Search results for: digital transformation artificial intelligence

Authors: Jong-Jy Shyu, Soo-Chang Pei, Yun-Da Huang

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In this paper, design of wide-range variable fractional-delay (WR-VFD) finite impulse response (FIR) digital filters is proposed. With respect to the conventional VFD filter which is designed such that its delay is adjustable within one unit, the proposed VFD FIR filter is designed such that its delay can be tunable within a wider range. By the traces of coefficients of the fractional-delay FIR filter, it is found that the conventional method of polynomial substitution for filter coefficients no longer satisfies the design demand, and the circuits perform the sinc function (sinc converter) are added to overcome this problem. In this paper, least-squares method is adopted to design WR-VFD FIR filter. Throughout this paper, several examples will be proposed to demonstrate the effectiveness of the presented methods.

Keywords: digital filter, FIR filter, variable fractional-delay (VFD) filter, least-squares approximation

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Authors: Kemi Olalekan Oduntan

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Transformation is a strong word that portends a radical, structural and basic reappraisal of the basic assumptions that underline our economic reform and developmental efforts. The challenges before government are how to move the nation away from an oil-dominated economy, institute the basics for a private sector-driven economy, build the local economy on international best practices, transform a passive oil industry to a more pro-active one and reposition the country along the lines of a more decentralized federalism. But beyond this, Nigeria is faced with management and leadership challenges to contend with building an efficient and effective polity, inspiring a shared vision, remodeling a corrupt polity, redefining the essentials of transformational leadership and creating Nigerian dream that will inspire patriotism and commitment in the citizenry.

Keywords: economic, economic growth, patriotism, polity, transformational

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Authors: Joel Zapata

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Chicana/o Activism in the Southern Plains Through Time and Space, a digital history project available at PlainsMovement.com, helps reveal an understudied portion of the Chicana/o Civil Rights Movement: the way it unfolded on the Southern Plains. The project centers around an approachable interactive map and timeline along with a curated collection of materials. Therefore, the project provides a digital museum experience that has not emerged within the region’s museums. That is, this digital history project takes scholarly research to the wider public, making it is also a publicly facing history project. In this way, the project adds to both scholarly and socially significant conversations, showing that the region was home to a burgeoning wing of the Chicana/o Movement and that instances of police brutality largely spurred this wing of the social justice movement. Moreover, the curated collection of materials demonstrates that police brutality united the plains’ Mexican population across political ideology, a largely overlooked aspect within the study of Mexican American civil rights movements. Such a finding can be of use today since contemporary Latina/o social justice organizations generally ignore policing issues even amid a rise in national awareness regarding police abuse. In making history accessible to Mexican origin and Latina/o communities, these same communities may in-turn use the knowledge gained from historical research towards the betterment of their social positions—the foundational goal of Chicana/o history and the related field of Chicana/o Studies. Ultimately, this digital history project is intended to draw visitors to further explore the Chicana/o Civil Rights Movement within and beyond the plains.

Keywords: Chicana/o Movement, digital history, police brutality, newspapers, protests, student activism

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Authors: Carolina Busco, Daniela Osses

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The development of digital literacy has become a fundamental element that allows for citizen inclusion, access to quality jobs, and a labor market capable of responding to the digital economy. There are no methodological instruments available in Chile to measure the workforce’s digital literacy and improve national policies on this matter. Thus, the objective of this research is to develop a survey to measure digital literacy in a sample of 200 Chilean workers. Dimensions considered in the instrument are sociodemographics, access to infrastructure, digital education, digital skills, and the ability to use e-government services. To achieve the research objective of developing a digital literacy model of indicators and a research instrument for this purpose, along with an exploratory analysis of data using factor analysis, we used an empirical, quantitative-qualitative, exploratory, non-probabilistic, and cross-sectional research design. The research instrument is a survey created to measure variables that make up the conceptual map prepared from the bibliographic review. Before applying the survey, a pilot test was implemented, resulting in several adjustments to the phrasing of some items. A validation test was also applied using six experts, including their observations on the final instrument. The survey contained 49 items that were further divided into three sets of questions: sociodemographic data; a Likert scale of four values ranked according to the level of agreement; iii) multiple choice questions complementing the dimensions. Data collection occurred between January and March 2022. For the factor analysis, we used the answers to 12 items with the Likert scale. KMO showed a value of 0.626, indicating a medium level of correlation, whereas Bartlett’s test yielded a significance value of less than 0.05 and a Cronbach’s Alpha of 0.618. Taking all factor selection criteria into account, we decided to include and analyze four factors that together explain 53.48% of the accumulated variance. We identified the following factors: i) access to infrastructure and opportunities to develop digital skills at the workplace or educational establishment (15.57%), ii) ability to solve everyday problems using digital tools (14.89%), iii) online tools used to stay connected with others (11.94%), and iv) residential Internet access and speed (11%). Quantitative results were discussed within six focus groups using heterogenic selection criteria related to the most relevant variables identified in the statistical analysis: upper-class school students; middle-class university students; Ph.D. professors; low-income working women, elderly individuals, and a group of rural workers. The digital divide and its social and economic correlations are evident in the results of this research. In Chile, the items that explain the acquisition of digital tools focus on access to infrastructure, which ultimately puts the first filter on the development of digital skills. Therefore, as expressed in the literature review, the advance of these skills is radically different when sociodemographic variables are considered. This increases socioeconomic distances and exclusion criteria, putting those who do not have these skills at a disadvantage and forcing them to seek the assistance of others.

