Search results for: geospatial technology competency model

Authors: Luojie Tang, Libin Ouyang, Yihang Gao

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The natural landscape and urban-rural structure, with their attractiveness in the Dali area around Erhai Lake, exhibit striking similarities with Howard's Garden City. With the emergence of the unique phenomenon of the first large-scale gathering of digital nomads in China in Dali, an analysis of Dali's natural, economic, and cultural representations and structures reveals that the Garden City model can no longer fully explain the current overall human living environment in Dali. By interpreting the bottom-up local construction process in Dali based on landscape identity, the transformation of production and lifestyle under new technologies such as ICT(Information and Communication Technology), and the values and lifestyle reshaping embodied in the "reverse urbanization" phenomenon of the middle class in Dali, it is believed that Dali has moved towards a "contemporary garden city influenced by new technology." The article summarizes the characteristics and connotations of this Garden City and provides corresponding strategies for its continued healthy development.

Keywords: dali, ICT, rural-urban relationship, garden city model

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Authors: Kevin F. Hsu, Alvin Chua, Sarah X. Lin

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As a multilingual society, Singaporean names for different parts of the city have changed over time. Residents included Indigenous Malays, dialect-speakers from China, European settler-colonists, and Tamil-speakers from South India. Each group would name locations in their own languages. Today, as ancestral tongues are increasingly supplanted by English, contemporary Singaporeans’ understanding of once-common place names is disappearing. After demolition or redevelopment, some urban places will only exist in archival records or in human memory. United Nations conferences on the standardization of geographic names have called attention to how place names relate to identity, well-being, and a sense of belonging. The Singapore Place-Naming Project responds to these imperatives by capturing past and present place names through digitizing historical maps, mining archival records, and applying selective crowd-sourcing to trace the evolution of place names throughout the city. The project ensures that both formal and vernacular geographical names remain accessible to historians, city planners, and the public. The project is compiling a gazetteer, a geospatial archive of placenames, with streets, buildings, landmarks, and other points of interest (POI) appearing in the historic maps and planning documents of Singapore, currently held by the National Archives of Singapore, the National Library Board, university departments, and the Urban Redevelopment Authority. To create a spatial layer of information, the project links each place name to either a geo-referenced point, line segment, or polygon, along with the original source material in which the name appears. This record is supplemented by crowd-sourced contributions from civil service officers and heritage specialists, drawing from their collective memory to (1) define geospatial boundaries of historic places that appear in past documents, but maybe unfamiliar to users today, and (2) identify and record vernacular place names not captured in formal planning documents. An intuitive interface allows participants to demarcate feature classes, vernacular phrasings, time periods, and other knowledge related to historical or forgotten spaces. Participants are stratified into age bands and ethnicity to improve representativeness. Future iterations could allow additional public contributions. Names reveal meanings that communities assign to each place. While existing historical maps of Singapore allow users to toggle between present-day and historical raster files, this project goes a step further by adding layers of social understanding and planning documents. Tracking place names illuminates linguistic, cultural, commercial, and demographic shifts in Singapore, in the context of transformations of the urban environment. The project also demonstrates how a moderated, selectively crowd-sourced effort can solicit useful geospatial data at scale, sourced from different generations, and at higher granularity than traditional surveys, while mitigating negative impacts of unmoderated crowd-sourcing. Stakeholder agencies believe the project will achieve several objectives, including Supporting heritage conservation and public education; Safeguarding intangible cultural heritage; Providing historical context for street, place or development-renaming requests; Enhancing place-making with deeper historical knowledge; Facilitating emergency and social services by tagging legal addresses to vernacular place names; Encouraging public engagement with heritage by eliciting multi-stakeholder input.

Keywords: collective memory, crowd-sourced, digital heritage, geospatial, geographical names, linguistic heritage, place-naming, Singapore, Southeast Asia

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Authors: Feng Tao, Han Ye, Shaoyi Liao

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City constructions collapse after earthquake and people will be buried under ruins. Search and rescue should be conducted as soon as possible to save them. Therefore, according to the complicated environment, irregular aftershocks and rescue allow of no delay, a kind of target localization method based on RSSI (Received Signal Strength Indication) is proposed in this article. The target localization technology based on RSSI with the features of low cost and low complexity has been widely applied to nodes localization in WSN (Wireless Sensor Networks). Based on the theory of RSSI transmission and the environment impact to RSSI, this article conducts the experiments in five scenes, and multiple filtering algorithms are applied to original RSSI value in order to establish the signal propagation model with minimum test error respectively. Target location can be calculated from the distance, which can be estimated from signal propagation model, through improved centroid algorithm. Result shows that the localization technology based on RSSI is suitable for large-scale nodes localization. Among filtering algorithms, mixed filtering algorithm (average of average, median and Gaussian filtering) performs better than any other single filtering algorithm, and by using the signal propagation model, the minimum error of distance between known nodes and target node in the five scene is about 3.06m.

