Search results for: universal testing machine

Authors: Emmanuel Chinaguh, Kehinde Adeosun

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Nigerians die untimely, with 55.75 years of life expectancy, which is 17.45 below the world average of 73.2 (Worldometer, 2020). This is due, among other factors, to the country's limited access to high-quality healthcare. To increase access to good and affordable healthcare services, the National Health Insurance Authority (NHIA) Bill 2022 – which repealed the National Health Insurance Scheme Act 2004 – was passed into law. Applying Jacob Mey’s (2001) pragmatics act (pract) theory, this study explores how NHIA seeks to actualise these healthcare goals by characterising the general situational prototype or pragmemes and pragmatic acts in institutional communications. Data was sourced from the NHIA operational guidelines, which has 147 pages and four sections, and shared posters on NHIA Nigeria Twitter Handle with 14,200 followers. Digital humanities tools, like AntConc and Voyant, were engaged in the data analysis for text encoding and data visualisation. This study identifies these discourse tokens in the data: advertisement and programmes, standards and accreditation, records and information, and offences and penalties. Advertisement and programmes pract facilitating, propagating, prospecting, advising and informing; standards and accreditation, and records and information pract stating, informing and instructing; and offences and penalties pract stating and sanctioning. These practs combined to advance the goals of affordable care and universal accessibility to quality healthcare services. The pragmatic acts were marked by these pragmatic tools: shared situational knowledge (SSK), relevance (REL), reference (REF) and inference (INF). This paper adds to the understanding of health insurance discourse in Nigeria as a mediated social practice that promotes the health of Nigerians.

Keywords: affordable care, NHIA, Nigeria’s health insurance discourse, pragmatic acts.

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Authors: Dasom Kim, William Xiu Shun Wong, Yoonjin Hyun, Donghoon Lee, Minji Paek, Sungho Byun, Namgyu Kim

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There have been many researches on document classification for classifying voluminous documents automatically. Through document classification, we can assign a specific category to each unlabeled document on the basis of various machine learning algorithms. However, providing labeled documents manually requires considerable time and effort. To overcome the limitations, the semi-supervised learning which uses unlabeled document as well as labeled documents has been invented. However, traditional document classifiers, regardless of supervised or semi-supervised ones, cannot sufficiently explain the reason or the process of the classification. Thus, in this paper, we proposed a methodology to visualize major topics and class components of each document. We believe that our methodology for visualizing topics and classes of each document can enhance the reliability and explanatory power of document classifiers.

Keywords: data mining, document classifier, text mining, topic modeling

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Authors: Hidir S. Nogay

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In this study, two systems were created to predict interior temperature in induction motor. One of them consisted of a simple ANN model which has two layers, ten input parameters and one output parameter. The other one consisted of eight ANN models connected each other as cascaded. Cascaded ANN system has 17 inputs. Main reason of cascaded system being used in this study is to accomplish more accurate estimation by increasing inputs in the ANN system. Cascaded ANN system is compared with simple conventional ANN model to prove mentioned advantages. Dataset was obtained from experimental applications. Small part of the dataset was used to obtain more understandable graphs. Number of data is 329. 30% of the data was used for testing and validation. Test data and validation data were determined for each ANN model separately and reliability of each model was tested. As a result of this study, it has been understood that the cascaded ANN system produced more accurate estimates than conventional ANN model.

Keywords: cascaded neural network, internal temperature, inverter, three-phase induction motor

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Authors: F. Christie, M. Staber

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Malnutrition is a predictor of poor clinical outcome in the elderly. Up to 60% of hip fracture patients are clinically malnourished on admission. This study assessed the perioperative nutritional state of patients admitted with a proximal femoral fracture and examined if adequate nutritional support was achieved. Methods: Prospective, the observational audit of 30 patients, admitted with a proximal femoral fracture, over a one-month period. We recorded: patient demographics; surgical delay; nutritional state on admission; documentation of Malnutrition Universal Screening Tool (MUST) score; dietician input and daily calorie intake through food charts. The nutritional state was re-assessed weekly and at discharge. The outcome was measured by the length of hospital stay and thirty-day mortality. Results: Mean age 87, M:F 1:2 and all patients were ASA three or four. Five patients (17%) had a prolonged ( >24 hours) fasting period. All patients had a MUST score completed on admission, 27% were underweight and 30% were high risk for malnutrition. Twenty-six patients (87%) were appropriately assessed for dietician referral. Thirteen patients had food charts; on average, hospital meals provided 1500kcal daily. No patient achieved > 75% of the provided calories with 69% of patients achieving 50% or less. Only three patients were started on nutritional supplements. Twenty-three patients (77%) lost weight, averaging 6% weight loss during admission. Mean length of stay (LOS) was 23 days and 30-day mortality 9%. Four patients (13%) gained weight, their mean LOS was 17 days and 30-day mortality 0%. Discussion: Malnutrition in the elderly originates in the community. Following major trauma it’s difficult to reverse nutritional deficits in hospitals. It’s therefore concerning that no high-risk patient achieved their recommended calorie intake. Perioperative optimisation needs to include early nutritional intervention, early anaesthetic review and adjusted anaesthetic techniques to support feeding.

