Search results for: online flood prediction system

Authors: Melissa C. LaDuke

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The purpose of this literature review was to identify the use of online communities of practice (CoPs) within e-learning environments as a method to build social interaction and student-centered educational experiences. A literature review was conducted to survey and collect scholarly thoughts concerning CoPs from a variety of sources. Data collected included best practices, ties to educational theories, and examples of online CoPs. Social interaction has been identified as a critical piece of the learning infrastructure, specifically for adult learners. CoPs are an effective way to help students connect to each other and the material of interest. The use of CoPs falls in line with many educational theories, including situated learning theory, social constructivism, connectivism, adult learning theory, and motivation. New literacies such as social media and gamification can help increase social interaction in online environments and provide methods to host CoPs. Steps to build and sustain a CoP were discussed in addition to CoP considerations and best practices.

Keywords: community of practice, knowledge sharing, social interaction, online course design, new literacies

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Authors: K. Durairaj, I. N. Umar

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The asynchronous discussion forum is one of the most widely used activities in learning management system environment. Online forum allows participants to interact, construct knowledge, and can be used to complement face to face sessions in blended learning courses. However, to what extent do the students perceive the benefits or advantages of forum remain to be seen. Through content and social network analyses, instructors will be able to gauge the students’ engagement and knowledge construction level. Thus, this study aims to analyze the students’ level of knowledge construction and their participation level that occur through online discussion. It also attempts to investigate the relationship between the level of knowledge construction and their social interaction patterns. The sample involves 23 students undertaking a master course in one public university in Malaysia. The asynchronous discussion forum was conducted for three weeks as part of the course requirement. The finding indicates that the level of knowledge construction is quite low. Also, the density value of 0.11 indicating that the overall communication among the participants in the forum is low. This study reveals that strong and significant correlations between SNA measures (in-degree centrality, out-degree centrality) and level of knowledge construction. Thus, allocating these active students in a different groups aids the interactive discussion takes place. Finally, based upon the findings, some recommendations to increase students’ level of knowledge construction and also for further research are proposed.

Keywords: asynchronous discussion forums, content analysis, knowledge construction, social network analysis

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Authors: Samia Jamshed Nauman Majeed

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Purpose: Globally, the pandemic of COVID -19 has created a massive distraction for educational reforms influencing learning options, education access, and outcomes of students in more than 190 countries which has carved marks in history. To explore the challenges and complications confronted by students and faculty members while ensuring access to online education, qualitative research was conducted. Methodology: For this purpose, a series of focus group discussions were conducted in different regions of Pakistan, which revealed interesting findings shared by Panelists, which include Vice-Chancellors, Rectors, and Deans of different private and public sector universities of Pakistan. The qualitative research aims to explore the challenges and success factors of online educations by students with diverse backgrounds of higher education institutions to maximize student educational outcomes. Findings: The findings revealed several challenges and opportunities when it comes to online education for students of higher education institutions. Simultaneously, the researchers discovered the key success factors necessary for online education. Lastly, the paper presents the research limitations and future research recommendations to streamline online education in a better way ensuring the students' success. Originality: The pandemic has forced the closure of social, business, and educational activities, which has drastically influence the quality of education with its subsequent impact on the economy. In response, numerous universities across the globe are forced to suspend their educational activities by closing the universities. Though online education has been adopted worldwide by the universities, which brought numerous issues for academia, particularly for underdeveloped countries, and Pakistani higher education reforms are no exception to this.

Keywords: online education, higher education institutions, COVID-19, challenges, key success factors

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Authors: Gabrielle Peck, Ryan Hayes

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This research presents the design and creation of a drone gas analyser, aimed at addressing the need for independent data collection and analysis of gas emissions during large-scale fires, particularly wasteland fires. The analyser drone, comprising a lightweight gas analysis system attached to a remote-controlled drone, enables the real-time assessment of smoke toxicity and the monitoring of gases released into the atmosphere during such incidents. The key components of the analyser unit included two gas line inlets connected to glass wool filters, a pump with regulated flow controlled by a mass flow controller, and electrochemical cells for detecting nitrogen oxides, hydrogen cyanide, and oxygen levels. Additionally, a non-dispersive infrared (NDIR) analyser is employed to monitor carbon monoxide (CO), carbon dioxide (CO₂), and hydrocarbon concentrations. Thermocouples can be attached to the analyser to monitor temperature, as well as McCaffrey probes combined with pressure transducers to monitor air velocity and wind direction. These additions allow for monitoring of the large fire and can be used for predictions of fire spread. The innovative system not only provides crucial data for assessing smoke toxicity but also contributes to fire prediction and management. The remote-controlled drone's mobility allows for safe and efficient data collection in proximity to the fire source, reducing the need for human exposure to hazardous conditions. The data obtained from the gas analyser unit facilitates informed decision-making by emergency responders, aiding in the protection of both human health and the environment. This abstract highlights the successful development of a drone gas analyser, illustrating its potential for enhancing smoke toxicity analysis and fire prediction capabilities. The integration of this technology into fire management strategies offers a promising solution for addressing the challenges associated with wildfires and other large-scale fire incidents. The project's methodology and results contribute to the growing body of knowledge in the field of environmental monitoring and safety, emphasizing the practical utility of drones for critical applications.