Keywords: signal propagation model, centroid algorithm, localization, mixed filtering, RSSI

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Authors: Li Yong

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Using the data of 135 financial institutions in China from 2018 to 2022, this paper deeply analyzes the underlying theoretical mechanism of artificial intelligence (AI) technology promoting financial development and examines the impact of AI technology on the digital transformation performance of financial enterprises. It is found that the level of AI technology has a significant positive impact on the development of finance. Compared with the impact on the expansion of financial scale, AI technology plays a greater role in improving the performance of financial institutions, reflecting the trend characteristics of the current AI technology to promote the evolution of financial structure. By investigating the intermediary transmission effects, we found that AI technology plays a positive role in promoting the performance of financial institutions by reducing operating costs and improving customer satisfaction, but its function in innovating financial products and mitigating financial risks is relatively limited. In addition, the promotion of AI technology in financial development has significant heterogeneity in terms of the type, scale, and attributes of financial institutions.

Keywords: artificial intelligence technology, financial development, China, heterogeneity

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Authors: Thilivhali E. Rasimphi, David Tinarwo

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Access to energy is crucial in poverty alleviation, economic growth, education, and agricultural improvement. The best renewable energy source is one which is locally available, affordable, and can easily be used and managed by local communities. The usage of renewable energy technology has the potential to alleviate many of the current problems facing rural areas. To address energy poverty, biogas technology has become an important part of resolving such. This study, therefore, examines the performance of digesters in Gawula village; it also identifies the contributing factors to the adoption and use of the technology. Data was collected using an open-ended questionnaire from biogas users. To evaluate the performance of the digesters, a data envelopment analysis (DEA) non-parametric technique was used, and to identify key factors affecting adoption, a logit model was applied. The reviewed critical barriers to biogas development in the area seem to be a poor institutional framework, poor infrastructure, a lack of technical support, user training on maintenance and operation, and as such, the implemented plants have failed to make the desired impact. Thus most digesters were abandoned. To create awareness amongst rural communities, government involvement is key, and there is a need for national programs. Biogas technology does what few other renewable energy technologies do, which is to integrate waste management and energy. This creates a substantial opportunity for biogas generation and penetration. That is, a promising pathway towards achieving sustainable development through biogas technology.

Keywords: domestic biogas technology, economic, sustainable, social, rural development

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Authors: Myungjin Lee, Daegun Han, Jongsung Kim, Soojun Kim, Hung Soo Kim

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Recently, the localized heavy rainfall and typhoons are frequently occurred due to the climate change and the damage is becoming bigger. Therefore, we may need a more accurate prediction of the rainfall and runoff. However, the gauge rainfall has the limited accuracy in space. Radar rainfall is better than gauge rainfall for the explanation of the spatial variability of rainfall but it is mostly underestimated with the uncertainty involved. Therefore, the ensemble of radar rainfall was simulated using error structure to overcome the uncertainty and gauge rainfall. The simulated ensemble was used as the input data of the rainfall-runoff models for obtaining the ensemble of runoff hydrographs. The previous studies discussed about the accuracy of the rainfall-runoff model. Even if the same input data such as rainfall is used for the runoff analysis using the models in the same basin, the models can have different results because of the uncertainty involved in the models. Therefore, we used two models of the SSARR model which is the lumped model, and the Vflo model which is a distributed model and tried to simulate the optimum runoff considering the uncertainty of each rainfall-runoff model. The study basin is located in Han river basin and we obtained one integrated runoff hydrograph which is an optimum runoff hydrograph using the blending methods such as Multi-Model Super Ensemble (MMSE), Simple Model Average (SMA), Mean Square Error (MSE). From this study, we could confirm the accuracy of rainfall and rainfall-runoff model using ensemble scenario and various rainfall-runoff model and we can use this result to study flood control measure due to climate change. Acknowledgements: This work is supported by the Korea Agency for Infrastructure Technology Advancement(KAIA) grant funded by the Ministry of Land, Infrastructure and Transport (Grant 18AWMP-B083066-05).

