Search results for: task

Authors: Jawdat Goussous, Samer Abu Ghazaleh

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Heritage is closely linked with the national identity and because Jordan is a rich country of heritage where many civilizations had lived from early beginning of history ,therefore the conservation of this heritage is national task that gives many benefits as correlation between local inhabitance and enhance the linked with spirit of place . This study takes into account the most important concentration on some of old hospitals in Jordan ,which were constructed between 1890-1950 ,looking in their historical and architectural heritage values gained by their architectural distinguished ,longevity and their linked with events that happened in the region. then Focus on the study and analysis of some of them in terms of conservation methodology that have been followed to conserve the early hospitals such as preservation ,maintenance ,adaptive reuse , And their positive effects on these buildings, emphasize the importance of these buildings because of their historical and architectural values.

Keywords: evangelical missionary, early hospitals, medical services, renovation

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Authors: Tharini N. de Silva, Xiao Zhibo, Zhao Rui, Mao Kezhi

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Causal relation identification is a crucial task in information extraction and knowledge discovery. In this work, we present two approaches to causal relation identification. The first is a classification model trained on a set of knowledge-based features. The second is a deep learning based approach training a model using convolutional neural networks to classify causal relations. We experiment with several different convolutional neural networks (CNN) models based on previous work on relation extraction as well as our own research. Our models are able to identify both explicit and implicit causal relations as well as the direction of the causal relation. The results of our experiments show a higher accuracy than previously achieved for causal relation identification tasks.

Keywords: causal realtion extraction, relation extracton, convolutional neural network, text representation

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Authors: Cesar Ferreira Amorim, Tamotsu Hirata, Runer Augusto Marson

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The purpose of this study was to determine the effect of strength ramp isometric contraction on changes in surface electromyography (sEMG) signal characteristics of the hamstrings muscles. All measurements were obtained from 20 healthy well trained healthy adults (age 19.5 ± 0.8 yrs, body mass 63.4 ± 1.5 kg, height: 1.65 ± 0.05 m). Subjects had to perform isometric ramp contractions in knee flexion with the force gradually increasing from 0 to 40% of the maximal voluntary contraction (MVC) in a 20s period. The root mean square (RMS) amplitude of sEMG signals obtained from the biceps femoris (caput longum) were calculated at four different strength levels (10, 20, 30, and 40% MVC) from the ramp isometric contractions (5s during the 20s task %MVC). The main results were a more pronounced increase non-linear in sEMG-RMS amplitude for the muscles. The protocol described here may provide a useful index for measuring of strength neuromuscular fatigue.

Keywords: biosignal, surface electromyography, ramp contractions, strength

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Authors: Abdelhak-Djamel Seriai, Selim Kebir, Allaoua Chaoui

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During the last decades, object oriented program- ming has been massively used to build large-scale systems. However, evolution and maintenance of such systems become a laborious task because of the lack of object oriented programming to offer a precise view of the functional building blocks of the system. This lack is caused by the fine granularity of classes and objects. In this paper, we use a post object-oriented technology namely software components, to propose an approach based on the identification of the functional building blocks of an object oriented system by analyzing its source code. These functional blocks are specified as software components and the result is a multi-layer component based software architecture.

Keywords: software comprehension, software component, object oriented, software architecture, reverse engineering

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Authors: Mario Kubek, Herwig Unger

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Due to the large amount of information in the World Wide Web (WWW, web) and the lengthy and usually linearly ordered result lists of web search engines that do not indicate semantic relationships between their entries, the search for topically similar and related documents can become a tedious task. Especially, the process of formulating queries with proper terms representing specific information needs requires much effort from the user. This problem gets even bigger when the user's knowledge on a subject and its technical terms is not sufficient enough to do so. This article presents the new and interactive search application DocAnalyser that addresses this problem by enabling users to find similar and related web documents based on automatic query formulation and state-of-the-art search word extraction. Additionally, this tool can be used to track topics across semantically connected web documents

Keywords: DocAnalyser, interactive web search, search word extraction, query formulation, source topic detection, topic tracking

