Search results for: adaptive thermal comfort model

Authors: Soumi Banerjee

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In this research paper we will go deep into understanding Benedict Anderson’s definition of the nation as an imagined community and we will analyze why and how national identities were created through long and complex processes, and how there can exist strong emotional bonds between people within an imagined community, given the fact that these people have never known each other personally, but will still feel some form of imagined unity. Such identity construction on the part of an individual or within societies are always in some sense in a state of flux as imagined communities are ever changing, which provides us with the ontological foundation for reaching on this paper. This sort of identity crisis among individuals living in the Western world, who are in search for psychological comfort and security, illustrates a possible need for spatially dislocated, ontologically insecure and vulnerable individuals to have a secure identity. To create such an identity there has to be something to build upon, which could be achieved through what may be termed as ‘homesteading’. This could in short, and in my interpretation of Kinnvall and Nesbitt’s concept, be described as a search for security that involves a search for ‘home’, where home acts as a secure place, which one can build an identity around. The next half of the paper will then look into how populism and identity have played an increasingly important role in the political elections in the so-called western democracies of the world, using the U.S. as an example. Notions of ‘us and them’, the people and the elites will be looked into and analyzed through a social constructivist theoretical lens. Here we will analyze how such narratives about identity and the nation state affects people, their personality development and identity in different ways by studying the U.S. President Donald Trump’s speeches and analyze if and how he used different identity creating narratives for gaining political and popular support. The reason to choose narrative analysis as a method in this research paper is to use the narratives as a device to understand how the perceived notions of 'us and them' can initiate huge identity crisis with a community or a nation-state. This is a relevant subject as results and developments such as rising populist rightwing movements are being felt in a number of European states, with the so-called Brexit vote in the U.K. and the election of Donald Trump as president are two of the prime examples. This paper will then attempt to argue that these mechanisms are strengthened and gaining significance in situations when humans in an economic, social or ontologically vulnerable position, imagined or otherwise, in a general and broad meaning perceive themselves to be under pressure, and a sense of insecurity is rising. These insecurities and sense of being under threat have been on the rise in many of the Western states that are otherwise usually perceived to be some of the safest, democratically stable and prosperous states in the world, which makes it of interest to study what has changed, and help provide some part of the explanation as to how creating a ‘them’ in the discourse of national identity can cause massive security crisis.

Keywords: identity crisis, migration, ontological security(in), nation-states

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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: Umut Tuğlu Karslı

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While, port function had a major role during the antiquity and medieval times, it has started to lose its significance in 19th century. In many port cities, while heavy industrial functions and ports have been moved out of the former port districts, the resulting derelict spaces have been transformed to new waterfront quarters to accommodate commercial, tourism, cultural, residential and public uses. Primary aim of these operations is to revitalize abandoned spaces of historical potential and re-establish a relationship between the city and the coast. Karakoy Port, field of this study, located in the Bosphorus, was surrounded by the city centre in time due to the transformation of urban functions, and as a result it has lost its former significance. While Karakoy has 24 hours lively residential and commercial uses in old times; in early 1980s, became a district of mechanical, plumbing and electronic parts suppliers during the day and a place for homeless at night. Today, activities for revitalization of this region continue in two forms and scales. First of these activities is the "planned transformation projects," which also includes the most important one “Galataport project”, and the second one is "spontaneous transformation," which consists of individual interventions. Galataport project that based on the idea of arranging the area specifically for tourists was prepared in 2005 and became a topic of tremendous public debate. On the other hand, the "spontaneous transformation" that is observed in the Karakoy District starts in 2004 with the foundation of “Istanbul Modern Museum”. Istanbul Modern, the first contemporary arts museum of the city, allowed the cultural integration of old naval warehouses of the port to the daily life. Following this adaptive reuse intervention, the district started to accommodate numerous art galleries, studios, café-workshops and design stores. In this context, this paper briefly examines revitalization studies in obsolete port regions, analyzes the planned and ongoing socio-spatial transformations in the specific case of Karakoy under the subjects of "planned transformation projects" and "spontaneous transformation", and realizes a critical review of the sustainability of the proposals on how to reinstate the district in the active life of Istanbul.