Keywords: radar rainfall ensemble, rainfall-runoff models, blending method, optimum runoff hydrograph

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Authors: Yating Yang, Xue Zhang, Chengli Zhao

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Technology capability refers to the comprehensive ability that influences all factors of technological development. Among them, researchers’ resources serve as the foundation and driving force for technology capability, representing a significant manifestation of a country/region's technological capability. Therefore, the cross-border transfer behavior of researchers to some extent reflects changes in technological capability between countries/regions, providing a unique research perspective for technological capability assessment. This paper proposes a technological capability assessment model based on personnel transfer networks, which consists of a researchers' transfer network model and a country/region role evolution model. It evaluates the changes in a country/region's technological capability roles from the perspective of researcher transfers and conducts an analysis using artificial intelligence as a case study based on literature data. The study reveals that the United States, China, and the European Union are core nodes, and identifies the role evolution characteristics of several major countries/regions.

Keywords: transfer network, technological capability assessment, central-peripheral structure, role evolution

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Authors: S. Karmokar

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Over the last 20 years, there has been increasing interest in the topic of entrepreneurship education as it is seen in many countries as a way of enhancing the enterprise culture and promote capability building among community. There is also rapid growth of emerging technologies across the globe and forced entrepreneurs to searching for a new model of economic growth. There are two movements that are dominating and creating waves, Technology Entrepreneurship and Social Entrepreneurship. An increasing number of entrepreneurs are awakening to the possibility of combining the scalable tools and methodology of Technology Entrepreneurship with the value system of Social Entrepreneurship–‘Transformational Entrepreneurship’. To do this transitional educational institute’s need to figure out how to unite the scalable tools of Technology Entrepreneurship with the moral ethos of Social Entrepreneurship. The traditional entrepreneurship education model is wedded to top-down instructive approaches, that is widely used in management education have led to passive educational model. Despite the effort, disruptive’ pedagogies are rare in higher education; they remain underused and often marginalized. High impact and transformational entrepreneurship education and training require universities to adopt new practices and revise current, traditional ways of working. This is a conceptual research paper exploring the potential and growth of transformational entrepreneurship, investigating links between social entrepreneurship. Based on empirical studies and theoretical approaches, this paper outlines some educational approach for both academics and educational institutes to deliver emerging transformational entrepreneurship in tertiary education. The paper presents recommendations for tertiary educators to inform the designing of teaching practices, revise current delivery methods and encourage students to fulfill their potential as entrepreneurs.

Keywords: educational pedagogies, emerging technologies, social entrepreneurship, transformational entrepreneurship

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Authors: Shahnaz Bashir, Abel Usoro, Imran Khan

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Hofstede’s culture model is an important model to study culture between different societies. He collected data from world-wide and performed a comprehensive study. Hofstede’s cultural model is widely accepted and has been used to study cross cultural influences in different areas like cross-cultural psychology, cross cultural management, information technology, and intercultural communication. This study investigates the societal cultural aspects of knowledge sharing in virtual communities.

Keywords: knowledge management, knowledge sharing, societal culture, virtual communities

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Authors: Elsie L. Echeverri-Carroll

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Entrepreneurial ecosystems have become an important concept to explain the birth and sustainability of technology-based entrepreneurship within regions. However, as a theoretical concept, the temporal evolution of entrepreneurship systems remain underdeveloped, making it difficult to understand their dynamic contributions to entrepreneurs. This paper argues that successful technology-based ecosystems go over three cumulative spawning stages: corporate spawning, entrepreneurial spawning, and community spawning. The importance of corporate incubation in vibrant entrepreneurial ecosystems is well documented in the entrepreneurial literature. Similarly, entrepreneurial spawning processes for venture capital-backed startups are well documented in the financial literature. In contrast, there is little understanding of both the third stage of entrepreneurial spawning (when a community of entrepreneurs become a source of firm spawning) and the temporal sequence in which spawning effects occur in a region. We test this three-stage model of entrepreneurial spawning using data from two large databases on firm births—the Secretary of State (160,000 observations) and the National Establishment Time Series (NEST with 150,000 observations)—and information collected from 60 1½-hour interviews with startup founders and representatives of key entrepreneurial organizations. This temporal model is illustrated with case study of Austin, Texas ranked by the Kauffman Foundation as the number one entrepreneurial city in the United States in 2015 and 2016. The 1½-year study founded by the Kauffman Foundation demonstrates the importance of taken into consideration the temporal contributions of both large and entrepreneurial firms in understanding the factors that contribute to the birth and growth of technology-based entrepreneurial regions. More important, these learnings could offer an important road map for regions that pursue to advance their entrepreneurial ecosystems.