Keywords: trauma, nutrition, neck of femur fracture

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Authors: Manish Madappa, Madhavi Gayathri Raman

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The primary vehicle of human communication is language. A breakdown occurring in any aspect of communication may lead to frustration and isolation among the learners and the teachers. Over seven percent of the population in the world currently experience limitations and those children who exhibit a deviant/deficient language acquisition curve even when being in a language rich environment as their peers may be at risk of having a language disorder or language impairment. The difficulty may be in the word level [vocabulary/word knowledge] and/or the sentence level [syntax/morphology) Children with SLI appear to be developing normally in all aspects except for their receptive and/or expressive language skills. Thus, it is utmost importance to identify children with or at risk of SLI so that an early intervention can foster language and social growth, provide the best possible learning environment with special support for language to be explicitly taught and a step in providing continuous and ongoing support. The present study looks at Kannada English bilingual children and works towards identifying children at risk of “specific language impairment”. The study was conducted through an exploratory study which systematically enquired into the narratives of young Kannada-English bilinguals and to investigate the data for story structure in their narrative formulations. Oral narrative offers a rich source of data about a child’s language use in a relatively natural context. The fundamental objective is to ensure comparability and to be more universal and thus allows for the evaluation narrative text competence. The data was collected from 10 class three students at a primary school in Mysore, Karnataka and analyzed for macrostructure component reflecting the goal directed behavior of a protagonist who is motivated to carry out some kind of action with the intention of attaining a goal. The results show that the children exhibiting a deviation of -1.25 SD are at risk of SLI. Two learners were identified to be at risk of Specific Language Impairment with a standard deviation of more the 1.25 below the mean score.

Keywords: bilingual, oral narratives, SLI, macrostructure

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Authors: Shamraiz Ahmad, Riaz Ahmad, Adnan Maqsood

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This paper describes the application of 2k-design of experiment in order to screen the geometric parameters and experimental refinement of ceiling fan blades. The ratio of the air delivery to the power consumed is commonly known as service value (SV) in ceiling fan designer’s community. Service value was considered as the response for 56 inch ceiling fan and four geometric parameters (bend position at root, bend position at tip, bent angle at root and bent angle at tip) of blade were analyzed. With two levels, the 4-design parameters along with their eleven interactions were studied and design of experiment was employed for experimental arrangement. Blade manufacturing and testing were done in a medium scale enterprise. The objective was achieved and service value of ceiling fan was increased by 10.4 % without increasing the cost of production and manufacturing system. Experiments were designed and results were analyzed using Minitab® 16 software package.

Keywords: parametric screening, 2k-design of experiment, ceiling fan, service value, performance improvement

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Authors: E. A. Mlybari, M. S. Elbisy, A. H. Alshahri, O. M. Albarakati

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Sea level rise threatens to increase the impact of future storms and hurricanes on coastal communities. Accurate sea level change prediction and supplement is an important task in determining constructions and human activities in coastal and oceanic areas. In this study, support vector machines (SVM) is proposed to predict daily tidal levels along the Jeddah Coast, Saudi Arabia. The optimal parameter values of kernel function are determined using a genetic algorithm. The SVM results are compared with the field data and with back propagation (BP). Among the models, the SVM is superior to BPNN and has better generalization performance.

Keywords: tides, prediction, support vector machines, genetic algorithm, back-propagation neural network, risk, hazards

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Authors: Ayyaz Hussain, Tariq Sadad

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Breast cancer (BC) is one of the widespread ailments among females globally. The early prognosis of BC can decrease the mortality rate. Exact findings of benign tumors can avoid unnecessary biopsies and further treatments of patients under investigation. However, due to variations in images, it is a tough job to isolate cancerous cases from normal and benign ones. The machine learning technique is widely employed in the classification of BC pattern and prognosis. In this research, a deep convolution neural network (DCNN) called AlexNet architecture is employed to get more discriminative features from breast tissues. To achieve higher accuracy, K-nearest neighbor (KNN) classifiers are employed as a substitute for the softmax layer in deep learning. The proposed model is tested on a widely used breast image database called MIAS dataset for experimental purposes and achieved 99% accuracy.

