Search results for: index structural equation model

Authors: S. Candamano, A. Iorfida, F. Crea, A. Macario

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Recently, basalt fabric reinforced cementitious composites (FRCM) have attracted great attention because they result to be effective in structural strengthening and cost/environment efficient. In this study, authors investigate their mechanical behavior when an inorganic matrix, belonging to the family of alkali-activated binders, is used. In particular, the matrix has been designed to contain high amounts of industrial by-products and waste, such as Ground Granulated Blast Furnace Slag (GGBFS) and Fly Ash. Fresh state properties, such as workability, mechanical properties and shrinkage behavior of the matrix have been measured, while microstructures and reaction products were analyzed by Scanning Electron Microscopy and X-Ray Diffractometry. Reinforcement is made up of a balanced, coated bidirectional fabric made out of basalt fibres and stainless steel micro-wire, with a mesh size of 8x8 mm and an equivalent design thickness equal to 0.064 mm. Mortars mixes have been prepared by maintaining constant the water/(reactive powders) and sand/(reactive powders) ratios at 0.53 and 2.7 respectively. An appropriate experimental campaign based on direct tensile tests on composite specimens and single-lap shear bond test on brickwork substrate has been thus carried out to investigate their mechanical behavior under tension, the stress-transfer mechanism and failure modes. Tensile tests were carried out on composite specimens of nominal dimensions equal to 500 mm x 50 mm x 10 mm, with 6 embedded rovings in the loading direction. Direct shear tests (DST) were carried out on brickwork substrate using an externally bonded basalt-FRCM composite strip 10 mm thick, 50 mm wide and a bonded length of 300 mm. Mortars exhibit, after 28 days of curing, an average compressive strength of 32 MPa and flexural strength of 5.5 MPa. Main hydration product is a poorly crystalline aluminium-modified calcium silicate hydrate (C-A-S-H) gel. The constitutive behavior of the composite has been identified by means of direct tensile tests, with response curves showing a tri-linear behavior. Test results indicate that the behavior is mainly governed by cracks development (II) and widening (III) up to failure. The ultimate tensile strength and strain were respectively σᵤ = 456 MPa and ɛᵤ= 2.20%. The tensile modulus of elasticity in stage III was EIII= 41 GPa. All single-lap shear test specimens failed due to composite debonding. It occurred at the internal fabric-to-matrix interface, and it was the result of a fracture of the matrix between the fibre bundles. For all specimens, transversal cracks were visible on the external surface of the composite and involved only the external matrix layer. This cracking appears when the interfacial shear stresses increase and slippage of the fabric at the internal matrix layer interface occurs. Since the external matrix layer is bonded to the reinforcement fabric, it translates with the slipped fabric. Average peak load around 945 N, peak stress around 308 MPa and global slip around 6 mm were measured. The preliminary test results allow affirming that Alkali-Activated Materials can be considered a potentially valid alternative to traditional mortars in designing FRCM composites.

Keywords: Alkali-activated binders, Basalt-FRCM composites, direct shear tests, structural strengthening

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Authors: Aliya Grig, Konstantin Sokolov, Igor Shatalin

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The report describes the methodology for collecting data and building an ML model for determining the personality psychotype using profiling and personality traits methods based on several short messages of a user communicating on an arbitrary topic with a chitchat bot. In the course of the experiments, the minimum amount of text was revealed to confidently determine aspects of personality. Model accuracy - 85%. Users' language of communication is English. AI for a personalized communication with a user based on his mood, personality, and current emotional state. Features investigated during the research: personalized communication; providing empathy; adaptation to a user; predictive analytics. In the report, we describe the processes that captures both structured and unstructured data pertaining to a user in large quantities and diverse forms. This data is then effectively processed through ML tools to construct a knowledge graph and draw inferences regarding users of text messages in a comprehensive manner. Specifically, the system analyzes users' behavioral patterns and predicts future scenarios based on this analysis. As a result of the experiments, we provide for further research on training AI models to be empathetic, creating personalized communication for a user

Keywords: AI, empathetic, chatbot, AI models

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Authors: Omar Al Denali, Abdelaziz Badi

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The ASTM A516 Grade 70 steel is a suitable material used for the fabrication of boiler pressure vessels working in moderate and lower temperature services, and it has good weldability and excellent notch toughness. The post-weld heat treatment (PWHT) or stress-relieving heat treatment has significant effects on avoiding the martensite transformation and resulting in high hardness, which can lead to cracking in the heat-affected zone (HAZ). An adaptive neuro-fuzzy inference system (ANFIS) was implemented to predict the material tensile strength of post-weld heat treatment (PWHT) experiments. The ANFIS models presented excellent predictions, and the comparison was carried out based on the mean absolute percentage error between the predicted values and the experimental values. The ANFIS model gave a Mean Absolute Percentage Error of 0.556 %, which confirms the high accuracy of the model.

