Search results for: physical traffic model

Authors: Ferry Kurniawan

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In this paper, we nowcast quarterly output growth in Indonesia by exploiting higher frequency data (monthly indicators) using a mixed-frequency factor model and exploiting both quarterly and monthly data. Nowcasting quarterly GDP in Indonesia is particularly relevant for the central bank of Indonesia which set the policy rate in the monthly Board of Governors Meeting; whereby one of the important step is the assessment of the current state of the economy. Thus, having an accurate and up-to-date quarterly GDP nowcast every time new monthly information becomes available would clearly be of interest for central bank of Indonesia, for example, as the initial assessment of the current state of the economy -including nowcast- will be used as input for longer term forecast. We consider a small scale mixed-frequency factor model to produce nowcasts. In particular, we specify variables as year-on-year growth rates thus the relation between quarterly and monthly data is expressed in year-on-year growth rates. To assess the performance of the model, we compare the nowcasts with two other approaches: autoregressive model –which is often difficult when forecasting output growth- and Mixed Data Sampling (MIDAS) regression. In particular, both mixed frequency factor model and MIDAS nowcasts are produced by exploiting the same set of monthly indicators. Hence, we compare the nowcasts performance of the two approaches directly. To preview the results, we find that by exploiting monthly indicators using mixed-frequency factor model and MIDAS regression we improve the nowcast accuracy over a benchmark simple autoregressive model that uses only quarterly frequency data. However, it is not clear whether the MIDAS or mixed-frequency factor model is better. Neither set of nowcasts encompasses the other; suggesting that both nowcasts are valuable in nowcasting GDP but neither is sufficient. By combining the two individual nowcasts, we find that the nowcast combination not only increases the accuracy - relative to individual nowcasts- but also lowers the risk of the worst performance of the individual nowcasts.

Keywords: nowcasting, mixed-frequency data, factor model, nowcasts combination

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Authors: Lela Mirtskhulava, Mariam Khunjgurua, Nino Lomineishvili, Koba Bakuria

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Software reliability prediction gives a great opportunity to measure the software failure rate at any point throughout system test. A software reliability prediction model provides with the technique for improving reliability. Software reliability is very important factor for estimating overall system reliability, which depends on the individual component reliabilities. It differs from hardware reliability in that it reflects the design perfection. Main reason of software reliability problems is high complexity of software. Various approaches can be used to improve the reliability of software. We focus on software reliability model in this article, assuming that there is a time redundancy, the value of which (the number of repeated transmission of basic blocks) can be an optimization parameter. We consider given mathematical model in the assumption that in the system may occur not only irreversible failures, but also a failure that can be taken as self-repairing failures that significantly affect the reliability and accuracy of information transfer. Main task of the given paper is to find a time distribution function (DF) of instructions sequence transmission, which consists of random number of basic blocks. We consider the system software unreliable; the time between adjacent failures has exponential distribution.

Keywords: exponential distribution, conditional mean time to failure, distribution function, mathematical model, software reliability

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Authors: Abolfazl Hedayatipoor, Mohammad Younesi Alamooti

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In order to study the effect of conservative tillage on a number of physical properties of soil and the yield of rainfed wheat, an experiment in the form of a randomized complete block design (RCBD) with three replications was conducted in a field in Aliabad County, Iran. The study treatments included: T1) Conventional method, T2) Combined moldboard plow method, T3) Chisel-packer method, and T4) Direct planting method. During early October, the study soil was prepared based on these treatments in a field which was used for rainfed wheat farming in the previous year. The apparent specific gravity of soil, weighted mean diameter (WMD) of soil aggregates, soil mechanical resistance, and soil permeability were measured. Data were analyzed in MSTAT-C. Results showed that the tillage practice had no significant effect on grain yield (p < 0.05). Soil permeability was 10.9, 16.3, 15.7 and 17.9 mm/h for T1, T2, T3 and T4, respectively.

Keywords: rainfed agriculture, conservative tillage, energy consumption, wheat

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Authors: Surajbhan Sevda

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Metal containing wastewater is generated in large quintiles due to rapid industrialization. Generally, the metal present in wastewater is not biodegradable and can be accumulated in living animals, humans and plant tissue, causing disorder and diseases. The conventional metal recovery methods include chemical, physical and biological methods, but these are chemical and energy intensive. The recent development in microbial fuel cell (MFC) technology provides a new approach for metal recovery; this technology offers a flexible platform for both reduction and oxidation reaction oriented process. The use of MFCs will be a new platform for more efficient and low energy approach for metal recovery from the wastewater. So far metal recover was extensively studied using chemical, physical and biological methods. The MFCs present a new and efficient approach for removing and recovering metals from different wastewater, suggesting the use of different electrode for metal recovery can be a new efficient and effective approach.

