Search results for: event study methodology

Authors: D. Y. Fong, C. Y. Kuo, Y. T. Chiang, W. C. Lin

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Objectives: Qigong is an ancient Chinese practice in pursuit of a healthier body and a more peaceful mindset. It emphasizes on the restoration of vital energy (Qi) in body, mind, and spirit. The practice is the combination of gentle movements and mild breathing which help the doers reach the condition of tranquility. On account of the features of Qigong, first, we use cross-sectional methodology to compare the differences among the varied levels of Qigong practitioners on cognitive function with event-related potential (ERP) and electroencephalography (EEG). Second, we use the longitudinal methodology to explore the effects on the Qigong trainees for pretest and posttest on ERP and EEG. Current study adopts Attentional Network Test (ANT) task to examine the participants’ cognitive function, and aging-related researches demonstrated a declined tread on the cognition in older adults and exercise might ameliorate the deterioration. Qigong exercise integrates physical posture (muscle strength), breathing technique (aerobic ability) and focused intention (attention) that researchers hypothesize it might improve the cognitive function in aging adults. Method: Sixty participants were involved in this study, including 20 young adults (21.65±2.41 y) with normal physical activity (YA), 20 Qigong experts (60.69 ± 12.42 y) with over 7 years Qigong practice experience (QE), and 20 normal and healthy adults (52.90±12.37 y) with no Qigong practice experience as experimental group (EG). The EG participants took Qigong classes 2 times a week and 2 hours per time for 24 weeks with the purpose of examining the effect of Qigong intervention on cognitive function. ANT tasks (alert network, orient network, and executive control) were adopted to evaluate participants’ cognitive function via ERP’s P300 components and P300 amplitude topography. Results: Behavioral data: 1.The reaction time (RT) of YA is faster than the other two groups, and EG was faster than QE in the cue and flanker conditions of ANT task. 2. The RT of posttest was faster than pretest in EG in the cue and flanker conditions. 3. No difference among the three groups on orient, alert, and execute control networks. ERP data: 1. P300 amplitude detection in QE was larger than EG at Fz electrode in orient, alert, and execute control networks. 2. P300 amplitude in EG was larger at pretest than posttest on the orient network. 3. P300 Latency revealed no difference among the three groups in the three networks. Conclusion: Taken together these findings, they provide neuro-electrical evidence that older adults involved in Qigong practice may develop a more overall compensatory mechanism and also benefit the performance of behavior.

Keywords: Qigong, cognitive function, aging, event-related potential (ERP)

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Authors: Natasha Correa Vitória Bandeira, Lais Cordeiro Soares, Claudineia Brazil, Luciane Teresa Salvi

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The intense rain event that occurred between February 16 and 18, 2018, in the city of Barcarena in Pará, located in the North region of Brazil, demonstrates the importance of analyzing this type of event. The metropolitan mesoregion of Belem was severely punished by rains much above the averages normally expected for that time of year; this phenomenon affected, in addition to the capital, the municipalities of Barcarena, Murucupi and Muruçambá. Resulting in a great flood in the rivers of the region, whose basins were affected with great intensity of precipitation, causing concern for the local population because in this region, there are located companies that accumulate ore tailings, and in this specific case, the dam of any of these companies, leaching the ore to the water bodies of the Murucupi River Basin. This article aims to characterize this phenomenon through a special analysis of the distribution of rainfall, using data from atmospheric soundings, satellite images, radar images and data from the GPCP (Global Precipitation Climatology Project), in addition to rainfall stations located in the study region. The results of the work demonstrated a dissociation between the data measured in the meteorological stations and the other forms of analysis of this extreme event. Monitoring carried out solely on the basis of data from pluviometric stations is not sufficient for monitoring and/or diagnosing extreme weather events, and investment by the competent bodies is important to install a larger network of pluviometric stations sufficient to meet the demand in a given region.

Keywords: extreme precipitation, great flood, GPCP, ore dam

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Authors: Penn P. Wu

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Recent advances in virtual reality (VR) technologies have made it possible for students to experience a virtual on-the-scene or virtual in-person observation of an educational event. In an experimental class, the author uses VR, particularly 360° videos, to virtually engage students in an event, through a wide spectrum of educational resources, such s a virtual “bystander.” Students were able to observe the event as if they were physically on site, although they could not intervene with the scene. The author will describe the adopted equipment, specification, and cost of building them as well as the quality of VR. The author will discuss (a) feasibility, effectiveness, and efficiency of using VR as a supplemental technology to teach college students and criteria and methodologies used by the authors to evaluate them; (b) barriers and issues of technological implementation; and (c) pedagogical practices learned through this experiment. The author also attempts to explore (a) how VR could provide an interactive virtual in-person learning experience; (b) how VR can possibly change traditional college education and online education; (c) how educators and balance six critical factors: cost, time, technology, quality, result, and content.