Keywords: prediction, post-weld heat treatment, adaptive neuro-fuzzy inference system, mean absolute percentage error

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Authors: V. Benidze

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After the Rose Revolution of 2003, Georgia has achieved an unparalleled socioeconomic success. However, economic growth since 2012 has been sluggish and certainly not enough to rapidly improve the county’s standard of living that still remains substantially low compared to that in developed nations. Recent poor economic performance has shown that some key challenges need to be addressed if Georgia is to achieve high future economic growth that will decrease the poverty rate and create a middle class in the country. This paper offers in detail analysis of the economic performance of Georgia since 2012 and identifies key challenges facing the country’s economy. The main challenge going forward will be transforming Georgia from a consumption-driven to a production-oriented economy. It is identified that mobilizing domestic investment through savings, attracting foreign investment in tradable sectors and expanding the country’s export base will be crucial in the facilitation of the above-mentioned structural transformation. As the outcome of the research, the paper suggests a strategy for accelerating Georgia’ future economic growth and offers recommendations based on the relevant conclusions.

Keywords: challenges, development, economic growth, economic policy, Georgia

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Authors: Victor William Harris

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This research is a validation study of the Social Emotional Ability Inventory (SEAI), a multi-dimensional self-report instrument informed by positive psychology, emotional intelligence, social intelligence, and sociocultural learning theory. Designed for use in tandem with the Social Emotional Development (SEAD) theoretical model, the SEAI provides diagnostic-level guidance for professionals and individuals interested in investigating, identifying, and understanding social, emotional strengths, as well as remediating specific social competency deficiencies. The SEAI was shown to be psychometrically sound, exhibited strong internal reliability, and supported the a priori hypotheses of the SEAD. Additionally, confirmatory factor analysis provided evidence of goodness of fit, convergent and divergent validity, and supported a theoretical model that reflected SEAD expectations. The SEAI and SEAD hold potentially far-reaching and important practical implications for theoretical guidance and diagnostic-level measurement of social, emotional competency across a wide range of domains. Strategies researchers, practitioners, educators, and individuals might use to deploy SEAI in order to improve quality of life outcomes are discussed.

Keywords: emotion, emotional ability, positive psychology-social emotional ability, social emotional ability, social emotional ability instrument

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Authors: Yogi Wibisono Budhi, Ferry Iskandar, Veinardi Suendo, Muhammad Fakhrudin, Neng Tresna Umi Culsum

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Oil palm empty fruit bunch (OPEFB), an abundant agro-waste in Indonesia, is being studied as raw material of Cellulose Nanocrystals (CNC) synthesis. Instead of conventional acid mineral, phosphotungstic acid (H₃PW₁₂O₄₀, HPW) was used to hydrolyze cellulose due to recycling ability and easy handling. Before hydrolysis process, dried EFB was treated by 4% NaOH solution at 90oC for 2 hours and then bleached using 2% NaClO₂ solution at 80oC for 3 hours to remove hemicellulose and lignin. Hydrolysis reaction parameters such as temperature, acid concentration, and reaction time were optimized with fixed solid-liquid ratio of 1:40. Response surface method was used for experimental design to determine the optimum condition of each parameter. HPW was extracted from the mixed solution and recycled with diethyl ether. CNC was separated from the solution by centrifuging and washing with distilled water and ethanol to remove degraded sugars and unreacted celluloses. In this study, pulp from dried EFB produced 44.8% yield of CNC. Dynamic Light Scattering (DLS) analysis showed that most of CNC equivalent diameter was 140 nm. Crystallinity index was observed at 73.3% using X-ray Diffraction (XRD) analysis. Thus, a green established process for the preparation of CNC was achieved.

Keywords: acid hydrolysis, cellulose nanocrystals, oil palm empty fruit bunch, phosphotungstic acid

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Authors: Anders Troedsson

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For us humans, risks are intimately linked to human vulnerabilities - where there is vulnerability, there is potentially insecurity, and risk. Reducing vulnerability through compensatory measures means increasing security and decreasing risk. The paper suggests that a meaningful way to approach the study of risks (including threats, assaults, crisis etc.), is to understand the vulnerabilities these external phenomena evoke in humans. As is argued, the basis of risk evaluation, as well as responses, is the more or less subjective perception by the individual person, or a group of persons, exposed to the external event or phenomena in question. This will be determined primarily by the vulnerability or vulnerabilities that the external factor are perceived to evoke. In this way, risk perception is primarily an inward dynamic, rather than an outward one. Therefore, a route towards an understanding of the perception of risks, is a closer scrutiny of the vulnerabilities which they can evoke, thereby approaching an understanding of what in the paper is called the essence of risk (including threat, assault etc.), or that which a certain perceived risk means to an individual or group of individuals. As a necessary basis for gauging the wide spectrum of potential risks and their meaning, the paper proposes a model of human vulnerabilities, drawing from i.a. a long tradition of needs theory. In order to account for the subjectivity factor, which mediates between the innate vulnerabilities on the one hand, and the event or phenomenon out there on the other hand, an ensuing ontological discussion about the timespace characteristics of risk/threat/assault as perceived by humans leads to the positing of two dimensions. These two dimensions are applied on the vulnerabilities, resulting in a modelling effort featuring four realms of vulnerabilities which are related to each other and together represent a dynamic whole. In approaching the problem of risk perception, the paper thus defines the relevant realms of vulnerabilities, depicting them as a dynamic whole. With reference to a substantial body of literature and a growing international policy trend since the 1990s, this model is put in the language of human security - a concept relevant not only for international security studies and policy, but also for other academic disciplines and spheres of human endeavor.