Keywords: metal recovery, microbial fuel cell, wastewater, bioelectricity

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Authors: Noora Al-Shanfari, M. Mazharul Islam

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The cumulative incidence function (CIF) is a fundamental approach for analyzing survival data in the presence of competing risks, which estimates the marginal probability for each competing event. Parametric modeling of CIF has the advantage of fitting various shapes of CIF and estimates the impact of covariates with maximum efficiency. To calculate the total CIF's covariate influence using a parametric model., it is essential to parametrize the baseline of the CIF. As the CIF is an improper function by nature, it is necessary to utilize an improper distribution when applying parametric models. The Gompertz distribution, which is an improper distribution, is limited in its applicability as it only accounts for monotone hazard shapes. The generalized Gompertz distribution, however, can adapt to a wider range of hazard shapes, including unimodal, bathtub, and monotonic increasing or decreasing hazard shapes. In this paper, the generalized Gompertz distribution is used to parametrize the baseline of the CIF, and the parameters of the proposed model are estimated using the maximum likelihood approach. The proposed model is compared with the existing Gompertz model using the Akaike information criterion. Appropriate statistical test procedures and model-fitting criteria will be used to test the adequacy of the model. Both models are applied to the ‘colon’ dataset, which is available in the “biostat3” package in R.

Keywords: competing risks, cumulative incidence function, improper distribution, parametric modeling, survival analysis

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Authors: Emir H. Pernet, Jeimy J. Cano

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Maturity models, used descriptively to explain changes in reality or normatively to guide managers to make interventions to make organizations more effective and efficient, are based on the principles of statistical quality control promulgated by Shewhart in the years 30, and on the principles of PDCA continuous improvement (Plan, Do, Check, Act) developed by Deming and Juran. Some frameworks developed over the concept of maturity models includes COBIT, CMM, and ITIL. This paper presents some limitations of traditional maturity models, most of them based on points of reflection and analysis done by some authors. Almost all limitations are related to the mechanistic and reductionist approach of the principles over those models are built. As Systems Theory helps the understanding of the dynamics of organizations and organizational change, the development of a systemic maturity model can help to overcome some of those limitations. This document proposes a systemic maturity model, based on a systemic conceptualization of organizations, focused on the study of the functioning of the parties, the relationships among them, and their behavior as a whole. The concept of maturity from the system theory perspective is conceptually defined as an emergent property of the organization, which arises from as a result of the degree of alignment and integration of their processes. This concept is operationalized through a systemic function that measures the maturity of an organization, and finally validated by the measuring of maturity in organizations. For its operationalization and validation, the model was applied to measure the maturity of organizational Governance, Risk and Compliance (GRC) processes.

Keywords: GRC, maturity model, systems theory, viable system model

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Authors: Gideon C. Joseph

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The ability to localize mobile devices is quite important, as some applications may require location information of these devices to operate or deliver better services to the users. Although there are several ways of acquiring location data of mobile devices, the WLAN fingerprinting approach has been considered in this work. This approach uses the Received Signal Strength Indicator (RSSI) measurement as a function of the position of the mobile device. RSSI is a quantitative technique of describing the radio frequency power carried by a signal. RSSI may be used to determine RF link quality and is very useful in dense traffic scenarios where interference is of major concern, for example, indoor environments. This research aims to design a system that can predict the location of a mobile device, when supplied with the mobile’s RSSIs. The developed system takes as input the RSSIs relating to the mobile device, and outputs parameters that describe the location of the device such as the longitude, latitude, floor, and building. The relationship between the Received Signal Strengths (RSSs) of mobile devices and their corresponding locations is meant to be modelled; hence, subsequent locations of mobile devices can be predicted using the developed model. It is obvious that describing mathematical relationships between the RSSIs measurements and localization parameters is one option to modelling the problem, but the complexity of such an approach is a serious turn-off. In contrast, we propose an intelligent system that can learn the mapping of such RSSIs measurements to the localization parameters to be predicted. The system is capable of upgrading its performance as more experiential knowledge is acquired. The most appealing consideration to using such a system for this task is that complicated mathematical analysis and theoretical frameworks are excluded or not needed; the intelligent system on its own learns the underlying relationship in the supplied data (RSSI levels) that corresponds to the localization parameters. These localization parameters to be predicted are of two different tasks: Longitude and latitude of mobile devices are real values (regression problem), while the floor and building of the mobile devices are of integer values or categorical (classification problem). This research work presents artificial neural network based intelligent systems to model the relationship between the RSSIs predictors and the mobile device localization parameters. The designed systems were trained and validated on the collected WLAN fingerprint database. The trained networks were then tested with another supplied database to obtain the performance of trained systems on achieved Mean Absolute Error (MAE) and error rates for the regression and classification tasks involved therein.