Keywords: port cities, socio-spatial transformation, urban regeneration, urban revitalization

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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: Srutirekha Giri, Manoranjan Sahoo, Anuradha Das, Pravanjan Mallick, Biswajit Mallick

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Ion Beam (IB) technique is a very powerful experimental technique for both material synthesis and material modifications. In this work, 3MeV proton beam was generated using the 3MV Tandem machine of the Institute of Physics, Bhubaneswar and extracted into air for the irradiation-induced modification purpose[1]. The polymeric material can be modeled for a three-phase system viz. crystalline(I), amorphous(II) and mesomorphic(III). So far, our knowledge is concerned. There are only few techniques reported for the synthesis of this third-phase(III) of polymer. The IB induced technique is one of them and has been reported very recently [2-4]. It was observed that by irradiating polyethylene terephthalate (PET) fiber at very low proton fluence, 10¹⁰ - 10¹² p/s, possess 2D mesophase structure. This was confirmed using X-ray diffraction technique. A low-intensity broad peak was observed at small angle of about 2θ =6º, when the fiber axis was mounted parallel to the X-ray direction. Such peak vanished in the diffraction spectrum when the fiber axis was mounted perpendicular to the beam direction. The appearance of this extra peak in a particular orientation confirms that the phase is 2-dimensionally oriented (mesophase). It is well known that the mesophase is a 2-dimensionally ordered structure but 3-dimensionally disordered. Again, the crystallite of the mesophase peak particle was measured about 3nm. The MeV proton-induced 2D mesophase patterning of nanocrystallites (3nm) of PET due to irradiation was observed within the above low fluence range and failed in high proton fluence. This is mainly due to the breaking of crystallites, radiation-induced thermal degradation, etc.

Keywords: Ion irradiation, mesophase, nanocrystallites, polymer

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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: Yogish Huchaiah, Chandrashekara Krishnappa

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This study considers the optimization and validation of experimental results using Multi-Functional Criteria Technique (MFCT). MFCT is concerned with structuring and solving decision and planning problems involving multiple variables. Production of biodiesel from Composite Oil Methyl Esters (COME) of Jatropha and Pongamia oils, mixed in various proportions and Biodiesel thus obtained from two step transesterification process were tested for various Physico-Chemical properties and it has been ascertained that they were within limits proposed by ASTME. They were blended with Petrodiesel in various proportions. These Methyl Esters were blended with Petrodiesel in various proportions and coded. These blends were used as fuels in a computerized CI DI engine to investigate Performance and Emission characteristics. From the analysis of results, it was found that 180MEM4B20 blend had the maximum Performance and minimum Emissions. To validate the experimental results, MFCT was used. Characteristics such as Fuel Consumption (FC), Brake Power (BP), Brake Specific Fuel Consumption (BSFC), Brake Thermal Efficiency (BTE), Carbon dioxide (CO2), Carbon Monoxide (CO), Hydro Carbon (HC) and Nitrogen oxide (NOx) were considered as dependent variables. It was found from the application of this method that the optimized combination of Injection Pressure (IP), Mix and Blend is 178MEM4.2B24. Overall corresponding variation between optimization and experimental results was found to be 7.45%.

Keywords: COME, IP, MFCT, optimization, PI, PN, PV

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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: Iftikhar Ahmad, Abulhakim Almajid