Keywords: breast cancer, DCNN, KNN, mammography

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Authors: Jawid Ahmad Baktash, Mursal Dawodi, Tomokazu Nagata

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With the rapid growth of Cloud Computing, Formal Methods became a good choice for the refinement of message specification and verification for Dynamic Routing in Cloud Computing. Cloud-based Dynamic Routing is becoming increasingly popular. We propose feedback in Formal Methods for Dynamic Routing and Cloud Computing; the model and topologies show how to send messages from index zero to all others formally. The responsibility of proper verification becomes crucial with Dynamic Routing in the cloud. Formal Methods can play an essential role in the routing and development of Networks, and the testing of distributed systems. Event-B is a formal technique that consists of describing the problem rigorously and introduces solutions or details in the refinement steps. Event-B is a variant of B, designed for developing distributed systems and message passing of the dynamic routing. In Event-B and formal methods, the events consist of guarded actions occurring spontaneously rather than being invoked.

Keywords: cloud, dynamic routing, formal method, Pro-B, event-B

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Authors: Haider Javed Uppal, Javed Yunas Uppal

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In today's globalized world, it is necessary to develop a form of music that is able to evoke equal emotional responses among people from diverse cultural backgrounds. Indigenous cultures throughout history have developed their own music cognition, specifically in terms of the connections between music and mood. With the advancements in artificial intelligence technologies, it has become possible to analyze and categorize music features such as timbre, harmony, melody, and rhythm and relate them to the resulting mood effects experienced by listeners. This paper presents a model that utilizes a screenshot translator to convert music from different origins into waveforms, which are then analyzed using machine learning and information retrieval techniques. By connecting these waveforms with Thayer's matrix of moods, a mood classifier has been developed using fuzzy logic algorithms to determine the emotional impact of different types of music on listeners from various cultures.

Keywords: cognition, world music, artificial intelligence, Thayer’s matrix

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Authors: Phawin Sangsuvan, Chutimet Srinilta

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This Paper presents the applications of Particle Swarm Optimization (PSO) Method for Thai optical character recognition (OCR). OCR consists of the pre-processing, character recognition and post-processing. Before enter into recognition process. The Character must be “Prepped” by pre-processing process. The PSO is an optimization method that belongs to the swarm intelligence family based on the imitation of social behavior patterns of animals. Route of each particle is determined by an individual data among neighborhood particles. The interaction of the particles with neighbors is the advantage of Particle Swarm to determine the best solution. So PSO is interested by a lot of researchers in many difficult problems including character recognition. As the previous this research used a Projection Histogram to extract printed digits features and defined the simple Fitness Function for PSO. The results reveal that PSO gives 67.73% for testing dataset. So in the future there can be explored enhancement the better performance of PSO with improve the Fitness Function.

Keywords: character recognition, histogram projection, particle swarm optimization, pattern recognition techniques

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Authors: Noriyoshi Yamauchi, Etsuo Horikawa, Takunori Tsuji

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Training by exoskeleton robot is drawing attention as a rehabilitation method for body paralysis seen in many cases, and there are many forms that assist with the myoelectric signal generated by exercise commands from the brain. Rehabilitation requires more frequent training, but it is one of the reasons that the technology is required for the identification of the myoelectric potential derivation site and attachment of the device is preventing the spread of paralysis. In this research, we focus on improving the efficiency of gait training by exoskeleton type robots, improvement of myoelectric acquisition and analysis method using active matrix sensing method, and improvement of walking rehabilitation and walking by optimization of robot control.

Keywords: active matrix sensing, brain machine interface (BMI), the central pattern generator (CPG), myoelectric signal processing, robot rehabilitation

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Authors: Saurav Bhattacharjee, Syam Nair

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Lime stabilization is a sustainable and economically viable option to address strength deficiencies of subgrade soils. However, exposure of stabilized layers to environmental elements can lead to a reduction in post stabilization strength gain expected in these layers. The current study investigates the impact of carbonation on strength properties of lime-treated soils. Manufactured soils prepared using varying proportions of bentonite silica mixtures was used in the study. Lime treated mixtures were exposed to different atmospheric conditions created by varying the concentrations of CO₂ in the testing chamber. Impact of CO₂ diffusion was identified based on changes in carbonate content and strength (UCS) properties. Changes in soil morphology were also investigated as part of the study. Rate of carbonation was observed to vary polynomially (2nd order) with exposure time. Strength properties of the mixes were observed to decrease with exposure time.