Keywords: human security, timespace, vulnerabilities, risk perception

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Authors: T. Taşköprü, M. Zor, E. Turan

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The advantages of nickel oxide as an electrochromic material are its good contrast of transmittance and its suitable use as a secondary electrochromic film with WO3 for electrochromic devices. Electrochromic nickel oxide film was prepared by using a simple and inexpensive chemical deposition bath (CBD) technique onto fluorine-doped tin oxide (FTO) coated glass substrates from nickel nitrate solution. The films were ace centered cubic NiO with preferred orientation in the (2 0 0) direction. The electrochromic (EC) properties of the films were studied as a function of pH (8, 9, 10 and 11) in an aqueous alkaline electrolyte (0.3 M KOH) using cyclic voltammetry (CV). The EC cell was formed with the following configuration; FTO/nickel oxide film/0.3 M KOH/Pt The potential was cycled from 0.1 to 0.6V at diffferent potential sweep rates in the range 10- 50 mV/s. The films exhibit anodic electrochromism, changing colour from transparent to black.CV results of a nickel oxide film showed well-resolved anodic current peak at potential; 45 mV and cathodic peak at potential 28 mV. The structural, morphological, and optical changes in NiO film following the CV were investigated by means of X-ray diffractometer (XRD), field emission electron microscopy (FESEM) and UV-Vis- NIR spectrophotometry. No change was observed in XRD, besides surface morphology undergoes change due to the electrical discharge. The change in tansmittance between the bleached and colored state is 68% for the film deposited with pH=11 precursor.

Keywords: nickel oxide, XRD, SEM, cyclic voltammetry

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Authors: Givi Kupatadze

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Backward economies are facing a challenge of achieving sustainable high economic growth rate. Dominant growth models represent a roadmap in framing economic development strategy. This paper examines a relevance of the dominant growth models for backward economies. Cobb-Douglas production function, the Harrod-Domar model of economic growth, the Solow growth model and general formula of gross domestic product are examined to undertake a comprehensive study of the dominant growth models. Deductive research method allows to uncover major weaknesses of the dominant growth models and to come up with practical implications for economic development strategy. The key finding of the paper shows, contrary to what used to be taught by textbooks of economics, that constant returns to scale property of the dominant growth models are a mere coincidence and its generalization over space and time can be regarded as one of the most unfortunate mistakes in the whole field of political economy. The major suggestion of the paper for backward economies is that understanding and considering taxonomy of economic activities based on increasing and diminishing returns to scale represent a cornerstone of successful economic development strategy.

Keywords: backward economies, constant returns to scale, dominant growth models, taxonomy of economic activities

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Authors: Miladi Yasmine, Bouhlel Salah, Garnit Hechmi

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Hydrothermal vein-type deposits of the Hammam Jedidi F-Ba(Pb-Zn-Cu) are hosted in Lower Jurassic, Cretaceous and Tertiary series, and located near a very important structural lineament (NE-SW) corresponding to the Hammam Jedidi Fault in the Tunisian Dorsale. The circulation of the ore forming fluid is triggered by a regional tectonic compressive phase which occurred during the miocène time. Mineralization occurs as stratabound and vein-type orebodies adjacent to the Triassic salt diapirs and within fault in Jurassic limestone. Fluid inclusions data show that two distinct fluids were involved in the mineralisation deposition: a warmer saline fluid (180°C, 20 wt % NaCl equivalent) and cooler less saline fluid (126°C, 5wt%NaCl equivalent). The contrasting salinities and halogen ratios suggest that this two fluid derived from one of the brine originated after the dissolution of halite as suggested by its high salinity. The other end member, as indicated by the low Cl/Br ratios, acquired its low salinity by dilution of Br enriched evaporated seawater. These results are compatible with Mississippi-Valley- type mineralization.

Keywords: Jebel Oust, fluid inclusions, North Eastern Tunisia, mineralization

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Authors: Yosr Ghozzi

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The Cyber-Physical Systems terminology has been well received by the industrial community and specifically appropriated in educational settings. Indeed, our latest educational activities are based on the development of experimental platforms on an industrial scale. In fact, we built a collaborative learning model because of an international market study that led us to place ourselves at the heart of this technology. To align with these findings, a competency-based approach study was conducted, and program content was revised by reflecting the projectbased approach. Thus, this article deals with the development of educational devices according to a generated curriculum and specific educational activities while respecting the repository of skills adopted from what constitutes the educational cyber-physical production systems and the laboratories that are compliant and adapted to them. The implementation of these platforms was systematically carried out in the school's workshops spaces. The objective has been twofold, both research and teaching for the students in mechatronics and logistics of the electromechanical department. We act as trainers and industrial experts to involve students in the implementation of possible extension systems around multidisciplinary projects and reconnect with industrial projects for better professional integration.