Keywords: learning with VR, virtual experience of learning, virtual in-person learning, virtual reality for education

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Authors: Viraj Tyagi, Ajai Jain, P. K. Jain, Aarushi Jain

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This paper presents a genetic algorithm based loading methodology for a capacity constrained job-shop with the consideration of alternative process plans for each part to be produced. Performance analysis of the proposed methodology is carried out for two case studies by considering two different manufacturing scenarios. Results obtained indicate that the methodology is quite effective in improving the shop load balance, and hence, it can be included in the frameworks of manufacturing planning systems of job-shop oriented industries.

Keywords: manufacturing planning, loading, genetic algorithm, job shop

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Authors: Zita Fomukong Andam

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The decision on where to host sport events does not depend on the national politicians or specific international sport event bodies but also involves the residents of the hosting country. Sport tourism is one of the fast growing industries in the world. Cameroonians consider sport as a point of unity and growth within the country. It has a huge variety of sporting activities like swimming, canoe racing, tug of war and most especially soccer well known as football. The football national team made an impact in 1990 at the FIFA world cup. They also won the African Nations Cup five times. Being the winner of the 2017 African Cup of Nations, they are to host the 2019 African cup of Nations. The purpose of this research is to analyse the impacts of sport tourism event in Cameroon and specifically examine how this event influences the residents. A deep research discourse conducted with randomly selected 300 inbound residents and 200 Cameroonian residents living abroad. Survey questionnaires, interviews and direct observations were carried out as a method of collecting data. The results showed that sport events brings a lot of prestige and honor to the country; generate revenues to the country’s economy and particularly to the local businesses. On the other hand, the results showed that the local residents lose their intimacy, privacy, and their daily life routine is affected. In addition to this, they face negative social inequalities and environmental impacts. Understanding these results the national government and international bodies might be able to contribute to future studies and propose efficient measures to maximize the positive benefits and minimize the negative benefits.

Keywords: sport Tourism, economic impact, resident altitude, african Cup of nations

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Authors: Jill Stephenson, Marie Vaganay, Robert Cameron, Caoimhe McGurk, Neil Hewitt

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Purpose: The key aim of the research was to identify the secondary stressors experienced by businesses affected by single or repeated flooding and to determine to what extent businesses were affected by these stressors, along with any resulting impact on health. Additionally, the research aimed to establish the likelihood of businesses being re-exposed to the secondary stressors through assessing awareness of flood risk, implementation of property protection measures and level of community resilience. Design/methodology/approach: The chosen research method involved the distribution of a questionnaire survey to businesses affected by either single or repeated flood events. The questionnaire included the Impact of Event Scale (a 15-item self-report measure which assesses subjective distress caused by traumatic events). Findings: 55 completed questionnaires were returned by flood impacted businesses. 89% of the businesses had sustained internal flooding while 11% had experienced external flooding. The results established that the key secondary stressors experienced by businesses, in order of priority, were: flood damage, fear of reoccurring flooding, prevention of access to the premise/closure, loss of income, repair works, length of closure and insurance issues. There was a lack of preparedness for potential future floods and consequent vulnerability to the emergence of secondary stressors among flood affected businesses, as flood resistance or flood resilience measures had only been implemented by 11% and 13% respectively. In relation to the psychological repercussions, the Impact of Event scores suggested that potential prevalence of post-traumatic stress disorder (PTSD) was noted among 8 out of 55 respondents (l5%). Originality/value: The results improve understanding of the enduring repercussions of flood events on businesses, indicating that not only residents may be susceptible to the detrimental health impacts of flood events and single flood events may be just as likely as reoccurring flooding to contribute to ongoing stress. Lack of financial resources is a possible explanation for the lack of implementation of property protection measures among businesses, despite 49% experiencing flooding on multiple occasions. Therefore it is recommended that policymakers should consider potential sources of financial support or grants towards flood defences for flood impacted businesses. Any form of assistance should be made available to businesses at the earliest opportunity as there was no significant association between the time of the last flood event and the likelihood of experiencing PTSD symptoms.

Keywords: flood event, flood resilience, flood resistance, PTSD, secondary stressors

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Authors: Wanchalerm Patanacharoenwong, Panaya Sudta, Prachya Bumrungkun