Keywords: fire prediction, drone, smoke toxicity, analyser, fire management

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Authors: Krzysztof Pomorski

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In the given work we present universal mathematical framework for modeling of cattle farm system that can set and validate various hypothesis that can be tested against experimental data. The presented work is preliminary but it is expected to be valid tool for future deeper analysis that can result in new class of prediction methods allowing early detection of cow dieseaes as well as cow performance. Therefore the presented work shall have its meaning in agriculture models and in machine learning as well. It also opens the possibilities for incorporation of certain class of biological models necessary in modeling of cow behavior and farm performance that might include the impact of environment on the farm system. Particular attention is paid to the model of coupled oscillators that it the basic building hypothesis that can construct the model showing certain periodic or quasiperiodic behavior.

Keywords: coupled ordinary differential equations, cattle farm system, numerical methods, stochastic differential equations

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Authors: Marcho Setiawan Handok, Samuel S. Lemma, Abdoulaye Fofana, Naseef Mansoor

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This paper is proposing a method to predict the outcome of the National Football League match with data from 2019 to 2022 and compare it with other popular models. The model uses open-source statistical data of each team, such as passing yards, rushing yards, fumbles lost, and scoring. Each statistical data has offensive and defensive. For instance, a data set of anticipated values for a specific matchup is created by comparing the offensive passing yards obtained by one team to the defensive passing yards given by the opposition. We evaluated the model’s performance by contrasting its result with those of established prediction algorithms. This research is using a neural network to predict the score of a National Football League match and then predict the winner of the game.

Keywords: game prediction, NFL, football, artificial neural network

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Authors: Wanida Suwunniponth

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The purpose of this research was to investigate the relationship between the factors of using online social network for tourism destination in case of Bangkok area in Thailand, by extending the use of technology acceptance model (TAM). This study employed by quantitative research and the target population were entrepreneurs and local people in Bangkok who use social network-Facebook concerning tourist destinations in Bangkok. Questionnaire was used to collect data from 300 purposive samples. The multiple regression analysis and path analysis were used to analyze data. The results revealed that most people who used Facebook for promoting tourism destinations in Bangkok perceived ease of use, perceived usefulness, perceived trust in using Facebook and influenced by social normative as well as having positive attitude towards using this application. Addition, the hypothesis results indicate that acceptance of online social network-Facebook was related to the positive attitude towards using of Facebook and related to their intention to use this application for tourism.

Keywords: Facebook, online social network, technology acceptance model, tourism destination

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Authors: Nicole A. Alford

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The study of online graduate education started just 30 years ago, with the first online graduate program in the 1990s. Institutions are looking for ways to increase retention and support the needs of students with the rapid expansion of online higher education due to the global pandemic. Online education provides access and opportunities to those who otherwise would be unable to pursue an advanced degree for logistical reasons. Thus, the objective of the critical literature review is to survey current research of student experiences given the expanding role of online doctoral programs. The guiding research questions are: What are the personal, professional, and student life practices of graduate students who enrolled in a fully online university doctoral program or course? and How do graduate students who enrolled in a fully online doctoral program or course describe the factors that contributed to their continued study? The systematic literature review was conducted employing a variety of databases to locate articles using key Boolean terms and synonyms within three categories of the e-learning, doctoral education, and student perspectives. Inclusion criteria for the literature review consisted of empirical peer-reviewed studies with original data sources that focused on doctoral programs and courses within a fully online environment and centered around student experiences. A total of 16 articles were selected based on the inclusion criteria and systemically analyzed through coding using the Boote and Beile criteria. Major findings suggest that doctoral students face stressors related to social and emotional wellbeing in the online environment. A lack of social connection, isolation, and burnout were the main challenges experienced by students. Students found support from their colleagues, advisors, and faculty to persist. Communities and cohorts of online doctoral students were found to guard against these challenges. Moreover, in the methods section of the articles, there was a lack of specificity related to student demographics, general student information, and insufficient detail about the online doctoral program. Additionally, descriptions regarding the experiences of cohorts and communities in the online environment were vague and not easily replicable with the given details. This literature review reveals that doctoral students face social and emotional challenges related to isolation and the rigor of the academic process and lean on others for support to continue in their studies. Given the lack of current knowledge about online doctoral students, it proves to be a challenge to identify effective practices and create high-retention doctoral programs in online environments. The paucity of information combined with the dramatic transition to e-learning due to the global pandemic can provide a perfect storm for attrition in these programs. Several higher education institutions have transitioned graduate studies online, thus providing an opportunity for further exploration. Given the new necessity of online learning, this work provides insight into examining current practices in online doctoral programs that have moved to this modality during the pandemic. The significance of the literature review provides a springboard for research into online doctoral programs as the solution to continue advanced education amongst a global pandemic.