Keywords: entrepreneurial ecosystems, entrepreneurial industrial clusters, high-technology, temporal changes

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Authors: Geuna Kim, Sanghyun Kim

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This study investigates various factors that may influence the ISM process, including the organization’s internal needs and external pressure, and examines the role of regulatory pressure in ISM development and performance. The 105 sets of data collected in a survey were tested against the research model using SEM. The results indicate that NP and TP had positive effects on the ISM process, except for perceived benefits. Regulatory pressure had a positive effect on the relationship between ISM awareness and ISM development and performance.

Keywords: information security management, need pull, technology push, regulatory pressure

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Authors: Fatima Ibnchahid

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Competence approach is considered, since the early 80's as one of the major development of HR policies. Many approaches to manage the professional skills were declined. Some processes are mature whereas the others have been abandoned. Competence can be defined as the set of knowledge (theoretical and practical), know-how (experience) and life skills (personality traits) mobilized by a person in the company. The skills must master a logistics manager are divided into two main categories: depending on whether technical skills, or managerial skills and human. The firsts are broken down into skills on logistical techniques and on general skills in business, seconds in social skills (self with others) and personal (with oneself). Logisticians are faced with new challenges and new constraints that are revolutionizing the way to treat the physical movement of goods and operations related to information flows that trigger, they control and guide the physical movements of these major changes, we can mention the development of information technology and communication, the emergence of strong environmental and security constraints. These changes have important effects on the skills needs of the members of the logistical function and sensitive development for training requested by logistical managers to perform better in their job changes. In this article, we will address two main points, first, a brief overview of the management skills and secondly answer the question asked in the title of the article to know what are the skills that will master a logistical manager.

Keywords: skills, competence, management, logistical function

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Authors: Farid Fahami

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This article explores the transformative role of technology in the finance, banking, and insurance sectors. It examines key technological trends such as AI, blockchain, data analytics, and digital platforms and their impact on operations, customer experiences, and business models. The article highlights the benefits of technology adoption, including improved efficiency, cost reduction, enhanced customer experiences, and expanded financial inclusion. It also addresses challenges like cybersecurity, data privacy, and the need for upskilling. Real-world case studies demonstrate successful technology integration, and recommendations for stakeholders emphasize embracing innovation and collaboration. The article concludes by emphasizing the importance of technology in shaping the future of these sectors.

Keywords: banking, finance, insurance, technology

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Authors: Ionel Botef

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Studies show that, for qualitative coatings, the knowledge of cold spray technology must focus on a variety of interdisciplinary fields and a framework for problem solving. The integrated disciplines include, but are not limited to, engineering, material sciences, and physics. Due to its importance, the purpose of this paper is to summarize the state of the art of this technology alongside its theoretical and experimental studies, and explore the role and impact of physics upon cold spraying technology.

Keywords: surface engineering, cold spray, physics, modelling

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Authors: Shimaa Holail, Tamer Saleh, Xiongwu Xiao

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Building change detection (BCD) from satellite imagery is an essential topic in urbanization monitoring, agricultural land management, and updating geospatial databases. Recently, methods for detecting changes based on deep learning have made significant progress and impressive results. However, it has the problem of being insensitive to changes in buildings with complex spectral differences, and the features being extracted are not discriminatory enough, resulting in incomplete buildings and irregular boundaries. To overcome these problems, we propose a dual Siamese network based on the Unet model with the addition of a deep supervision strategy (DS) in this paper. This network consists of a backbone (encoder) based on ImageNet pre-training, a fusion block, and feature pyramid networks (FPN) to enhance the step-by-step information of the changing regions and obtain a more accurate BCD map. To train the proposed method, we created a new dataset (EGY-BCD) of high-resolution and multi-temporal aerial images captured over New Cairo in Egypt to detect building changes for this purpose. The experimental results showed that the proposed method is effective and performs well with the EGY-BCD dataset regarding the overall accuracy, F1-score, and mIoU, which were 91.6 %, 80.1 %, and 73.5 %, respectively.

Keywords: building change detection, deep supervision, semantic segmentation, EGY-BCD dataset

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Authors: Andreas Gohs, Reinhold Kosfeld

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This study should be of interest for practitioners who want to predict precisely the sales numbers of vehicles equipped with an innovative propulsion technology as well as for researchers interested in applied (regional) time series analysis. The study is based on the numbers of new registrations of pure electric and hybrid cars. Methods of time series analysis like ARIMA are compared with the Bass Diffusion-model concerning their forecasting performances for new registrations in Germany at the national and federal state levels. Especially it is investigated if the additional information content from regional data increases the forecasting accuracy for the national level by adding predictions for the federal states. Results of parameters of the Bass Diffusion Model estimated for Germany and its sixteen federal states are reported. While the focus of this research is on the German market, estimation results are also provided for selected European and other countries. Concerning Bass-parameters and forecasting performances, we get very different results for Germany's federal states and the member states of the European Union. This corresponds to differences across the EU-member states in the adoption process of this innovative technology. Concerning the German market, the adoption is rather proceeded in southern Germany and stays behind in Eastern Germany except for Berlin.