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The paper focuses on the development of a system that combines Internet of Things (IoT) technologies and deep learning algorithms for anomaly detection in residential Electric Vehicle (EV) charging in smart cities. With the increasing number of EVs, ensuring efficient and reliable charging systems has become crucial. The aim of this research is to develop an integrated IoT and deep learning system for detecting anomalies in residential EV charging and enhancing EV load profiling and event detection in smart cities. This approach utilizes IoT devices equipped with infrared cameras to collect thermal images and household EV charging profiles from the database of Thailand utility, subsequently transmitting this data to a cloud database for comprehensive analysis. The methodology includes the use of advanced deep learning techniques such as Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM) algorithms. IoT devices equipped with infrared cameras are used to collect thermal images and EV charging profiles. The data is transmitted to a cloud database for comprehensive analysis. The researchers also utilize feature-based Gaussian mixture models for EV load profiling and event detection. Moreover, the research findings demonstrate the effectiveness of the developed system in detecting anomalies and critical profiles in EV charging behavior. The system provides timely alarms to users regarding potential issues and categorizes the severity of detected problems based on a health index for each charging device. The system also outperforms existing models in event detection accuracy. This research contributes to the field by showcasing the potential of integrating IoT and deep learning techniques in managing residential EV charging in smart cities. The system ensures operational safety and efficiency while also promoting sustainable energy management. The data is collected using IoT devices equipped with infrared cameras and is stored in a cloud database for analysis. The collected data is then analyzed using RNN, LSTM, and feature-based Gaussian mixture models. The approach includes both EV load profiling and event detection, utilizing a feature-based Gaussian mixture model. This comprehensive method aids in identifying unique power consumption patterns among EV owners and outperforms existing models in event detection accuracy. In summary, the research concludes that integrating IoT and deep learning techniques can effectively detect anomalies in residential EV charging and enhance EV load profiling and event detection accuracy. The developed system ensures operational safety and efficiency, contributing to sustainable energy management in smart cities.

Keywords: cloud computing framework, recurrent neural networks, long short-term memory, Iot, EV charging, smart grids

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Authors: Essam Almuhsin, Ben Soh, Alice Li, Azmat Ullah

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It is widely accepted that university students must acquire new knowledge, skills, awareness, and understanding to increase opportunities for professional and personal growth. The study reveals a significant increase in users engaging in e-coaching activities and a growing need for it during the COVID-19 pandemic. The paper proposes an e-coaching methodology for higher education in Saudi Arabia to address the need for effective coaching in the current online learning environment.

Keywords: role of e-coaching, e-coaching in higher education, Saudi higher education environment, e-coaching methodology, the importance of e-coaching

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Authors: Chiara Mansanta, Daniela Sani

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The present paper presents the further development of the application of a standard methodology to boost innovation inside real case studies of manufacturing companies. The proposed methodology provides a viable solution for manufacturing companies that have to evaluate new business ideas. The study underlined the concept of entrepreneurship and how a manager can use it to promote innovation inside their companies. Starting from a literature study on entrepreneurship, this paper examines the role of the manager in supporting a company’s development. The empirical part of the study is based on two manufacturing companies that used the proposed methodology to favour entrepreneurship through an alternative approach. The research demonstrated the need for companies to have a structured and well-defined methodology to achieve their goals. The purpose of this article is to understand the significance of business models inside companies and explore how they affect business strategy and innovation management. The idea is to use business models to support entrepreneurs in their decision-making processes, reducing risks and avoiding errors.

Keywords: entrepreneurship, manufacturing companies, solution validation, strategic management

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Authors: Claudio Díaz, Mabel Ortiz

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An EFL teacher education programme in Chile takes five years to train a future teacher of English. Preservice teachers are prepared to learn an advanced level of English and teach the language from 5th to 12th grade in the Chilean educational system. In the context of their first EFL Methodology course in year four, preservice teachers have to create a five-minute digital story that starts from a critical incident they have experienced as teachers-to-be during their observations or interventions in the schools. A critical incident can be defined as a happening, a specific incident or event either observed by them or involving them. The happening sparks their thinking and may make them subsequently think differently about the particular event. When they create their digital stories, preservice teachers put technology, teaching practice and theory together to narrate a story that is complemented by still images, moving images, text, sound effects and music. The story should be told as a personal narrative, which explains the critical incident. This presentation will focus on the creation process of 50 Chilean preservice teachers’ digital stories highlighting the critical incidents they started their stories. It will also unpack preservice teachers’ beliefs and reflections when approaching their teaching practices in schools. These beliefs will be coded and categorized through content analysis to evidence preservice teachers’ most rooted conceptions about English teaching and learning in Chilean schools. The findings seem to indicate that preservice teachers’ beliefs are strongly mediated by contextual and affective factors.

Keywords: beliefs, digital stories, preservice teachers, practicum

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Authors: M. Mueller, M. Kuehn, M. Voelker