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Alumina (Al2O3) is an attractive structural ceramic however; brittleness turns Al2O3 down for advanced applications. Development of multi-phase phase ceramics systems is promising to curtail the brittleness and the incorporation of strong/elastic graphene, as third phase, into dual phase (Al2O3-SiC) is striking for mechanical upgrading purpose. Thin graphene nanosheets (GNS) were prepared by thermal exfoliation process and reinforced into dual phase ceramic system. The hybrid nanocomposite was consolidated by novel HF-IH (high-frequency induction heating) sintering furnace at 1500 °C under 50 MPa in vacuum conditions. Structural features and grain size of the resulting nanocomposite were analyzed by SEM and TEM whilst the mechanical properties were assessed by microhardness and nanoindentation techniques. The fracture toughness of the hybrid nanocomposites was appraised by direct crack measurement method. Electron microscopic investigations confirmed the preparation of thin (< 10 nm) graphene nanosheets (GNS). HF-IH sintering route condensed the three-phase (GNS-Al2O3-SiC) hybrid nanocomposite system to > 99% relative densities. SEM of the hybrid nanocomposites fractured surfaces revealed even distribution of the nanocomposite constituents and changed in fracture-mode. Structurally, 88% grain reduction into hybrid nanocomposite was also obtained. Mechanically, enhanced fracture toughness (50%) and hardness (53%) were also achieved for hybrid nanocomposites were attained against bench marked monolithic Al2O3.

Keywords: alumina, graphene, hybrid nanocomposites, rapid sintering

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Authors: H. C. Woo, F. Bouanis, C. S. Cojocaur

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Graphene, which consists of a single layer of carbon atoms in a honeycomb lattice, is an interesting potential optoelectronic material because of graphene’s high carrier mobility, zero bandgap, and electron–hole symmetry. Graphene can absorb light and convert it into a photocurrent over a wide range of the electromagnetic spectrum, from the ultraviolet to visible and infrared regimes. Over the last several years, a variety of graphene-based photodetectors have been reported, such as graphene transistors, graphene-semiconductor heterojunction photodetectors, graphene based bolometers. It is also reported that there are several physical mechanisms enabling photodetection: photovoltaic effect, photo-thermoelectric effect, bolometric effect, photogating effect, and so on. In this work, we report a simple approach for the realization of graphene based resistive photo-detection devices and the measurements of their photoelectrical response. The graphene were synthesized directly on the glass substrate by novel growth method patented in our lab. Then, the metal electrodes were deposited by thermal evaporation on it, with an electrode length and width of 1.5 mm and 300 μm respectively, using Co to fabricate simple graphene based resistive photosensor. The measurements show that the graphene resistive devices exhibit a photoresponse to the illumination of visible light. The observed re-sistance response was reproducible and similar after many cycles of on and off operations. This photoelectrical response may be attributed not only to the direct photocurrent process but also to the desorption of oxygen. Our work shows that the simple graphene resistive devices have potential in photodetection applications.

Keywords: graphene, resistive sensor, optoelectronics, photoresponse

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Authors: T. Hadj Sadok, R. Hattab Bey, K. Rebiha

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The valuation of juice from prickly pear of Opuntia ficus indica inermis as cocktails appears an attractive alternative because of their nutritional intake and functional compound has anti-radical activity (polyphenols, vitamin C, carotenoids, Betalaines, fiber and minerals). The juice from the fruit pulp is characterized by a high pH 5.85 which makes it difficult for its conservation and preservation requires a thermal treatment at high temperatures (over 100 °C) harmful for bioactive constituents compared to juice orange more acidic and processed at temperatures < 100 °C. The valuation as fig cocktails-orange is particularly interesting thanks to the contribution of polyph2nols, fiber, vitamin C, reducing sugar (sweetener) and betalaine, minerals while allowing lower temperature processing to decrease pH. The heat treatment of these juices: orange alone or in cocktails showed that the antioxidant power decreases by 12% in presence of 30% of juice treated by the heat and of 28 and 32% in the presence of 10 and 20% juice which shows the effect prickly pear juice of Opuntia. During storage for 4 weeks the loss of vitamin C is 40 and 38% in the presence of 10 and 20% juice and 33% in the presence of 30% pear juice parallel, a treatment of stabilization by heat affects relatively the polyphenols rate which decreases from 10.5% to 30% in the cocktail, and 6.11-6.71pour cocktails at 10% and 20%. Vitamin C decreases to 12 to 24 % after a heat treatment at 85°C for 30 minutes respectively for the orange juice and pear juice; this reduction is higher when the juice is in the form of cocktails composed of 10 to 30 % pear juice.