Keywords: e-learning, experiences, higher education, literature review

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Authors: Archen Sara Vincent

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Gambling is the practice or act of betting or wagering on uncertain events with the hope of winning money or any other valuable assets. Nowadays, the practice of gambling can be seen in almost all grounds of events, especially in sports. In sports, this is commonly known among people as sports betting. The history of gambling can be traced about 2,000 years back. It originated from Greeks, from Greeks to the Romans, then to England, where betting on horse races was much popular among the elites. The evolution of gambling in sports has made a greater impact in the modern era. In India, the legality of gambling in sports is regulated by The Public Gambling Act 1867, which prohibits gambling activities in public places. The major draw of this statute is that it does not have specific laws regarding online sports gambling. Section 30 of The Indian Contract Act 1872 considers wagering agreements void. However, there are certain exceptions for this section, that is, (1) state-owned lotteries and (2) wagering on horse races with a sum of Rupees 500 or upward. As per the Indian Constitution, the rules regarding sports gambling are within the powers of the state legislatures. Some of the states have enacted their own laws which explicitly permit or prohibit gambling within their jurisdiction. Recently in Tamilnadu, The Tamilnadu Gaming Act was amended in 2021 to completely ban online gambling and betting. Moreover, the Central Government has introduced the Online Gaming and Prevention of Fraud Bill, 2018, to legalize and regulate sports betting in India. However, this bill has not yet been passed as law. Now as the Indian legal system does not have a specific rule regarding online sports gambling, sports betting companies use this major drawback and attract people to use the gambling and betting apps by advertising with well-known sports players and other celebrities. This paper aims to critically evaluate gambling in sports and the laws relating to it in India.

Keywords: history of gambling, The Public Gambling Act 1862, state legislations, gambling in India

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Authors: Lindsey Watson

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This research is aimed at facilitating and listening to the voices of younger children, recognising their contributions to research about the things that matter to them. Digital technology increasingly impacts on the lives of young children, therefore this study aimed at increasing children’s agency through recognising and involving their perspectives to help contribute to a wider understanding of younger children’s perceptions of online safety. Using a phenomenological approach, the paper discusses how storytelling as a creative methodological approach enabled an agentic space for children to express their views, knowledge, and perceptions of their engagement with the digital world. Setting and parental informed consent were gained in addition to an adapted approach to child assent through the use of child-friendly language and emoji stickers, which was also recorded verbally. Findings demonstrate that younger children are thinking about many aspects of digital technology and how this impacts on their lives and that storytelling as a research method is a useful tool to facilitate conversations with young children. The paper thus seeks to recognise and evaluate how creative methodologies can provide insights into children’s understanding of online safety and how this can influence practitioners and parents in supporting younger children in a digital world.

Keywords: early childhood, family, online safety, phenomenology, storytelling

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Authors: Nadish Anand, Richard D. Gould

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A simplistic model is introduced for determining the thermal characteristics of a Low-rise Residential (LRR) building and then predicts the energy usage by its Heating Ventilation & Air Conditioning (HVAC) system according to changes in weather conditions which are reflected in the Ambient Temperature (Outside Air Temperature). The LRR buildings are treated as a simple lump for solving the heat transfer problem and the model is derived using the lumped capacitance model of transient conduction heat transfer from bodies. Since most contemporary HVAC systems have a thermostat control which will have an offset temperature and user defined set point temperatures which define when the HVAC system will switch on and off. The aim is to predict without any error the Body Temperature (i.e. the Inside Air Temperature) which will estimate the switching on and off of the HVAC system. To validate the mathematical model derived from lumped capacitance we have used EnergyPlus simulation engine, which simulates Buildings with considerable accuracy. We have predicted through the low order model the Inside Air Temperature of a single house kept in three different climate zones (Detroit, Raleigh & Austin) and different orientations for summer and winter seasons. The prediction error from the model for the same day as that of model parameter calculation has showed an error of < 10% in winter for almost all the orientations and climate zones. Whereas the prediction error is only <10% for all the orientations in the summer season for climate zone at higher latitudes (Raleigh & Detroit). Possible factors responsible for the large variations are also noted in the work, paving way for future research.