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Authors: Jaiden X. Schraut

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Medical Imaging Segmentation of Chest X-rays is used for the purpose of identification and differentiation of lung cancer, pneumonia, COVID-19, and similar respiratory diseases. Widespread application of computer-supported perception methods into the diagnostic pipeline has been demonstrated to increase prognostic accuracy and aid doctors in efficiently treating patients. Modern models attempt the task of segmentation and classification separately and improve diagnostic efficiency; however, to further enhance this process, this paper proposes a multi-output network that follows a U-Net architecture for image segmentation output and features an additional CNN module for auxiliary classification output. The proposed model achieves a final Jaccard Index of .9634 for image segmentation and a final accuracy of .9600 for classification on the COVID-19 radiography database.

Keywords: chest X-ray, deep learning, image segmentation, image classification

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Authors: Mohsine Khazrouni

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The present study is an attempt to highlight the importance of adaptation in translation. To convey the message, the translator needs to take into account not only the text but also extra-linguistic factors such as the target audience. The present paper claims that adaptation is an unavoidable translation strategy when dealing with texts that are heavy with religious and cultural themes. The translation task becomes even more challenging when dealing with children’s literature as the audience are children whose comprehension, experience and world knowledge are limited. The study uses the Arabic translation of the short story ‘Christmas Every Day’ as a case study. The short story will be translated, and the pragmatic problems involved will be discussed. The focus will be on the issue of adaptation. i.e., the source text should be adapted to the target language audience`s social and cultural environment.

Keywords: pragmatic adaptation, Arabic translation, children's literature, equivalence

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Authors: Prakher Mishra, Dikshant Bodana, Saloni Desai, Sudhanshu Dixit, Sopan Agarwal, Shriraj Patel

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Railways are sometimes lifeline of nations as they consist of huge network of rail lines and bridges. Reportedly many of the bridges are aging, weak, distressed and accident prone. It becomes a really challenging task for Engineers and workers to keep up a regular maintenance schedule for proper functioning which itself is quite a hard hitting job. In this paper we have come up with an innvovative wireless system of maintenance called BriMAIN. In this system we have installed two types of sensors, first one is called a force sensor which will continously analyse the readings of pressure at joints of the bridges and secondly an MPU-6050 triaxial gyroscope+accelerometer which will analyse the deflection of the deck of the bridge. Apart from this a separate database is also being made at the server room so that the data can be visualized by the engineers and a warning can be issued in case reading of the sensors goes above threshold.

Keywords: Accelerometer, B-MAIN, Gyroscope, MPU-6050

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Authors: Abdelkrim Belhaoua, Jean-Pierre Radoux

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In France, the railway network is one of the main transport infrastructures and is the second largest European network. Therefore, railway inspection is an important task in railway maintenance to ensure safety for passengers using significant means in personal and technical facilities. Artificial vision has recently been applied to several railway applications due to its potential to improve the efficiency and accuracy when analyzing large databases of acquired images. In this paper, we present a vision system able to detect fastening elements based on artificial vision approach. This system acquires railway images using a CCD camera installed under a control carriage. These images are stitched together before having processed. Experimental results are presented to show that the proposed method is robust for detection fasteners in a complex environment.

Keywords: computer vision, image processing, railway inspection, image stitching, fastener recognition, neural network

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Authors: Khaled Jaber

Abstract:

The estimation of effort in software development is a complex task. The traditional Waterfall approach used to develop software systems requires a lot of time to estimate the effort needed to implement user requirements. Agile manifesto, however, is currently more used in the industry than the Waterfall to develop software systems. In Agile, the user requirement is referred to as a user story. Agile teams mostly use the Fibonacci sequence 1, 2, 3, 5, 8, 11, etc. in estimating the effort needed to implement the user story. This work shows through analysis that the Arithmetic sequence, e.g., 3, 6, 9, 12, etc., is more effective than the Fibonacci sequence in estimating the user stories. This paper mathematically and visually proves the effectiveness of the Arithmetic sequence over the FB sequence.