Keywords: prickly pear juice, orange cocktail, polyphenol, Opuntia ficus indica, vitamin

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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

Procedia PDF Downloads 163

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: 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: Abhishek Soni, A. Kumaraswamy, M. S. Mahesh

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Bullet penetration in steel plate is investigated with the help of three-dimensional, non-linear, transient, dynamic, finite elements analysis using explicit time integration code LSDYNA. The effect of large strain, strain-rate and temperature at very high velocity regime was studied from number of simulations of semi-spherical nose shape bullet penetration through single layered circular plate with 2 mm thickness at impact velocities of 500, 1000, and 1500 m/s with the help of Johnson Cook material model. Mie-Gruneisen equation of state is used in conjunction with Johnson Cook material model to determine pressure-volume relationship at various points of interests. Two material models viz. Plastic-Kinematic and Johnson- Cook resulted in different deformation patterns in steel plate. It is observed from the simulation results that the velocity drop and loss of kinetic energy occurred very quickly up to perforation of plate, after that the change in velocity and changes in kinetic energy are negligibly small. The physics behind this kind of behaviour is presented in the paper.

Keywords: AISI 4340 steel, ballistic impact simulation, bullet penetration, non-linear FEM

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Authors: Farnaz Amidi Fazli

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After long period of human experience about food processing from raw eating to canning of food in the last century now it is time to use novel technologies which are sometimes completely different from common technologies. It is possible to decontaminate food without using heat or the foods are stored without using cold chain. Pulsed electric field (PEF) processing is a non-thermal method of food preservation that uses short bursts of electricity, PEF can be used for processing liquid and semi-liquid food products. PEF processing offers high quality fresh-like liquid foods with excellent flavor, nutritional value, and shelf-life. High pressure processing (HPP) technology has the potential to fulfill both consumer and scientific requirements. The use of HPP for over 50 years has found applications in non-food industries. For food applications, ‘high pressure’ can be generally considered to be up to 600 MPa for most food products. After years, freezing has its high potential to food preservation due to new and quick freezing methods. Foods which are prepared by this technology have more acceptability and high quality comparing with old fashion slow freezing. Thus, quick freezing has further been adopted as a widespread commercial method for long-term preservation of perishable foods which improved both the health and convenience of everyone in the industrialised countries. Above parameters are achieved by Fluidised-bed freezing systems, freezing by immersion and Hydrofluidisation on the other hand new thawing methods like high-pressure, microwave, ohmic, and acoustic thawing have a key role in quality and adaptability of final product.

Keywords: quick freezing, thawing, high pressure, pulse electric, hydrofluidisation

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Authors: Aamna Lawrence, Ashutosh Mishra

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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

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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: Uchechukwu Vincent Okpala

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Under the Sun, energy is a key factor for the sustenance of life and its environment. The need to protect the environment as energy is generated and consumed has called for renewable and green energy sources. To be part of this green revolution, we synthesized and characterized undoped and velvet tamarind doped zinc sulfide (ZnS) crystals using sol-gel methods. Velvet tamarind was whittled down using the top-down approach of nanotechnology. Sodium silicate, tartaric acid, zinc nitrate, and thiourea were used as precursors. The grown samples were annealed at 105°C. Structural, optical, and compositional analyses of the grown samples revealed crystalline structures with varied crystallite sizes influenced by doping. Energy-dispersive X-ray spectroscopy confirmed elemental compositions of Zn, S, C and O in the films. Atomic percentages of the elements varied with VT doping. FT-IR analysis indicated the presence of functional groups like O-H stretching (alcohol), C=C=C stretching (alkene group), C=C bending, C-H stretching (alkane), N-H stretching (aliphatic primary amine) and N=C=S stretching (isothiocyanate) constituent in the film. The transmittance of the samples increased from the visible region to the infrared region making the samples good for poultry and solar energy applications. The bandgap energy of the films decreased as the number of VT drops increased, from 2.4 to 2.2. They were wide band gap materials and were good for optoelectronic, photo-thermal, high temperature, high power and solar cell applications.