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In small and medium-sized enterprises (SMEs), the challenge is to create a well-grounded and reliable basis for process analysis, optimization and planning due to a lack of data. SMEs have limited access to methods with which they can effectively and efficiently analyse processes and identify cause-and-effect relationships in order to generate the necessary database and derive optimization potential from it. The implementation of digitalization within the framework of Industry 4.0 thus becomes a particular necessity for SMEs. For these reasons, the abstract presents an analysis methodology that is subject to the objective of developing an SME-appropriate methodology for efficient, temporarily feasible data collection and evaluation in flexible production and logistics systems as a basis for process analysis and optimization. The overall methodology focuses on retrospective, event-based tracing and analysis of material flow objects. The technological basis consists of Bluetooth low energy (BLE)-based transmitters, so-called beacons, and smart mobile devices (SMD), e.g. smartphones as receivers, between which distance data can be measured and derived motion profiles. The distance is determined using the Received Signal Strength Indicator (RSSI), which is a measure of signal field strength between transmitter and receiver. The focus is the development of a software-based methodology for interpretation of relative movements of transmitters and receivers based on distance data. The main research is on selection and implementation of pattern recognition methods for automatic process recognition as well as methods for the visualization of relative distance data. Due to an existing categorization of the database regarding process types, classification methods (e.g. Support Vector Machine) from the field of supervised learning are used. The necessary data quality requires selection of suitable methods as well as filters for smoothing occurring signal variations of the RSSI, the integration of methods for determination of correction factors depending on possible signal interference sources (columns, pallets) as well as the configuration of the used technology. The parameter settings on which respective algorithms are based have a further significant influence on result quality of the classification methods, correction models and methods for visualizing the position profiles used. The accuracy of classification algorithms can be improved up to 30% by selected parameter variation; this has already been proven in studies. Similar potentials can be observed with parameter variation of methods and filters for signal smoothing. Thus, there is increased interest in obtaining detailed results on the influence of parameter and factor combinations on data quality in this area. The overall methodology is realized with a modular software architecture consisting of independently modules for data acquisition, data preparation and data storage. The demonstrator for initialization and data acquisition is available as mobile Java-based application. The data preparation, including methods for signal smoothing, are Python-based with the possibility to vary parameter settings and to store them in the database (SQLite). The evaluation is divided into two separate software modules with database connection: the achievement of an automated assignment of defined process classes to distance data using selected classification algorithms and the visualization as well as reporting in terms of a graphical user interface (GUI).

Keywords: event-based tracing, machine learning, process classification, parameter settings, RSSI, signal smoothing

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Authors: Gamal Abd El-Nasser A. Said, El-Sayed M. El-Horbaty

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Container handling problems at container terminals are NP-hard problems. This paper presents an approach using discrete-event simulation modeling to optimize solution for storage space allocation problem, taking into account all various interrelated container terminal handling activities. The proposed approach is applied on a real case study data of container terminal at Alexandria port. The computational results show the effectiveness of the proposed model for optimization of storage space allocation in container terminal where 54% reduction in containers handling time in port is achieved.

Keywords: container terminal, discrete-event simulation, optimization, storage space allocation

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Authors: Eva Čáslavová, Andrej Višněvský

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This research focused on the dimensions of brand personality of the Ice Hockey World Championship sporting event. The authors compared the elements in relation to different demographic groups including gender, age, level of education and student status of the population of Prague. Moreover, the differences of opinions of respondents who had experience of visiting a sports event and those who had not were assessed. In the research, the modified brand personality scale was used. This modified scale consists of five dimensions: responsibility, activity, toughness, individuality and emotionality, none of which was previously tested. The authors had an intentional sample of 291 respondents from Prague available, ranging in age from 18 years to 75 years, with either a high school or university education. The respondents rated the characteristic features in a seven-point Likert Scale and the data was collected in November 2012. The results suggest that the Ice Hockey World Championship is most identified with these dimensions: responsibility, emotionality and activity. Men had higher mean scores (4.93) on the Likert Scale in the emotionality dimension, while women had higher mean scores (4.91) in the activity dimension. Those respondents with experience visiting an Ice Hockey World Championship match had the highest mean score (5.10) in the emotionality dimension. This research had expected to show more pronounced mean values (above six) on the Likert scale in the emotionality and activity dimensions that more strongly characterize the brand personality of the Ice Hockey World Championship, however this expectation was not confirmed.

Keywords: dimensions, brand personality, ice hockey, international sports event, marketing

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Authors: Entisar A. Elgmati

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Recurrent infant diarrhea is studied using daily data collected in Salvador, Brazil over one year and three months. A logistic regression model is fitted instead of Aalen's additive model using the same covariates that were used in the analysis with the additive model. The model gives reasonably similar results to that using additive regression model. In addition, the problem with the estimated conditional probabilities not being constrained between zero and one in additive model is solved here. Also martingale residuals that have been used to judge the goodness of fit for the additive model are shown to be useful for judging the goodness of fit of the logistic model.

Keywords: additive model, cumulative probabilities, infant diarrhoea, recurrent event

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Authors: Preeda Sansakorn, Min An

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In order to be capable of dealing with uncertainties, subjectivities, including vagueness arising in building construction projects, the application of fuzzy reasoning technique based on fuzzy set theory is proposed. This study contributes significantly to the development of a fuzzy reasoning safety risk assessment model for building construction projects that could be employed to assess the risk magnitude of each hazardous event identified during construction, and a third parameter of probability of consequence is incorporated in the model. By using the proposed safety risk analysis methodology, more reliable and less ambiguities, which provide the safety risk management project team for decision-making purposes.

