Search results for: incidental information processing

Authors: Umme Habiba Jasmine, Mzikazi Nduna

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Due to the dearth of exploratory research in Bangladesh on parenting practices and transmission thereof, there is a lack of information on culture-sensitive methodology in studying this topic. This paper aims to share some methodological reflections from the research field, which will address this knowledge gap. Eleven dyads of biological mothers and maternal grandmothers of school-going children constituted the sample, and a female fieldworker conducted one-to-one, semi-structured, in-depth interviews with them. The participants were recruited through purposive sampling through a representative of a cooperative society in Mirpur area in Bangladesh. Four dyads of the sample outside that eleven dyads were discarded because of the unavailability of the other participant of the dyads or unsuitability for an in-depth interview. The sample recruitment strategy of approaching mothers without their known reference body had to be discarded because of existing social insecurity in Dhaka city. To meet the cultural demand of the research field the researcher had to change in the research plan and comply with the cultural tradition of mutual entertainment with food while conducting interviews which helped in engaging in positive interaction. Also, the researcher had to compromise the strict confidentiality to a collectivistic sense of confidentiality of the in-depth interview sessions. This study suggests future researchers to investigate Bangladeshi traditional practices and accommodate the applicable ones in their research plan for qualitative studies, especially the Bengali tradition of hospitality and shared confidentiality for building rapport and for proper access to the targeted information and research participants. Sample recruitment should always accompany a well-accepted reference person in the targeted research field.

Keywords: confidentiality, culture-sensitive, ethics, parenting practices, sampling

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Authors: Omolola A. Tajelawi, Hari L. Garbharran

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Revenue leakages are one of the major challenges manufacturers face in production processes, as most of the input materials that should emanate as products from the lines are lost as waste. Rather than generating income from material input which is meant to end-up as products, losses are further incurred as costs in order to manage waste generated. In addition, due to the lack of a clear view of the flow of resources on the lines from input to output stage, acquiring information on the true cost of waste generated have become a challenge. This has therefore given birth to the conceptualization and implementation of waste minimization strategies by several manufacturing industries. This paper reviews the principles and applications of three environmental management accounting tools namely Activity-based Costing (ABC), Life-Cycle Assessment (LCA) and Material Flow Cost Accounting (MFCA) in the manufacturing industry and their effectiveness in curbing revenue leakages. The paper unveils the strengths and limitations of each of the tools; beaming a searchlight on the tool that could allow for optimal resource utilization, transparency in production process as well as improved cost efficiency. Findings from this review reveal that MFCA may offer superior advantages with regards to the provision of more detailed information (both in physical and monetary terms) on the flow of material inputs throughout the production process compared to the other environmental accounting tools. This paper therefore makes a case for the adoption of MFCA as a viable technique for the identification and reduction of waste in production processes, and also for effective decision making by production managers, financial advisors and other relevant stakeholders.

Keywords: MFCA, environmental management accounting, resource efficiency, waste reduction, revenue losses

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Authors: Zoe Wong

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The purpose of this paper is to develop a framework for internet education. This framework uses the personalized learning approach for everyone who can freely develop their qualifications & careers. The key components of the framework includes students, teachers, assessments and infrastructure. It allows remove the challenges and limitations of the current educational system and allows learners' to cope with progressing learning materials.

Keywords: internet education, personalized approach, information technology, framework

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Authors: J. K. Visser, H. T. Malan

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A need exists to identify the sources of risks associated with the process automation systems within petrochemical companies or similar energy related industries. These companies use many different process automation technologies in its value chain. A crucial part of the process automation system is the information technology component featuring in the supervisory control layer. The ever-changing technology within the process automation layers and the rate at which it advances pose a risk to safe and predictable automation system performance. The age of the automation equipment also provides challenges to the operations and maintenance managers of the plant due to obsolescence and unavailability of spare parts. The main objective of this research was to determine the risk sources associated with the equipment that is part of the process automation systems. A secondary objective was to establish whether technology managers and technicians were aware of the risks and share the same viewpoint on the importance of the risks associated with automation systems. A conceptual model for risk sources of automation systems was formulated from models and frameworks in literature. This model comprised six categories of risk which forms the basis for identifying specific risks. This model was used to develop a questionnaire that was sent to 172 instrument technicians and technology managers in the company to obtain primary data. 75 completed and useful responses were received. These responses were analyzed statistically to determine the highest risk sources and to determine whether there was difference in opinion between technology managers and technicians. The most important risks that were revealed in this study are: 1) the lack of skilled technicians, 2) integration capability of third-party system software, 3) reliability of the process automation hardware, 4) excessive costs pertaining to performing maintenance and migrations on process automation systems, and 5) requirements of having third-party communication interfacing compatibility as well as real-time communication networks.