Keywords: doping, sol-gel, velvet tamarind, ZnS.

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Authors: Minase Yitbarek Mengistu, Abrham Melkamu, Dawit Yisfaw, Bisrat Belihu, Abdulhakim Lalega

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This research was aimed at reducing and recycling waste paper and sawdust from our environment, thereby reducing environmental pollution resulting from the management/disposal of these waste materials. In this research, some mechanical properties of composite ceiling board materials made from waste paper, sawdust, and pineapple leaf fibers were investigated to determine their suitability for use in low-cost construction work. The ceiling board was obtained from the waste of paper, sawdust chips, and pineapple leaf fibers by manual mechanical bonding techniques using dissolved polystyrene films as a binding agent. The results obtained showed that the water absorption values of between 6 % and 8.1 %; as well as density values of 500 kg/mm3 and 611.1 kg/mm3.From our result, the better one is a ratio of pineapple leaf fiber 25%, sawdust 40%, binder 25%, and waste paper 10%. The composite ceiling boards were successfully nailed with firm grips. These values obtained were compared with those of the conventional ceiling boards and it was observed that these composite materials can be used for internal low-cost construction work and Insulation (acoustic and thermal) performance. It is highly recommended that small and medium enterprises be encouraged to venture into waste recycling and the production of these composite ceiling materials to create jobs for skilled and unskilled labor that are locally available.

Keywords: composite material, environment, textile, ceiling board

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Authors: Hesam Sedaghat Nejad, Navid Hosseini, Arash Nikvar Hassani

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Determination of the optimum block size with high profitability is one of the significant parameters in designation of the building stone mines. The aim of this study was to determine the optimum dimensions of building stone blocks in Delichai travertine mine of Damavand in Tehran province through combining the effective parameters proven in determination of the optimum dimensions in building stones such as the spacing of joints and gaps, extraction tools constraints with the help of modeling by Gemcom software. To this end, following simulation of the topography of the mine, the block model was prepared and then in order to use spacing joints and discontinuities as a limiting factor, the existing joints set was added to the model. Since only one almost horizontal joint set with a slope of 5 degrees was available, this factor was effective only in determining the optimum height of the block, and thus to determine the longitudinal and transverse optimum dimensions of the extracted block, the power of available loader in the mine was considered as the secondary limiting factor. According to the aforementioned factors, the optimal block size in this mine was measured as 3.4×4×7 meter.

Keywords: building stone, optimum block size, Delichay travertine mine, loader power

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Authors: Hussain Ali Bekhet, Tuan Ab. Rashid Bin Tuan Abdullah, Tahira Yasmin

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The strong relationship between energy consumption and economic growth is widely recognised. Most countries’ energy demand declined during the economic depression known as the Global Financial Crisis (GFC) of 2008–2009. The objective of the current study is to investigate the energy consumption and performance of Malaysia’s manufacturing sectors during the GFC. We applied the output multiplier approach, which is based on the input-output model. Two input-output tables of Malaysia covering 2005 and 2010 were used. The results indicate significant changes in the output multipliers of the manufacturing sectors between 2005 and 2010. Moreover, the energy-to-manufacturing sectors’ output multipliers also decreased during the GFC due to a decline in export-oriented industries during the crisis. The increasing importance of the manufacturing sector to the development of Malaysian trade resulted in a noticeable decrease in the consumption of each energy sector’s output, especially the electricity and gas sector. Based on the research findings, the Malaysian government released several policy implementations in the form of stimulus packages to enhance these sectors’ performance and generally improve the Malaysian economy.