Keywords: agie, scrum, estimation, fibonacci sequence

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Authors: Pengchao Wei, Xiangzhong Fang

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Noise is ubiquitous in this world. Denoising is an essential technology, especially in image semantic segmentation, where noises are generally categorized into two main types i.e. feature noise and label noise. The main focus of this paper is aiming at modeling label noise, investigating the behaviors of different types of label noise on image semantic segmentation tasks using K-Nearest-Neighbor and Convolutional Neural Network classifier. The performance without label noise and with is evaluated and illustrated in this paper. In addition to that, the influence of feature noise on the image semantic segmentation task is researched as well and a feature noise reduction method is applied to mitigate its influence in the learning procedure.

Keywords: convolutional neural network, denoising, feature noise, image semantic segmentation, k-nearest-neighbor, label noise

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Authors: A. Elbyed

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Nowadays, ontologies are used for achieving a common understanding within a user community and for sharing domain knowledge. However, the de-centralized nature of the web makes indeed inevitable that small communities will use their own ontologies to describe their data and to index their own resources. Certainly, accessing to resources from various ontologies created independently is an important challenge for answering end user queries. Ontology mapping is thus required for combining ontologies. However, mapping complete ontologies at run time is a computationally expensive task. This paper proposes a system in which mappings between concepts may be generated dynamically as the concepts are encountered during user queries. In this way, the interaction itself defines the context in which small and relevant portions of ontologies are mapped. We illustrate application of the proposed system in the context of Technology Enhanced Learning (TEL) where learners need to access to learning resources covering specific concepts.

Keywords: resources query, ontologies, ontology mapping, similarity measures, semantic web, e-learning

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Authors: Beste Kaysı, Yasemin Topaloğlu

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Usability is one of the most important quality attributes for web-based information systems. Specifically, for e-commerce applications, usability becomes more prominent. In this study, we aimed to explore the features that experienced users seek in e-commerce applications. We used eye tracking method in evaluations. Eye movement data are obtained from the eye-tracking method and analyzed based on task completion time, number of fixations, as well as heat map and gaze plot measures. The results of the analysis show that the eye movements of participants' are too static in certain areas and their areas of interest are scattered in many different places. It has been determined that this causes users to fail to complete their transactions. According to the findings, we outlined the issues to improve the usability of e-commerce websites. Then we propose solutions to identify the issues. In this way, it is expected that e-commerce sites will be developed which will make experienced users more satisfied.

Keywords: e-commerce websites, eye tracking method, usability, website evaluations

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Authors: Adesuwa Omorede, Rufai Haruna Kilu

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Affective motivation (motivation that is emotionally laden usually related to affect, passion, emotions, moods) in the workplace stimulates individuals to reinforce, persist and commit to their task, which leads to the individual and organizational performance. This leads individuals to reach goals especially in situations where task are highly challenging and hostile. In such situations, individuals are more disposed to be more creative, innovative and see new opportunities from the loopholes in their workplace. However, when individuals feel displaced and less important, an adverse reaction may suffice which may be detrimental to the organization and its performance. One sector where affective motivation is eminently present and relevant, is the mining industry. Due to its intense work environment; mostly dominated by men and masculinity cultures; and deliberate exclusion of women in this environment which, makes the women working in these environments to feel marginalized. In Ghana, the mining industry is mostly seen as a very physical environment especially underground and mostly considerd as 'no place for a woman'. Despite the fact that these women feel less 'needed' or 'appreciated' in such environments, they still have to juggle between intense work shifts; face violence and other health risks with their families, which put a strain on their affective motivational reaction. Beyond these challenges, however, several mining companies in Ghana today are working towards providing a fair and equal working situation for both men and women miners, by recognizing them as key stakeholders, as well as including them in the stages of mining projects from the planning and designing phase to the evaluation and implementation stage. Drawing from the psychology and gender literature, this study takes a narrative approach to identify and understand the shifting gender dynamics within the mine works in Ghana, occasioning a change in background disposition of miners, which leads to more women taking up mine jobs in the country. In doing so, a qualitative study was conducted using semi-structured interviews from Ghana. Several women working within the mining industries in Ghana shared their experiences and how they felt and still feel in their workplace. In addition, archival documents were gathered to support the findings. The results suggest a change in enrolment regimes in a mining and technology university in Ghana, making room for a more gender equal enrolments in the university. A renowned university that train and feed mine work professional into the industry. The results further acknowledge gender equal and diversity recruitment policies and initiatives among the mining companies of Ghana. This study contributes to the psychology and gender literature by highlighting the hindrances women face in the mining industry as well as highlighting several of their affective reactions towards gender inequality. The study also provides several suggestions for decision makers in the mining industry of what can be done in the future to reduce the gender inequality gap within the industry.