Keywords: education 4.0, competency-based learning, teaching factory, project-based learning, cyber-physical systems, industry 4.0

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Authors: Asad Rehman

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Although a vast majority relates the concept of ‘halal’ or what is permissible in Islam to food only. However, halal industry covers many sectors such as food, fashion, transport, finance and even tourism. Halal tourism is not just about halal food; it is also about the overall experience, which is amenable with the Shariah (Islamic jurisprudence). Oman has a plethora of natural beauty and many places of interest for all types of tourists. It is one of the most secure and peaceful countries in the world. Having a well-developed Infrastructure, Oman is ready to take its tourism to new heights. The ever-hospitable Omanis are proud of their rich cultural and historical heritage. Thus, Oman appears to have all what it takes to become a prime destination for halal tourism. The objective of this study is to assess the prospects of Oman as a destination for halal tourism. Based on the interviews of experts like academicians, tourism professionals, officials and clerics, Oman’s competitiveness as a destination for halal tourism was assessed by developing a Strengths, Weaknesses, Opportunities and Threats (SWOT) profile. The findings of the SWOT were compared with the data from the Global Muslim Travel Index (GMTI) from the year 2014 to 2018. Based on the analysis, Oman is found to have the right mix of environment and enabling services for halal tourism. However, it is found lacking in public transport, communication and customer outreach. Oman is also found to be losing its rank among the top 10 destinations for halal tourism to close competitors like Qatar, Bahrain, Morocco, etc. The concerned authorities need to make conscious efforts to resolve these issues as it becomes imperative for Oman to revamp its tourism strategy.

Keywords: destination, halal, Islam, SWOT, tourism

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Authors: Khader A. Almhdawi, Hassan Alrabbaie

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Background: Musculoskeletal disorders (MSDs) represent a significant challenge for registered nurses. To our best knowledge, there is no published study that investigated the prevalence of MSDs among nurses and their associated factors comprehensively in Jordan. This study aimed to find the prevalence of MSDs, their possible predictors among registered nurses in Jordanian hospitals. Methods: A cross-sectional design was used. Outcome measures included Nordic Musculoskeletal Questioner (NMQ), Depression Anxiety Stress Scale (DASS), Pittsburgh Sleep Quality Index (PSQI), IPAQ, and sociodemographic data. Prevalence of musculoskeletal complaints was reported using descriptive analysis. Logistic regression analyses were conducted to identify predictors of MSDs. Results: 597 nurses from different hospitals in Jordan participated in this study. Reported MSDs prevalence was the highest at neck (61.1%), followed by upper back (47.2%), shoulder (46.7%), wrist and hands (27.3%), and elbow (13.9%). Significant predictors of MSDs among Jordanian nurses included: being a female, poor sleep quality, high physical activity levels, poor ergonomics, increased workload, and mental stress. Conclusion: This study showed a high prevalence of MSDs among Jordanian nurses and identified their significant predictors. Future studies are needed to investigate the progressive nature of MSDs and their effective treatment strategies.

Keywords: musculoskeletal disorders, nursing, ergonomic, occupational stress

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Authors: D. Jagath Kumari, K. Srinivasa Rao

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Quality assurance of the structures subjected to high temperatures is now enforcing measure for the Structural Engineers. The existing relations between strength and nondestructive measurements have been established under normal conditions are not suitable to concretes that have been exposed to high temperatures. The scope of the work is to investigate the influence of high temperatures of short durations on the residual properties of reinforced HVFA concrete columns that affect the strength by non-destructive tests (NDT). Fly ash concrete is increasingly used in the design of normal strength, high strength and high performance concretes. In this paper, the authors revealed the influence of high temperatures on HVFA concrete columns. These columns are heated from 100oC to 800oC with increments of 100oC and allowed to cool to room temperature by two methods one is air cooling method and the other immediate water quenching method. All the specimens were tested identically, before heating and after heating for compressive strength and material integrity by rebound hammer and ultrasonic pulse velocity (UPV) meter respectively. HVFA concrete retained more residual strength by water quenching method than air-cooling method.

Keywords: HVFA concrete, NDT methods, residual strength, non-destructive tests

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Authors: F. N. Bolu-Steve, T. A. Ajiboye

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A study was carried out on the awareness of counselling needs of psychiatric patients as perceived by medical personnel in the Federal Neuropsychiatric hospital, Aro, Abeokuta, Nigeria. The respondents comprised of medical personnel of the Neuropsychiatric hospital in Aro. Purposive sampling technique was used to select the respondents. The target population of the study consisted of all medical doctors treating the psychiatric patients. A total of 200 respondents participated in the study out of which 143 were males and 57 of them were females. With their years of experience as a medical doctors, 49.5% of them have worked between 1-5 years, 30.5% of the respondents have 6-10 years’ experience while those with 16 years and above experience are 7.0%. The major counselling need of psychiatric patients as expressed by medical doctors is the need to have information about the right balance diet. The data were analyzed using percentages, mean, frequency, Analysis of Variance (ANOVA) and t-test statistical tools. The instrument used for data collection was the structured questionnaire titled “Counselling Needs of Psychiatric Patients Questionnaire” (CNPPQ). This instrument was drafted by the researchers through the review of related literature. The reliability of the instrument was established using test-retest method. A reliability index of 0.74 was obtained. Three of the hypotheses were rejected while two of them were accepted at 0.05 alpha level of significance. Based on the findings of the study, it was recommended that broad based counselling services should be provided to psychiatric patients in order to assist them to develop positive self- image and to cope with their challenges.