Keywords: indoor localization, WLAN fingerprinting, neural networks, classification, regression

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Authors: Sanja Manchevska, Vaska Antevska, Lidija Todorovska, Beti Dejanova, Sunchica Petrovska, Ivanka Karagjozova, Elizabeta Sivevska, Jasmina Pluncevic Gligoroska

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Introduction: A number of positive effects on the player’s physical status, including the body mass components are attributed to training process. As young soccer players grow up qualitative and quantitative changes appear and contribute to better performance. Player’s anthropometric and physiologic characteristics are recognized as important determinants of performance. Material: A sample of 52 soccer players with an age span from 9 to 14 years were divided in two groups differentiated by age. The younger group consisted of 25 boys under 11 years (mean age 10.2) and second group consisted of 27 boys with mean age 12.64. Method: The set of basic anthropometric parameters was analyzed: height, weight, BMI (Body Mass Index) and body mass components. Maximal oxygen uptake was tested using the treadmill protocol by Brus. Results: The group aged under 11 years showed the following anthropometric and physiological features: average height= 143.39cm, average weight= 44.27 kg; BMI= 18.77; Err = 5.04; Hb= 13.78 g/l; VO2=37.72 mlO2/kg. Average values of analyzed parameters were as follows: height was 163.7 cm; weight= 56.3 kg; BMI = 19.6; VO2= 39.52 ml/kg; Err=5.01; Hb=14.3g/l for the participants aged 12 to14 years. Conclusion: Physiological parameters (maximal oxygen uptake, erythrocytes and Hb) were insignificantly higher in the older group compared to the younger group. There were no statistically significant differences between analyzed anthropometric parameters among the two groups except for the basic measurements (height and weight).

Keywords: body composition, young soccer players, BMI, physical status

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Authors: Baljinder Singh, Navneet Sharma

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The skin can be used as the site for drug administration for continuous transdermal drug infusion into the systemic circulation. For the continuous diffusion/penetration of the drugs through the intact skin surface membrane-moderated systems, matrix dispersion type systems, adhesive diffusion controlled systems and micro reservoir systems have been developed. Various penetration enhancers are used for the drug diffusion through skin. In matrix dispersion type systems, the drug is dispersed in the solvent along with the polymers and solvent allowed to evaporate forming a homogeneous drug-polymer matrix. Matrix type systems were developed in the present study. In the present work, an attempt has been made to develop a matrix-type transdermal therapeutic system comprising of ondansetron-HCl with different ratios of hydrophilic and hydrophobic polymeric combinations using solvent evaporation technique. The physicochemical compatibility of the drug and the polymers was studied by infrared spectroscopy. The results obtained showed no physical-chemical incompatibility between the drug and the polymers. The patches were further subjected to various physical evaluations along with the in-vitro permeation studies using rat skin. On the basis of results obtained form the in vitro study and physical evaluation, the patches containing hydrophilic polymers i.e. polyvinyl alcohol and poly vinyl pyrrolidone with oleic acid as the penetration enhancer(5%) were considered as suitable for large scale manufacturing with a backing layer and a suitable adhesive membrane.

Keywords: transdermal drug delivery, penetration enhancers, hydrophilic and hydrophobic polymers, ondansetron HCl

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Authors: Nitin Ghule, S. G. Taji

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A mathematical model of hot-wall condensers used in refrigerators is presented. The model predicts the heat transfer characteristics of condenser and the effects of various design and operating parameters on condenser tube length and capacity. A finite element approach was used to model the condenser. The condenser tube is divided into elemental units, with each element consisting of adhesive tape, refrigerant tube and outer metal sheet. The heat transfer characteristics of each section are then analyzed by considering the heat transfer through the tube wall, tape and the outer sheet. Variations in inner heat transfer coefficient and pressure drop are considered depending on temperature, fluid phase, type of flow and orientation of tube. Variation in outer heat transfer coefficient is also taken into account. Various materials were analysed for the tube, tape and outer sheet.

Keywords: condenser, domestic refrigerator, heat transfer, mathematical model

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Authors: O. Benabdeljelil, A. Karioun, S. Amami, R. Rouger, M. Hamidine

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A model for preventing the risks related to climate conditions in the agricultural sector is presented. It will determine the yearly optimum premium to be paid by a producer in order to reach his required turnover. The model is based on both climatic stability and 'soft' responses of usually grown species to average climate variations at the same place and inside a safety ball which can be determined from past meteorological data. This allows the use of linear regression expression for dependence of production result in terms of driving meteorological parameters, the main ones of which are daily average sunlight, rainfall and temperature. By simple best parameter fit from the expert table drawn with professionals, optimal representation of yearly production is determined from records of previous years, and yearly payback is evaluated from minimum yearly produced turnover. The model also requires accurate pricing of commodity at N+1. Therefore, a pricing model is developed using 3 state variables, namely the spot price, the difference between the mean-term and the long-term forward price, and the long-term structure of the model. The use of historical data enables to calibrate the parameters of state variables, and allows the pricing of commodity. Application to beet sugar underlines pricer precision. Indeed, the percentage of accuracy between computed result and real world is 99,5%. Optimal premium is then deduced and gives the producer a useful bound for negotiating an offer by insurance companies to effectively protect its harvest. The application to beet production in French Oise department illustrates the reliability of present model with as low as 6% difference between predicted and real data. The model can be adapted to almost any agricultural field by changing state parameters and calibrating their associated coefficients.