Keywords: distributed control system, identification of risks, information technology, process automation system

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Authors: Mengxin Feng, Feng Xu, Zhiyong Lai

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As a typical representative of the countryside, traditional Chinese villages are rich in cultural landscape resources and historical information, but they are still in continuous decline. The problems of people's weak protection awareness and low cultural recognition are still serious, and the protection of cultural heritage is imminent. At the same time, with the rapid development of rural tourism, its cultural value has been explored and paid attention to again. From the perspective of tourists, this study aimed to explore people's perception and identity of cultural landscape resources under the current cultural tourism development background. We selected eleven typical landscape elements of Lingshui Village, a traditional village in Beijing, as research objects and conducted a questionnaire survey with two scales of perception and identity to explore the characteristics of people's perception and identification of landscape elements. We found that there was a strong positive correlation between the perception and identity of each element and that geographical location influenced visitors' overall perception. The perception dimensions scored the highest in location, and the lowest in history and culture, and the identity dimensions scored the highest in meaning and lowest in emotion. We analyzed the impact of visitors' backgrounds on people's perception and identity characteristics and found that age and education were two important factors. The elderly had a higher degree of perceived identity, as the familiarity effect increased their attention. Highly educated tourists had more stringent criteria for perception and identification. The above findings suggest strategies for conserving and optimizing landscape elements in the traditional village to improve the acceptance and recognition of cultural information in traditional villages, which will inject new vitality into the development of traditional villages.

Keywords: traditional village, tourist perception, landscape elements, perception and identity

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Authors: Muhammad Mohsin, Fawad Ahmad, Fatima Batool, Muhammad Kaab Zarrar

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The integration of the Internet of Things (IoT) and edge computing devices offers a transformative approach to electronic waste management, particularly in the dismantling of printed circuit boards (PCBs). This paper explores how these technologies optimize operational efficiency and improve environmental sustainability by addressing challenges such as data security, interoperability, scalability, and real-time data processing. Proposed solutions include advanced machine learning algorithms for predictive maintenance, robust encryption protocols, and scalable architectures that incorporate edge computing. Case studies from leading e-waste management facilities illustrate benefits such as improved material recovery efficiency, reduced environmental impact, improved worker safety, and optimized resource utilization. The findings highlight the potential of IoT and edge computing to revolutionize e-waste dismantling and make the case for a collaborative approach between policymakers, waste management professionals, and technology developers. This research provides important insights into the use of IoT and edge computing to make significant progress in the sustainable management of electronic waste

Keywords: internet of Things, edge computing, waste PCB disassembly, electronic waste management, data security, interoperability, machine learning, predictive maintenance, sustainable development

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Authors: Olaniyan Rotimi Francis

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Agbabu Water, Oluwa River is used for artisanal fishing, ferrying and domestic activities in Odigbo Local Government Area (OLGA), Ondo State. The river receives bitumen spills and domestic and agricultural wastes, which could adversely impact on the water quality and resident biota. In spite of anthropogenic activities, there is a dearth of information on the limnology and biota of the river. Extensive bitumen spills, as well as uncontrolled discharge of domestic wastes have pollution implications as they alter prevailing conditions and destroy the habitats of aquatic organisms. The aim of this study was to investigate the physic-chemical parameters of Agbabu Water in order to provide baseline information for effective management. Monthly water samples were collected on the surface of Agbabu water, Oluwa River, for a period of 6 months (June,2024 to November,2024). All physic-chemicals were collected and analyzed according to APHA (2005) standard methods. Results showed that temperature ranged between 26.0-32.0oC, transparency (1.0-8.0 m), alkalinity (14.0-25.0 mg/l), electrical conductivity (18-105 µS/cm), dissolved oxygen (1.2-3.8 mg/l), sulphate (0.0 -4.0mg/l) and total dissolved solids (18-36). The parameters at the downstream (station A) accounted for the bulk of the highest values; there were, however, no significant differences between the stations at P<0.05. The results obtained from the physic-chemical parameters agree with the limits set by both national and international bodies for drinking and fish growth. It was recommended that urgent checks and monitoring by relevant agencies, government representatives, public health practitioners, and community leaders are required.

Keywords: physico-chemical, water, Agbabu, River

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Authors: Aneeqa Suhail, Shabana Naveed

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The public sector (in both developed and developing countries) has gone through various waves of radical reforms in recent decades. In Pakistan, under the influence of New Public Management(NPM) Reforms; best practices of private sector are introduced in the public sector to modernize public organizations. Human Resource Information System (HRIS) has been popular in the private sector and proven to be a successful system, therefore it is being adopted in the public sector too. However, implementation of private business practices in public organizations us very challenging due to differences in context. This implementation gets further critical in Pakistan due to a centralizing tendency and lack of autonomy in public organizations. Adoption of HRIS by public organizations in Pakistan raises several questions: What challenges are faced by public organizations in implementation of HRIS? Are benefits of HRIS such as efficiency, process integration and cost reduction achieved? How is the previous system improved with this change and what are the impacts? Yet, it is an under-researched topic, especially in public enterprises. This study contributes to the existing body of knowledge by empirically exploring benefits and challenges of implementation of HRIS in public organizations. The research adopts a case study approach and uses qualitative data based on in-depth interviews conducted at various levels in the hierarchy including top management, departmental heads and employees. The unit of analysis is LESCO, the Lahore Electric Supply Company, a state-owned entity that generates, transmits and distributes electricity to 4 big cities in Punjab, Pakistan. The findings of the study show that LESCO has not achieved the benefits of HRIS as established in literature. The implementation process remained quite slow and costly. Various functions of HR are still in isolation and integration is a big challenge for the organization. Although the data is automated, the previous system of manually record maintenance and paperwork is still in work, resulting in the presence of parallel practices. The findings also identified resistance to change from top management and labor workforce, lack of commitment and technical knowledge, and costly vendors as major barriers that affect the effective implementation of HRIS. The paper suggests some potential actions to overcome these barriers and to enhance effective implementation of HR-technology. The findings are explained in light of an institutional logics perspective. HRIS’ new logic of automated and integrated HR system is in sharp contrast with the prevailing logic of process-oriented manual data maintenance, leading to resistance to change and deadlock.