Keywords: counselling, needs, psychiatric, medical personnel, patients

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Authors: Marjan Mahdavi-Roshan, Arsalan Salari, Mahboobeh Gholipour, Moona Naghshbandi

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Background and objectives: Before any nutritional intervention, it is necessary to have the prospect of eating habits of people with cardiovascular risk factors. In this study, we assessed the adherence of healthy diet based on Mediterranean dietary pattern and related factors in adults in the north of Iran. Methods: This study was conducted on 550 men and women with cardiovascular risk factors that referred to Heshmat hospital in Rasht, northern Iran. Information was collected by interview and reading medical history and measuring anthropometric indexes. The Mediterranean Diet Adherence Screener was used for assessing dietary adherence, this screener was modified according to religious beliefs and culture of Iran. Results: The mean age of participants was 58±0.38 years. The mean of body mass index was 27±0.01 kg/m², and the mean of waist circumference was 98±0.2 cm. The mean of dietary adherence was 5.76±0.07. 45% of participants had low adherence, and just 4% had suitable adherence. The mean of dietary adherence in men was significantly higher than women (p=0. 07). Participants in rural area and high educational participants insignificantly had an unsuitable dietary Adherence. There was no significant association between some cardiovascular disease risk factors and dietary adherence. Conclusion: Education to different group about dietary intake correction and using a Mediterranean dietary pattern that is similar to dietary intake in the north of Iran, for controlling cardiovascular disease is necessary.

Keywords: dietary adherence, Mediterranean dietary pattern, cardiovascular disease, north of Iran

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Authors: Sarantos Psycharis

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Physical Computing, as an instructional model, is applied in the framework of the Engineering Pedagogy to teach “transversal/cross-cutting ideas” in a STEM content approach. Labview and Arduino were used in order to connect the physical world with real data in the framework of the so called Computational Experiment. Tertiary prospective engineering educators were engaged during their course and Computational Thinking (CT) concepts were registered before and after the intervention across didactic activities using validated questionnaires for the relationship between self-efficacy, computer programming, and CT concepts when STEM content epistemology is implemented in alignment with the Computational Pedagogy model. Results show a significant change in students’ responses for self-efficacy for CT before and after the instruction. Results also indicate a significant relation between the responses in the different CT concepts/practices. According to the findings, STEM content epistemology combined with Physical Computing should be a good candidate as a learning and teaching approach in university settings that enhances students’ engagement in CT concepts/practices.

Keywords: arduino, computational thinking, computer programming, Labview, self-efficacy, STEM

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Authors: Rosdyana Mangir Irawan Kusuma, Wei-Chun Kao, Ho-Thi Trang, Yu-Yen Ou, Kai-Lung Hua

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Stock market prediction is still a challenging problem because there are many factors that affect the stock market price such as company news and performance, industry performance, investor sentiment, social media sentiment, and economic factors. This work explores the predictability in the stock market using deep convolutional network and candlestick charts. The outcome is utilized to design a decision support framework that can be used by traders to provide suggested indications of future stock price direction. We perform this work using various types of neural networks like convolutional neural network, residual network and visual geometry group network. From stock market historical data, we converted it to candlestick charts. Finally, these candlestick charts will be feed as input for training a convolutional neural network model. This convolutional neural network model will help us to analyze the patterns inside the candlestick chart and predict the future movements of the stock market. The effectiveness of our method is evaluated in stock market prediction with promising results; 92.2% and 92.1 % accuracy for Taiwan and Indonesian stock market dataset respectively.

Keywords: candlestick chart, deep learning, neural network, stock market prediction

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Authors: N. Borjalilu, P. Rabiei, A. Enjoo

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Flight Data Monitoring (FDM) program assists an operator in aviation industries to identify, quantify, assess and address operational safety risks, in order to improve safety of flight operations. FDM is a powerful tool for an aircraft operator integrated into the operator’s Safety Management System (SMS), allowing to detect, confirm, and assess safety issues and to check the effectiveness of corrective actions, associated with human errors. This article proposes a model for safety risk assessment level of flight data in a different aspect of event focus based on fuzzy set values. It permits to evaluate the operational safety level from the point of view of flight activities. The main advantages of this method are proposed qualitative safety analysis of flight data. This research applies the opinions of the aviation experts through a number of questionnaires Related to flight data in four categories of occurrence that can take place during an accident or an incident such as: Runway Excursions (RE), Controlled Flight Into Terrain (CFIT), Mid-Air Collision (MAC), Loss of Control in Flight (LOC-I). By weighting each one (by F-TOPSIS) and applying it to the number of risks of the event, the safety risk of each related events can be obtained.