Keywords: agriculture, production model, optimal price, meteorological factors, 3-factor model, parameter calibration, forward price

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Authors: Elham Sharifineyestani, Mohammad Farshchin

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Tropical cyclones are one of the most expensive and deadliest natural disasters. They cause heavy rainfall and serious flash flooding that result in billions of dollars of damage and considerable mortality each year in the United States. Prediction of the frequency of tropical cyclone-induced rainfall events can be helpful in emergency planning and flood risk management. In this study, we have developed a machine-learning model to predict the exceedance frequencies of tropical cyclone-induced rainfall events in the United States. Model results show a satisfactory agreement with available observations. To examine the effectiveness of our approach, we also have compared the result of our predictions with the exceedance frequencies predicted using a physics-based rainfall model by Feldmann.

Keywords: flash flooding, tropical cyclones, frequencies, machine learning, risk management

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Authors: Yudhajit Datta

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Will is a phenomenon that has puzzled humanity for a long time. It is a belief that Will Power of an individual affects the success achieved by an individual in life. It is thought that a person endowed with great will power can overcome even the most crippling setbacks of life while a person with a weak will cannot make the most of life even the greatest assets. Behavioral aspects of the human experience such as will are rarely subjected to quantitative study owing to the numerous uncontrollable parameters involved. This work is an attempt to subject the phenomena of will to the test of an artificial neural network. The claim being tested is that will power of an individual largely determines success achieved in life. In the study, an attempt is made to incorporate the behavioral phenomenon of will into a computational model using data pertaining to the success of individuals obtained from an experiment. A neural network is to be trained using data based upon part of the model, and subsequently used to make predictions regarding will corresponding to data points of success. If the prediction is in agreement with the model values, the model is to be retained as a candidate. Ultimately, the best-fit model from among the many different candidates is to be selected, and used for studying the correlation between success and will.

Keywords: will power, will, success, apathy factor, random factor, characteristic function, life story

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Authors: V. K. Arora, V. G. Havanagi, A. K. Sinha

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Copper slag and Jarofix are waste materials, generated during the manufacture of copper and zinc respectively, which have potential for utility in embankment and road construction. Accordingly, a research project was carried out to study the characteristics of copper slag and Jarofix to utilize in the construction of road. In this study, copper slag and Jarofix were collected from Tuticorin, State of Tamil Nadu and Hindustan Zinc Ltd., Chittorgarh, Rajasthan state, India respectively. These materials were investigated for their physical, chemical, and geotechnical characteristics. The materials were collected from the disposal area and laboratory investigations were carried out to study its feasibility for use in the construction of embankment and sub grade layers of road pavement. This paper presents the results of physical, chemical and geotechnical characteristics of copper slag and Jarofix. It was concluded that copper slag and Jarofix may be utilized in the construction of road.

Keywords: copper slag, Jarofix waste, material, road construction

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Authors: Jan Barak, Karel Frana, Joerg Stiller

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This work presents results of moist air condensation in heat exchanger. It describes theoretical knowledge and definition of moist air. Model with geometry of square canal was created for better understanding and post processing of condensation phenomena. Different approaches were examined on this model to find suitable software and model. Obtained knowledge was applied to geometry of real heat exchanger and results from experiment were compared with numerical results. One of the goals is to solve this issue without creating any user defined function in the applied code. It also contains summary of knowledge and outlook for future work.

Keywords: condensation, exchanger, experiment, validation

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Authors: Tesfaye Worku

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Human hair, chicken feathers, and hairs of other birds and animals are commonly described as waste products, and the currently available disposal methods, such as burying and burning these waste products, are contributing to environmental pollution. However, those waste products are used to develop fiber-reinforced textile composite material. In this research work, the composite was developed using human hair fiber and analysis of the mechanical and physical properties of the developed composite sample. A composite sample was made with different ratios of human hair and unsaturated polyester resin, and an analysis of the mechanical and physical properties of the developed composite sample was tested according to standards. The fabricated human hair fibers reinforced polymer matrix composite sample has given encouraging results in terms of high strength and rigidity for lightweight house ceiling board material.