Keywords: safety risk assessment, building construction safety, fuzzy reasoning, construction risk assessment model, building construction projects

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Authors: Giovanni Forte, Melania De Falco, Antonio Santo

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On 24th August 2016, central Italy was affected by a Mw 6.0 earthquake, representing the main shock of a long seismic sequence, which had a second shock Mw 6.6 on 26th October and lasts still nowadays. After the event, several field survey were carried out in the affected areas, which is made of historical masonry buildings. The post event reconnaissance missions were aimed at collecting information on the damage states of the buildings, the triggering of the landslides and the relationships with site effects. In this paper, the data collected after the event are analyzed considering the role of the geological and geomorphological setting and the ground motion scenario. The buildings displayed an uneven damage distribution, which was affected by both topographic and stratigraphic amplification. As pertains the landslides, which were the most recurrent among the ground failures, consisted mainly of rock falls and subordinately of translational slides. Finally, the collected knowledge showed a strong contribution of the local geological and geomorphological site condition on the resulting damage.

Keywords: Amatrice earthquake, damage states, landslides, site effects

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Authors: Nancy Elizabeth Naranjo Garcia

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Canoa (1976) by Felipe Cazals is a film that exposes the consequences of power that the Mexican State exercised over the 1968 student movement. The film, in this particular way, approaches the Tlatelolco Massacre from a point of view that takes into consideration the events that led up to it. Nonetheless, the reference to the political tension in Canoa remains ambiguous. Thus, the cinematographic representation refers to an event that leaves space for reflection, and as a consequence leaves evidence of an image that signals the notion of survival as Georges Didi-Huberman points out. In addition to denouncing the oppressive force by the Mexican State, the images in Canoa also emphasize what did not happen in Tlatelolco and its condensation with the student activists. To observe the images that Canoa offers in a new light, this work proposes further exploration with the following questions; How do the images in Canoa narrate? How are the images inserted in the film? In this fashion, a more profound comprehension of the objective and the essence of the images becomes feasible. As a result, it is possible to analyze the images of Canoa with the real killing at San Miguel Canoa in literature. The film visualizes a testimony of the event that once seemed unimaginable, an image that anticipates and structures the proceeding event. Therefore, this study takes a second look at how Canoa considers not only the killing at San Miguel Canoa and the Tlatlelolco Massacre, but goes further on contextualize an unimaginable image.

Keywords: cinematographic representation, student movement, Tlatelolco Massacre, unimaginable image

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Authors: Rui Du

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This paper attempts to assess the impact of a major sporting event —the Super Bowl on the local economies. The identification strategy is to compare the winning and losing cities at the National Football League (NFL) conference finals under the assumption of similar pre-treatment trends. The stock market performances of companies headquartered in these cities are used to capture the sudden changes in local economic activities during a short time span. The exogenous variations in the football game outcome allow a straightforward difference-in-differences approach to identify the effect. This study finds that the post-event trends in winning and losing cities diverge despite the fact that both cities have economically and statistically similar pre-event trends. Empirical analysis provides suggestive evidence of a positive, significant local economic impact of conference final wins, possibly through city image enhancement. Further empirical evidence shows the presence of heterogeneous effects across industrial sectors, suggesting that city image enhancing the effect of the Super Bowl participation is empirically relevant for the changes in the composition of local industries. Also, this study also adopts a similar strategy to examine the local economic impact of Super Bowl successes, however, finds no statistically significant effect.

Keywords: Super Bowl Participation, local economies, city image enhancement, difference-in-differences, industrial sectors

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Authors: Yawei Liang

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Threat from cruise missiles is among the most dangerous considerations to a warship in the modern era: anti-ship cruise missiles are fast, accurate, and extremely destructive. In this paper, the goal was to use an object-orientated environment to program a simulation to model a scenario in which a lone frigate is attacked by a wave of missiles fired at given intervals. The parameters of the simulation are modified to examine the relationships between different variables in the situation, and an analysis is performed on various aspects of the defending ship’s equipment. Finally, the results are presented, along with a brief discussion.

Keywords: discrete event simulation, Monte Carlo simulation, naval resource management, weapon-target allocation/assignment

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Authors: Roukaya Dalbouchi, Abdelkrin Zitouni

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In this paper, we propose a novel design methodology for Dynamic Partial Reconfigurable (DPR) system. This type of system has the property of being able to be modified after its design and during its execution. The suggested design methodology is generic in terms of granularity, number of modules, and reconfigurable region and suitable for any type of modern application. It is based on the interconnection between several design stages. The recommended methodology represents a guide for the design of DPR architectures that meet compromise reconfiguration/performance. To validate the proposed methodology, we use as an application a video watermarking. The comparison result shows that the proposed methodology supports all stages of DPR architecture design and characterized by a high abstraction level. It provides a dynamic/partial reconfigurable architecture; it guarantees material efficiency, the flexibility of reconfiguration, and superior performance in terms of frequency and power consumption.

Keywords: dynamically reconfigurable system, block matching algorithm, partial reconfiguration, motion vectors, video watermarking

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Authors: Hassan Naseh, Javad Roozgard

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This paper represents the methodology based on Artificial Intelligent (AI) applied to Liquid Propellant Engine (LPE) optimization. The AI methodology utilized from Adaptive neural Fuzzy Inference System (ANFIS). In this methodology, the optimum objective function means to achieve maximum performance (specific impulse). The independent design variables in ANFIS modeling are combustion chamber pressure and temperature and oxidizer to fuel ratio and output of this modeling are specific impulse that can be applied with other objective functions in LPE design optimization. To this end, the LPE’s parameter has been modeled in ANFIS methodology based on generating fuzzy inference system structure by using grid partitioning, subtractive clustering and Fuzzy C-Means (FCM) clustering for both inferences (Mamdani and Sugeno) and various types of membership functions. The final comparing optimization results shown accuracy and processing run time of the Gaussian ANFIS Methodology between all methods.