Keywords: digital literacy, digital society, workforce digitalization, digital skills

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Authors: Gaurav Sancheti

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This study presents an impacting approach of Artificial Neural Networks (ANNs) in determining the quantity of High Tensile Steel (HTS) strands required in post-tensioned (PT) slabs. Various PT slab configurations were generated by varying the span and depth of the slab. For each of these slab configurations, quantity of required HTS strands were recorded. ANNs with backpropagation algorithm and varying architectures were developed and their performance was evaluated in terms of Mean Square Error (MSE). The recorded data for the quantity of HTS strands was used as a feeder database for training the developed ANNs. The networks were validated using various validation techniques. The results show that the proposed ANNs have a great potential with good prediction and generalization capability.

Keywords: artificial neural networks, back propagation, conceptual design, high tensile steel strands, post tensioned slabs, validation techniques

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Authors: Roman Graf, Sergiu Gordea, Heather M. Ryan

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This paper presents an approach for the classification of an unstructured format description for identification of file formats. The main contribution of this work is the employment of data mining techniques to support file format selection with just the unstructured text description that comprises the most important format features for a particular organisation. Subsequently, the file format indentification method employs file format classifier and associated configurations to support digital preservation experts with an estimation of required file format. Our goal is to make use of a format specification knowledge base aggregated from a different Web sources in order to select file format for a particular institution. Using the naive Bayes method, the decision support system recommends to an expert, the file format for his institution. The proposed methods facilitate the selection of file format and the quality of a digital preservation process. The presented approach is meant to facilitate decision making for the preservation of digital content in libraries and archives using domain expert knowledge and specifications of file formats. To facilitate decision-making, the aggregated information about the file formats is presented as a file format vocabulary that comprises most common terms that are characteristic for all researched formats. The goal is to suggest a particular file format based on this vocabulary for analysis by an expert. The sample file format calculation and the calculation results including probabilities are presented in the evaluation section.

Keywords: data mining, digital libraries, digital preservation, file format

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Authors: Moumita Chanda, Md. Fazlul Karim Patwary

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Smoking is one of the most popular recreational drug use behaviors, and it contributes to birth defects, COPD, heart attacks, and erectile dysfunction. To completely eradicate this disease, it is imperative that it be identified and treated. Numerous smoking cessation programs have been created, and they demonstrate how beneficial it may be to help someone stop smoking at the ideal time. A tomography meter is an effective smoking detector. Other wearables, such as RF-based proximity sensors worn on the collar and wrist to detect when the hand is close to the mouth, have been proposed in the past, but they are not impervious to deceptive variables. In this study, we create a machine that can discriminate between smokers and non-smokers in real-time with high sensitivity and specificity by watching and collecting the human lung and analyzing the X-ray data using machine learning. If it has the highest accuracy, this machine could be utilized in a hospital, in the selection of candidates for the army or police, or in university entrance.

Keywords: CNN, smoker detection, non-smoker detection, OpenCV, artificial Intelligence, X-ray Image detection

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Authors: Sara Fayez Fawzy Mikhael

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Inclusive education services for students with Autism remains in its early developmental stages in Thailand. Despite many more children with autism are attending schools since the Thai government introduced the Education Provision for People with Disabilities Act in 2008, the services students with autism and their families receive are generally lacking. This quantitative study used Attitude and Preparedness to Teach Students with Autism Scale (APTSAS) to investigate 110 primary school teachers’ attitude and preparedness to teach students with autism in the general education classroom. Descriptive statistical analysis of the data found that student behavior was the most significant factor in building teachers’ negative attitudes students with autism. The majority of teachers also indicated that their pre-service education did not prepare them to meet the learning needs of children with autism in particular, those who are non-verbal. The study is significant and provides direction for enhancing teacher education for inclusivity in Thailand.