Keywords: human resource information system, technological changes, state-owned enterprise, implementation challenges

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Authors: Ahmed Negm, George Aggidis, Xiandong Ma

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With the diverse nature of urban cities, customer demand patterns, landscape topologies or even seasonal weather trends; managing our water distribution networks (WDNs) has proved a complex task. These unpredictable circumstances manifest as pipe failures, intermittent supply and burst events thus adding to water loss, energy waste and increased carbon emissions. Whilst these events are unavoidable, advanced pressure management has proved an effective tool to control and mitigate them. Henceforth, water utilities have struggled with developing a real-time control method that is resilient when confronting the challenges of water distribution. In this paper we use deep reinforcement learning (DRL) algorithms as a novel pressure control strategy to minimise pressure violations and leakage under both burst and background leakage conditions. Agents based on asynchronous actor critic (A2C) and recurrent proximal policy optimisation (Recurrent PPO) were trained and compared to benchmarked optimisation algorithms (differential evolution, particle swarm optimisation. A2C manages to minimise leakage by 32.48% under burst conditions and 67.17% under background conditions which was the highest performance in the DRL algorithms. A2C and Recurrent PPO performed well in comparison to the benchmarks with higher processing speed and lower computational effort.

Keywords: deep reinforcement learning, pressure management, water distribution networks, leakage management

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Authors: Ming-Yang Guo, Cheng-Xian Wu, Wei-Xiang Chen, Chun-Yuan Lin, Yen-Jen Lin, Ann-Shyn Chiang

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With more and more Drosophila Driver and Neuron images, it is an important work to find the similarity relationships among them as the functional inference. There is a general problem that how to find a Drosophila Driver image, which can cover a set of Drosophila Driver/Neuron images. In order to solve this problem, the intersection/union region for a set of images should be computed at first, then a comparison work is used to calculate the similarities between the region and other images. In this paper, three encoding schemes, namely Integer, Boolean, Decimal, are proposed to encode each image as a one-dimensional structure. Then, the intersection/union region from these images can be computed by using the compare operations, Boolean operators and lookup table method. Finally, the comparison work is done as the union region computation, and the similarity score can be calculated by the definition of Tanimoto coefficient. The above methods for the region computation are also implemented in the multi-core CPUs environment with the OpenMP. From the experimental results, in the encoding phase, the performance by the Boolean scheme is the best than that by others; in the region computation phase, the performance by Decimal is the best when the number of images is large. The speedup ratio can achieve 12 based on 16 CPUs. This work was supported by the Ministry of Science and Technology under the grant MOST 106-2221-E-182-070.

Keywords: Drosophila driver image, Drosophila neuron images, intersection/union computation, parallel processing, OpenMP

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Authors: Xiaoqing Peng, Aijing Luo, Yang Chen

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Background: Cyberchondria, as an "emerging risk" accompanied by the information era, is a new abnormal pattern characterized by excessive or repeated online searches for health-related information and escalating health anxiety, which endangers people's physical and mental health and poses a huge threat to public health. Objective: To explore and discuss the research status, hotspots and trends of Cyberchondria. Methods: Based on a total of 77 articles regarding "Cyberchondria" extracted from Web of Science from the beginning till October 2019, the literature trends, countries, institutions, hotspots are analyzed by bibliometric analysis, the concept definition of Cyberchondria, instruments, relevant factors, treatment and intervention are discussed as well. Results: Since "Cyberchondria" was put forward for the first time in 2001, the last two decades witnessed a noticeable increase in the amount of literature, especially during 2014-2019, it quadrupled dramatically at 62 compared with that before 2014 only at 15, which shows that Cyberchondria has become a new theme and hot topic in recent years. The United States was the most active contributor with the largest publication (23), followed by England (11) and Australia (11), while the leading institutions were Baylor University(7) and University of Sydney(7), followed by Florida State University(4) and University of Manchester(4). The WoS categories "Psychiatry/Psychology " and "Computer/ Information Science "were the areas of greatest influence. The concept definition of Cyberchondria is not completely unified in the world, but it is generally considered as an abnormal behavioral pattern and emotional state and has been invoked to refer to the anxiety-amplifying effects of online health-related searches. The first and the most frequently cited scale for measuring the severity of Cyberchondria called “The Cyberchondria Severity Scale (CSS) ”was developed in 2014, which conceptualized Cyberchondria as a multidimensional construct consisting of compulsion, distress, excessiveness, reassurance, and mistrust of medical professionals which was proved to be not necessary for this construct later. Since then, the Brazilian, German, Turkish, Polish and Chinese versions were subsequently developed, improved and culturally adjusted, while CSS was optimized to a simplified version (CSS-12) in 2019, all of which should be worthy of further verification. The hotspots of Cyberchondria mainly focuses on relevant factors as follows: intolerance of uncertainty, anxiety sensitivity, obsessive-compulsive disorder, internet addition, abnormal illness behavior, Whiteley index, problematic internet use, trying to make clear the role played by “associated factors” and “anxiety-amplifying factors” in the development of Cyberchondria, to better understand the aetiological links and pathways in the relationships between hypochondriasis, health anxiety and online health-related searches. Although the treatment and intervention of Cyberchondria are still in the initial stage of exploration, there are kinds of meaningful attempts to seek effective strategies from different aspects such as online psychological treatment, network technology management, health information literacy improvement and public health service. Conclusion: Research on Cyberchondria is in its infancy but should be deserved more attention. A conceptual consensus on Cyberchondria, a refined assessment tool, prospective studies conducted in various populations, targeted treatments for it would be the main research direction in the near future.