Keywords: carbonation, soil, stabilization, morphology

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Authors: Matthew J. Zagumny

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The QUEST is an assessment of scientific epistemic beliefs and was developed to measure students’ intellectual development in regards to beliefs about knowledge and knowing. The QUEST utilizes Q-sort methodology, which requires participants to rate the degree to which statements describe them personally. As a measure of personal theories of knowledge, the QUEST instrument is described with the Q-sort distribution and scoring explained. A preliminary demonstration of the QUEST assessment is described with two samples of undergraduate students (novice/lower division compared to advanced/upper division students) being assessed and their average QUEST scores compared. The usefulness of an assessment of epistemology is discussed in terms of the principle that assessment tends to drive educational practice and university mission. The critical need for university and academic programs to focus on development of students’ scientific epistemology is briefly discussed.

Keywords: scientific epistemology, critical thinking, Q-sort method, STEM undergraduates

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Authors: Elizabeth Hoyos, Hernán Alvarez, Diana Lopez, Yesid Montoya

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The main goal of this research relates to the modeling of FSW from a different or unusual perspective coming from mechanical engineering, particularly looking for a way to establish process windows by assessing soundness of the joints as a priority and with the added advantage of lower computational time. This paper presents the use of a previously developed model applied to specific aspects of soundness evaluation of AA7075 FSW welds. EMSO software (Environment for Modeling, Simulation, and Optimization) was used for simulation and an adapted CNC machine was used for actual welding. This model based approach showed good agreement with the experimental data, from which it is possible to set a window of operation for commercial aluminum alloy AA7075, all with low computational costs and employing simple quality indicators that can be used by non-specialized users in process modeling.

Keywords: aluminum AA7075, friction stir welding, phenomenological based semiphysical model, processing map

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Authors: Jumazulhisham Abdul Shukor, Mohd. Sazali Said, Roshanizah Harun, Shuib Husin, Ahmad Razlee Ab Kadir

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This paper applies Taguchi Optimization Method in determining the best machining parameters for pocket milling process on Polypropylene (PP) using CNC milling machine where the surface roughness is considered and the Carbide inserts cutting tool are used. Three machining parameters; speed, feed rate and depth of cut are investigated along three levels; low, medium and high of each parameter (Taguchi Orthogonal Arrays). The setting of machining parameters were determined by using Taguchi Method and the Signal-to-Noise (S/N) ratio are assessed to define the optimal levels and to predict the effect of surface roughness with assigned parameters based on L9. The final experimental outcomes are presented to prove the optimization parameters recommended by manufacturer are accurate.

Keywords: inserts, milling process, signal-to-noise (S/N) ratio, surface roughness, Taguchi Optimization Method

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Authors: Chan Jong Park, Hye Min Park, Jeong Ho Kim, Ki Hyun Park, Koan Sik Joo

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This research used the MCNPX simulation program to evaluate the utility of a filter that was developed to minimize the damage to a semiconductor device during defect testing with X-ray. The X-ray generator was designed using the MCNPX code, and the X-ray absorption spectrum of the semiconductor device was obtained based on the designed X-ray generator code. To evaluate the utility of the filter, the X-ray absorption rates of the semiconductor device were calculated and compared for Ag, Rh, Mo and V filters with thicknesses of 25μm, 50μm, and 75μm. The results showed that the X-ray absorption rate varied with the type and thickness of the filter, ranging from 8.74% to 49.28%. The Rh filter showed the highest X-ray absorption rates of 29.8%, 15.18% and 8.74% for the above-mentioned filter thicknesses. As shown above, the characteristics of the X-ray absorption with respect to the type and thickness of the filter were identified using MCNPX simulation. With these results, both time and expense could be saved in the production of the desired filter. In the future, this filter will be produced, and its performance will be evaluated.