Keywords: attitude, autism, teachers, thailandsports activates, movement skills, motor skills

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Authors: R. Clancy, M. Ahern, D. O’Sullivan, K. Bruton

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The manufacturing industry is currently undergoing a digital transformation as part of the mega-trend Industry 4.0. As part of this phase of the industrial revolution, traditional manufacturing processes are being combined with digital technologies to achieve smarter and more efficient production. To successfully digitally transform a manufacturing facility, the processes must first be digitized. This is the conversion of information from an analogue format to a digital format. The objective of this study was to explore the research area of digitizing manufacturing data as part of the worldwide paradigm, Industry 4.0. The formal methodology of a systematic mapping study was utilized to capture a representative sample of the research area and assess its current state. Specific research questions were defined to assess the key benefits and limitations associated with the digitization of manufacturing data. Research papers were classified according to the type of research and type of contribution to the research area. Upon analyzing 54 papers identified in this area, it was noted that 23 of the papers originated in Germany. This is an unsurprising finding as Industry 4.0 is originally a German strategy with supporting strong policy instruments being utilized in Germany to support its implementation. It was also found that the Fraunhofer Institute for Mechatronic Systems Design, in collaboration with the University of Paderborn in Germany, was the most frequent contributing Institution of the research papers with three papers published. The literature suggested future research directions and highlighted one specific gap in the area. There exists an unresolved gap between the data science experts and the manufacturing process experts in the industry. The data analytics expertise is not useful unless the manufacturing process information is utilized. A legitimate understanding of the data is crucial to perform accurate analytics and gain true, valuable insights into the manufacturing process. There lies a gap between the manufacturing operations and the information technology/data analytics departments within enterprises, which was borne out by the results of many of the case studies reviewed as part of this work. To test the concept of this gap existing, the researcher initiated an industrial case study in which they embedded themselves between the subject matter expert of the manufacturing process and the data scientist. Of the papers resulting from the systematic mapping study, 12 of the papers contributed a framework, another 12 of the papers were based on a case study, and 11 of the papers focused on theory. However, there were only three papers that contributed a methodology. This provides further evidence for the need for an industry-focused methodology for digitizing and analyzing manufacturing data, which will be developed in future research.

Keywords: analytics, digitization, industry 4.0, manufacturing

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Authors: Lingju Wu, Hao Hua

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This paper presents a digital fashion production methodology and workflow based on fused deposition modeling additive manufacturing technology, as demonstrated through a 3D printed fashion show held at Southeast University in Nanjing, China. Unlike traditional fashion, 3D printed fashion allows for the creation of complex geometric shapes and unique structural designs, facilitating diverse reconfiguration and sustainable production of textile fabrics. The proposed methodology includes two components: morphogenesis and the 3D printing process. The morphogenesis part comprises digital design methods such as mesh deformation, structural reorganization, particle flow stretching, sheet partitioning, and spreading methods. The 3D printing process section includes three types of methods: sculptural objects, multi-material composite fabric, and self-forming composite fabrics. This paper focuses on multi-material composite fabrics and self-forming composite fabrics, both of which involve weaving fabrics with 3D-printed material sandwiches. Multi-material composite fabrics create specially tailored fabric from the original properties of the printing path and multiple materials, while self-forming fabrics apply pre-stress to the flat fabric and then print the sandwich, allowing the fabric's own elasticity to interact with the printed components and shape into a 3D state. The digital design method and workflow enable the integration of abstract sensual aesthetics and rational thinking, showcasing a digital aesthetic that challenges conventional handicraft workshops. Overall, this paper provides a comprehensive framework for the production of 3D-printed fashion, from concept to final product.