Keywords: cyberchondria, hypochondriasis, health anxiety, online health-related searches

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Authors: C. Busuioc, S. I. Jinga, E. Pavel

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The continuous need of more non-volatile memories with a higher storage capacity, smaller dimensions and weight, as well as lower costs, has led to the exploration of optical lithography on active media, as well as patterned magnetic composites. In this context, optical lithography is a technique that can provide a significant decrease of the information bit size to the nanometric scale. However, there are some restrictions that arise from the need of breaking the optical diffraction limit. Major achievements have been obtained by employing a vitoceramic material as active medium and a laser beam operated at low power for the direct writing procedure. Thus, optical discs with ultra-high density were fabricated by a conventional melt-quenching method starting from analytical purity reagents. They were subsequently used for 3D recording based on their photosensitive features. Naturally, the next step consists in the elucidation of the composition and structure of the active centers, in correlation with the use of silver and rare-earth compounds for the synthesis of the optical supports. This has been accomplished by modern characterization methods, namely transmission electron microscopy coupled with selected area electron diffraction, scanning transmission electron microscopy and electron energy loss spectroscopy. The influence of laser diode parameters, silver concentration and fluorescent compounds formation on the writing process and final material properties was investigated. The results indicate performances in terms of capacity with two order of magnitude higher than other reported information storage systems. Moreover, the fluorescent photosensitive vitroceramics may be integrated in other applications which appeal to nanofabrication as the driving force in electronics and photonics fields.

Keywords: data storage, fluorescent compounds, laser writing, vitroceramics

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Authors: Priyadharshini Ahrumugam

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Cooperative groups through much research have been recognized to churn remarkable achievements instead of solitary or individualistic efforts. Based on Johnson and Johnson’s model of cooperative learning, the five key components of cooperation are positive interdependence, face-to-face promotive interaction, individual accountability, social skills and group processing. In 2011, the Malaysian Ministry of Higher Education (MOHE) introduced the Holistic Student Development policy with the aim to develop morally sound individuals equipped with lifelong learning skills. The Community Service project was included in the improvement initiative. The purpose of this study is to assess the relationship of team-based learning in facilitating particularly students’ positive interdependence and face-to-face promotive interaction. The research methods involve in-depth interviews with the team leaders and selected team members, and a content analysis of the undergraduate students’ reflective journals. A significant positive relationship was found between students’ progressive outlook towards teamwork and the highlighted two components. The key findings show that students have gained in their individual learning and work results through teamwork and interaction with other students. The inclusion of Community Service as a MOHE subject resonates with cooperative learning methods that enhances supportive relationships and develops students’ social skills together with their professional skills.

Keywords: community service, cooperative learning, positive interdependence, teamwork

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Authors: Geumchan Hwang

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Professional sport leagues in Europe and North America are shut down due to novel coronavirus disease (COVID-19) outbreak. Football leagues in Europe (e.g., La Liga, English Premier League, Bundesliga, Serie A, and Ligue 1) and big four professional sport leagues in North America (e.g., National Football League, Major League Baseball, National Basketball Association, and National Hockey League) are indefinitely suspended or delayed. COVID-19 outbreak has a growing negative impact on economics of sport leagues. For example, loss of revenue in Europe’s top five leagues due to the COVID-19 pandemic was estimated at € 4 billion and loss of revenue in the NBA was estimated at $650 million as of March 2020. In the unprecedented difficult situation, sport teams and leagues try to communicate with sport fans through diverse media platforms. In sport, however, very few studies have been done regarding how sport organizations effectively communicate with sport fans during pandemics, such as COVID-19 outbreak. Understanding sport organizations’ crisis communication is important to develop effective crisis management strategies for sport organizations. Therefore, the purpose of the study is to examine how sport organizations communicate with sport fans via online platforms in COVID-19 outbreak and how sport fans evaluate their communication strategies. 9 official sport league sites (i.e., five major football leagues in Europe and four major sport leagues in North America) and COVID-19 news articles published between January and June in 2020 will be analyzed in terms of coronavirus information, teams and players’ live update, fan interaction, fan support, and community engagement. In addition, comments posted on social media sites (i.e., Facebook and Twitter) of major sport leagues will be also analyzed to examine how sport fans perceive online messages provided by sport leagues as an effective communication strategy. To measure the effectiveness of crisis communication performance, five components (i.e., prompt, compassionate, honest, informative, and interactive) of crisis communication will be collected from leagues’ official websites information and social media posts. Upon completing data collection, content analysis method will be used to evaluate effectiveness of crisis communication among 9 professional sport leagues. The results of the study will provide athletic directors, administrators, and public relations managers in sport organizations with practical information regarding how athlete celebrities and sport organizations should interact with their fans in pandemic situations. In particular, this study will contribute to developing specific crisis management plan for sport organizations. For instance, football teams and leagues in Europe will be able to create standard manuals to minimize damages caused by disease outbreak, such as COVID-19 outbreak.