Keywords: F-topsis, fuzzy set, flight data monitoring (FDM), flight safety

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Authors: Bandar Alkahlan

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The King Abdulaziz City for Science and Technology (KACST) created the Saudi Future Dwelling (SFD) initiative to identify, localize and commercialize a scalable home manufacturing technology suited to deployment across the Kingdom of Saudi Arabia (KSA). This paper outlines the journey, the creation of the international project delivery team, the product design, the selection of the process technologies, and the outcomes. A target was set to remove 85% of the construction and finishing processes from the building site as these activities could be more efficiently completed in a factory environment. Therefore, integral to the SFD initiative is the successful industrialization of the home building process using appropriate technologies, automation, robotics, and manufacturing logistics. The technologies proposed for the SFD housing system are designed to be energy efficient, economical, fit for purpose from a Saudi cultural perspective, and will minimize the use of concrete, relying mainly on locally available Saudi natural materials derived from the local resource industries. To this end, the building structure is comprised of a hybrid system of structural insulated panels (SIP), combined with a light gauge steel framework manufactured in a large format panel system. The paper traces the investigative process and steps completed by the project team during the selection process. As part of the SFD Project, a pathway was mapped out to include a proof-of-concept prototype housing module and the set-up and commissioning of a lab-factory complete with all production machinery and equipment necessary to simulate a full-scale production environment. The prototype housing module was used to validate and inform current and future product design as well as manufacturing process decisions. A description of the prototype design and manufacture is outlined along with valuable learning derived from the build and how these results were used to enhance the SFD project. The industrial engineering concepts and lab-factory detailed design and layout are described in the paper, along with the shop floor I.T. management strategy. Special attention was paid to showcase all technologies within the lab-factory as part of the engagement strategy with private investors to leverage the SFD project with large scale factories throughout the Kingdom. A detailed analysis is included in the process surrounding the design, specification, and procurement of the manufacturing machinery, equipment, and logistical manipulators required to produce the SFD housing modules. The manufacturing machinery was comprised of a combination of standardized and bespoke equipment from a wide range of international suppliers. The paper describes the selection process, pre-ordering trials and studies, and, in some cases, the requirement for additional research and development by the equipment suppliers in order to achieve the SFD objectives. A set of conclusions is drawn describing the results achieved thus far, along with a list of recommended ongoing operational tests, enhancements, research, and development aimed at achieving full-scale engagement with private sector investment and roll-out of the SFD project across the Kingdom.

Keywords: automation, dwelling, manufacturing, product design

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Authors: Hsin-Yang Wang, K. M. A. Salam, Ying-Jia Lin, Daniel Tan, Tzu-Hsuan Chou, Hung-Yu Kao

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Detecting user intent from natural language expression has a wide variety of use cases in different natural language processing applications. Recently few-shot training has a spike of usage on commercial domains. Due to the lack of significant sample features, the downstream task performance has been limited or leads to an unstable result across different domains. As a state-of-the-art method, the pre-trained BERT model gathering the sentence-level information from a large text corpus shows improvement on several NLP benchmarks. In this research, we are proposing a method to change multi-class classification tasks into binary classification tasks, then use the confidence score to rank the results. As a language model, BERT performs well on sequence data. In our experiment, we change the objective from predicting labels into finding the relations between words in sequence data. Our proposed method achieved 71.0% accuracy in the internal intent detection dataset and 63.9% accuracy in the HuffPost dataset. Acknowledgment: This work was supported by NCKU-B109-K003, which is the collaboration between National Cheng Kung University, Taiwan, and SoftBank Corp., Tokyo.

Keywords: OSML, BERT, text classification, one shot

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Authors: Pranee Liamputtong, Hala Kurban

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Based on the therapeutic landscape theory, this paper examines how young Middle-Eastern refugee individuals perceive their health and well-being and address the barriers they face in their new homeland and the means that helped them to form social connections in their new social environment. Qualitative methods (in-depth interviews and mapping activities) were conducted with ten young people from refugee backgrounds. Thematic analysis method was used to analyse the data. Findings suggested that the young refugees face various structural and cultural inequalities that significantly influenced their health and well-being. Mental health well-being was their greatest health concern. All reported the significant influence the English language had on their ability to adapt and form connections with their social environment. The presence of positive social support in their new social environment had a great impact on the health and well-being of the participants. The findings of this study have implications for social justice among refugees. They also contributed to the role of therapeutic landscapes and social support in helping young refugees to feel that they belonged to the society, and hence assisted them to adapt to their new living situation.

Keywords: young refugees, Middle-Eastern, social support, social justice

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Authors: Saahith M. S., Sivakami R.

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In the realm of football analytics, particularly focusing on predicting football player performance, the ability to forecast player success accurately is of paramount importance for teams, managers, and fans. This study introduces an elaborate examination of predicting football player performance through the integration of data visualization methods and machine learning algorithms. The research entails the compilation of an extensive dataset comprising player attributes, conducting data preprocessing, feature selection, model selection, and model training to construct predictive models. The analysis within this study will involve delving into feature significance using methodologies like Select Best and Recursive Feature Elimination (RFE) to pinpoint pertinent attributes for predicting player performance. Various machine learning algorithms, including Random Forest, Decision Tree, Linear Regression, Support Vector Regression (SVR), and Artificial Neural Networks (ANN), will be explored to develop predictive models. The evaluation of each model's performance utilizing metrics such as Mean Squared Error (MSE) and R-squared will be executed to gauge their efficacy in predicting player performance. Furthermore, this investigation will encompass a top player analysis to recognize the top-performing players based on the anticipated overall performance scores. Nationality analysis will entail scrutinizing the player distribution based on nationality and investigating potential correlations between nationality and player performance. Positional analysis will concentrate on examining the player distribution across various positions and assessing the average performance of players in each position. Age analysis will evaluate the influence of age on player performance and identify any discernible trends or patterns associated with player age groups. The primary objective is to predict a football player's overall performance accurately based on their individual attributes, leveraging data-driven insights to enrich the comprehension of player success on the field. By amalgamating data visualization and machine learning methodologies, the aim is to furnish valuable tools for teams, managers, and fans to effectively analyze and forecast player performance. This research contributes to the progression of sports analytics by showcasing the potential of machine learning in predicting football player performance and offering actionable insights for diverse stakeholders in the football industry.