Keywords: X-ray, MCNPX, filter, semiconductor, damage

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Authors: Juneseok You, Chanho Park, Kuehwan Jang, Sungsoo Na

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Sensing of nanotoxic materials is strongly important, as their engineering applications are growing recently and results in that nanotoxic material can harmfully influence human health and environment. In current study we report the quartz crystal microbalance (QCM)-based, in situ and real-time sensing of nanotoxic-material by frequency shift. We propose the in situ detection of nanotoxic material of zinc oxice by using QCM functionalized with a taget-specific DNA. Since the mass of a target material is comparable to that of an atom, the mass change caused by target binding to DNA on the quartz electrode is so small that it is practically difficult to detect the ions at low concentrations. In our study, we have demonstrated the in-situ and fast detection of zinc oxide using the quartz crystal microbalance (QCM). The detection was derived from the DNA hybridization between the DNA on the quartz electrode. The results suggest that QCM-based detection opens a new avenue for the development of a practical water-testing sensor.

Keywords: nanotoxic material, qcm, frequency, in situ sensing

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Authors: Jamal Alqinai

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A pragmatic approach to translation studies the rules and principles governing the use of language over and above the rules of syntax or morphology, and what makes some uses of language more appropriate than others in [communicative] situations. It attempts to explain translation as a procedure and product from the point of view of how, why and what is done by the source text author (ST) and what is to be done in the target text (TT) rendition. The latter will be subject to evaluation not as generated by the linguistics system but as conveyed and manipulated by participants in a communicative situation according to the referential and pragmatic standards employed. The failure of a purely lexical or structural translation stems from ignoring the relation between words as signs and the effect they have on their users. A more refined approach would also consider those processes that are sometimes labeled extra-linguistic or intuitive and which translators strive to reproduce unscathed in the translation process. We need to grasp the kind of actions an ST author performs on his readers by combining linguistic and non-linguistic elements against a backdrop of beliefs and cultural values. In other words, aside from considering the cohesive ties at the textual level, one needs to understand how the whole ST discourse hangs together logically in order to reproduce a coherent TT. The latter can only be achieved by an analysis of the pragmatic elements of presuppositions, implicatures and acts performed in the ST. Establishing cohesive ties within a text may require seeking reference outside the immediate text. The illocutionary functions manifested in one language/culture are relatively autonomous cultural/linguistic categories, but are imaginable by members of other cultures and, to some extent , are translatable though not, of course, without translation loss. Globalization and the spread of literacy worldwide may have created a universal empathy to comprehend the performative aspect of utterances when explained by approximate glosses or by paraphrase. Yet, it is often the multilayered and the culture-specific nature of illocutionary functions that de-universalize their possible interpretations. This paper addresses the pragmatic interpretation of culturally specific texts with examples adduced from a number of distinct settings to illustrate the influence of the pragmatic factors at stake.

Keywords: pragmatic, presupposition, implicature, cohesion

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Authors: A. Mudau, T. R. Stacey, R. A. Govender

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This paper reports for the first time the findings on the dynamic compressive strength data of Bushveld Complex brittle rock materials. These rocks were subjected to both quasi-static and impact loading tests to help understand their behaviour both under quasi-static and dynamic loading conditions. Unlike quasi-static tests, characterization of dynamic behaviour of materials is challenging, in particularly brittle rock materials. The split Hopkinson pressure bar (SHPB) results reported for anorthosite and norite showed relatively low values for dynamic compressive strength compared to the quasi-static uniaxial compressive strength data. It was noticed that the dynamic stress conditions were not fully attained during testing, as well as constant strain rate.

Keywords: Bushveld Complex, dynamic comperession, rock brittleness, stress equilibrium

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Authors: Gyozo Molnar, Nancy Spencer-Cavaliere

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Research in the area of physical activity and sport, while becoming multidisciplinary, is still dominated by post-positivist approaches that have the tendency to position the researcher as an expert and the participant as subordinate thereby perpetuating an unequal balance of power. Despite physical activity’s and sport’s universal appeal, their historic practices have excluded particular groups of people who assumed lesser forms of human capital. Adapted physical activity (APA) is a field that has responded to those segregations with specific application and relevance to people with impairments. Nevertheless, to date, similar to physical activity and sport, research in APA is still dominated by post-positivist epistemology. Stemming from this, there is gradually growing criticism within the field related to the abundance of research ‘on’ people with impairments and lack of research ‘with’ and ‘by’ people with impairments. Furthermore, research questions in the field are most often pursued from a single axis of analysis and constructed by non-disabled researchers. Concurrently, while calls for interdisciplinary approaches to understanding disability are growing in popularity, there is also a clear need to take an intersectionality-informed research methodology to understanding physical activity and sport and power (im)balances therein. In other words, impairment needs to be considered in conjunction with other socially and politically constructed and historically embedded differences such as gender, race, class, etc. when analyzing physical activity and sport experiences for people with impairments. Moreover, it is reasonable to argue that non-disabled researchers must recognize and theorize ableism in its complicated intersectional manifestation to show the structural constraints that disabled scholars face in the field. Consequently, this presentation will offer an alternative approach that acknowledges and prioritizes the perspectives and experiences of people with impairments to expand the field of APA. As such, the importance of broadening epistemologies in APA and prioritizing an appreciation for multiple bits of knowledge of people with impairments through intersections of social locations (e.g., gender, race, class) will be considered.