Keywords: COVID-19, communication, sport leagues, fans

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Authors: Ho Yeon Park, Kyoung-Jae Kim

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Recently, user’s interests for location-based social network service increases according to the advances of social web and location-based technologies. It may be easy to recommend preferred items if we can use user’s preference, context and social network information simultaneously. In this study, we propose context-aware POI (point-of-interests) recommender systems using location-based network analysis and sentiment analysis which consider context, social network information and implicit user’s preference score. We propose a context-aware POI recommendation system consisting of three sub-modules and an integrated recommendation system of them. First, we will develop a recommendation module based on network analysis. This module combines social network analysis and cluster-indexing collaboration filtering. Next, this study develops a recommendation module using social singular value decomposition (SVD) and implicit SVD. In this research, we will develop a recommendation module that can recommend preference scores based on the frequency of POI visits of user in POI recommendation process by using social and implicit SVD which can reflect implicit feedback in collaborative filtering. We also develop a recommendation module using them that can estimate preference scores based on the recommendation. Finally, this study will propose a recommendation module using opinion mining and emotional analysis using data such as reviews of POIs extracted from location-based social networks. Finally, we will develop an integration algorithm that combines the results of the three recommendation modules proposed in this research. Experimental results show the usefulness of the proposed model in relation to the recommended performance.

Keywords: sentiment analysis, network analysis, recommender systems, point-of-interests, business analytics

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Authors: Alex Gonzalez Caceres, Jan Karlshøj, Tor Arvid Vik

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Life cycle of residential buildings are expected to be several decades, 40% of European residential buildings have inefficient energy conservation measure. The existing building represents 20-40% of the energy use and the CO₂ emission. Since net zero energy buildings are a short-term goal, (should be achieved by EU countries after 2020), is necessary to plan the next logical step, which is to prepare the existing outdated stack of building to retrofit them into an energy efficiency buildings. In order to accomplish this, two specialize and widespread tool can be used Building Information Modelling (BIM) and life-cycle assessment (LCA). BIM and LCA are tools used by a variety of disciplines; both are able to represent and analyze the constructions in different stages. The combination of these technologies could improve greatly the retrofitting techniques. The incorporation of the carbon footprint, introducing a single database source for different material analysis. To this is added the possibility of considering different analysis approaches such as costs and energy saving. Is expected with these measures, enrich the decision-making. The methodology is based on two main activities; the first task involved the collection of data this is accomplished by literature review and interview with experts in the retrofitting field and BIM technologies. The results of this task are presented as an evaluation checklist of BIM ability to manage data and improve decision-making in retrofitting projects. The last activity involves an evaluation using the results of the previous tasks, to check how far the IFC format can support the requirements by each specialist, and its uses by third party software. The result indicates that BIM/LCA have a great potential to improve the retrofitting process in existing buildings, but some modification must be done in order to meet the requirements of the specialists for both, retrofitting and LCA evaluators.

Keywords: retrofitting, BIM, LCA, energy efficiency

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Authors: Bahareh Golchin, Nooshin Riahi

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One of the most significant issues as attended a lot in recent years is that of recognizing the sentiments and emotions in social media texts. The analysis of sentiments and emotions is intended to recognize the conceptual information such as the opinions, feelings, attitudes and emotions of people towards the products, services, organizations, people, topics, events and features in the written text. These indicate the greatness of the problem space. In the real world, businesses and organizations are always looking for tools to gather ideas, emotions, and directions of people about their products, services, or events related to their own. This article uses the Twitter social network, one of the most popular social networks with about 420 million active users, to extract data. Using this social network, users can share their information and opinions about personal issues, policies, products, events, etc. It can be used with appropriate classification of emotional states due to the availability of its data. In this study, supervised learning and deep neural network algorithms are used to classify the emotional states of Twitter users. The use of deep learning methods to increase the learning capacity of the model is an advantage due to the large amount of available data. Tweets collected on various topics are classified into four classes using a combination of two Bidirectional Long Short Term Memory network and a Convolutional network. The results obtained from this study with an average accuracy of 93%, show good results extracted from the proposed framework and improved accuracy compared to previous work.

Keywords: emotion classification, sentiment analysis, social networks, deep neural networks

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Authors: E. E. S. Uy, T. Noda, K. Nakai, J. R. Dungca

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Cyclic threshold shear strain is the cyclic shear strain amplitude that serves as the indicator of the development of pore water pressure. The parameter can be obtained by performing either cyclic triaxial test, shaking table test, cyclic simple shear or resonant column. In a cyclic triaxial test, other researchers install measuring devices in close proximity of the soil to measure the parameter. In this study, an attempt was made to estimate the cyclic threshold shear strain parameter using full-field measurement technique. The technique uses a camera to monitor and measure the movement of the soil. For this study, the technique was incorporated in a strain-controlled consolidated undrained cyclic triaxial test. Calibration of the camera was first performed to ensure that the camera can properly measure the deformation under cyclic loading. Its capacity to measure deformation was also investigated using a cylindrical rubber dummy. Two-dimensional image processing was implemented. Lucas and Kanade optical flow algorithm was applied to track the movement of the soil particles. Results from the full-field measurement technique were compared with the results from the linear variable displacement transducer. A range of values was determined from the estimation. This was due to the nonhomogeneous deformation of the soil observed during the cyclic loading. The minimum values were in the order of 10-2% in some areas of the specimen.