Keywords: bass diffusion model, electric vehicles, forecasting performance, market diffusion

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Authors: Jim Shi, Jasmine Chang, Nesreen El-Rayes

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The world has been experiencing a steadily increasing trend in both the production and consumption of plastic. The global consumer revolution should not have been possible without plastic, thanks to its salient feature of inexpensiveness and durability. But, as a two-edged sword, its durable quality has returned to haunt and even jeopardized us. That exacerbating the plastic crisis has attracted various global initiatives and actions. Simultaneously, firms are eager to adopt new technology as they witness and perceive more potential and merit of Industry 4.0 technologies. For example, Blockchain technology (BCT) is drawing the attention of numerous stakeholders because of its wide range of outstanding features that promise to enhance supply chain operations. However, from a research perspective, most of the literature addresses the plastic crisis from either environmental or social perspectives. In contrast, analysis from the data science perspective and technology is relatively scarce. To this end, this study aims to fill this gap and cover the plastic crisis from a holistic view of environmental, social, technological, and business perspectives. In particular, we propose a mathematical model to examine the inclusion of BCT to enhance and improve the efficiency on the upstream and the downstream sides of the plastic value, where the whole value chain is coordinated systematically, and its interoperability can be optimized. Consequently, the Environmental, Social, and Governance (ESG) goal and Circular Economics (CE) sustainability can be maximized.

Keywords: blockchain technology, plastic, circular economy, sustainability

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Authors: Masica Jordan Alston, Angela N. Bullock, Angela S. Henderson, Stephanie Strianse, Sade Dunn, Joseph Hackett, Alaysia Black Hackett, Marcus Mason

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The Energy Model of Cumulative Grief was created in 2018. The Energy Model of Cumulative Grief utilizes historic models of grief stage theories. The innovative model is additionally unique due to its focus on cultural responsiveness. The Energy Model of Cumulative Grief helps to train practitioners who work with clients dealing with grief and loss. This paper assists in introducing the world to this innovative model and exploring how this model positively impacted a convenience sample of 140 practitioners and individuals experiencing grief and loss. Respondents participated in Webinars provided by the National Grief and Loss Center of America (NGLCA). Participants in this cross-sectional research design study completed one of three Grief and Loss Surveys created by the Grief and Loss Centers of America. Data analysis for this study was conducted via SPSS and Survey Hero to examine survey results for respondents. Results indicate that the Energy Model of Cumulative Grief was an effective resource for participants in addressing grief and loss. The majority of participants found the Webinars to be helpful and a conduit to providing them with higher levels of hope. The findings suggest that using The Energy Model of Cumulative Grief is effective in providing culturally responsive grief and loss resources to practitioners and clients. There are far reaching implications with the use of technology to provide hope to those suffering from grief and loss worldwide through The Energy Model of Cumulative Grief.

Keywords: grief, loss, grief energy, grieving brain

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Authors: Langa Hendrick Musawenkosi, Twala Bhekisipho

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The success or failure of students is a concern for every academic institution, college, university, governments and students themselves. Several approaches have been researched to address this concern. In this paper, a view is held that when a student enters a university or college or an academic institution, he or she enters an academic environment. The academic environment is unique concept used to develop the solution for making predictions effectively. This paper presents a model to determine the propensity of a student to succeed or fail in the French South African Schneider Electric Education Center (FSASEC) at the Vaal University of Technology (VUT). The Decision Tree algorithm is used to implement the model at FSASEC.