Keywords: building energy, energy consumption, energy+, HVAC, low order model, lumped capacitance

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Authors: Dinnah Feye H. Andal, Ann Laurice V. Salonga

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The paper investigates the flooding event that was experienced by Marikina City residents during the onslaught of Tropical Storm Ondoy on September 26, 2009 and during the heavy downpour caused by the southwest monsoon (Habagat) on August 1-8, 2012. Typhoon Ketsana, locally known as Tropical Storm Ondoy, devastated the whole of Marikina City, displacing a lot of people from their homes and damages properties as well, as flood rose at a very short period of time. Meanwhile, the massive amount of rain water brought by the southwest monsoon lasted for a week that also caused flooding to different parts of Metro Manila including Marikina City. This paper examines how the respondents’ experiences of the flooding caused by Tropical Storm Ondoy informed the coping strategies that the households in Barangay Tumana and Provident Village employed during the flooding brought by the southwest monsoon rains. Specifically, the research compares the coping strategies to flood hazards between residents of Barangay Tumana and Provident Village before, during and after the flooding caused by the southwest monsoon rains. Both study sites have relatively low elevation and are located along rivers and creeks which make them highly susceptible to flood. Interviews with affected residents were undertaken to understand how a household's coping strategies contribute to the development of community coping strategies at the respective neighborhood level. Based from the findings, income levels, local politics, religion and social relations between and among neighbors affect the way household and community coping strategies differ in the two case study sites.

Keywords: community coping strategies, Habagat, Marikina, Ondoy

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Authors: Jingling Li, Yi Zhang, Wei Liang, Tao Cui, Jun Li

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Compared with terrestrial network, the traffic of spatial information network has both self-similarity and short correlation characteristics. By studying its traffic prediction method, the resource utilization of spatial information network can be improved, and the method can provide an important basis for traffic planning of a spatial information network. In this paper, considering the accuracy and complexity of the algorithm, the spatial information network traffic is decomposed into approximate component with long correlation and detail component with short correlation, and a time series hybrid prediction model based on wavelet decomposition is proposed to predict the spatial network traffic. Firstly, the original traffic data are decomposed to approximate components and detail components by using wavelet decomposition algorithm. According to the autocorrelation and partial correlation smearing and truncation characteristics of each component, the corresponding model (AR/MA/ARMA) of each detail component can be directly established, while the type of approximate component modeling can be established by ARIMA model after smoothing. Finally, the prediction results of the multiple models are fitted to obtain the prediction results of the original data. The method not only considers the self-similarity of a spatial information network, but also takes into account the short correlation caused by network burst information, which is verified by using the measured data of a certain back bone network released by the MAWI working group in 2018. Compared with the typical time series model, the predicted data of hybrid model is closer to the real traffic data and has a smaller relative root means square error, which is more suitable for a spatial information network.

Keywords: spatial information network, traffic prediction, wavelet decomposition, time series model

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Authors: R. O. Osaseri, A. R. Usiobaifo

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The power transformer which is responsible for the voltage transformation is of great relevance in the power system and oil-immerse transformer is widely used all over the world. A prompt and proper maintenance of the transformer is of utmost importance. The dissolved gasses content in power transformer, oil is of enormous importance in detecting incipient fault of the transformer. There is a need for accurate prediction of the incipient fault in transformer oil in order to facilitate the prompt maintenance and reducing the cost and error minimization. Study on fault prediction and diagnostic has been the center of many researchers and many previous works have been reported on the use of artificial intelligence to predict incipient failure of transformer faults. In this study machine learning technique was employed by using gradient decent algorithms and Support Vector Machine (SVM) in predicting incipient fault diagnosis of transformer. The method focuses on creating a system that improves its performance on previous result and historical data. The system design approach is basically in two phases; training and testing phase. The gradient decent algorithm is trained with a training dataset while the learned algorithm is applied to a set of new data. This two dataset is used to prove the accuracy of the proposed model. In this study a transformer fault diagnostic model based on Support Vector Machine (SVM) and gradient decent algorithms has been presented with a satisfactory diagnostic capability with high percentage in predicting incipient failure of transformer faults than existing diagnostic methods.

Keywords: diagnostic model, gradient decent, machine learning, support vector machine (SVM), transformer fault

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Authors: A. Caicedo Padilla, J. Zambrano Nájera

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Cali, the capital of Valle del Cauca and the second city of Colombia, is located in the Cauca River Valley between the Western and Central Cordillera that is South West of the country. The topography of the city is mainly flat, but it is possibly to find mountains in the west. The city has increased urbanization during XX century, especially since 1958 when started a rapid growth due to migration of people from other parts of the region. Much of that population has settled in eastern of Cali, an area originally intended for cane cultivation and a zone of flood from Cauca River and its tributaries. Due to the unplanned migration, settling was inadequate and produced changes in natural dynamics of the basins, which has resulted in increases in runoff volumes, peak flows and flow velocities, that in turn increases flood risk. Sewerage networks capacity were not enough for this higher runoff volume, because in first term they were not adequately designed and built, causing its failure. This in turn generates increasingly recurrent floods generating considerable effects on the economy and development of normal activities in Cali. Thus, it becomes very important to know hydrological behavior of Urban Watersheds. This research aims to determine the impact of urbanization on hydrology of watersheds with very low slopes. The project aims to identify changes in natural drainage patterns caused by the changes made on landscape. From the identification of such modifications it will be defined the most critical areas due to recurring flood events in the city of Cali. Critical areas are defined as areas where the sewerage system does not work properly as surface runoff increases considerable with storm events, and floods are recurrent. The assessment will be done from the analysis of Geographic Information Systems (GIS) theme layers from CVC Environmental Institution of Regional Control in Valle del Cauca, hydrological data and disaster database developed by OSSO Corporation. Rainfall data from a network and historical stream flow data will be used for analysis of historical behavior and change of precipitation and hydrological response according to homogeneous zones characterized by EMCALI S.A. public utility enterprise of Cali in 1999.