Keywords: ANFIS methodology, artificial intelligent, liquid propellant engine, optimization

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Authors: Md. Rafiul Biswas, Uzair Shah, Mohammad Alkayal, Zubair Shah, Othman Althawadi, Kamila Swart

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Background: Social media platforms play a significant role in the mediated consumption of sport, especially so for sport mega-event. The characteristics of Twitter data (e.g., user mentions, retweets, likes, #hashtag) accumulate the users in one ground and spread information widely and quickly. Analysis of Twitter data can reflect the public attitudes, behavior, and sentiment toward a specific event on a larger scale than traditional surveys. Qatar is going to be the first Arab country to host the mega sports event FIFA World Cup 2022 (Q22). Qatar has hosted the FIFA Arab Cup 2021 (FAC21) to serve as a preparation for the mega-event. Objectives: This study investigates public sentiments and experiences about FAC21 and provides an insight to enhance the public experiences for the upcoming Q22. Method: FCA21-related tweets were downloaded using Twitter Academic research API between 01 October 2021 to 18 February 2022. Tweets were divided into three different periods: before T1 (01 Oct 2021 to 29 Nov 2021), during T2 (30 Nov 2021 -18 Dec 2021), and after the FAC21 T3 (19 Dec 2021-18 Feb 2022). The collected tweets were preprocessed in several steps to prepare for analysis; (1) removed duplicate and retweets, (2) removed emojis, punctuation, and stop words (3) normalized tweets using word lemmatization. Then, rule-based classification was applied to remove irrelevant tweets. Next, the twitter-XLM-roBERTa-base model from Huggingface was applied to identify the sentiment in the tweets. Further, state-of-the-art BertTopic modeling will be applied to identify trending topics over different periods. Results: We downloaded 8,669,875 Tweets posted by 2728220 unique users in different languages. Of those, 819,813 unique English tweets were selected in this study. After splitting into three periods, 541630, 138876, and 139307 were from T1, T2, and T3, respectively. Most of the sentiments were neutral, around 60% in different periods. However, the rate of negative sentiment (23%) was high compared to positive sentiment (18%). The analysis indicates negative concerns about FAC21. Therefore, we will apply BerTopic to identify public concerns. This study will permit the investigation of people’s expectations before FAC21 (e.g., stadium, transportation, accommodation, visa, tickets, travel, and other facilities) and ascertain whether these were met. Moreover, it will highlight public expectations and concerns. The findings of this study can assist the event organizers in enhancing implementation plans for Q22. Furthermore, this study can support policymakers with aligning strategies and plans to leverage outstanding outcomes.

Keywords: FIFA Arab Cup, FIFA, Twitter, machine learning

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Authors: Jia-Chao Wang

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The cosmic microwave background radiation (CMB) freed during the recombination era can be considered as a photon source of small duration; a one-time event happened everywhere in the universe simultaneously. If space is divided into concentric shells centered at an observer’s location, one can imagine that the CMB photons originated from the nearby shells would reach and pass the observer first, and those in shells farther away would follow as time goes forward. In the Big Bang model, space expands rapidly in a time-dependent manner as described by the scale factor. This expansion results in an event horizon coincident with one of the shells, and its radius can be calculated using cosmological calculators available online. Using Planck 2015 results, its value during the recombination era at cosmological time t = 0.379 million years (My) is calculated to be Revent = 56.95 million light-years (Mly). The event horizon sets a boundary beyond which the freed CMB photons will never reach the observer. The photons within the event horizon also exhibit a peculiar behavior. Calculated results show that the CMB observed today was freed in a shell located at 41.8 Mly away (inside the boundary set by Revent) at t = 0.379 My. These photons traveled 13.8 billion years (Gy) to reach here. Similarly, the CMB reaching the observer at t = 1, 5, 10, 20, 40, 60, 80, 100 and 120 Gy are calculated to be originated at shells of R = 16.98, 29.96, 37.79, 46.47, 53.66, 55.91, 56.62, 56.85 and 56.92 Mly, respectively. The results show that as time goes by, the R value approaches Revent = 56.95 Mly but never exceeds it, consistent with the earlier statement that beyond Revent the freed CMB photons will never reach the observer. The difference Revert - R can be used as a measure of the remaining observable CMB photons. Its value becomes smaller and smaller as R approaching Revent, indicating a dwindling supply of the observable CMB radiation. In this paper, detailed dwindling effects near the event horizon are analyzed with the help of online cosmological calculators based on the lambda cold dark matter (ΛCDM) model. It is demonstrated in the literature that assuming the CMB to be a blackbody at recombination (about 3000 K), then it will remain so over time under cosmological redshift and homogeneous expansion of space, but with the temperature lowered (2.725 K now). The present result suggests that the observable CMB photon density, besides changing with space expansion, can also be affected by the dwindling supply associated with the event horizon. This raises the question of whether the blackbody of CMB at recombination can remain so over time. Being able to explain the blackbody nature of the observed CMB is an import part of the success of the Big Bang model. The present results cast some doubts on that and suggest that the model may have an additional challenge to deal with.