Keywords: global financial crisis, input-output model, manufacturing, output multipliers, energy, Malaysia

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Authors: Yooncheol Lee, Jeongmin Kim, Kwang Ryel Ryu

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This paper deals with the establishment of a short-term operational plan for an air conditioner for efficient energy management of exhibition hall. The short-term operational plan is composed of a time series of operational schedules, which we have searched using genetic algorithms. Establishing operational schedule should be considered the future trends of the variables affecting the exhibition hall environment. To reflect continuously changing factors such as external temperature and occupant, short-term operational plans should be updated in real time. But it takes too much time to evaluate a short-term operational plan using EnergyPlus, a building emulation tool. For that reason, it is difficult to update the operational plan in real time. To evaluate the short-term operational plan, we designed prediction models based on machine learning with fast evaluation speed. This model, which was created by learning the past operational data, is accurate and fast. The collection of operational data and the verification of operational plans were made using EnergyPlus. Experimental results show that the proposed method can save energy compared to the reactive control method.

Keywords: exhibition hall, energy management, predictive model, simulation-based optimization

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Authors: Muhammad Jamil, Ning He, Wei Zhao

Abstract:

It is a rough estimation that the aerospace companies received orders of 37000 new aircraft, including the air ambulances, until 2037. And titanium alloys have a 15% contribution in modern aircraft's manufacturing owing to the high strength/weight ratio. Despite their application in the aerospace and medical equipment manufacturing industry, still, their high-speed machining puts a challenge in terms of tool wear, heat generation, and poor surface quality. Among titanium alloys, Ti-6Al-4V is the major contributor to aerospace application. However, its poor thermal conductivity (6.7W/mK) accumulates shear and friction heat at the tool-chip interface zone. To dissipate the heat generation and friction effect, cryogenic cooling, Minimum quantity lubrication (MQL), nanofluids, hybrid cryogenic-MQL, solid lubricants, etc., are applied frequently to underscore their significant effect on improving the machinability of Ti-6Al-4V. Nowadays, hybrid lubri-cooling is getting attention from researchers to explore their effect regarding the hard-to-cut Ti-6Al-4V. Therefore, this study is devoted to exploring the effect of hybrid ethanol-ester oil MQL regarding the cutting temperature, surface integrity, and tool life. As the ethanol provides -OH group and ester oil of long-chain molecules provide a tribo-film on the tool-workpiece interface. This could be a green manufacturing alternative for the manufacturing industry.

Keywords: hybrid lubri-cooling, surface roughness, tool wear, MQL

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Authors: Nirere Martine

Abstract:

Purpose –The purpose of this study aims to understand the intention of customers to adopt sustainable packaging and the impact of sustainable packaging on customers’ willingness to buy a product using sustainable packaging. Design/methodology/approach – A new research model based on the technology acceptance model (TAM) and structural equation modeling are used to examine causality and test relationship based on the data collected from 251 Rwanda samples. Findings – The findings indicated that perceived ease of use positively affects perceived usefulness. However, perceived usefulness and perceived ease of use positively affect the intention to adopt sustainable packaging. However, perceived risk and perceived cost negatively affect the intention to adopt sustainable packaging. The intention to adopt sustainable packaging positively affects the willingness to buy a product using sustainable packaging. Originality/value – Many researchers have investigated the issue of a consumers’ behavior to purchase a product. In particular, they have examined whether customers are willing to pay extra for a packaging product. There has been no study that has examined the impact of sustainable packaging on customers’ willingness to buy. The results of this study can help manufacturers form a better understanding of customers’ willingness to purchase a product using sustainable packaging.

Keywords: consumers’ behavioral, sustainable packaging, TAM, Rwanda

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Authors: Thi Thanh Nga Pham, Damien Philippon, Alexis Drogoul, Thi Thu Thuy Nguyen, Tien Cong Nguyen