Keywords: drainage systems, land cover changes, urban hydrology, urban planning

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Authors: Mehdi Mirzaei Alavijeh, Farzad Jalilian

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Background: Marijuana is the most widely used illicit drug worldwide, especially among adolescents and young adults, which can cause numerous complications. The aim of this study was to determine the pattern, motivation use, and factors related to marijuana use among Iranian youths based on the integrative model of behavioral prediction Methods: A cross-sectional study was conducted among 174 youths marijuana user in Kermanshah County and Isfahan County, during summer 2014 which was selected with the convenience sampling for participation in this study. A self-reporting questionnaire was applied for collecting data. Data were analyzed by SPSS version 21 using bivariate correlations and linear regression statistical tests. Results: The mean marijuana use of respondents was 4.60 times at during week [95% CI: 4.06, 5.15]. Linear regression statistical showed, the structures of integrative model of behavioral prediction accounted for 36% of the variation in the outcome measure of the marijuana use at during week (R2 = 36% & P < 0.001); and among them attitude, marijuana refuse, and subjective norms were a stronger predictors. Conclusion: Comprehensive health education and prevention programs need to emphasize on cognitive factors that predict youth’s health-related behaviors. Based on our findings it seems, designing educational and behavioral intervention for reducing positive belief about marijuana, marijuana self-efficacy refuse promotion and reduce subjective norms encourage marijuana use has an effective potential to protect youths marijuana use.

Keywords: marijuana, youth, integrative model of behavioral prediction, Iran

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Authors: Suzana Ramli, Wardah Tahir

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Estimation of surface runoff depth is a vital part in any rainfall-runoff modeling. It leads to stream flow calculation and later predicts flood occurrences. GIS (Geographic Information System) is an advanced and opposite tool used in simulating hydrological model due to its realistic application on topography. The paper discusses on calculation of surface runoff depth for two selected events by using GIS with Curve Number method for Upper Klang River basin. GIS enables maps intersection between soil type and land use that later produces curve number map. The results show good correlation between simulated and observed values with more than 0.7 of R2. Acceptable performance of statistical measurements namely mean error, absolute mean error, RMSE, and bias are also deduced in the paper.

Keywords: surface runoff, geographic information system, curve number method, environment

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Authors: Lee P. Leon, Raymond Charles

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This paper presents a method of evaluating the effect of aggregate angularity on hot mix asphalt (HMA) properties and its relationship to the Permanent Deformation resistance. The research concluded that aggregate particle angularity had a significant effect on the Permanent Deformation performance, and also that with an increase in coarse aggregate angularity there was an increase in the resistance of mixes to Permanent Deformation. A comparison between the measured data and predictive data of permanent deformation predictive models showed the limits of existing prediction models. The numerical analysis described the permanent deformation zones and concluded that angularity has an effect of the onset of these zones. Prediction of permanent deformation help road agencies and by extension economists and engineers determine the best approach for maintenance, rehabilitation, and new construction works of the road infrastructure.

Keywords: aggregate angularity, asphalt concrete, permanent deformation, rutting prediction

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Authors: Abrar Al-Hasan

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Web 2.0 has significantly increased the amount of information available to users not only about firms and their offerings, but also about the activities of other individuals in their networks and markets. It is widely acknowledged that this increased availability of ‘social’ information, particularly about other individuals, is likely to influence a user’s behavior and choices. However, there are very few systematic studies of how such increased information transparency on the behavior of other users in a focal users’ network influences a focal users’ behavior in the emerging marketplace of online language learning. This study seeks to examine the value and impact of ‘social activities’ – wherein, a user sees and interacts with the learning activities of her peers – on her language learning efficiency. An online experiment in a peer-to-peer language marketplace was conducted to compare the learning efficiency of users with ‘social’ information versus users with no ‘social’ information. The results of this study highlight the impact and importance of ‘social’ information within the language learning context. The study concludes by exploring how these insights may inspire new developments in online education.

Keywords: e-Learning, language learning marketplace, peer-to-peer, social network

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Authors: Waqas A. Toor, Anis U. Baig, Nuaman Shafqat, Raafia Irfan, Muhammad Ashraf

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A 2.45GHz microwave plasma system and its few applications have been developed. Argon and helium plasma is produced by metallic nozzle and also in a quartz tube at atmospheric pressure, using WR-340 waveguide and its tapered version. The waveguide applicator is also simulated in HFSS and field patterns are analyzed for maximum power absorption in the load. The system is tuned to operate at less than 10% reflected power. Various experimental techniques are used to initiate and sustain the plasma at atmospheric pressure. Plasma of atmospheric air is also produced without using any other shielding gas. The plasma flame is also characterized by its spectrum. Spectral analyses of plasma flame can be used for online analysis of combustion gases produced in industry. The applications of the system include glass and quartz processing, vitrification, emission spectroscopy, plasma coating. Low pressure plasma applications of the system include intense UV light for water purification and ozone generation.