Keywords: FSASEC, academic environment model, decision trees, k-nearest neighbor, machine learning, popularity index, support vector machine

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Authors: R. Abdulrahman, A. Eardley, A. Soliman

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The proliferation in the development of mobile learning (m-learning) has played a vital role in the rapidly growing electronic learning market. This relatively new technology can help to encourage the development of in learning and to aid knowledge transfer a number of areas, by familiarizing students with innovative information and communications technologies (ICT). M-learning plays a substantial role in the deployment of learning methods for nursing students by using the Internet and portable devices to access learning resources ‘anytime and anywhere’. However, acceptance of m-learning by students is critical to the successful use of m-learning systems. Thus, there is a need to study the factors that influence student’s intention to use m-learning. This paper addresses this issue. It outlines the outcomes of a study that evaluates the unified theory of acceptance and use of technology (UTAUT) model as applied to the subject of user acceptance in relation to m-learning activity in nurse education. The model integrates the significant components across eight prominent user acceptance models. Therefore, a standard measure is introduced with core determinants of user behavioural intention. The research model extends the UTAUT in the context of m-learning acceptance by modifying and adding individual innovativeness (II) and quality of service (QoS) to the original structure of UTAUT. The paper goes on to add the factors of previous experience (of using mobile devices in similar applications) and the nursing students’ readiness (to use the technology) to influence their behavioural intentions to use m-learning. This study uses a technique called ‘convenience sampling’ which involves student volunteers as participants in order to collect numerical data. A quantitative method of data collection was selected and involves an online survey using a questionnaire form. This form contains 33 questions to measure the six constructs, using a 5-point Likert scale. A total of 42 respondents participated, all from the Nursing Institute at the Armed Forces Hospital in Saudi Arabia. The gathered data were then tested using a research model that employs the structural equation modelling (SEM), including confirmatory factor analysis (CFA). The results of the CFA show that the UTAUT model has the ability to predict student behavioural intention and to adapt m-learning activity to the specific learning activities. It also demonstrates satisfactory, dependable and valid scales of the model constructs. This suggests further analysis to confirm the model as a valuable instrument in order to evaluate the user acceptance of m-learning activity.

Keywords: mobile learning, nursing institute students’ acceptance of m-learning activity in Saudi Arabia, unified theory of acceptance and use of technology model (UTAUT), structural equation modelling (SEM)

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Authors: Theoktisti Makridou, Konstantinos Tsaprailis, George Arvanitakis, Charalampos Kontoes

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In the literature, the data-driven approaches for mosquito abundance prediction relaying on supervised machine learning models that get trained with historical in-situ measurements. The counterpart of this approach is once the model gets trained on pointlevel (specific x,y coordinates) measurements, the predictions of the model refer again to point-level. These point-level predictions reduce the applicability of those solutions once a lot of early warning and mitigation actions applications need predictions for an area level, such as a municipality, village, etc... In this study, we apply a data-driven predictive model, which relies on public-open satellite Earth Observation and geospatial data and gets trained with historical point-level in-Situ measurements of mosquito abundance. Then we propose a methodology to extract information from a point-level predictive model to a broader area-level prediction. Our methodology relies on the randomly spatial sampling of the area of interest (similar to the Poisson hardcore process), obtaining the EO and geomorphological information for each sample, doing the point-wise prediction for each sample, and aggregating the predictions to represent the average mosquito abundance of the area. We quantify the performance of the transformation from the pointlevel to the area-level predictions, and we analyze it in order to understand which parameters have a positive or negative impact on it. The goal of this study is to propose a methodology that predicts the mosquito abundance of a given area by relying on point-level prediction and to provide qualitative insights regarding the expected performance of the area-level prediction. We applied our methodology to historical data (of Culex pipiens) of two areas of interest (Veneto region of Italy and Central Macedonia of Greece). In both cases, the results were consistent. The mean mosquito abundance of a given area can be estimated with similar accuracy to the point-level predictor, sometimes even better. The density of the samples that we use to represent one area has a positive effect on the performance in contrast to the actual number of sampling points which is not informative at all regarding the performance without the size of the area. Additionally, we saw that the distance between the sampling points and the real in-situ measurements that were used for training did not strongly affect the performance.

Keywords: mosquito abundance, supervised machine learning, culex pipiens, spatial sampling, west nile virus, earth observation data

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Authors: Jan-Peter Mund, Christian Kind

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In view of the ongoing climate change and global warming, fires along railways in Germany are occurring more frequently, with sometimes massive consequences for railway operations and affected railroad infrastructure. In the absence of systematic studies within the infrastructure network of German Rail, little is known about the causes of such embankment fires. Since a further increase in these hazards is to be expected in the near future, there is a need for a sound knowledge of triggers and drivers for embankment fires as well as methodical knowledge of prediction tools. Two predictable future trends speak for the increasing relevance of the topic: through the intensification of the use of rail for passenger and freight transport (e.g..: doubling of annual passenger numbers by 2030, compared to 2019), there will be more rail traffic and also more maintenance and construction work on the railways. This research project approach uses satellite data to identify historical embankment fires along rail network infrastructure. The team links data from these fires with infrastructure and weather data and trains a machine-learning model with the aim of predicting fire hazards on sections of the track. Companies reflect on the results and use them on a pilot basis in precautionary measures.