Keywords: digital fashion, composite fabric, self-forming structure, additive manufacturing, generating design

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Authors: Samwail Fahmi Francis Yacoub

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Inclusive education services for students with Autism remains in its early developmental stages in Thailand. Despite many more children with autism are attending schools since the Thai government introduced the Education Provision for People with Disabilities Act in 2008, the services students with autism and their families receive are generally lacking. This quantitative study used Attitude and Preparedness to Teach Students with Autism Scale (APTSAS) to investigate 110 primary school teachers’ attitude and preparedness to teach students with autism in the general education classroom. Descriptive statistical analysis of the data found that student behavior was the most significant factor in building teachers’ negative attitudes students with autism. The majority of teachers also indicated that their pre-service education did not prepare them to meet the learning needs of children with autism in particular, those who are non-verbal. The study is significant and provides direction for enhancing teacher education for inclusivity in Thailand.

Keywords: attitude, autism, teachers, movement skills, motor skills, children, behavior.

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Authors: Eirini Busack

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Since the outbreak of the Covid-19 pandemic and the sudden transfer to online teaching, teachers have struggled to reconstruct their teaching and learning materials to adapt them to the new reality of online teaching and learning. Consequently, the pupils’ learning was disrupted during this orientation phase. Due to the above situation, teachers from all fields concluded that it is vital that their pupils should be able to continue their learning even without the teacher being physically present. Various websites and applications have been in use since then in hope that pupils will still enjoy a qualitative education; unfortunately, this was often not the case. To address this issue, it was therefore decided to focus the research on the development of digital learning paths. The fundamentals of these learning paths include the implementation of scenario-based learning (digital storytelling), the integration of media-didactic theory to make it pedagogically appropriate for learners, alongside instructional design knowledge and the drive to promote autonomous learners. This particular research is being conducted within the frame of the research project “Sustainable integration of subject didactic digital teaching-learning concepts” (InDiKo, 2020-2023), which is currently conducted at the University of Education Karlsruhe and investigates how pre-service teachers can acquire the necessary interdisciplinary and subject-specific media-didactic competencies to provide their future learners with digitally enhanced learning opportunities, and how these competencies can be developed continuously and sustainably. As English is one of the subjects involved in this project, the English Department prepared a seminar for the pre-service secondary teachers: “Media-didactic competence development: Developing learning paths & Digital Storytelling for English grammar teaching.” During this seminar, the pre-service teachers plan and design a Moodle-based differentiated lesson sequence on an English grammar topic that is to be tested by secondary school pupils. The focus of the present research is to assess the secondary school pupils’ expectations from an English grammar-focused digital learning path created by pre-service English teachers. The nine digital learning paths that are to be distributed to 25 pupils were produced over the winter and the current summer semester as the artifact of the seminar. Finally, the data to be quantitatively analysed and interpreted derive from the online questionnaires that the secondary school pupils fill in so as to reveal their expectations on what they perceive as a stimulating and thus effective grammar-focused digital learning path.

Keywords: digital storytelling, learning paths, media-didactics, autonomous learning

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Authors: Sophia Liang Zhou

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For investors, businesses, consumers, and governments, an accurate assessment of future housing prices is crucial to critical decisions in resource allocation, policy formation, and investment strategies. Previous studies are contradictory about macroeconomic determinants of housing price and largely focused on one or two areas using point prediction. This study aims to develop data-driven models to accurately predict future housing market trends in different markets. This work studied five different metropolitan areas representing different market trends and compared three-time lagging situations: no lag, 6-month lag, and 12-month lag. Linear regression (LR), random forest (RF), and artificial neural network (ANN) were employed to model the real estate price using datasets with S&P/Case-Shiller home price index and 12 demographic and macroeconomic features, such as gross domestic product (GDP), resident population, personal income, etc. in five metropolitan areas: Boston, Dallas, New York, Chicago, and San Francisco. The data from March 2005 to December 2018 were collected from the Federal Reserve Bank, FBI, and Freddie Mac. In the original data, some factors are monthly, some quarterly, and some yearly. Thus, two methods to compensate missing values, backfill or interpolation, were compared. The models were evaluated by accuracy, mean absolute error, and root mean square error. The LR and ANN models outperformed the RF model due to RF’s inherent limitations. Both ANN and LR methods generated predictive models with high accuracy ( > 95%). It was found that personal income, GDP, population, and measures of debt consistently appeared as the most important factors. It also showed that technique to compensate missing values in the dataset and implementation of time lag can have a significant influence on the model performance and require further investigation. The best performing models varied for each area, but the backfilled 12-month lag LR models and the interpolated no lag ANN models showed the best stable performance overall, with accuracies > 95% for each city. This study reveals the influence of input variables in different markets. It also provides evidence to support future studies to identify the optimal time lag and data imputing methods for establishing accurate predictive models.