Keywords: composite, human hair fiber, matrix, unsaturated polyester

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Authors: Payal Bose

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The impact of music on consumers' attention and emotions at different parts of the day are rarely/never studied. Music has been widely studied in different parameters, such as in-store music and its atmospheric effects, to understand consumer arousal, in-store traffic, perceptions of visual stimuli, and actual time spent in the store. Further other parameters such as tempo, shopper's age, volume, music preference, and its usage as foreground or background music acting as a mediator and impacting consumer behavior is also well researched. However, no study has traversed the influence of music on social media advertisements and its impact on the consumer mind. Most studies have catered to the influence of music on consumers conscious. A recent study found that playing pleasant music is more effective on weekdays in enhancing supermarkets' sales than on weekends. This led to a more pertinent question about the impact of music on different parts of the day and how it impacts the attention and emotion in the consumers’ mind is an interesting question to be asked given the fact that there is a high usage of social media advertisement consumption in the recent past on a day-to-day basis. This study would help brands on social media to structure their advertisements and engage more consumers towards their products. Prior literature has examined the effects or influence of music on consumers largely in retail, brick-and-mortar format. Hence most of the outcomes are favorable for physical retail environments. However, with the rise of Web 3.0 and social media marketing, it would be interesting to see how consumers' attention and emotion can be studied with the effects of music embedded in an advertisement during different parts of the day. A smartphone is considered a personal gadget, and viewing social media advertisements on them is mostly an intimate experience. Hence in a social media advertisement, most of the viewing happens on a one-on-one basis between the consumer and the brand advertisement. To the best of our knowledge, little or no work has explored the influence of music on different parts of the day (per the circadian rhythm) in advertising research. Previous works on social media advertisement have explored the timing of social media posts, deploying Targeted Content Advertising, appropriate content, reallocation of time, and advertising expenditure. Hence, I propose studying advertisements embedded with music during different parts of the day and its influence on consumers' attention and emotions. To address the research objectives and knowledge gap, it is intended to use a neuroscientific approach using fMRI and eye-tracking. The influence of music embedded in social media advertisement during different parts of the day would be assessed.

Keywords: music, neuromarketing, circadian rhythm, social media, engagement

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Authors: Ali Abbas

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This paper presents a descriptive model of organizational misconduct based on observed patterns that occur before and after an ethical collapse. The patterns were classified by categorizing media articles in both "for-profit" and "not-for-profit" organizations. Based on the model parameters, the paper provides a descriptive model of various organizational deflection strategies under numerous scenarios, including situations where ethical complaints build-up, situations under which whistleblowers become more prevalent, situations where large scandals that relate to leadership occur, and strategies by which organizations deflect blame when pressure builds up or when media finds out. The model parameters start with the premise of a tolerance to double standards in unethical acts when conducted by leadership or by members of corporate governance. Following this premise, the model explains how organizations engage in discursive strategies to cover up the potential conflicts that arise, including secret agreements and weakening stakeholders who may oppose the organizational acts. Deflection strategies include "preemptive" and "post-complaint" secret agreements, absence of (or vague) documented procedures, engaging in blame and scapegoating, remaining silent on complaints until the media finds out, as well as being slow (if at all) to acknowledge misconduct and fast to cover it up. The results of this paper may be used to guide organizational leaders into the implications of such shortsighted strategies toward unethical acts, even if they are deemed legal. Validation of the model assumptions through numerous media articles is provided.

Keywords: ethical decision making, prediction, scandals, organizational strategies

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Authors: Ahmet Karakuş, Akif Can Kilic, Emre Alptekin

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A growing number of studies have been conducted to determine how well-being may be predicted using well-designed models. It is necessary to investigate the backgrounds of features in order to construct a viable Subjective Well-Being (SWB) model. We have picked the suitable variables from the literature on SWB that are acceptable for real-world data instructions. The goal of this work is to evaluate the model by feeding it with SWB characteristics and then categorizing the stress levels using machine learning methods to see how well it performs on a real dataset. Despite the fact that it is a multiclass classification issue, we have achieved significant metric scores, which may be taken into account for a specific task.

Keywords: machine learning, multiclassification problem, subjective well-being, perceived stress scale

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Authors: Matthew Fleet, Savannah Elliott