Keywords: embankment fires, railway maintenance, machine learning, remote sensing, VIIRS data

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Authors: Lovemore Motsi

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The rapid pace of technological innovation, along with a global fascination with the internet, continues to result in a dominating call to integrate internet technologies in institutions of learning. However, the pressing question remains – how can online in-service training for teachers, support quality and success in professional development programmers. The aim of this study was to examine an integrated model that extended the Unified Theory of Acceptance and Use of Technology (UTAUT) with additional constructs – including attitude and behaviour intention – adopted from the Theory of Planned Behaviour (TPB) to answer the question. Data was collected from secondary school teachers at 10 selected schools in the Tshwane South district by means of the Statistical Package for Social Scientists (SPSS v 23.0), and the collected data was analysed quantitatively. The findings are congruent with model testing under conditions of volitional usage behaviour. In this regard, the role of facilitating condition variables is insignificant as a determinant of usage behaviour. Social norm variables also proved to be a weak determinant of behavioural intentions. Findings demonstrate that effort expectancy is the key determinant of online INSET usage. Based on these findings, the variable social influence and facilitating conditions are important factors in ensuring the acceptance of online INSET among teachers in selected secondary schools in the Tshwane South district.

Keywords: unified theory of acceptance and use of technology (UTAUT), teacher professional development, secondary schools, online INSET

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Authors: Sultan Alotaibi, Dmitri Roussinov

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Many governments recently started to change the ways of providing their services by allowing their citizens to access services from anywhere without the need of visiting the location of the service provider. Mobile government (M-government) is one of the techniques that fulfill that goal. It has been adopted by many governments. M-government can be defined as an implementation of Electronic Government (E-Government) by using mobile technology with the aim of improving service delivery to citizens, businesses and all government agencies. There have been several research projects developing models to understand the behavior of individuals towards the adoption of m-government. This paper proposes a model for adoption of m-government services in Saudi Arabia by extending Technology Acceptance Model (TAM) by introducing external factors. This paper also reports on the development of a survey instrument designed to measure user perception of mobile government acceptance. A survey instrument has been developed by using existing scales from prior instruments and a pilot study has been conducted by distributing the survey to 33 participants. As a result, a survey instrument has been refined to retain 43 items. The results also showed that the reliabilities of all the scales in the survey instrument are above the levels acceptable in current academic research, thus the instruments developed by us are capable of analyzing the factors in M-government adoption.

Keywords: TAM, m-government, e-government, model, acceptance, mobile government

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Authors: Komal Ghafoor, Tauqir Ahmad, Murtaza Hanif, Hira Zaheer

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Assistive technology has been developed to support visually impaired people in their social interactions. Conversation assistive technology is designed to enhance communication skills, facilitate social interaction, and improve the quality of life of visually impaired individuals. This technology includes speech recognition, text-to-speech features, and other communication devices that enable users to communicate with others in real time. The technology uses natural language processing and machine learning algorithms to analyze spoken language and provide appropriate responses. It also includes features such as voice commands and audio feedback to provide users with a more immersive experience. These technologies have been shown to increase the confidence and independence of visually impaired individuals in social situations and have the potential to improve their social skills and relationships with others. Overall, conversation-assistive technology is a promising tool for empowering visually impaired people and improving their social interactions. One of the key benefits of conversation-assistive technology is that it allows visually impaired individuals to overcome communication barriers that they may face in social situations. It can help them to communicate more effectively with friends, family, and colleagues, as well as strangers in public spaces. By providing a more seamless and natural way to communicate, this technology can help to reduce feelings of isolation and improve overall quality of life. The main objective of this research is to give blind users the capability to move around in unfamiliar environments through a user-friendly device by face, object, and activity recognition system. This model evaluates the accuracy of activity recognition. This device captures the front view of the blind, detects the objects, recognizes the activities, and answers the blind query. It is implemented using the front view of the camera. The local dataset is collected that includes different 1st-person human activities. The results obtained are the identification of the activities that the VGG-16 model was trained on, where Hugging, Shaking Hands, Talking, Walking, Waving video, etc.

Keywords: dataset, visually impaired person, natural language process, human activity recognition

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Authors: Ngo the Bach

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Information technology and communications are growing strongly and penetrated almost the entire Vietnamese economy and society. The article presents an overview of information technology and application communications in the management the Central Sector of the Imperial Citadel of Thang Long (Hanoi, Vietnam) - A World Heritage Site. The author also points out the opportunities and challenges of the information technology and communications in the sectors of culture and heritage; the use of information technology as an effective tool to develop mass and interactive communications. The article emphasizes on the advantage of information technology and communications in supporting effectively the management reform with respect to the Imperial Citadel of Thang Long in particular and the management of world heritage sites in Vietnam in general.