Keywords: cyclic loading, cyclic threshold shear strain, full-field measurement, optical flow

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Authors: Neha Sharma, Kanthi K. Kondepudi, Naveen Gupta

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Phytases are phytate specific phosphatases catalyzing the step-wise dephosphorylation of phytate, which acts as an anti-nutritional factor in food due to its strong binding capacity to minerals. In recent years microbial phytases have been explored for improving nutritional quality of food. But the major limitation is acceptability of phytases from these microorganisms. Therefore, efforts are being made to isolate organisms which are generally regarded as safe for human consumption such as Lactic Acid Bacteria (LAB). Phytases from these organisms will have an edge over other phytase sources due to its probiotic attributes. Only few LAB have been reported to give phytase activity that too is generally seen as intracellular. LAB producing extracellular phytase will be more useful as it can degrade phytate more effectively. Moreover, enzyme from such isolate will have application in food processing also. Only few species of Lactobacillus producing extracellular phytase have been reported so far. This study reports the isolation of a probiotic strain of Lactobacillus fermentum spp KA1 which produces extracellular phytase. Conditions for the optimal production of phytase have been optimized and the enzyme production resulted in an approximately 13-fold increase in yield. The phytate degradation potential of extracellular phytase in rice bran has been explored and conditions for optimal degradation were optimized. Under optimal conditions, there was 43.26% release of inorganic phosphate and 6.45% decrease of phytate content.

Keywords: Lactobacillus, phytase, phytate reduction, rice bran

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Authors: Sara Gardideh, Mansoor Barati

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The mineral carbonation approach for reducing global warming has garnered interest on a worldwide scale. Due to the benefits of permanent storage and abundant mineral resources, mineral carbonation (MC) is one of the most effective strategies for sequestering CO₂. The combination of mineral processing for primary metal recovery and mineral carbonation for carbon sequestration is an emerging field of study with the potential to minimize capital costs. A detailed study of low-pressures–solid carbonation of ultramafic tailings in a dry environment has been accomplished. In order to track the changing structure of serpentine minerals and their reactivity as a function of temperature (300-900 ᵒC), CO₂ partial pressure (25-90 mol %), and thermal preconditioning, thermogravimetry has been utilized. The incongruent CO₂ van der Waals molecular diameters with the octahedral-tetrahedral lattice constants of serpentine were used to explain the mild carbonation reactivity. Serpentine requires additional thermal-treatment to remove hydroxyl groups, resulting in the chemical transformation to pseudo-forsterite, which is a mineral composed of isolated SiO₄ tetrahedra linked by octahedrally coordinated magnesium ions. The heating treatment above 850 ᵒC is adequate to remove chemically bound water from the lattice. Particles with a diameter < 34 (μm) are desirable, and thermally treated serpentine at 850 ᵒC for 2.30 hours reached 65% CO₂ storage capacity. The decrease in particle size, increase in temperature, and magnetic separation can dramatically enhance carbonation.

Keywords: particle size, thermogravimetry, thermal-treatment, serpentine

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Authors: Sushish Baral, Pratibha Joshi, Yaman Maharjan

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Glaucoma is a chronic eye condition that causes vision loss that is irreversible. Early detection and treatment are critical to prevent vision loss because it can be asymptomatic. For the identification of glaucoma, multiple deep learning algorithms are used. Transformer-based architectures, which use the self-attention mechanism to encode long-range dependencies and acquire extremely expressive representations, have recently become popular. Convolutional architectures, on the other hand, lack knowledge of long-range dependencies in the image due to their intrinsic inductive biases. The aforementioned statements inspire this thesis to look at transformer-based solutions and investigate the viability of adopting transformer-based network designs for glaucoma detection. Using retinal fundus images of the optic nerve head to develop a viable algorithm to assess the severity of glaucoma necessitates a large number of well-curated images. Initially, data is generated by augmenting ocular pictures. After that, the ocular images are pre-processed to make them ready for further processing. The system is trained using pre-processed images, and it classifies the input images as normal or glaucoma based on the features retrieved during training. The Vision Transformer (ViT) architecture is well suited to this situation, as it allows the self-attention mechanism to utilise structural modeling. Extensive experiments are run on the common dataset, and the results are thoroughly validated and visualized.

Keywords: glaucoma, vision transformer, convolutional architectures, retinal fundus images, self-attention, deep learning

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Authors: Ewenam Gbormittah

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Because of the effects of the pandemic, companies are focusing on the future of work arrangements for their employees. This includes adapting to a remote or hybrid working model. It is important that employers provide those working remotely or in a hybrid mode a rewarding onboarding experience and opportunities for interaction. Although, Information & Communication Technologies (ICT) have transformed the ways organisations manage employees over the years, there is still a need for a platform where organisations can adjust their onboarding to suit the social and interactive aspects of their employees, to facilitate successful integration. This study aimed to explore this matter by investigating whether Virtual Reality (VR) technology contributes to new employees integration into the organisation during their job-onboarding (JOB) process. The research questions are as follows: (1) To what extent does VR have an impact on employees successful integration into the organisation, and (2) How does VR help elements of new employees Psychological Contract (PC) during the course of interactions. An exploratory case study approach, which consisted of a semi-structured interview was conducted on 20 employees, split from two different case organisations. The results of the data were analysed according to each case, and then a cross-case comparison was provided. The results have generated 8 themes, presenting in excess of 7 sub-themes for CS1 and presented 7 themes, in excess of 7 sub-themes for CS2. The cross-case analysis has revealed that VR does have the potential to support employees integration into the organisation. However, the effects were shown to be stronger for employees in CS2, compared to employees in CS1. The results highlight practical implications for onboarding psychology and strategic talent solutions within recruitment. Such strategy this research particularly outlines, involves providing insights on how to manage the PC of employees from the recruitment stage to creating successful employment relationships.