Keywords: blackbody of CMB, CMB radiation, dwindling supply of CMB, event horizon

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Authors: Samuel Quashie

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Ph.D. Construction Management methodology and mixed methods are organized to guide the researcher to assemble and assess data in the research activities. Construction management research is close to business management and social science research. It also contributes to researching the phenomenon and answering the research question, generating an integrated management system for post-disaster reconstruction in construction and related industries. Research methodology and methods drive the research to achieve the goal or goals, contribute to knowledge, or increase knowledge. This statement means the research methodology, mixed methods, aim, objectives, and processes address the research question, facilitate its achievement and foundation to conduct the study. Mixed methods use project-based case studies, interviews, observations, literature and archival document reviews, research questionnaires, and surveys, and evaluation of integrated systems used in the construction industry and related industries to address the research work. The research mixed methods (qualitative, quantitative) define the research topic and establish a more in-depth study. The research methodology is action research, which involves the collaboration of participants and service users to collect and evaluate data, studying the phenomenon, research question(s) to improve the situation in post-disaster reconstruction phase management.

Keywords: methodology, Ph.D. research, post-disaster reconstruction, mixed-methods qualitative and quantitative

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Authors: Hanna Poikonen, Petri Toiviainen, Mari Tervaniemi

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Event-related potentials (ERPs) evoked by simple tones in the brain have been extensively studied. However, in reality the music surrounding us is spectrally and temporally complex and dynamic. Thus, the research using natural sounds is crucial in understanding the operation of the brain in its natural environment. Music is an excellent example of natural stimulation, which, in various forms, has always been an essential part of different cultures. In addition to sensory responses, music elicits vast cognitive and emotional processes in the brain. When compared to laymen, professional musicians have stronger ERP responses in processing individual musical features in simple tone sequences, such as changes in pitch, timbre and harmony. Here we show that the ERP responses evoked by rapid changes in individual musical features are more intense in musicians than in laymen, also while listening to long excerpts of the composition Carmen. Interestingly, for professional dancers, the amplitudes of the cognitive P300 response are weaker than for musicians but still stronger than for laymen. Also, the cognitive P300 latencies of musicians are significantly shorter whereas the latencies of laymen are significantly longer. In contrast, sensory N100 do not differ in amplitude or latency between musicians and laymen. These results, acquired from a novel ERP methodology for natural music, suggest that we can take the leap of studying the brain with long pieces of natural music also with the ERP method of electroencephalography (EEG), as has already been made with functional magnetic resonance (fMRI), as these two brain imaging devices complement each other.

Keywords: electroencephalography, expertise, musical features, real-life music

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Authors: Mohamed Ibrahim, Suzan Kholeif

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The Cenomanian-Turonian boundary was a ‘greenhouse’ period. The atmosphere at that time was characterized by high CO₂; in addition, there was the widespread deposition of organic-rich sediments anomalously rich in organic carbon. The sediments, palynological, total organic carbon (TOC), stable carbon and oxygen isotopes (δ¹³C, δ¹⁸O, organic) of the Cenomanian-Turonian Bahariya and basal Abu Roash formations at the southern Tethys margin were studied in two deep wells (AG5 and AG-13), Abu Gharadig Oil Field, North Western Desert, Egypt. Some of the marine (dinoflagellate cysts), as well as the terrestrial palynoflora (spores and pollen grains), reveal extinction and origination patterns that are known elsewhere, although other species may be survived across the Cenomanian-Turonian boundary. This implies control of global changes on the palynoflora, i.e., impact of Oceanic Anoxic Event OAE2 (Bonarelli Event), rather than changes in the local environmental conditions. The basal part of the Abu Roach Formation ('G' and 'F' members, late Cenomanian) shows a positive δ ¹³C excursion of the organic fraction. The TOC is generally high between 2.20 and 3.04 % in the basal Abu Roash Formation: shale of 'G' and carbonate of 'F' members, which indicates that these two members are the main Cretaceous source rocks in the Abu Gharadig Basin and have a type I-II kerogen composition. They are distinguished by an abundance of amorphous organic matter AOM and Chlorococcalean algae, mainly Pediastrum and Scenedesmus, along with subordinate dinoflagellate cysts.