Keywords: linear regression, random forest, artificial neural network, real estate price prediction

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Authors: Beatriz Botella-Gil, Patricio Martínez-Barco, Lea Canales

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The Internet and ICT are an integral element of and omnipresent in our daily lives. Technologies have changed the way we see the world and relate to it. The number of companies in the ICT sector is increasing every year, and there has also been an increase in the work that occurs online, from sending e-mails to the way companies promote themselves. In social life, ICT’s have gained momentum. Social networks are useful for keeping in contact with family or friends that live far away. This change in how we manage our relationships using electronic devices and social media has been experienced differently depending on the age of the person. According to currently available data, people are increasingly connected to social media and other forms of online communication. Therefore, it is no surprise that violent content has also made its way to digital media. One of the important reasons for this is the anonymity provided by social media, which causes a sense of impunity in the victim. Moreover, it is not uncommon to find derogatory comments, attacking a person’s physical appearance, hobbies, or beliefs. This is why it is necessary to develop artificial intelligence tools that allow us to keep track of violent comments that relate to violent events so that this type of violent online behavior can be deterred. The objective of our research is to create a guide for detecting and recording violent messages. Our annotation guide begins with a study on the problem of violent messages. First, we consider the characteristics that a message should contain for it to be categorized as violent. Second, the possibility of establishing different levels of aggressiveness. To download the corpus, we chose the social network Twitter for its ease of obtaining free messages. We chose two recent, highly visible violent cases that occurred in Spain. Both of them experienced a high degree of social media coverage and user comments. Our corpus has a total of 633 messages, manually tagged, according to the characteristics we considered important, such as, for example, the verbs used, the presence of exclamations or insults, and the presence of negations. We consider it necessary to create wordlists that are present in violent messages as indicators of violence, such as lists of negative verbs, insults, negative phrases. As a final step, we will use automatic learning systems to check the data obtained and the effectiveness of our guide.

Keywords: human language technologies, language modelling, offensive language detection, violent online content

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Authors: Julio Albuja, David Zaldumbide

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Data analysis is an important step before taking a decision about money. The aim of this work is to analyze the factors that influence the final price of the houses through data mining algorithms. To our best knowledge, previous work was researched just to compare results. Furthermore, before using the data of the data set, the Z-Transformation were used to standardize the data in the same range. Hence, the data was classified into two groups to visualize them in a readability format. A decision tree was built, and graphical data is displayed where clearly is easy to see the results and the factors' influence in these graphics. The definitions of these methods are described, as well as the descriptions of the results. Finally, conclusions and recommendations are presented related to the released results that our research showed making it easier to apply these algorithms using a customized data set.

Keywords: algorithms, data, decision tree, transformation

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Authors: Fentahun Ayu Muche

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This review investigates the application of digital twin technology in 3D-printed concrete (3DPC) structures, with a primary focus on the early-age behavior of concrete. The integration of digital twins into 3DPC construction holds significant promise for monitoring, predicting, and optimizing structural performance during critical early stages, such as curing and setting. Digital twin technology integrates a range of advanced systems, including 3D modeling, machine learning, physical modeling, simulation technologies, communication technologies, and IOT. 3DPC, an additive manufacturing (AM) technology, constructs concrete structures layer by layer without deformation. The process begins with the mixer tank, pump, and nozzle system. Compared to traditional concrete construction methods, 3DPC offers numerous advantages, such as enhanced design flexibility, material efficiency, faster construction speed, reduced costs, higher quality, minimal material wastage, and elimination of formwork, reduced errors, and decreased labor requirements. Concrete, the most widely used construction material globally, is composed of materials such as cement, aggregates, admixtures, additives, supplementary cementitious materials (SCMs), fibers, and geopolymer components. At early ages, properties such as fresh state behavior, mechanical characteristics, hydration processes, microstructure, and chemical properties are particularly critical. This paper synthesizes current research, identifies key challenges, and highlights future directions in the evolving field of digital twins in 3DPC, emphasizing their transformative potential for advancing construction technologies.

Keywords: digital twin, 3DCP, concrete, early age properties, material composition

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Authors: H. Kiani, S. Moradi, B. Soltani Soulgani, S. Mousavian

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Desalting/dehydration plants (DDP) are often installed in crude oil production units in order to remove water-soluble salts from an oil stream. In order to optimize this process, desalting unit should be modeled. In this research, artificial neural network is used to model efficiency of desalting unit as a function of input parameter. The result of this research shows that the mentioned model has good agreement with experimental data.