Keywords: job-onboarding, psychological contract, virtual reality, case study one, case study two

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Authors: V. Ayishwarya Bharathi, S. M. Hasker, J. Indhu, M. Mohamed Azarudeen, G. Gowthami, R. Vinoth Rajan, N. Vijayarangan

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Identification of water quality conditions in a river system based on limited observations is an essential task for meeting the goals of environmental management. The traditional method of water quality testing is to collect samples manually and then send to laboratory for analysis. However, it has been unable to meet the demands of water quality monitoring today. So a set of automatic measurement and reporting system of water quality has been developed. In this project specifies Water quality parameters collected by multi-parameter water quality probe are transmitted to data processing and monitoring center through GPRS wireless communication network of mobile. The multi parameter sensor is directly placed above the water level. The monitoring center consists of GPRS and micro-controller which monitor the data. The collected data can be monitor at any instant of time. In the pollution control board they will monitor the water quality sensor data in computer using Visual Basic Software. The system collects, transmits and processes water quality parameters automatically, so production efficiency and economy benefit are improved greatly. GPRS technology can achieve well within the complex environment of poor water quality non-monitored, and more specifically applicable to the collection point, data transmission automatically generate the field of water analysis equipment data transmission and monitoring.

Keywords: multiparameter sensor, GPRS, visual basic software, RS232

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Authors: Eva Tolmeijer, Emmanuelle Peters, Veena Kumari, Liam Mason

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Cognitive behavioral therapy for psychosis (CBTp) is effective in many but not all patients, making it important to better understand the factors that determine treatment outcomes. To date, no studies have examined whether neuroimaging can make clinically useful predictions about who will respond to CBTp. To this end, we used machine learning methods that make predictions about symptom improvement at the individual patient level. Prior to receiving CBTp, 22 patients with a diagnosis of schizophrenia completed a social-affective processing task during functional MRI. Multivariate pattern analysis assessed whether treatment response could be predicted by brain activation responses to facial affect that was either socially threatening or prosocial. The resulting models did significantly predict symptom improvement, with distinct multivariate signatures predicting psychotic (r=0.54, p=0.01) and affective (r=0.32, p=0.05) symptoms. Psychotic symptom improvement was accurately predicted from relatively focal threat-related activation across hippocampal, occipital, and temporal regions; affective symptom improvement was predicted by a more dispersed profile of responses to prosocial affect. These findings enrich our understanding of the neurobiological underpinning of treatment response. This study provides a foundation that will hopefully lead to greater precision and tailoring of the interventions offered to patients.

Keywords: cognitive behavioral therapy, machine learning, psychosis, schizophrenia

Procedia PDF Downloads 274

Authors: M. Mulumpwa, W. W. L. Jere, M. Lazaro, A. H. N. Mtethiwa

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The study considered Seasonal Autoregressive Integrated Moving Average (SARIMA) processes to select an appropriate stochastic model to forecast the monthly data from the Lake Malawi water levels for the period 1986 through 2015. The appropriate model was chosen based on SARIMA (p, d, q) (P, D, Q)S. The Autocorrelation function (ACF), Partial autocorrelation (PACF), Akaike Information Criteria (AIC), Bayesian Information Criterion (BIC), Box–Ljung statistics, correlogram and distribution of residual errors were estimated. The SARIMA (1, 1, 0) (1, 1, 1)12 was selected to forecast the monthly data of the Lake Malawi water levels from August, 2015 to December, 2021. The plotted time series showed that the Lake Malawi water levels are decreasing since 2010 to date but not as much as was the case in 1995 through 1997. The future forecast of the Lake Malawi water levels until 2021 showed a mean of 474.47 m ranging from 473.93 to 475.02 meters with a confidence interval of 80% and 90% against registered mean of 473.398 m in 1997 and 475.475 m in 1989 which was the lowest and highest water levels in the lake respectively since 1986. The forecast also showed that the water levels of Lake Malawi will drop by 0.57 meters as compared to the mean water levels recorded in the previous years. These results suggest that the Lake Malawi water level may not likely go lower than that recorded in 1997. Therefore, utilisation and management of water-related activities and programs among others on the lake should provide room for such scenarios. The findings suggest a need to manage the Lake Malawi jointly and prudently with other stakeholders starting from the catchment area. This will reduce impacts of anthropogenic activities on the lake’s water quality, water level, aquatic and adjacent terrestrial ecosystems thereby ensuring its resilience to climate change impacts.

Keywords: forecasting, Lake Malawi, water levels, water level fluctuation, climate change, anthropogenic activities

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Authors: Aliyaa Zaidan, Rayan Bahabri

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The twenty-first century revealed an accelerating change and intensifying complexity of communication technology. Online social networking engines have gained astounding recognition worldwide. The influence of those social media platforms on dentistry and dental students is not well established. Therefore, this study aimed to evaluate the impact of using social media on professional and profile level among dental students in Saudi Arabia. A cross-sectional study developed via online questionnaire concerning on social media usage and its effect on professional and profile level of dental students and dental interns from several universities in Saudi Arabia. A total of 296 dental students and dental interns in Saudi Arabia responded to the questionnaire. Ninety-eight percent of the participants usually use the social media on a regular basis. Most social media sites used among the participants were Snapchat, Instagram, and YouTube by 85%, 81%, 77% respectively. Forty-one percent of the participants agreed that using social media in the dental field is a necessity nowadays. Thirty-eight percent of participants agreed that using social media is an easy way to gain a reliable knowledge, while 43% agreed that social media will improve the quality of healthcare. Furthermore, 65% of the students deemed using social media for academic purposes will improve their performance. Fifty-five percent of the respondents often use social media tools to obtain information about subject or procedures related to the dental field. Regarding profile reputation of dental students, 40% of the respondents agreed that their profile information published on social networking websites, could be used by others to judge their level of professionalism. Male and female dental students both agreed that their reputation would be adversely affected by 37%,63%, respectively, if their social networking activity were viewed by members of the public. The discrepancy among student levels reveals that social media profile positively influence the acceptance to postgraduate programs (P= 0.01).