Keywords: adapted physical activity, disability, intersectionality, post-positivist, power imbalances

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Authors: Yiea Funk Te, Daniel Mueller, Irena Pletikosa Cvijikj

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Small and medium enterprises (SMEs) play an important role in the economy of many countries. When the overall world economy is considered, SMEs represent 95% of all businesses in the world, accounting for 66% of the total employment. Existing studies show that the current business environment is characterized as highly turbulent and strongly influenced by modern information and communication technologies, thus forcing SMEs to experience more severe challenges in maintaining their existence and expanding their business. To support SMEs at improving their competitiveness, researchers recently turned their focus on applying data mining techniques to build risk and growth prediction models. However, data used to assess risk and growth indicators is primarily obtained via questionnaires, which is very laborious and time-consuming, or is provided by financial institutes, thus highly sensitive to privacy issues. Recently, web mining (WM) has emerged as a new approach towards obtaining valuable insights in the business world. WM enables automatic and large scale collection and analysis of potentially valuable data from various online platforms, including companies’ websites. While WM methods have been frequently studied to anticipate growth of sales volume for e-commerce platforms, their application for assessment of SME risk and growth indicators is still scarce. Considering that a vast proportion of SMEs own a website, WM bears a great potential in revealing valuable information hidden in SME websites, which can further be used to understand SME risk and growth indicators, as well as to enhance current SME risk and growth prediction models. This study aims at developing an automated system to collect business-relevant data from the Web and predict future growth trends of SMEs by means of WM and data mining techniques. The envisioned system should serve as an 'early recognition system' for future growth opportunities. In an initial step, we examine how structured and semi-structured Web data in governmental or SME websites can be used to explain the success of SMEs. WM methods are applied to extract Web data in a form of additional input features for the growth prediction model. The data on SMEs provided by a large Swiss insurance company is used as ground truth data (i.e. growth-labeled data) to train the growth prediction model. Different machine learning classification algorithms such as the Support Vector Machine, Random Forest and Artificial Neural Network are applied and compared, with the goal to optimize the prediction performance. The results are compared to those from previous studies, in order to assess the contribution of growth indicators retrieved from the Web for increasing the predictive power of the model.

Keywords: data mining, SME growth, success factors, web mining

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Authors: Josef Steinberger, Vanni Zavarella, Hristo Tanev

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Natural disasters cause tens of thousands of victims and massive material damages. We refer to all those events caused by natural disasters, such as damage on people, infrastructure, vehicles, services and resource supply, as micro events. This paper addresses the problem of micro - event detection in online media sources. We present a natural language grammar learning algorithm and apply it to online news. The algorithm in question is based on distributional clustering and detection of word collocations. We also explore the extraction of micro-events from social media and describe a Twitter mining robot, who uses combinations of keywords to detect tweets which talk about effects of disasters.

Keywords: online news, natural language processing, machine learning, event extraction, crisis computing, disaster effects, Twitter

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Authors: Zin Mar Lwin

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Brain Computer Interface (BCI) Systems have developed for people who suffer from severe motor disabilities and challenging to communicate with their environment. BCI allows them for communication by a non-muscular way. For communication between human and computer, BCI uses a type of signal called Electroencephalogram (EEG) signal which is recorded from the human„s brain by means of an electrode. The electroencephalogram (EEG) signal is an important information source for knowing brain processes for the non-invasive BCI. Translating human‟s thought, it needs to classify acquired EEG signal accurately. This paper proposed a typical EEG signal classification system which experiments the Dataset from “Purdue University.” Independent Component Analysis (ICA) method via EEGLab Tools for removing artifacts which are caused by eye blinks. For features extraction, the Time and Frequency features of non-stationary EEG signals are extracted by Matching Pursuit (MP) algorithm. The classification of one of five mental tasks is performed by Multi_Class Support Vector Machine (SVM). For SVMs, the comparisons have been carried out for both 1-against-1 and 1-against-all methods.