Keywords: desalting unit, crude oil, neural networks, simulation, recovery, separation

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Authors: Rajiv Kumar, Amit Sachan, Arindam Mukherjee

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Despite the transparency and benefits of e-government, and its potential to serve citizens better, there is low diffusion and adoption of e-government services in India. Limited access to computer and internet, lack of computer and internet skills, low trust in technology, and risk associated in using e-government services are major hindrances in e-government adoption in India. Despite a large number of citizens belonging to the non-adopter category, the government has made some services mandatory to be accessed online where citizens have no other choice. Also despite the digital divide, a large number of citizens prefer online access to government services. In such cases intermediaries like common service centers, internet café and services agents’ roles are significant for accessing e-government services. Hence research is needed to explore this. The study aims to investigate the role of intermediaries in online access to public services by citizens. Qualitative research methodology using semi-structured interview was used. The results show that intermediaries play an important role in bridging the digital divide. The study also highlights on what circumstances citizens are taking help of these intermediaries. The study then highlights its limitations and discusses scope for future study.

Keywords: adoption, digital divide, e-government, India, intermediaries

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Authors: F. Amin, S. Feizi

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Big data has the potential to improve the quality of services; enable infrastructure that businesses depend on to adapt continually and efficiently; improve the performance of employees; help organizations better understand customers; and reduce liability risks. Analytics and marketing models of fixed and mobile operators are falling short in combating churn and declining revenue per user. Big Data presents new method to reverse the way and improve profitability. The benefits of Big Data and next-generation network, however, are more exorbitant than improved customer relationship management. Next generation of networks are in a prime position to monetize rich supplies of customer information—while being mindful of legal and privacy issues. As data assets are transformed into new revenue streams will become integral to high performance.

Keywords: big data, next generation networks, network transformation, strategy

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Authors: Pedram Saadati, Zahra Nazari

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Anticipating and identifying future opportunities and challenges facing industry activists for the emergence and entry of new knowledge and technologies of personal financial planning, and providing practical solutions is one of the goals of this research. For this purpose, a future research tool based on receiving opinions from the main players of the insurance industry has been used. The research method in this study was in 4 stages; including 1- a survey of the specialist salesforce of life insurance in order to identify the variables 2- the ranking of the variables by experts selected by a researcher-made questionnaire 3- holding a panel of experts with the aim of understanding the mutual effects of the variables and 4- statistical analyzes of the mutual effects matrix in Mick Mac software is done. The integrated analysis of influencing variables in the future has been done with the method of Structural Analysis, which is one of the efficient and innovative methods of future research. A list of opportunities and challenges was identified through a survey of best-selling life insurance representatives who were selected by snowball sampling. In order to prioritize and identify the most important issues, all the issues raised were sent to selected experts who were selected theoretically through a researcher-made questionnaire. The respondents determined the importance of 36 variables through scoring, so that the prioritization of opportunity and challenge variables can be determined. 8 of the variables identified in the first stage were removed by selected experts, and finally, the number of variables that could be examined in the third stage became 28 variables, which, in order to facilitate the examination, were divided into 6 categories, respectively, 11 variables of organization and management. Marketing and sales 7 cases, social and cultural 6 cases, technological 2 cases, rebranding 1 case and insurance 1 case were divided. The reliability of the researcher-made questionnaire was confirmed with the Cronbach's alpha test value of 0.96. In the third stage, by forming a panel consisting of 5 insurance industry experts, the consensus of their opinions about the influence of factors on each other and the ranking of variables was entered into the matrix. The matrix included the interrelationships of 28 variables, which were investigated using the structural analysis method. By analyzing the data obtained from the matrix by Mic Mac software, the findings of the research indicate that the categories of "correct training in the use of the software, the weakness of the technology of insurance companies in personalizing products, using the approach of equipping the customer, and honesty in declaring no need Customer to Insurance", the most important challenges of the influencer and the categories of "salesforce equipping approach, product personalization based on customer needs assessment, customer's pleasant experience of being consulted with consulting robots, business improvement of the insurance company due to the use of these tools, increasing the efficiency of the issuance process and optimal customer purchase" were identified as the most important opportunities for influence.