Keywords: dental students, professional, reputation, social media

Procedia PDF Downloads 211

Authors: E. Y. Igde, S. Aydogan, F. E. Boran, D. Akay

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Patent data have an increasingly important role in economic growth, innovation, technical advantages and business strategies and even in countries competitions. Analyzing of patent data is crucial since patents cover large part of all technological information of the world. In this paper, we have used the linguistic summarization technique to prove the validity of the hypotheses related to patent data stated in the literature.

Keywords: data mining, fuzzy sets, linguistic summarization, patent data

Procedia PDF Downloads 272

Authors: Naouel Zoghlami

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Spoken-word recognition involves the simultaneous activation of potential word candidates which compete with each other for final correct recognition. In continuous speech, the activation-competition process gets more complicated due to speech reductions existing at word boundaries. Lexical processing is more difficult in L2 than in L1 because L2 listeners often lack phonetic, lexico-semantic, syntactic, and prosodic knowledge in the target language. In this study, we investigate the on-line lexical segmentation hypotheses that French listeners of L2 English form and then revise as subsequent perceptual evidence is revealed. Our purpose is to shed further light on the processes of L2 spoken-word recognition in context and better understand L2 listening difficulties through a comparison of skilled and unskilled reactions at the point where their working hypothesis is rejected. We use a variant of the gating experiment in which subjects transcribe an English sentence presented in increments of progressively greater duration. The spoken sentence was “And this amazing athlete has just broken another world record”, chosen mainly because it included common reductions and phonetic features in English, such as elision and assimilation. Our preliminary results show that there is an important difference in the manner in which proficient and less-proficient L2 listeners handle connected speech. Less-proficient listeners delay recognition of words as they wait for lexical and syntactic evidence to appear in the gates. Further statistical results are currently being undertaken.

Keywords: gating paradigm, spoken word recognition, online lexical segmentation, L2 listening

Procedia PDF Downloads 464

Authors: Ye Tian

Abstract:

Soft power has replaced hard power and become one of the most attractive ways nations pursue to expand their international influence. One of the ways to improve a nation’s soft power is to commercialise the country and brand or rebrand it to the international audience, and thus attract interests or foreign investments. In this process, translation has often been regarded as merely a tool, and researches in it are either in translating literature as culture export or in how (in)accuracy of translation influences the branding campaign. This paper proposes to analyse nation branding campaign with framing theory, and thus gives an entry for translation studies to come to a central stage in today’s soft power research. To frame information or elements of a text, an event, or, as in this paper, a nation is to put them in a mental structure. This structure can be built by outsiders or by those who create the text, the event, or by citizens of the nation. To frame information like this can be regarded as a process of translation, as what translation does in its traditional meaning of ‘translating a text’ is to put a framework on the text to, deliberately or not, highlight some of the elements while hiding the others. In the discourse of nations, then, people unavoidably simplify a national image and put the nation into their imaginary framework. In this way, problems like stereotype and prejudice come into being. Meanwhile, if nations seek ways to frame or reframe themselves, they make efforts to have in control what and who they are in the eyes of international audiences, and thus make profits, economically or politically, from it. The paper takes African nations, which are usually perceived as a whole, and the United Kingdom as examples to justify passive and active framing process, and assesses both positive and negative influence framing has on nations. In conclusion, translation as framing causes problems like prejudice, and the image of a nation is not always in the hands of nation branders, but reframing the nation in a positive way has the potential to turn the tide.

Keywords: framing, nation branding, stereotype, translation

Procedia PDF Downloads 155

Authors: Nazli Hardy

Abstract:

Multidisciplinary application of computer science, interactive database-driven web application, the Internet of Things (IoT) represents a digital ecosystem that has pervasive technological, social, and economic, impact on the human population. It is a long-term technology, and its development is built around the connection of everyday objects, to the Internet. It is estimated that by 2020, with billions of people connected to the Internet, the number of connected devices will exceed 50 billion, and thus IoT represents a paradigm shift in in our current interconnected ecosystem, a communication shift that will unavoidably affect people, businesses, consumers, clients, employees. By nature, in order to provide a cohesive and integrated service, connected devices need to collect, aggregate, store, mine, process personal and personalized data on individuals and corporations in a variety of contexts and environments. A significant factor in this paradigm shift is the necessity for secure and appropriate transmission, processing and storage of the data. Thus, while benefits of the applications appear to be boundless, these same opportunities are bounded by concerns such as trust, privacy, security, loss of control, and related issues. This poster and presentation look at a multi-factor authentication (MFA) mechanisms that need to change from the login-password tuple to an Identity and Access Management (IAM) model, to the more cohesive to Identity Relationship Management (IRM) standard. It also compares and contrasts messaging protocols that are appropriate for the IoT ecosystem.

Keywords: Internet of Things (IoT), authentication, protocols, survey

Procedia PDF Downloads 299