Keywords: affective motivation, gender shape shifting, mining industry, women miners

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Authors: Agata Matuszewska, Małgorzata Syczewska

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The movement of the upper limbs contributes significantly to balance control while walking in humans. However, the impact of different arm swing modes on gait stability is yet to be determined. This work intends to establish numerical parameters for assessing the arm swing. Nineteen people, comprising fifteen young, healthy individuals, two middle-aged individuals, and two individuals with dysfunctions, were analyzed using the movement analysis system. Proposed parameters such as ASᵢₐ (reflecting the arm swing amplitude) and Pearson’s correlation coefficient between the right and left upper limbs can be used to classify the type of movement task each participant performs. The results indicate that the ASᵢₐ parameter could potentially detect any abnormalities in upper limb functions, which may be due to musculoskeletal disorders or other malfunctions.

Keywords: arm swing, human balance, interlimb coordination, motion analysis system

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Authors: Usamah Al-Ali

Abstract:

We explore the effect of expanding space on the exoticity of the matter supporting a traversable Lorentzian wormhole of zero radial tide whose line element is given by ds2 = dt^2 − a^2(t)[ dr^2/(1 − kr2 −b(r)/r)+ r2dΩ^2 in the context of General Relativity. This task is achieved by deriving the Einstein field equations for anisotropic matter field corresponding to the considered cosmological wormhole metric and performing a classification of their solutions on the basis of a variable equations of state (EoS) of the form p = ω(r)ρ. Explicit forms of the shape function b(r) and the scale factor a(t) arising in the classification are utilized to construct the corresponding energy-momentum tensor where the energy conditions for each case is investigated. While the violation of energy conditions is inevitable in case of static wormholes, the classification we performed leads to interesting solutions in which this violation is either reduced or eliminated.

Keywords: general relativity, Einstein field equations, energy conditions, cosmological wormhole

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Authors: Nouha Khediri, Mohammed Ben Ammar, Monji Kherallah

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Recently, facial emotion recognition (FER) has become increasingly essential to understand the state of the human mind. Accurately classifying emotion from the face is a challenging task. In this paper, we present a facial emotion recognition approach named CV-FER, benefiting from deep learning, especially CNN and VGG16. First, the data is pre-processed with data cleaning and data rotation. Then, we augment the data and proceed to our FER model, which contains five convolutions layers and five pooling layers. Finally, a softmax classifier is used in the output layer to recognize emotions. Based on the above contents, this paper reviews the works of facial emotion recognition based on deep learning. Experiments show that our model outperforms the other methods using the same FER2013 database and yields a recognition rate of 92%. We also put forward some suggestions for future work.

Keywords: CNN, deep-learning, facial emotion recognition, machine learning

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Authors: Jonali Baruah, Keesha Green

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This experimental study examines the effects of anonymity in video meeting groups across the stages of innovation (idea generation, selection, and refinement) on various measures of creativity. A sample of 92 undergraduate students participated in small groups of three to four members to complete creativity, decision-making, and idea-refinement task in either anonymous or identified conditions. The study followed two anonymity (anonymous and identified) X 3 stages of innovation (idea generation, idea selection, and idea refinement) in a mixed factorial design. Results revealed that the anonymous groups produced ideas of the highest average quality in the refinement phase of innovation. The results of this study enhanced our understanding of the productivity and creativity of groups in computer-mediated communication.