Keywords: personal financial planning, wealth management, advisor robots, life insurance, digital transformation

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Authors: Tonderai Muchenje, Xolani Mkhwanazi

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Precision agriculture uses a number of technologies, devices, protocols, and computing paradigms to optimize agricultural processes. Big data, artificial intelligence, cloud computing, and edge computing are all used to handle the huge amounts of data generated by precision agriculture. However, precision agriculture is still emerging and has a low level of security features. Furthermore, future solutions will demand data availability and accuracy as key points to help farmers, and security is important to build robust and efficient systems. Since precision agriculture comprises a wide variety and quantity of resources, security addresses issues such as compatibility, constrained resources, and massive data. Moreover, conventional protection schemes used in the traditional internet may not be useful for agricultural systems, creating extra demands and opportunities. Therefore, this paper aims at reviewing state of the art of precision agriculture security, particularly in open field agriculture, discussing its architecture, describing security issues, and presenting the major challenges and future directions.

Keywords: precision agriculture, security, IoT, EIDE

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Authors: Rania Jradi, Christophe Marvillet, Mohamed Razak Jeday

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One of the most frequently encountered problems in industrial heat exchangers is fouling, which degrades the thermal and hydraulic performances of these types of equipment, leading thus to failure if undetected. And it occurs due to the accumulation of undesired material on the heat transfer surface. So, it is necessary to know about the heat exchanger fouling dynamics to plan mitigation strategies, ensuring a sustainable and safe operation. This paper proposes an Artificial Neural Network (ANN) approach to estimate the fouling resistance in a cross-flow heat exchanger by the collection of the operating data of the phosphoric acid concentration loop. The operating data of 361 was used to validate the proposed model. The ANN attains AARD= 0.048%, MSE= 1.811x10⁻¹¹, RMSE= 4.256x 10⁻⁶ and r²=99.5 % of accuracy which confirms that it is a credible and valuable approach for industrialists and technologists who are faced with the drawbacks of fouling in heat exchangers.

Keywords: cross-flow heat exchanger, fouling, estimation, phosphoric acid concentration loop, artificial neural network approach

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Authors: Mohammad A. Alia

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With the rapid evolution of the internet applications, cloud computing becomes one of today’s hottest research areas due to its ability to reduce costs associated with computing. Cloud is, therefore, increasing flexibility and scalability for computing services in the internet. Cloud computing is Internet based computing due to shared resources and information which are dynamically delivered to consumers. As cloud computing share resources via the open network, hence cloud outsourcing is vulnerable to attack. Therefore, this paper will explore data security of cloud computing by implementing chaotic cryptography. The proposal scenario develops a problem transformation technique that enables customers to secretly transform their information. This work proposes the chaotic cryptographic algorithms have been applied to enhance the security of the cloud computing accessibility. However, the proposed scenario is secure, easy and straightforward process. The chaotic encryption and digital signature systems ensure the security of the proposed scenario. Though, the choice of the key size becomes crucial to prevent a brute force attack.

Keywords: chaos, cloud computing, security, cryptography

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Authors: Laura Naka

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The invention of computer writing programs has changed the way of teaching second language writing. This artificial intelligence engine can provide students with feedback on their essays, on their grammatical and spelling errors, convenient writing and editing tools to facilitate student’s writing process. However, it is not yet proved if this technology is helping students to improve their writing skills. There are several programs that are of great assistance for students concerning their writing skills. New technology provides students with different software programs which enable them to be more creative, to express their opinions and ideas in words, pictures and sounds, but at the end main and most correct feedback should be given by their teachers. No matter how new technology affects in writing skills, always comes from their teachers. This research will try to present some of the advantages and disadvantages that new technology has in writing process for students. The research takes place in the University of Gjakova ‘’Fehmi Agani’’ Faculty of Education-Preschool Program. The research aims to provide random sample response by using questionnaires and observation.

Keywords: English language learning, technology, academic writing, teaching L2.

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Authors: Manuela Nayantara Jeyaraj

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Having moved into the 21^st century, it is way past being arguable that innovative technology needs to be incorporated into conventional classroom teaching. Though the Western world has found presumable success in achieving this, it is still a concept under battle in developing countries such as Sri Lanka. Reaching the acme of implementing interactive virtual learning within classrooms is a struggling idealistic fascination within the island. In order to overcome this problem, this study is set to reveal facts that limit the implementation of virtual, interactive learning within the school classrooms and provide hacks that could prove the augmented use of the Virtual World to enhance teaching and learning experiences. As each classroom moves along with the usage of technology to fulfill its functionalities, a few intense hacks provided will build the administrative onuses on a virtual system. These hacks may divulge barriers based on social conventions, financial boundaries, digital literacy, intellectual capacity of the staff, and highlight the impediments in introducing students to an interactive virtual learning environment and thereby provide the necessary actions or changes to be made to succeed and march along in creating an intellectual society built on virtual learning and lifestyle. This digital learning environment will be composed of multimedia presentations, trivia and pop quizzes conducted on a GUI, assessments conducted via a virtual system, records maintained on a database, etc. The ultimate objective of this study could enhance every child's basic learning environment; hence, diminishing the digital divide that exists in certain communities.