Keywords: BCI, EEG, ICA, SVM

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Authors: T. Sanches, K. Bousson

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As part of the development of a 4D autopilot system for unmanned aerial vehicles (UAVs), i.e. a time-dependent robust trajectory generation and control algorithm, this work addresses the problem of optimal path control based on the flight sensors data output that may be unreliable due to noise on data acquisition and/or transmission under certain circumstances. Although several filtering methods, such as the Kalman-Bucy filter or the Linear Quadratic Gaussian/Loop Transfer Recover Control (LQG/LTR), are available, the utter complexity of the control system, together with the robustness and reliability required of such a system on a UAV for airworthiness certifiable autonomous flight, required the development of a proper robust filter for a nonlinear system, as a way of further mitigate errors propagation to the control system and improve its ,performance. As such, a nonlinear algorithm based upon the LQG/LTR, is validated through computational simulation testing, is proposed on this paper.

Keywords: autonomous flight, LQG/LTR, nonlinear state estimator, robust flight control

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Authors: Yog Raj Sood, Rajnish Shrivastava, Anchal Wadhwa

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Power transformer is one of the electrical equipment that has a central and critical role in the power system. In order to avoid power transformer failure, information system that provides the transformer condition is needed. This paper presents an information system to know the exact situations prevailing within the transformer by declaring its health index. Health index of a transformer is decided by considering several diagnostic tools. The current work deals with UV-Vis, IFT, FP, BDV and Water Content. UV/VIS results have been pre-accessed using separate FL controller for concluding with the Furan contents. It is broadly accepted that the life of a power transformer is the life of the oil/ paper insulating system. The method relies on the use of furan analysis (insulation paper), and other oil analysis results as a means to declare health index. Fuzzy logic system is used to develop the information system. The testing is done on 5 samples of oil of transformers of rating 132/66 KV to obtain the results and results are analyzed using fuzzy logic model.

Keywords: interfacial tension analyzer (ift), flash point (fp), furfuraldehyde (fal), health index

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Authors: Anishur Rahman, Maria Areias, Diogo Simões, Ana Figeuiredo, Filipa Figueiredo, João Nunes

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The circular economy (CE) has gained increased awareness among academics, businesses, and decision-makers as it stimulates resource circularity in the production and consumption systems. A large epistemological study has explored the principles of CE, but scant attention eagerly focused on analysing how CE is evaluated, consented to, and enforced using economic metabolism data and business intelligent framework. Economic metabolism involves the ongoing exchange of materials and energy within and across socio-economic systems and requires the assessment of vast amounts of data to provide quantitative analysis related to effective resource management. Limited concern, the present work has focused on the regional flows pilot region from Portugal. By addressing this gap, this study aims to promote eco-innovation and sustainability in the regions of Intermunicipal Communities Região de Coimbra, Viseu Dão Lafões and Beiras e Serra da Estrela, using this data to find precise synergies in terms of material flows and give companies a competitive advantage in form of valuable waste destinations, access to new resources and new markets, cost reduction and risk sharing benefits. In our work, emphasis on applying artificial intelligence (AI) and, more specifically, on implementing state-of-the-art deep learning algorithms is placed, contributing to construction a business intelligent approach. With the emergence of new approaches generally highlighted under the sub-heading of AI and machine learning (ML), the methods for statistical analysis of complex and uncertain production systems are facing significant changes. Therefore, various definitions of AI and its differences from traditional statistics are presented, and furthermore, ML is introduced to identify its place in data science and the differences in topics such as big data analytics and in production problems that using AI and ML are identified. A lifecycle-based approach is then taken to analyse the use of different methods in each phase to identify the most useful technologies and unifying attributes of AI in manufacturing. Most of macroeconomic metabolisms models are mainly direct to contexts of large metropolis, neglecting rural territories, so within this project, a dynamic decision support model coupled with artificial intelligence tools and information platforms will be developed, focused on the reality of these transition zones between the rural and urban. Thus, a real decision support tool is under development, which will surpass the scientific developments carried out to date and will allow to overcome imitations related to the availability and reliability of data.