Keywords: creativity, anonymity, idea-generation, idea-refinement, innovation

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Authors: Mengdi Zhang, Zhenji Gao, Ning Kang, Rongmei Liu

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Management and application of geological big data is an important part of China's national big data strategy. With the implementation of a national big data strategy, geological big data management becomes more and more critical. At present, there are still a lot of technology barriers as well as cognition chaos in many aspects of geological big data management and application, such as data sharing, intellectual property protection, and application technology. Therefore, it’s a key task to make better use of new technologies for deeper delving and wider application of geological big data. In this paper, we briefly introduce the basic principle of blockchain technology at the beginning and then make an analysis of the application dilemma of geological data. Based on the current analysis, we bring forward some feasible patterns and scenarios for the blockchain application in geological big data and put forward serval suggestions for future work in geological big data management.

Keywords: blockchain, intellectual property protection, geological data, big data management

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Authors: Rahma Abed, Sahbi Bahroun, Ezzeddine Zagrouba

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Due to the huge amount of data in videos, extracting the relevant frames became a necessity and an essential step prior to performing face recognition. In this context, we propose a method for extracting keyframes from videos based on face quality and deep learning for a face recognition task. This method has two steps. We start by generating face quality scores for each face image based on the use of three face feature extractors, including Gabor, LBP, and HOG. The second step consists in training a Deep Convolutional Neural Network in a supervised manner in order to select the frames that have the best face quality. The obtained results show the effectiveness of the proposed method compared to the methods of the state of the art.

Keywords: keyframe extraction, face quality assessment, face in video recognition, convolution neural network

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Authors: Waseem Makai

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The term ‘political Islam’ now seem to have gained the centre stage in every discourse pertaining to Islamic legitimacy and compatibility in modern civilisations. A never ceasing tradition of the philosophy of caliphate that has kept overriding the options of any alternate political institution in the Muslim world still permeates a huge faction of believers. Fully accustomed with the proliferation of changes and developments in individual, social and natural dispositions of the world, Islamic theologians retaliated to this flux through both conventional and modernist approaches. The so-called conventional approach was quintessential of the interpretations put forth by Syed Maududi, with new comprehensive, academic and powerful vigour, as never seen before. He generated the avant-garde scholarship which would bear testimony to his statements, made to uphold the political institution of Islam as supreme and noble. However, it was not his trait to challenge the established views but to codify them in such a bracket which a man of the 20th century would find captivating to his heart and satisfactory to his rationale. The delicate microcosms like selection of a caliph, implementation of Islamic commandments (Sharia), interest free banking sectors, imposing tax (Jazyah) on non-believers, waging the holy crusade (Jihad) for the expansion of Islamic boundaries, stoning for committing adulteration and capital punishment for apostates were all there in his scholarship which he spent whole of his life defending in the best possible manner. What and where did he went wrong with all this, was supposedly to be notified later, by his once been disciple, Javed Ahmad Ghamidi. Ghamidi is being accused of struggling between Scylla and Charybdis as he tries to remain steadfast to his basic Islamic tenets while modernising their interpretations to bring them in harmony with the Western ideals of democracy and liberty. His blatant acknowledgement of putting democracy at a high pedestal, calling the implementation of Sharia a non-mandatory task and denial to bracket people in the categories of Zimmi and Kaafir fully vindicates his stance against conventional narratives like that of Syed Maududi. Ghamidi goes to the extent of attributing current forms of radicalism and extremism, as exemplified in the operations of organisations like ISIS in Iraq and Syria and Tehreek-e-Taliban in Pakistan, to such a version of political Islam as upheld not only by Syed Maududi but by other prominent theologians like Ibn-Timyah, Syed Qutub and Dr. Israr Ahmad also. Ghamidi is wretched, in a way that his allegedly insubstantial claims gained him enough hostilities to leave his homeland when two of his close allies were brutally murdered. Syed Maududi and Javed Ghamidi, both stand poles apart in their understanding of Islam and its political domain. Who has the appropriate methodology, scholarship and execution in his mode of comprehension, is an intriguing task, worth carrying out in detail.