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Background: This study investigates the use of teaching and learning to meet the needs of deaf children in the UK PE curriculum. Research has illustrated that deaf students in mainstream schools do not receive sufficient support from teachers in lessons. This research examines the impact of different types of hearing loss and its implications within Physical Education (PE) in secondary schools. Purpose: The purpose of this study is to highlight challenges PE teachers face and make recommendations for more inclusive learning environments for deaf students. The aims and objectives of this research are: to critically analyse the current situation for deaf students accessing the PE curriculum, by identifying barriers deaf students face; to identify the challenges for PE teachers in providing appropriate support for deaf students; to provide recommendations for deaf awareness training, to enhance PE teachers’ understanding and knowledge. Method: Semi-structured interviews collected data from both PE teachers and deaf students, to examine: the support available and coping mechanisms deaf students use when they do not receive support; strategies PE teachers use to provide support for deaf students; areas for improvement and potential strategies PE teachers can apply to their practice. Results & Conclusion: The findings from the study concluded that PE teachers were inconsistent in providing appropriate support for deaf students in PE lessons. Evidence illustrated that PE teachers had limited exposure to deaf awareness training. This impacted on their ability to support deaf students effectively. Communication was a frequent barrier for deaf students, affecting their ability to retain and learn information. Also, the use of assistive technology was found to be compromised in practical PE lessons.

Keywords: physical education, deaf, inclusion, education

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Authors: Chanya Inprasit, Ching-Liang Hsieh, Yi-Wen Lin

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Obesity (OB) is a hazardous global health problem that has been increasing in prevalence, more severely in last decade. It is the mainly resultant from the imbalance between food consumption and energy expenditure, which is concordant with a modern lifestyle, implying an increase in calories with poorer quality of food intake accompanied by a decrease in physical activities. Obesity does not concern the appearance only but is also a major factor contributing to poor physiology, psychology, society and economic issues. Moreover, OB induces low-grade inflammation in the body through the regulatory effect it enacts on the adipocyte function. Various alternative treatments were investigated for body weight control, including Acupoint Catgut Embedding (ACE). ACE is the implantation of absorbable catgut sutures at specific acupoints, displaying durable and potent stimulation and thereby reducing the treatment frequency. Our study utilized a mouse model to exclude any psychological factors of OB and ACE treatment. High-fat diet and body weight were measured once a week before subjects in ACE and Sham group received the ACE treatment or placebo treatment. We hypothesized that ACE can control body weight through the interaction of the TRPV1 pathways, as TRPV1 accordingly responds to inflammatory factors. The results of body weight variation show a significant decrease in body weight in ACE group compared with the baseline of control and Sham group. Meanwhile, converse results were explored in TRPV1 knockout mice, where a significant maintenance of normal body weight throughout the experiment period was observed. There was no significant difference in food consumption of each group. These finding indicated that TRPV1 pathways and its associated pathways may be involved in the maintenance of body weight, which can be controlled by ACE treatment of genetic manipulation.

Keywords: acupoint catgut embedding, obesity, hypothalamus, TRPV1

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Authors: Quentin C.P. Bourgogne, Vanessa Bouchart, Pierre Chevrier, Emmanuel Dattoli

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This study presents an experimental and theoretical work conducted on a PolyPhenylene Sulfide reinforced with 40%wt of short glass fibers (PPS GF40) and its matrix. Thermoplastics are widely used in the automotive industry to lightweight automotive parts. The replacement of metallic parts by thermoplastics is reaching under-the-hood parts, near the engine. In this area, the parts are subjected to high temperatures and are immersed in cooling liquid. This liquid is composed of water and glycol and can affect the mechanical properties of the composite. The aim of this work was thus to quantify the evolution of mechanical properties of the thermoplastic composite, as a function of temperature and liquid aging effects, in order to develop a reliable design of parts. An experimental campaign in the tensile mode was carried out at different temperatures and for various glycol proportions in the cooling liquid, for monotonic and cyclic loadings on a neat and a reinforced PPS. The results of these tests allowed to highlight some of the main physical phenomena occurring during these solicitations under tough hydro-thermal conditions. Indeed, the performed tests showed that temperature and liquid cooling aging can affect the mechanical behavior of the material in several ways. The more the cooling liquid contains water, the more the mechanical behavior is affected. It was observed that PPS showed a higher sensitivity to absorption than to chemical aggressiveness of the cooling liquid, explaining this dominant sensitivity. Two kinds of behaviors were noted: an elasto-plastic type under the glass transition temperature and a visco-pseudo-plastic one above it. It was also shown that viscosity is the leading phenomenon above the glass transition temperature for the PPS and could also be important under this temperature, mostly under cyclic conditions and when the stress rate is low. Finally, it was observed that soliciting this composite at high temperatures is decreasing the advantages of the presence of fibers. A new phenomenological model was then built to take into account these experimental observations. This new model allowed the prediction of the evolution of mechanical properties as a function of the loading environment, with a reduced number of parameters compared to precedent studies. It was also shown that the presented approach enables the description and the prediction of the mechanical response with very good accuracy (2% of average error at worst), over a wide range of hydrothermal conditions. A temperature-humidity equivalence principle was underlined for the PPS, allowing the consideration of aging effects within the proposed model. Then, a limit of improvement of the reachable accuracy was determinate for all models using this set of data by the application of an artificial intelligence-based model allowing a comparison between artificial intelligence-based models and phenomenological based ones.