Keywords: circular economy, artificial intelligence, economic metabolisms, machine learning

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Authors: Ma'ruf

Abstract:

Pilgrimage has a universal value, founded in every religion. No exception to Islam, has a ritual value, and became part of the religion, as well as the procession of a social culture in nature. The tradition of pilgrimage, especially in Indonesia, rooted in the society, because the Islam that entered into the archipelago through Sufism (tasawuf). In the Sufi tradition, the interconnecty of the human spirit (ruh) to the spirit (ruh) of God, must go through a guardian (wasilah) appointed by God himself ,the prophet Muhammad and wali. In the process of pilgrimage rituals usually by reading the prayer to praise God, the prophet and wali, then convey intent (hajat). In the pilgrimage procession, usually not only done in the house, but aslo completed the process by direct pilgrimage visiting the tombs of saints. The tradition of pilgrimage, especially in Indonesia continues to be maintained, and still attached to the traditions in Nahdiyin (NU followers). The relationship with God manifested in wasilah prayer to God, the prophet Muhammad, the best companions of the Prophet and Nine wali (Songo), who had been influential in spreading Islam in Java. The tradition of pilgrimage in Indonesia is also linked to the Shia community in Indonesia, along with a growing number of followers of the Shia in Indonesia, especially after the Islamic revolution of Iran after the 1979. Pilgrimage in the Shia community, Likewise NU members also pray with supplication of tawasul to the Prophet and Shia Imams. If NU members to make improvements pilgrimage to visit the tomb wali Songo in Java, residents Shia pilgrimage rituals abroad, usually one package with umrah trip, with a pilgrimage to the tomb of the prophet, proceed to the tomb of the Imam Shia, in Iran and Iraq. Trends of pilgrimage as a ritual in the Indonesian Shia tradition, together with the growing number of Shia residents increased, followed by increasing the awareness (syi’isme) - bond with the Imam, Shia. In every certain months (arbaeen, asyuro) Shia pilgrims routinely perform pilgrimage, along with increasing number spiritual travel.

Keywords: traditional approach, religious experience, culture, religion, pilgrimage, Syria

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Authors: Dler Abdullah Ahmed, Zozan Ahmed Mohammed

Abstract:

This study looked into contact surface temperature during a pin-on-disk test. Friction and wear between sliding surfaces raised the temperature differential between the contact surface and ambient temperatures Tdiff. Tdiff was significantly influenced by wear test variables. Tdiff rose with the increase of sliding speed and applied load while dropped with the increase in ambient temperature. The highest Tdiff was 289°C during the tests at room temperature and 2.5 m/s sliding speed, while the minimum was only 24 °C during the tests at 400°C and 0.5 m/s. However, the maximum contact temperature Tmax was found during tests conducted at high ambient temperatures. The Tmax was estimated based on the theoretical equation. The comparison of experimental and theoretical Tmax data revealed good agreement.

Keywords: pin on disk test, contact temperature, wear, sliding surface, friction, ambient temperature

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Authors: Jamal Almatawah, Hamad Matar, Abdulsalam Altemeemi

Abstract:

The World Health Organization (WHO) has recognized environmental noise as harmful pollution that causes adverse psychosocial and physiologic effects on human health. The motor vehicle is considered to be one of the main source of noise pollution. It is a universal phenomenon, and it has grown to the point that it has become a major concern for both the public and policymakers. The aim of this paper, therefore, is to investigate the Traffic noise levels and the contributing factors that affect its level, such as traffic volume, heavy-vehicle Speed and other metrological factors in Ishbiliyah as a sample of a residential area in Kuwait. Three types of roads were selected in Ishbiliyah expressway, major arterial and collector street. The other source of noise that interferes the traffic noise has also been considered in this study. Traffic noise level is measured and analyzed using the Bruel & Kjaer outdoor sound level meter 2250-L (2250 Light). The Count-Cam2 Video Camera has been used to collect the peak and off-peak traffic count. Ambient Weather WM-5 Handheld Weather Station is used for metrological factors such as temperature, humidity and wind speed. Also, the spot speed was obtained using the radar speed: Decatur Genesis model GHD-KPH. All the measurement has been detected at the same time (simultaneously). The results showed that the traffic noise level is over the allowable limit on all types of roads. The average equivalent noise level (LAeq) for the Expressway, Major arterial and Collector Street was 74.3 dB(A), 70.47 dB(A) and 60.84 dB(A), respectively. In addition, a Positive Correlation coefficient between the traffic noise versus traffic volume and between traffic noise versus 85th percentile speed was obtained. However, there was no significant relation and Metrological factors. Abnormal vehicle noise due to poor maintenance or user-enhanced exhaust noise was found to be one of the highest factors that affected the overall traffic noise reading.

Keywords: traffic noise, residential area, pollution, vehicle noise

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