Keywords: caliphate, democracy, ghamidi, maududi

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Authors: Abhishek Mangal, Kunal Tongaria, S. Mandal, Devendra Mohan

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Carbonation of reinforced concrete structures has emerged as one of the major challenges for Civil engineers across the world. With increasing emissions from various activities, carbon dioxide concentration in the atmosphere has been eve rising, enhancing its penetration in porous concrete, reaching steel bars and ultimately leading to premature failure. Several literatures have been published dealing with the various interdependent variables related to carbonation. However, with innumerable variability a generalization of these data proves to be a troublesome task. This paper looks into this carbonation anomaly in concrete structures caused by various external variables such as relative humidity, concentration of CO2, curing period and ambient temperature. Significant discussions and comparisons have been presented on the basis of various studies conducted with an aim to predict the depth of carbonation as a function of these multidimensional parameters using various numerical and statistical modelling techniques.

Keywords: carbonation, curing, exposure conditions, relative humidity

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Authors: Nebi Gedik

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One of the significant and continual public health problems in the world is breast cancer. Early detection is very important to fight the disease, and mammography has been one of the most common and reliable methods to detect the disease in the early stages. However, it is a difficult task, and computer-aided diagnosis (CAD) systems are needed to assist radiologists in providing both accurate and uniform evaluation for mass in mammograms. In this study, a multiresolution statistical method to classify mammograms as normal and abnormal in digitized mammograms is used to construct a CAD system. The mammogram images are represented by wave atom transform, and this representation is made by certain groups of coefficients, independently. The CAD system is designed by calculating some statistical features using each group of coefficients. The classification is performed by using support vector machine (SVM).

Keywords: wave atom transform, statistical features, multi-resolution representation, mammogram

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Authors: Muhammad Syahir Aminuddin, Zakaria Man, Mohamad Azmi Bustam Khalil

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In order to identify the best possible reaction media for performing H₂S conversion, a total number of 300 different ILs from a combination of 20 cations and 15 anions were screened via COSMO-RS model simulations. By COSMO-RS method, thermodynamic and physicochemical properties of 300 ILs, such as Henry's law constants, activity coefficient, selectivity, capacity, and performance index, are obtained and analyzed. Thus, by comparing the performance of ILs via COSMO-RS, a series of TSILs containing cation of [P66614] with metal chloride anions such as Fe, Ga, and Al were chosen and selected for synthesis based on their performance predicted by COSMO-RS and their economic values. Consequently, the physiochemical properties such as density, viscosity, thermal properties, as well as H₂S absorptive oxidation performances in those TSILs will be systematically investigated.

Keywords: conversion of hydrogen sulfide, hydrogen sulfide, H₂S, sour natural gas, task specific ionic liquids

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Authors: Roaa Sait, Richard Cross

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The synthesis and characterization of one dimensional nanostructure such as nanowires has received considerable attention. Much effort has concentrated on TiN material especially in the biological field due to its useful and unique properties in this field. Therefore, for the purpose of this project, synthesis of Titanium Nitride (TiN) nanowires (NWs) will be presented. They will be synthesised by growing titanium dioxide (Ti) NWs in an aqueous solution at low temperatures under atmospheric pressure. Then the grown nanowires will undergo a 'Nitrodation process' in which results in the formation of TiN NWs. The structure, morphology and composition of the grown nanowires will be characterized using Scanning Electron Microscopy (SEM), Transmission Electron Microscopy (TEM), X-ray Diffraction (XRD) and Cyclic Voltammetry (CV). Obtaining TiN NWs is a challenging task since it has not been formulated before, as far as we acknowledge. This might be due to the fact that nitriding Ti NWs can be difficult in terms of optimizing experimental parameters.