Keywords: football analytics, player performance prediction, data visualization, machine learning algorithms, random forest, decision tree, linear regression, support vector regression, artificial neural networks, model evaluation, top player analysis, nationality analysis, positional analysis

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Authors: Andrea Tonoli, Nicola Amati, Maria Cavatorta, Reza Mirsanei, Behzad Mozaffari, Hamed Ahani, Akbar Karamihafshejani, Mohammad Ghazivakili, Mohammad Abuabiah

Abstract:

The vibrations transmitted to the drivers and passengers through vehicle seat seriously effect on the level of their attention, fatigue and physical health and reduce the comfort and efficiency of the occupants. Recently, some researchers have focused on vibrations at low excitation frequency(0.5-5 Hz) which are considered to be the main risk factors for lumbar part of the backbone but they were not applicable to A and B-segment cars regarding to the size and weight. A semi-active system with two symmetric negative stiffness structures (NSS) in parallel to a positive stiffness structure and actuators has been proposed to attenuate low frequency excitation and makes system flexible regarding to different weight of passengers which is applicable for A and B-Segment cars. Here, the 3 degree of freedom system is considered, dynamic equation clearly is presented, then simulated in MATLAB in order to analysis of performance of the system. The design procedure is derived so that the resonance peak of frequency–response curve shift to the left, the isolating range is increased and especially, the peak of the frequency–response curve is minimized. According to ISO standard different class of road profile as an input is applied to the system to evaluate the performance of the system. To evaluate comfort issues, we extract the RMS value of the vertical acceleration acting on the passenger's body. Then apply the band-pass filter, which takes into account the human sensitivity to acceleration. According to ISO, this weighted acceleration is lower than 0.315 m/s^2, so the ride is considered as comfortable.

Keywords: low frequency excitation, negative stiffness, seat vehicle, vibration isolation

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Authors: Azin Shakibabarough, Mojtaba Valinejadshoubi, Ashutosh Bagchi

Abstract:

Structural vibration means repetitive motion that causes fatigue and reduction of the performance of a structure. An earthquake may release high amount of energy that can have adverse effect on all components of a structure. Therefore, decreasing of vibration or maintaining performance of structures such as bridges, dams, roads and buildings is important for life safety and reducing economic loss. When earthquake or any vibration happens, investigation on parts of a structure which sustain the seismic loads is mandatory to provide a safe condition for the occupants. One of the solutions for reducing the earthquake vibration in a structure is using of vibration control devices such as dampers and base isolators. The objective of this study is to investigate the optimal positions of friction dampers and base isolators for better seismic response of 2D frame. For this purpose, a two bay and six story frame with different distribution formats was modeled and some of their responses to earthquake such as inter-story drift, max joint displacement, max axial force and max bending moment were determined and compared using non-linear dynamic analysis.

Keywords: fast nonlinear analysis, friction damper, base isolator, seismic vibration control, seismic response

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Authors: Tabrej Khan, Tamer A. Sebaey, Balbir Singh, M. A. Umarfarooq

Abstract:

Spread-tow thin-ply-based technology has resulted in the progress of optimized reinforced composite plies with ultra-low thicknesses. There is wide use of composite bolted joints in the aircraft industry for load-bearing structures, and they are regarded as the primary source of stress concentration. The purpose of this study is to look into the bearing strength and structural performance of single shear bolt joint configurations in composite laminates, which are basically a combination of conventional thin-plies and thick-plies in some specific stacking sequence. The placement effect of thin-ply within the configured stack on bearing strength, as well as the potential damages, were investigated. Mechanical tests were used to understand the disfigurement mechanisms of the plies and their reciprocity, as well as to reflect on the single shear bolt joint properties and its load-bearing capacity. The results showed that changing the configuration of laminates by inserting the thin plies inside improved the bearing strength by up to 19%.

Keywords: hybrid composites, delamination, stress concentrations, mechanical testing, single bolt joint, thin-plies

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Authors: Aamna Lawrence, Ashutosh Mishra

Abstract:

Tremors occur in 60% of the patients who have Multiple Sclerosis (MS), the most common demyelinating disease that affects the central and peripheral nervous system, and are the primary cause of disability in young adults. While pharmacological agents provide minimal benefits, surgical interventions like Deep Brain Stimulation and Thalamotomy are riddled with dangerous complications which make non-invasive electrical stimulation an appealing treatment of choice for dealing with tremors. Hence, we hypothesized that if the non-invasive electrical stimulation parameters (mainly frequency) can be computed by mathematically modeling the nerve fibre to take into consideration the minutest details of the axon morphologies, tremors due to demyelination can be optimally alleviated. In this computational study, we have modeled the random demyelination pattern in a nerve fibre that typically manifests in MS using the High-Density Hodgkin-Huxley model with suitable modifications to account for the myelin. The internode of the nerve fibre in our model could have up to ten demyelinated regions each having random length and myelin thickness. The arrival time of action potentials traveling the demyelinated and the normally myelinated nerve fibre between two fixed points in space was noted, and its relationship with the nerve fibre radius ranging from 5µm to 12µm was analyzed. It was interesting to note that there were no overlaps between the arrival time for action potentials traversing the demyelinated and normally myelinated nerve fibres even when a single internode of the nerve fibre was demyelinated. The study gave us an opportunity to design DC pulses whose frequency of application would be a function of the random demyelination pattern to block only the delayed tremor-causing action potentials. The DC pulses could be delivered to the peripheral nervous system non-invasively by an electrode bracelet that would suppress any shakiness beyond it thus paving the way for wearable neuro-rehabilitative technologies.