Keywords: oceanic anoxic event, cenomanian-turonian, palynofacies, western desert, Egypt

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Authors: Misbah Shahzadi

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The present study was conducted to identify the emotional and behavioral disturbances among the News Reporters covering Traumatic events. In the present study, a sample of 50 News Reporters belonging to the national and the local news agencies were selected from Rawalpindi and Islamabad who had covered any traumatic event in the past one year. Rotter’s Incomplete Sentence Blank (RISB) and Impact of Event Scale interpretations were used to assess a variety of emotional and behavioral patterns of News Reporters. Results showed that some of the frequent emotional and behavioral reactions exhibited by individuals like withdrawal, anxiety\depression, aggression, hyperarousal and avoidance behavior whereas gender-based comparisons indicated that there is no significant gender difference in the News Reporters in manifestations of behavioral and emotional disturbances. It is concluded that significant negative emotional and behavioral reactions are exhibited by the News Reporters who cover traumatic events. The study identifies the negative emotional and behavioral reactions/disturbances after trauma, which can be helpful for identifying problematic areas for counseling and therapeutic interventions for these News Reporters.

Keywords: behavioural disturbance, emotional disturbance, news reporters, traumatic events

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Authors: Azrul Azlan Iskandar Mirza

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The purpose of Funds Transfer Pricing (FTP) for Islamic Bank is to promote prudent liquidity risk-taking behavior of business units. The acquirer of stable deposits will be rewarded whilst a business unit that generates long-term assets will be charged for added liquidity funding risks. In the end, it promotes risk-adjusted pricing by incorporating profit rate risk and liquidity risk component in the product pricing. However, in the event of Shariah non-compliant (SNCE), FTP components will be examined in the rectification plan especially when Islamic banks need to purify the non-compliance income. The finding shows that the determination between actual and provision cost will defer the decision among Shariah committee in Islamic banks. This paper will review each of FTP components to ensure the classification of actual and provision costs reflect the decision on rectification process on SNCE. This will benefit future decision and its consistency of Islamic banks.

Keywords: fund transfer pricing, Islamic banking, Islamic finance, shariah non-compliant event

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Authors: D. Tedesco, G. Feletti, P. Trucco

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The present study aims to develop a Decision Support System (DSS) to support the operational decision of the Emergency Medical Service (EMS) regarding the assignment of medical emergency requests to Emergency Departments (ED). In the literature, this problem is also known as “hospital selection” and concerns the definition of policies for the selection of the ED to which patients who require further treatment are transported by ambulance. The employed research methodology consists of the first phase of revision of the technical-scientific literature concerning DSSs to support the EMS management and, in particular, the hospital selection decision. From the literature analysis, it emerged that current studies are mainly focused on the EMS phases related to the ambulance service and consider a process that ends when the ambulance is available after completing a request. Therefore, all the ED-related issues are excluded and considered as part of a separate process. Indeed, the most studied hospital selection policy turned out to be proximity, thus allowing to minimize the transport time and release the ambulance in the shortest possible time. The purpose of the present study consists in developing an optimization model for assigning medical emergency requests to the EDs, considering information relating to the subsequent phases of the process, such as the case-mix, the expected service throughput times, and the operational capacity of different EDs in hospitals. To this end, a Discrete Event Simulation (DES) model was created to evaluate different hospital selection policies. Therefore, the next steps of the research consisted of the development of a general simulation architecture, its implementation in the AnyLogic software and its validation on a realistic dataset. The hospital selection policy that produced the best results was the minimization of the Time To Provider (TTP), considered as the time from the beginning of the ambulance journey to the ED at the beginning of the clinical evaluation by the doctor. Finally, two approaches were further compared: a static approach, which is based on a retrospective estimate of the TTP, and a dynamic approach, which is based on a predictive estimate of the TTP determined with a constantly updated Winters model. Findings reveal that considering the minimization of TTP as a hospital selection policy raises several benefits. It allows to significantly reduce service throughput times in the ED with a minimum increase in travel time. Furthermore, an immediate view of the saturation state of the ED is produced and the case-mix present in the ED structures (i.e., the different triage codes) is considered, as different severity codes correspond to different service throughput times. Besides, the use of a predictive approach is certainly more reliable in terms of TTP estimation than a retrospective approach but entails a more difficult application. These considerations can support decision-makers in introducing different hospital selection policies to enhance EMSs performance.

Keywords: discrete event simulation, emergency medical services, forecast model, hospital selection

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Authors: Taha Benarbia, Kay W. Axhausen, Anugrah Ilahi

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Electric car sharing system as ecologic transportation increasing in the world. The complexity of managing electric car sharing systems, especially one-way trips and battery autonomy have direct influence to on supply and demand of system. One must be able to precisely model the demand and supply of these systems to better operate electric car sharing and estimate its effect on mobility management and the accessibility that it provides in urban areas. In this context, our work focus to develop performances optimization model of the system based on discrete event simulation and stochastic Petri net. The objective is to search optimal decisions and management parameters of the system in order to fulfil at best demand while minimizing undesirable situations. In this paper, we present new model of electric cars sharing with relocation based on monitoring system. The proposed approach also help to precise the influence of battery charging level on the behaviour of system as important decision parameter of this complex and dynamical system.

Keywords: electric car-sharing systems, smart mobility, Petri nets modelling, discrete event simulation

Procedia PDF Downloads 183