web Usage Mining.

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Authors: K. Hosseini, MD., R. Mazaheri, MD., H.R. Khoddami Vishteh, MD., M.A. Mansournia, MD., H. Angoorani, MD

Abstract:

Background: Tissue Doppler Echocardiography (TDE) assesses diastolic function more accurately than routine pulse Doppler echo. Assessment of the effects of dynamic and static exercises on the heart by using TDE can provides new information about the athlete-s heart syndrome. Methods: This study was conducted on 20 elite wrestlers, 14 endurance runners at national level and 21 non-athletes as the control group. Participants underwent two-dimensional echocardiography, standard Doppler and TDE. Results: Wrestlers had the highest left ventricular mass index, enddiastolic inter-ventricular septum thickness and left ventricular Posterior wall thickness. Runners had the highest Left ventricular end-diastolic volume, LV ejection fraction, stroke volume and cardiac output. In TDE, the early diastolic velocity of mitral annulus to the late diastolic velocity ratio in athletic groups was greater than the controls with no significant difference. Conclusion: In spite of cardiac morphological changes in athletes, TDE shows that cardiac diastolic function won-t be adversely affected.

Keywords: Tissue Doppler Echocardiography, Diastolic function, Athlete's heart syndrome, Static exercise, Dynamic exercise

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Authors: Giovanni Luca Masala

Abstract:

Pattern recognition is the research area of Artificial Intelligence that studies the operation and design of systems that recognize patterns in the data. Important application areas are image analysis, character recognition, fingerprint classification, speech analysis, DNA sequence identification, man and machine diagnostics, person identification and industrial inspection. The interest in improving the classification systems of data analysis is independent from the context of applications. In fact, in many studies it is often the case to have to recognize and to distinguish groups of various objects, which requires the need for valid instruments capable to perform this task. The objective of this article is to show several methodologies of Artificial Intelligence for data classification applied to biomedical patterns. In particular, this work deals with the realization of a Computer-Aided Detection system (CADe) that is able to assist the radiologist in identifying types of mammary tumor lesions. As an additional biomedical application of the classification systems, we present a study conducted on blood samples which shows how these methods may help to distinguish between carriers of Thalassemia (or Mediterranean Anaemia) and healthy subjects.

Keywords: Computer Aided Detection, mammary tumor, pattern recognition, thalassemia.

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Authors: Taher M. Abou-deif, Mahmoud A. Fouad, Essam E. Khalil

Abstract:

The present paper was concerned primarily with the analysis, simulation of the air flow and thermal patterns in a lecture room. The paper is devoted to numerically investigate the influence of location and number of ventilation and air conditioning supply and extracts openings on air flow properties in a lecture room. The work focuses on air flow patterns, thermal behaviour in lecture room where large number of students. The effectiveness of an air flow system is commonly assessed by the successful removal of sensible and latent loads from occupants with additional of attaining air pollutant at a prescribed level to attain the human thermal comfort conditions and to improve the indoor air quality; this is the main target during the present paper. The study is carried out using computational fluid dynamics (CFD) simulation techniques as embedded in the commercially available CFD code (FLUENT 6.2). The CFD modelling techniques solved the continuity, momentum and energy conservation equations in addition to standard k – ε model equations for turbulence closure. Throughout the investigations, numerical validation is carried out by way of comparisons of numerical and experimental results. Good agreement is found among both predictions.

Keywords: Air Conditioning, CFD, Lecture Rooms, Thermal Comfort

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Authors: Nittaya Kerdprasop, Kittisak Kerdprasop

Abstract:

Data mining (DM) is the process of finding and extracting frequent patterns that can describe the data, or predict unknown or future values. These goals are achieved by using various learning algorithms. Each algorithm may produce a mining result completely different from the others. Some algorithms may find millions of patterns. It is thus the difficult job for data analysts to select appropriate models and interpret the discovered knowledge. In this paper, we describe a framework of an intelligent and complete data mining system called SUT-Miner. Our system is comprised of a full complement of major DM algorithms, pre-DM and post-DM functionalities. It is the post-DM packages that ease the DM deployment for business intelligence applications.

Keywords: Business intelligence, data mining, functionalprogramming, intelligent system.

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Authors: M. Sharanreddy, P. K. Kulkarni

Abstract:

Brain tumor is inherently serious and life-threatening disease. Brain tumor builds the intracranial pressure in the brain, by shifting the brain or pushing against the skull, and also damaging nerves and healthy brain tissues. This intracranial pressure affects and interferes with normal brain functionality, which results in generation of abnormal electrical activities from brain. With recent development in the medical engineering and instruments, EEG instruments are able to record the brain electric activities with high accuracy, which establishes EEG as a primary tool for diagnosing the brain abnormalities. Research scholars and general physicians, often face difficulty in understanding EEG patterns. This paper presents the EEG patterns associated with brain tumor by combing medicine theory and neurologist experience. Paper also explains the pros-cons of the EEG based brain tumor identification.

Keywords: Brain tumor, Electroencephalogram (EEG).

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Authors: A. I. A. Rahman, Sh-Hussain Salleh, K. Ahmad, K. Anuar

Abstract:

Analysis of vocal fold vibration is essential for understanding the mechanism of voice production and for improving clinical assessment of voice disorders. This paper presents a Dynamic Time Warping (DTW) based approach to analyze and objectively classify vocal fold vibration patterns. The proposed technique was designed and implemented on a Glottal Area Waveform (GAW) extracted from high-speed laryngeal images by delineating the glottal edges for each image frame. Feature extraction from the GAW was performed using Linear Predictive Coding (LPC). Several types of voice reference templates from simulations of clear, breathy, fry, pressed and hyperfunctional voice productions were used. The patterns of the reference templates were first verified using the analytical signal generated through Hilbert transformation of the GAW. Samples from normal speakers’ voice recordings were then used to evaluate and test the effectiveness of this approach. The classification of the voice patterns using the technique of LPC and DTW gave the accuracy of 81%.

Keywords: Dynamic Time Warping, Glottal Area Waveform, Linear Predictive Coding, High-Speed Laryngeal Images, Hilbert Transform.

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Authors: Yogi Satrya Aryadinata, Anne Laurent, Michel Sala

Abstract:

Gradual patterns have been studied for many years as they contain precious information. They have been integrated in many expert systems and rule-based systems, for instance to reason on knowledge such as “the greater the number of turns, the greater the number of car crashes”. In many cases, this knowledge has been considered as a rule “the greater the number of turns → the greater the number of car crashes” Historically, works have thus been focused on the representation of such rules, studying how implication could be defined, especially fuzzy implication. These rules were defined by experts who were in charge to describe the systems they were working on in order to turn them to operate automatically. More recently, approaches have been proposed in order to mine databases for automatically discovering such knowledge. Several approaches have been studied, the main scientific topics being: how to determine what is an relevant gradual pattern, and how to discover them as efficiently as possible (in terms of both memory and CPU usage). However, in some cases, end-users are not interested in raw level knowledge, and are rather interested in trends. Moreover, it may be the case that no relevant pattern can be discovered at a low level of granularity (e.g. city), whereas some can be discovered at a higher level (e.g. county). In this paper, we thus extend gradual pattern approaches in order to consider multiple level gradual patterns. For this purpose, we consider two aggregation policies, namely horizontal and vertical.

Keywords: Gradual Pattern.

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