Keywords: demyelination, Hodgkin-Huxley model, non-invasive electrical stimulation, tremor

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Authors: Reza Safdari, Goli Arji, Robab Abdolkhani Maryam zahmatkeshan

Abstract:

Background and purpose: Cardiovascular diseases are among the most common diseases in all societies. The most important step in minimizing myocardial infarction and its complications is to minimize its risk factors. The amount of medical data is increasingly growing. Medical data mining has a great potential for transforming these data into information. Using data mining techniques to generate predictive models for identifying those at risk for reducing the effects of the disease is very helpful. The present study aimed to collect data related to risk factors of heart infarction from patients’ medical record and developed predicting models using data mining algorithm. Methods: The present work was an analytical study conducted on a database containing 350 records. Data were related to patients admitted to Shahid Rajaei specialized cardiovascular hospital, Iran, in 2011. Data were collected using a four-sectioned data collection form. Data analysis was performed using SPSS and Clementine version 12. Seven predictive algorithms and one algorithm-based model for predicting association rules were applied to the data. Accuracy, precision, sensitivity, specificity, as well as positive and negative predictive values were determined and the final model was obtained. Results: five parameters, including hypertension, DLP, tobacco smoking, diabetes, and A+ blood group, were the most critical risk factors of myocardial infarction. Among the models, the neural network model was found to have the highest sensitivity, indicating its ability to successfully diagnose the disease. Conclusion: Risk prediction models have great potentials in facilitating the management of a patient with a specific disease. Therefore, health interventions or change in their life style can be conducted based on these models for improving the health conditions of the individuals at risk.

Keywords: decision trees, neural network, myocardial infarction, Data Mining

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Authors: Mazin Mohammed S. Sarhan

Abstract:

This study presents the performance of concrete beams reinforced with steel plates as a technique of reinforcement. Three reinforced concrete beams with the dimensions of 200 mm x 300 mm x 4000 mm (width x height x length, respectively) were experimentally investigated under flexural loading. The deformed steel bars were used as the main reinforcement for the first beam. A steel plate placed horizontally was used as the main reinforcement for the second beam. The bond between the steel plate and the surrounding concrete was enhanced by using steel bolts (with a diameter of 20 mm and length of 100 mm) welded to the steel plate at a regular distance of 200 mm. A pair of steel plates placed vertically was used as the main reinforcement for the third beam. The bond between the pair steel plates and the surrounding concrete was enhanced by using 4 equal steel angles (with the dimensions of 75 mm x 75 mm and the thickness of 8 mm) for each vertical steel plate. Two steel angles were welded at each end of the steel plate. The outcomes revealed that the bending stiffness of the beams reinforced with steel plates was higher than that reinforced with deformed steel bars. Also, the flexural ductile behavior of the second beam was much higher than the rest beams.

Keywords: concrete beam, deflection, ductility, plate

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Authors: P. Afsharian, S. Mousazadeh, M. Shahhoseini, R. Aflatoonian

Abstract:

Introduction: Matrix MetalloProteinases (MMPs) degrade extracellular matrix components to provide normal remodeling and contribute to pathological tissue destruction and cell migration in endometriosis. It is accepted that MMPs are resistant to suppression by progesterone in endometriotic tissues. The physiological effects of progesterone are mediated by its two progesterone receptor (PGR) isoforms, namely PGR-A and PGR-B. The capacity of progesterone affect to gene expression is dependent on the PGR-A/PGR-B ratio. The imbalance ratio in endometriotic tissue may be an important mechanism to be resulted in Progesterone resistance and modify progesterone action via differential regulation of specific progesterone response genes and improve endometriosis disease. Material and methods: RNA was extracted from twenty ectopic (endometriotic) and eutopic (endometrial) tissue samples of women undergoing laparoscopy for endometriosis and 20 healthy fertile women at Royan Institute, Tehran, Iran. Analysis of PGR-A, PGR-B, MMP-2 and MMP-9 mRNA expression was performed using Real-time PCR in ectopic and eutopic tissues. Then, Statistical analysis was calculated according to the 2-ΔΔCT equation for all samples. Results: Quantitative RT–PCR analyses of PGR-A and PGR-B mRNA revealed that there were differences in both isoformes of PGRs mRNA expressions between ectopic and control eutopic tissues. We were able to demonstrate low expression levels of PGR-B isoforms in ectopic tissues. Although, PGR-A expression was significantly higher in the same ectopic samples compare to controls.This method permitted us to demonstrate significant overexpression of MMP-2 and MMP-9 in ectopic samples compared to control endometrial tissues, as well. Conclusions: Our data suggest that low expression levels of PGR-B and overexpression of PGR-A can alter PGR-A/PGR-B ratio in endometriotic ectopic tissues. Imbalance ratio of PGRs in endometriotic tissue may be able to consequence MMP-2 and MMP-9 overexpression which can be important in pathogenesis and treatment of disease.

Keywords: endometriosis, matrix metalloproteinases, progesterone receptor -A and -B, PGR-A/PGR-B ratio

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