Keywords: nanowires, dissolution-growth, nucleation, PECVD, deposition, spin coating, scanning electron microscopic analysis, cyclic voltammetry analysis

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Authors: Ibtissem Daoudi, Raoudha Chebil, Wided Lejouad Chaari

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Serious games constitute actually a recent and attractive way supposed to replace the classical boring courses. However, the choice of the adapted serious game to a specific learning environment remains a challenging task that makes teachers unwilling to adopt this concept. To fill this gap, we present, in this paper, a multi-agent-based simulator allowing to predict the impact of a serious game integration in a learning environment given several game and players characteristics. As results, the presented tool gives intensities of several emotional aspects characterizing learners reactions to the serious game adoption. The presented simulator is tested to predict the effect of basing a coding course on the serious game ”CodeCombat”. The obtained results are compared with feedbacks of using the same serious game in a real learning process.

Keywords: emotion, learning process, multi-agent simulation, serious games

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Authors: Harsh Thakkar, Ganesh Iyer

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In this paper, we survey various user-centered or context-based biomedical health information retrieval systems. We present and discuss the performance of systems submitted in CLEF eHealth 2014 Task 3 for this purpose. We classify and focus on comparing the two most prevalent retrieval models in biomedical information retrieval namely: Language Model (LM) and Vector Space Model (VSM). We also report on the effectiveness of using external medical resources and ontologies like MeSH, Metamap, UMLS, etc. We observed that the LM based retrieval systems outperform VSM based systems on various fronts. From the results we conclude that the state-of-art system scores for MAP was 0.4146, P@10 was 0.7560 and NDCG@10 was 0.7445, respectively. All of these score were reported by systems built on language modeling approaches.

Keywords: clinical document retrieval, concept-based information retrieval, query expansion, language models, vector space models

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Authors: Seokbeen Lim, KyeongSeok Sim, DaKyeong Shin, Gilwon Yoon

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Event-related potential (ERP) is one of the useful tools for investigating cognitive reactions. In this study, the potential of ERP components detected after auditory and visual stimuli was examined. Subjects were asked to respond upon stimuli that were of three categories; Target, Non-Target and Standard stimuli. The ERP after stimulus was measured. In the experiment of visual evoked potentials (VEPs), the subjects were asked to gaze at a center point on the monitor screen where the stimuli were provided by the reversal pattern of the checkerboard. In consequence of the VEP experiments, we observed consistent reactions. Each peak voltage could be measured when the ensemble average was applied. Visual stimuli had smaller amplitude and a longer latency compared to that of auditory stimuli. The amplitude was the highest with Target and the smallest with Standard in both stimuli.

Keywords: auditory stimulus, EEG, event related potential, oddball task, visual stimulus

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Authors: Turki Mohammed Al Mohaid

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High arousal may lead to inhibited athletic performance, or high positive arousal may enhance performance is controversial. To evaluate and review this issue, 31 athletes (all male) were induced into high pre-determined goal arousal and high arousal without pre-determined goal motivational states and tested on a standard grip strength task. Paced breathing was used to change psychological and physiological arousal. It was noted that significant increases in grip strength performance occurred when arousal was high and experienced as delighted, happy, and pleasant excitement in those with no pre-determined goal motivational states. Blood pressure, heart rate, and other indicators of physiological activity were not found to mediate between psychological arousal and performance. In a situation where athletic performance necessitates maximal motor strength over a short period, performance benefits of high arousal may be enhanced by designing a specific motivational state.

Keywords: high arousal, athletic, performance, physiological

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Authors: Mahmoud I. Syam, Osama K. El-Hafy

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With lack of student motivation, there will be a little or no real learning in the class and this directly effects student achievement and test scores. Some students are naturally motivated to learn, but many students are not motivated, they do care little about learning and need their instructors to motivate them. Thus, motivating students is part of the instructor’s job. It’s a tough task to motivate students and make them have more attention and enthusiasm. As a part of this research, a questionnaire has been distributed among a sample of 155 students out of 1502 students from Foundation Program at Qatar University. The questionnaire helped us to determine some methods to motivate the students and encourage them to study such as variety of teaching activities, encouraging students to participate during the lectures, creating intense competition between the students, using instructional technology, not using grades as a threat and respecting the students and treating them in a good manner. Accordingly, some hypotheses are tested and some recommendations are presented.

Keywords: learning, motivating, student, teacher, testing hypotheses

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