Keywords: HFSS high frequency structure simulator, Microwave plasma, UV ultraviolet, WR rectangular waveguide

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Authors: Vivian Guo, Yan Qu

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Online marketplaces are not only digital places where consumers buy and sell merchandise, and they are also destinations for brands to connect with real consumers at the moment when customers are in the shopping mindset. For many marketplaces, brands have been important partners through advertising. There can be, however, a risk of advertising impacting a consumer’s shopping journey if it hurts the use experience or takes the user away from the site. Both could lead to the loss of transaction revenue for the marketplace. In this paper, we present user-based methods for cannibalization control by selectively turning off ads to users who are likely to be cannibalized by ads subject to business objectives. We present ways of measuring cannibalization of advertising in the context of an online marketplace and propose novel ways of measuring cannibalization through purchase propensity and uplift modeling. A/B testing has shown that our methods can significantly improve user purchase and engagement metrics while operating within business objectives. To our knowledge, this is the first paper that addresses cannibalization mitigation at the user-level in the context of advertising.

Keywords: cannibalization, machine learning, online marketplace, revenue optimization, yield optimization

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Authors: Ayanda Magida, Brian Armstrong

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The study aimed to assess the third level of the digital divide among the millennials and post-millennials in South Africa. The millennials are people born from 1981-to 1996, that is, people between the ages of 25-40 years old and post-millennials are people born from 1997 to date. For the study, only post-millennials born between 1997-2003 were included as they were old enough to consent to participation in the study. Data was collected as part of the Ph.D. project that focuses on the relationship between income inequality, the digital divide, and social cohesion in South Africa. The digital divide has three main levels, namely the first, second and third. The first and second focus on access and usage, respectively. The third-level digital divide can be defined as the differences in the benefits associated with being online. The current paper focuses on the third level: the benefits derived by being online using four domains: economic, educational, social, and personal benefits. The economic benefits include income, employment and finance-related activities; the social benefits include socializing belonging, identity, and informal networks. The personal benefits include personal wellbeing and self-actualization. A total of 763 participants completed the survey, and 61.3% were post-millennials between the ages of 18-24 and s 38.6 % were millennials between 25 and 40. The majority of the respondents were female (62%), male (34%) and nonbinary (1%), respectively. Most of the respondents were black, followed by whites, Indians and colored, respectively. Thus, they represented the status of the demographics of the country. Most of the respondents had access to the internet and smartphone. Most expressed that they use laptops (68%) or mobile (71%) to access the internet and 54 % access the internet using wireless/Wi-Fi. There were no differences between the millennial and post-millennial economic and educational benefits of being online. However, the post-millennials were more inclined to use the internet for social and personal benefits than the millennials. This could be attributed to many factors, such as age. The post-millennials are still discovering themselves and therefore would derive social and personal benefits associated with being online. The findings confirm studies that argue that younger generations derive more benefits from being online than the older generation. Based on the findings, it is evident that the post-millennials are not using the internet or online activities for social networks and socializing but can derive economic benefits such as job looking and education benefits from being online. It can be inferred that there are no significant differences between the two groups, and it seems like the third-level digital divide is not evident among the two groups as they both have been able to derive meaningful benefits from being online. Further studies should focus on the third-level divide between the baby boomers and Generation X.

Keywords: third-level digital divide, millennials, post-millennials, online activities

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Authors: Mohammed T. Hayajneh

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Machining of Metal Matrix Composites (MMCs) is very significant process and has been a main problem that draws many researchers to investigate the characteristics of MMCs during different machining process. The poor machining properties of hard particles reinforced MMCs make drilling process a rather interesting task. Unlike drilling of conventional materials, many problems can be seriously encountered during drilling of MMCs, such as tool wear and cutting forces. Cutting tool wear is a very significant concern in industries. Cutting tool wear not only influences the quality of the drilled hole, but also affects the cutting tool life. Prediction the cutting tool life during drilling is essential for optimizing the cutting conditions. However, the relationship between tool life and cutting conditions, tool geometrical factors and workpiece material properties has not yet been established by any machining theory. In this research work, fuzzy subtractive clustering system has been used to model the cutting tool life in drilling of Al₂O₃ particle reinforced aluminum alloy composite to investigate of the effect of cutting conditions on cutting tool life. This investigation can help in controlling and optimizing of cutting conditions when the process parameters are adjusted. The built model for prediction the tool life is identified by using drill diameter, cutting speed, and cutting feed rate as input data. The validity of the model was confirmed by the examinations under various cutting conditions. Experimental results have shown the efficiency of the model to predict cutting tool life.