Keywords: aging, analytical modeling, mechanical testing, polymer matrix composites, sequential model, thermomechanical

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Authors: Fehmi Bouguezzi

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This paper studies optimal licensing regimes in a linear Hotelling model where firms are located at the end points of the city and where the transportation cost is not linear but quadratic. We study for that a more general cost function and we try to compare the findings with the results of the linear cost. We find the same optimal licensing regimes. A per unit royalty is optimal when innovation is not drastic and no licensing is better when innovation is drastic. We also find that no licensing is always better than fixed fee licensing.

Keywords: Hotelling model, technology transfer, patent licensing, quadratic transportation cost

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Authors: Kwabena Asare, Ezekiel N. N. Nortey, Felix O. Mettle

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Modelling of extreme events has always been of interest in fields such as hydrology and meteorology. However, after the recent global financial crises, appropriate models for modelling of such rare events leading to these crises have become quite essential in the finance and risk management fields. This paper models the extreme values of the Ghana Stock Exchange All-Shares indices (2000-2010) by applying the Extreme Value Theory to fit a model to the tails of the daily stock returns data. A conditional approach of the EVT was preferred and hence an ARMA-GARCH model was fitted to the data to correct for the effects of autocorrelation and conditional heteroscedastic terms present in the returns series, before EVT method was applied. The Peak Over Threshold (POT) approach of the EVT, which fits a Generalized Pareto Distribution (GPD) model to excesses above a certain selected threshold, was employed. Maximum likelihood estimates of the model parameters were obtained and the model’s goodness of fit was assessed graphically using Q-Q, P-P and density plots. The findings indicate that the GPD provides an adequate fit to the data of excesses. The size of the extreme daily Ghanaian stock market movements were then computed using the Value at Risk (VaR) and Expected Shortfall (ES) risk measures at some high quantiles, based on the fitted GPD model.

Keywords: extreme value theory, expected shortfall, generalized pareto distribution, peak over threshold, value at risk

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Authors: Anwar U. Haque, Waqar Asrar, Ashraf Ali Omar, Erwin Sulaeman, Jaffer Sayed Mohamed Ali

Abstract:

Due to the interference effects, the intrinsic aerodynamic parameters obtained from the individual component testing are always fundamentally different than those obtained for complete model testing. Consideration and limitation for such testing need to be taken into account in any design work related to the component buildup method. In this paper, the scaled model of a straight rectangular canard of a hybrid buoyant aircraft is tested at 50 m/s in IIUM-LSWT (Low-Speed Wind Tunnel). Model and its attachment with the balance are kept rigid to have results free from the aeroelastic distortion. Based on the velocity profile of the test section’s floor; the height of the model is kept equal to the corresponding boundary layer displacement. Balance measurements provide valuable but limited information of the overall aerodynamic behavior of the model. Zero lift coefficient is obtained at -2.2o and the corresponding drag coefficient was found to be less than that at zero angles of attack. As a part of the validation of low fidelity tool, the plot of lift coefficient plot was verified by the experimental data and except the value of zero lift coefficient, the overall trend has under-predicted the lift coefficient. Based on this comparative study, a correction factor of 1.36 is proposed for lift curve slope obtained from the panel method.

Keywords: wind tunnel testing, boundary layer displacement, lift curve slope, canard, aerodynamics

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Authors: Jatupon Em-Udom, Nirand Pisutha-Arnond

Abstract:

The phase-field-crystal, PFC, approach is a density-functional-type material model with an atomic resolution on a diffusive timescale. Spatially, the model incorporates periodic nature of crystal lattices and can naturally exhibit elasticity, plasticity and crystal defects such as grain boundaries and dislocations. Temporally, the model operates on a diffusive timescale which bypasses the need to resolve prohibitively small atomic-vibration time steps. The PFC model has been used to study many material phenomena such as grain growth, elastic and plastic deformations and solid-solid phase transformations. In this study, the pressure-controlled dynamic equation for the PFC model was developed to simulate a single-component system under externally applied pressure; these coupled equations are important for studies of deformable systems such as those under constant pressure. The formulation is based on the non-equilibrium thermodynamics and the thermodynamics of crystalline solids. To obtain the equations, the entropy variation around the equilibrium point was derived. Then the resulting driving forces and flux around the equilibrium were obtained and rewritten as conventional thermodynamic quantities. These dynamics equations are different from the recently-proposed equations; the equations in this study should provide more rigorous descriptions of the system dynamics under externally applied pressure.