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Mekong River Delta region of Vietnam is recognized as one of the most vulnerable to climate change due to flooding and seawater rise and therefore an increased burden of climate change-related diseases. Changes in temperature and precipitation are likely to alter the incidence and distribution of vector-borne diseases such as dengue fever. In this region, the peak of the dengue epidemic period is around July to September during the rainy season. It is believed that climate is an important factor for dengue transmission. This study aims to enhance the capacity of dengue prediction by the relationship of dengue incidences with climate and environmental variables for Mekong River Delta of Vietnam during 2005-2015. Mathematical models for vector-host infectious disease, including larva, mosquito, and human being were used to calculate the impacts of climate to the dengue transmission with incorporating geospatial data for model input. Monthly dengue incidence data were collected at provincial level. Precipitation data were extracted from satellite observations of GSMaP (Global Satellite Mapping of Precipitation), land surface temperature and land cover data were from MODIS. The value of seasonal reproduction number was estimated to evaluate the potential, severity and persistence of dengue infection, while the final infected number was derived to check the outbreak of dengue. The result shows that the dengue infection depends on the seasonal variation of climate variables with the peak during the rainy season and predicted dengue incidence follows well with this dynamic for the whole studied region. However, the highest outbreak of 2007 dengue was not captured by the model reflecting nonlinear dependences of transmission on climate. Other possible effects will be discussed to address the limitation of the model. This suggested the need of considering of both climate variables and another variability across temporal and spatial scales.

Keywords: infectious disease, dengue, geospatial data, climate

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Authors: Chutikarn Sriviboon, Witthaya Mekhum

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The purposes of this research were to analyze and evaluate successful factors in OTOP production process for the developing of learning center on OTOP production process based on Sufficiency Economic Philosophy for sustainable life quality. The research has been designed as a qualitative study to gather information from 30 OTOP producers in Bangkontee District, Samudsongkram Province. They were all interviewed on 3 main parts. Part 1 was about the production process including 1) production 2) product development 3) the community strength 4) marketing possibility and 5) product quality. Part 2 evaluated appropriate successful factors including 1) the analysis of the successful factors 2) evaluate the strategy based on Sufficiency Economic Philosophy and 3) the model of learning center on OTOP production process based on Sufficiency Economic Philosophy for sustainable life quality. The results showed that the production did not affect the environment with potential in continuing standard quality production. They used the raw materials in the country. On the aspect of product and community strength in the past 1 year, it was found that there was no appropriate packaging showing product identity according to global market standard. They needed the training on packaging especially for food and drink products. On the aspect of product quality and product specification, it was found that the products were certified by the local OTOP standard. There should be a responsible organization to help the uncertified producers pass the standard. However, there was a problem on food contamination which was hazardous to the consumers. The producers should cooperate with the government sector or educational institutes involving with food processing to reach FDA standard. The results from small group discussion showed that the community expected high education and better standard living. Some problems reported by the community included informal debt and drugs in the community. There were 8 steps in developing the model of learning center on OTOP production process based on Sufficiency Economic Philosophy for sustainable life quality.

Keywords: production process, OTOP, sufficiency economic philosophy, learning center

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Authors: F. L. Motta, M. H. A. Santana

Abstract:

Humic Acids (HA) were produced by a Trichoderma viride strain under submerged fermentation in a medium based on the oil palm Empty Fruit Bunch (EFB) and the main variables of the process were optimized by using response surface methodology. A temperature of 40°C and concentrations of 50g/L EFB, 5.7g/L potato peptone and 0.11g/L (NH4)2SO4 were the optimum levels of the variables that maximize the HA production, within the physicochemical and biological limits of the process. The optimized conditions led to an experimental HA concentration of 428.4±17.5 mg/L, which validated the prediction from the statistical model of 412.0mg/L. This optimization increased about 7–fold the HA production previously reported in the literature. Additionally, the time profiles of HA production and fungal growth confirmed our previous findings that HA production preferably occurs during fungal sporulation. The present study demonstrated that T. viride successfully produced HA via the submerged fermentation of EFB and the process parameters were successfully optimized using a statistics-based response surface model. To the best of our knowledge, the present work is the first report on the optimization of HA production from EFB by a biotechnological process, whose feasibility was only pointed out in previous works.

Keywords: empty fruit bunch, humic acids, submerged fermentation, Trichoderma viride

Procedia PDF Downloads 300