Keywords: composite, fuzzy, tool life, wear

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Authors: Ankit Sinha, Soham Banerjee, Pratik Chattopadhyay

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Automated product recognition in retail stores is an important real-world application in the domain of Computer Vision and Pattern Recognition. In this paper, we consider the problem of automatically identifying the classes of the products placed on racks in retail stores from an image of the rack and information about the query/product images. We improve upon the existing approaches in terms of effectiveness and memory requirement by developing a two-stage object detection and recognition pipeline comprising of a Faster-RCNN-based object localizer that detects the object regions in the rack image and a ResNet-18-based image encoder that classifies the detected regions into the appropriate classes. Each of the models is fine-tuned using appropriate data sets for better prediction and data augmentation is performed on each query image to prepare an extensive gallery set for fine-tuning the ResNet-18-based product recognition model. This encoder is trained using a triplet loss function following the strategy of online-hard-negative-mining for improved prediction. The proposed models are lightweight and can be connected in an end-to-end manner during deployment to automatically identify each product object placed in a rack image. Extensive experiments using Grozi-32k and GP-180 data sets verify the effectiveness of the proposed model.

Keywords: retail stores, faster-RCNN, object localization, ResNet-18, triplet loss, data augmentation, product recognition

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Authors: Tomokazu Nagata, Jawid Ahmad Baktash

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The goal of this paper is to explore the use of formal methods for Electronic Identity Card System. Nowadays, one of the core research directions in a constantly growing distributed environment is the improvement of the communication process. The responsibility for proper verification becomes crucial. Formal methods can play an essential role in the development and testing of systems. The thesis presents two different methodologies for assessing correctness. Our first approach employs abstract interpretation techniques for creating a trace based model for Electronic Identity Card System. The model was used for building a semi decidable procedure for verifying the system model. We also developed the code for the eID System and can cover three parts login to system sending of Acknowledgment from user side, receiving of all information from server side and log out from system. The new concepts of impasse and spawned sessions that we introduced led our research to original statements about the intruder’s knowledge and eID system coding with respect to secrecy. Furthermore, we demonstrated that there is a bound on the number of sessions needed for the analysis of System.Electronic identity (eID) cards promise to supply a universal, nation-wide mechanism for user authentication. Most European countries have started to deploy eID for government and private sector applications. Are government-issued electronic ID cards the proper way to authenticate users of online services? We use the eID project as a showcase to discuss eID from an application perspective. The new eID card has interesting design features, it is contact-less, it aims to protect people’s privacy to the extent possible, and it supports cryptographically strong mutual authentication between users and services. Privacy features include support for pseudonymous authentication and per service controlled access to individual data items. The article discusses key concepts, the eID infrastructure, observed and expected problems, and open questions. The core technology seems ready for prime time and government projects deploy it to the masses. But application issues may hamper eID adoption for online applications.

Keywords: eID, event-B, Pro-B, formal method, message passing

Procedia PDF Downloads 224

Authors: Nasir Khalid, S. Thirumalaichelvam

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In most buildings, according to US Department of Energy Data Book, the electrical consumption attributable to centralized heating and ventilation of air- condition (HVAC) component can be as high as 40-60% of the total electricity consumption for an entire building. To provide efficient energy management for the market today, researchers are finding new ways to develop a system that can save electrical consumption of buildings even more. In this concept paper, a system known as Intelligent Chiller Energy Efficiency (iCEE) System is being developed that is capable of saving up to 25% from the chiller’s existing electrical energy consumption. In variable frequency drives (VFDs), research has found significant savings up to 30% of electrical energy consumption. Together with the VFDs at specific Air Handling Unit (AHU) of HVAC component, this system will save even more electrical energy consumption. The iCEE System is compatible with any make, model or age of centrifugal, rotary or reciprocating chiller air-conditioning systems which are electrically driven. The iCEE system uses engineering principles of efficiency analysis, enthalpy analysis, heat transfer, mathematical prediction, modified genetic algorithm, psychometrics analysis, and optimization formulation to achieve true and tangible energy savings for consumers.

Keywords: variable frequency drives, adjustable speed drives, ac drives, chiller energy system

Procedia PDF Downloads 552

Authors: Wei Zheng, Mao Ji, Zhe Hou, Meng Huang, Bo Qi

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The transformer is the key equipment of the power system. Winding deformation is one of the main transformer defects, and timely and effective detection of the transformer winding deformation can ensure the safe and stable operation of the transformer to the maximum extent. When winding deformation occurs, the size, shape and spatial position of the winding will change, which directly leads to the change of magnetic flux leakage distribution. Therefore, it is promising to study the online detection method of the transformer winding deformation based on magnetic flux leakage characteristics, in which the key step is to study the optimal placement method of magnetic flux leakage sensors inside the transformer. In this paper, a simulation model of the transformer winding deformation is established to obtain the internal magnetic flux leakage distribution of the transformer under normal operation and different winding deformation conditions, and the law of change of magnetic flux leakage distribution due to winding deformation is analyzed. The results show that different winding deformation leads to different characteristics of the magnetic flux leakage distribution. On this basis, an optimized placement of magnetic flux leakage sensors inside the transformer is proposed to provide a basis for the online detection method of transformer winding deformation based on the magnetic flux leakage characteristics.