Keywords: driving forces and flux, evolution equation, non equilibrium thermodynamics, Onsager’s reciprocal relation, phase field crystal model, thermodynamics of single-component solid

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Authors: Huey-Yeu Yan, Ching-Ying Lee, Hung-Ru Lin

Abstract:

Background: Physical assessment is a vital clinical nursing competence. The gap between conventional teaching method and the way e-generation students’ preferred could be bridged owing to the support of Internet technology, i.e. interacting with online media to manage learning works. Nursing instructors in the wake of new learning pattern of the e-generation students are challenged to actively adjust and make teaching contents and methods more versatile. Objective: The objective of this research is to explore the effects on teaching and learning with live webcast-assisted on a specific topic, Physical Assessment technique, on a designated group of young nursing majors. It’s hoped that, with a way of nursing instructing, more versatile learning resources may be provided to facilitate self-directed learning. Design: This research adopts a cross-sectional descriptive survey. The instructor demonstrated physical assessment techniques and operation procedures via live webcast broadcasted online to all students. It increased both the off-time interaction between teacher and students concerning teaching materials. Methods: A convenient sampling was used to recruit a total of 52 nursing-majors at a certain university. The nursing majors took two-hour classes of Physical Assessment per week for 18 weeks (36 hrs. in total). The instruction covered four units with live webcasting and then conducted an online anonymous survey of learning outcomes by questionnaire. The research instrument was the online questionnaire, covering three major domains—online media used, learning outcome evaluation and evaluation result. The data analysis was conducted via IBM SPSS Statistics Version 2.0. The descriptive statistics was undertaken to describe the analysis of basic data and learning outcomes. Statistical methods such as descriptive statistics, t-test, ANOVA, and Pearson’s correlation were employed in verification. Results: Results indicated the following five major findings. (1) learning motivation, about four fifth of the participants agreed the online instruction resources are very helpful in improving learning motivation and raising the learning interest. (2) learning needs, about four fifth of participants agreed it was helpful to plan self-directed practice after the instruction, and meet their needs of repetitive learning and/or practice at their leisure time. (3) learning effectiveness, about two third agreed it was helpful to reduce pre-exam anxiety, and improve their test scores. (4) course objects, about three fourth agreed that it was helpful to achieve the goal of ‘executing the complete Physical Assessment procedures with proper skills’. (5) finally, learning reflection, about all of participants agreed this experience of online instructing, learning, and practicing is beneficial to them, they recommend instructor to share with other nursing majors, and they will recommend it to fellow students too. Conclusions: Live webcasting is a low-cost, convenient, efficient and interactive resource to facilitate nursing majors’ motivation of learning, need of self-directed learning and practice, outcome of learning. When live webcasting is integrated into nursing teaching, it provides an opportunity of self-directed learning to promote learning effectiveness, as such to fulfill the teaching objective.

Keywords: innovative teaching, learning effectiveness, live webcasting, physical assessment technique

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Authors: Rida B. Arieby, Hameed N. Hameed

Abstract:

In this work, tensile tests on high density polyethylene have been carried out under various constant strain rate and strain rate jump tests. The dependency of the true stress and specially the variation of volume strain have been investigated, the volume strain due to the phenomena of damage was determined in real time during the tests by an optical extensometer called Videotraction. A modified constitutive equations, including strain rate and damage effects, are proposed, such a model is based on a non-equilibrium thermodynamic approach called (DNLR). The ability of the model to predict the complex nonlinear response of this polymer is examined by comparing the model simulation with the available experimental data, which demonstrate that this model can represent the deformation behavior of the polymer reasonably well.

Keywords: strain rate jump tests, volume strain, high density polyethylene, large strain, thermodynamics approach

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Authors: R. B. Mishra

Abstract:

Hidden Markov Model (HMM) has been used in prediction and determination of states that generate different neural activations as well as mental working conditions. This paper addresses two applications of HMM; one to determine the optimal sequence of states for two neural states: Active (AC) and Inactive (IA) for the three emission (observations) which are for No Working (NW), Waiting (WT) and Working (W) conditions of human beings. Another is for the determination of optimal sequence of intentionality i.e. Believe (B), Desire (D), and Intention (I) as the states and three observational sequences: NW, WT and W. The computational results are encouraging and useful.

Keywords: hiden markov model, believe desire intention, neural activation, simulation

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Authors: S. Channgam, A. Sae-Tang, T. Termsaithong

Abstract:

In this research, the occurrences of large size events in various system sizes of the Bak-Tang-Wiesenfeld sandpile model are considered. The system sizes (square lattice) of model considered here are 25×25, 50×50, 75×75 and 100×100. The cross-correlation between the ratio of sites containing 3 grain time series and the large size event time series for these 4 system sizes are also analyzed. Moreover, a prediction method of the large-size event for the 50×50 system size is also introduced. Lastly, it can be shown that this prediction method provides a slightly higher efficiency than random predictions.

Keywords: Bak-Tang-Wiesenfeld sandpile model, cross-correlation, avalanches, prediction method

Procedia PDF Downloads 370