Keywords: information technology, communications, management, culture, heritage

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Authors: M. Caporale

Abstract:

French Curricula across the US have recently suffered low enrollment and have experienced difficulties with retention, thus resulting in fewer students minoring and majoring in French and enrolling in upper-level classes. Successful undergraduate programs offer French courses with a strong cultural and interdisciplinary or multidisciplinary component. The World Language Curriculum in liberal arts colleges in America needs to take into account the cultural aspects of the language and encourage students to think critically about the country or countries they are studying. Limiting the critical inquiry to language or literature narrowly defined provides and incomplete and stagnant picture of France and the Francophone world in today's global community. This essay discusses the creation and implementation of a hybrid interdisciplinary L1/L2 course titled "Topics in Francophone Cinema" (subtitle "Francophone Women on Screen and Behind the Camera"). Content-based interdisciplinary courses undoubtedly increase the profile of French and Francophone cultural Studies by introducing students of other disciplines to fundamental questions relating to the French and Francophone cultures (in this case, women's rights in the Francophone world). At the same time, this study determines that through targeted reading and writing assignments, sustained aural exposure to L2 through film,and student participation in a one-credit supplementary weekly practicum (creative film writing workshop), significant advances in L2 competence are achieved with students' oral and written production levels evolving from Advanced Low to Advanced-mid, as defined by the ACFL guidelines. Use of differentiated assessment methods for L1/L2 and student learning outcomes for both groups will also be addressed.

Keywords: interdisciplinary, Francophone cultural studies, language competency, content-based

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Authors: Jessica Liqin Kong

Abstract:

Female engineers and scientists face unique challenges in their careers that make the development of professional networks crucial, but also more difficult. Working to overcome these challenges, ‘The Network’ was established in 2013 at the Queensland University of Technology (QUT) in Australia as an alumni chapter with the purpose of evoking continuous positive change for female participation and retention in science, technology, engineering and mathematics (STEM). ‘The Network’ adopts an innovative model for a Women in STEM alumni chapter which was inspired by the cradle to cradle approach to engagement, and the concept of growing and harvesting individual and collective social capital through a variety of initiatives. ‘The Network’ fosters an environment where the values exchanged in social and professional relationships can be capitalized for both current and future women in STEM. The model of ‘The Network’ acts as a simulation and opportunity for participants to further develop their leadership and other soft skills through learning, building and experimenting with ‘The Network’.

Keywords: women in STEM, engagement, Cradle-to-Cradle, social capital

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Authors: Halima Akhtar, Abhijeet Chandra

Abstract:

The paper attempts to analyze the factors that influence the Consumer Behavior to purchase apparel through the internet. The intentions to buy apparels online were based on in terms of user style, orientation, size and reputation of the merchant, social influence, perceived information utility, perceived ease of use, perceived pleasure and attractiveness and perceived trust and risk. The basic framework used was Technology acceptance model to explain apparels acceptance. A survey was conducted to gather the data from 200 people. The measures and hypotheses were analyzed using Correlation testing and would be further validated by the Structural Equation Modelling. The implications of the findings for theory and practice could be used by marketers of online apparel websites. Based on the values obtained, we can conclude that the factors such as social influence, Perceived information utility, attractiveness and trust influence the decision for a user to buy apparels online. The major factors which are found to influence an online apparel buying decision are ease of use, attractiveness that a website can offer and the trust factor which a user shares with the website.

Keywords: E-tailers, consumer behaviour, technology acceptance model, structural modelling

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Authors: Shinn-Dar Wu

Abstract:

This study aims to synthesize lithium iron phosphate cathode material using a recycling technology involving non-protective gas calcination. The advantages include lower cost and easier production than traditional methods that require a large amount of protective gas. The novel technology may have extensive industrial applications. Given that the traditional gas calcination has a large number of protection free Fe3+ production, this study developed a precursor iron phosphate (Fe2+) material recycling technology and conducted related tests and analyses. It focused on flow field design of calcination and new technology as well as analyzed the best conditions for powder calcination combination. The electrical properties were determined by button batteries and exhibited a capacity of 118 mAh/g (The use of new materials synthesis, capacitance is about 122 mAh/g). The cost reduced to 50% of the original.

Keywords: lithium battery, lithium iron phosphate, calcined technology, recycling technology

Procedia PDF Downloads 441