Keywords: magnetic flux leakage, sensor placement method, transformer, winding deformation

Procedia PDF Downloads 183

Authors: Denys Osipenko, Jonathan Crook

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Because of the variety of the card holders’ behaviour types and income sources each consumer account can be transferred to a variety of states. Each consumer account can be inactive, transactor, revolver, delinquent, defaulted and requires an individual model for the income prediction. The estimation of transition probabilities between statuses at the account level helps to avoid the memorylessness of the Markov Chains approach. This paper investigates the transition probabilities estimation approaches to credit cards income prediction at the account level. The key question of empirical research is which approach gives more accurate results: multinomial logistic regression or multistage conditional logistic regression with binary target. Both models have shown moderate predictive power. Prediction accuracy for conditional logistic regression depends on the order of stages for the conditional binary logistic regression. On the other hand, multinomial logistic regression is easier for usage and gives integrate estimations for all states without priorities. Thus further investigations can be concentrated on alternative modeling approaches such as discrete choice models.

Keywords: multinomial regression, conditional logistic regression, credit account state, transition probability

Procedia PDF Downloads 477

Authors: Emad A. Mohammed

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Utilizing the capabilities of Data Mining and Artificial Intelligence in the prediction of the minimum miscibility pressure (MMP) required for multi-contact miscible (MCM) displacement of reservoir petroleum by hydrocarbon gas flooding using Fuzzy Logic models and Artificial Neural Network models will help a lot in giving accurate results. The factors affecting the (MMP) as it is proved from the literature and from the dataset are as follows: XC2-6: Intermediate composition in the oil-containing C2-6, CO2 and H2S, in mole %, XC1: Amount of methane in the oil (%),T: Temperature (°C), MwC7+: Molecular weight of C7+ (g/mol), YC2+: Mole percent of C2+ composition in injected gas (%), MwC2+: Molecular weight of C2+ in injected gas. Fuzzy Logic and Neural Networks have been used widely in prediction and classification, with relatively high accuracy, in different fields of study. It is well known that the Fuzzy Inference system can handle uncertainty within the inputs such as in our case. The results of this work showed that our proposed models perform better with higher performance indices than other emprical correlations.

Keywords: MMP, gas flooding, artificial intelligence, correlation

Procedia PDF Downloads 135

Authors: Marike Venter de Villiers, Alicia Kruger

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The rapid development of the Internet has facilitated the proliferation of online stores. It has, therefore, become a pertinent issue for online retailers to provide the ultimate experience to customers in an attempt to maintain market share in this competitive landscape. Experiential marketing refers to the sensory dimensions that consumers experience when being faced with a purchase decision, such as getting them to sense, feel, think, act, and relate. The goal of experiential marketing is to provide a holistic experience for customers that allow them to engage in an activity where they may be motivated to purchase the concept behind the product. Creating a unique online experience holds several benefits to brands such as increased customer satisfaction, increased revisit intention, and higher levels of customer loyalty. Although several studies have explored the topic of experiential marketing in an online context, a lack of research exists on South African consumers, an emerging economy that is often overlooked globally. More specifically, the present study focused on professional females and their perceptions of experiential marketing when shopping for fashion products online. The main purpose of this study was to investigate the experiential factors that influence the online purchase intention of fashion products among female professionals. Furthermore, this study aimed to achieve the following objectives: firstly, to gain insight into key website characteristics that consumers value when shopping online for fashion products; secondly, to apply Pine and Gilmore’s (1989) Four Realms of an Experience (entertainment, education, esthetics, and escapism) to ground the study; and thirdly, to gain in-depth insight into the importance of these dimensions and identifying sub-categories that fashion marketers can use to enhance consumers’ online experience. By means of a qualitative study, a focus group was conducted comprising six professional females by using semi-structured questions. Respondents were selected using convenience sampling, and the results were analyzed using thematic analysis. The present research suggests that three of the four realms of experience influence purchase intention of fashion products online, namely, escapism, esthetics, and education. The fourth dimension, pleasure, was present but to a lesser degree. In other words, ‘escapism’ provides online shoppers with a sense of emotional and intellectual pleasure, while ‘esthetics’ refers to the website design, functionality, and product range, and ‘education’ comprises the product information such as the quality, fabric, price and available sizes. The findings of this study provide fashion marketers with insight into how they can maximize on experiential marketing when selling fashion products online. It further provides strategies and techniques for creating an enhanced online experience that ultimately may lead to increased purchase intention.

Keywords: experiential marketing, fashion, online, retail

Procedia PDF Downloads 127