Keywords: digital divide, digital learning, digitization, Sri Lanka, teaching methodologies

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Authors: Anastasis Petrou

Abstract:

Black Swan Theories (BSTs) have existed since the 2nd Century BC. However, problematisation in the interdisciplinary field of Public Administration and Informatics (PA&I) about the impact of Black Swans as rare events in Society is a more recent phenomenon but with a growing, although dispersed, body of research literature. This paper offers a synopsis of core issues and questions raised in PA&I literature about the impacts of rare events in Society, the need for knowledge accumulation and explainability processes about rare events and asks what could help explain the occurrence, severity, heterogeneity, overall impact of Black Swans and the challenges they represent to established scientific methods. The second part of the paper considers how the use of Artificial Intelligence (AI) could assist researchers in better explaining rare events in PA&I. However, the research shows that whilst AI use at the start of knowledge accumulation and explainability processes about rare events is beneficial it is also fraught with challenges discussed herein. The paper concludes with recommendations for future research.

Keywords: black swans, public administration, AI, informatics

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Authors: Yu-Chen Hsu, Kuang C. Lin

Abstract:

The artificial lung called extracorporeal membrane oxygenation (ECMO) is an important medical machine that supports persons whose heart and lungs dysfunction. Previously, investigation of steady deoxygenated blood flows passing through hollow fibers for oxygen transport was carried out experimentally and computationally. The present study computationally analyzes the effect of biological pulsatile flow on the oxygen transport in blood. A 2-D model with a pulsatile flow condition is employed. The power law model is used to describe the non-Newtonian flow and the Hill equation is utilized to simulate the oxygen saturation of hemoglobin. The dimensionless parameters for the physical model include Reynolds numbers (Re), Womersley parameters (α), pulsation amplitudes (A), Sherwood number (Sh) and Schmidt number (Sc). The present model with steady-state flow conditions is well validated against previous experiment and simulations. It is observed that pulsating flow amplitudes significantly influence the velocity profile, pressure of oxygen (PO2), saturation of oxygen (SO2) and the oxygen mass transfer rates (m ̇_O2). In comparison between steady-state and pulsating flows, our findings suggest that the consideration of pulsating flow in the computational model is needed when Re is raised from 2 to 10 in a typical range for flow in artificial lung.

Keywords: artificial lung, oxygen transport, non-Newtonian flows, pulsating flows

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Authors: Esmaeil Biazar

Abstract:

A nanofibrous PHBV nerve conduit has been used to evaluate its efficiency based on the promotion of nerve regeneration in rats. The designed conduits were investigated by physical, mechanical and microscopic analyses. The conduits were implanted into a 30-mm gap in the sciatic nerves of the rats. Four months after surgery, the regenerated nerves were evaluated by macroscopic assessments and histology. This polymeric conduit had sufficiently high mechanical properties to serve as a nerve guide. The results demonstrated that in the nanofibrous graft with cells, the sciatic nerve trunk had been reconstructed with restoration of nerve continuity and formatted nerve fibers with myelination. For the grafts especially the nanofibrous conduits with cells, muscle cells of gastrocnemius on the operated side were uniform in their size and structures. This study proves the feasibility of artificial conduit with Schwann cells for nerve regeneration by bridging a longer defect in a rat model.

Keywords: sciatic regeneration, Schwann cell, artificial conduit, nanofibrous PHBV, histological assessments

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Authors: Dong Tianxiang

Abstract:

In the context of the era of rural revitalization, rural land is popular for more and more active, and its process has been widely concerned by all walks of life. By analyzing and summarizing the actual situation of land transfer, the author found that land transfer has such problems as ambiguous land transfer benefit subjects, decentralized and disorderly land transfer forms, lack of guarantee system for land transfer, and land transfer affecting food production. Based on the above problems, the author first analyzes the specific situation of land transfer in the study area with relevant econometric models and ArcGIS spatial analysis methods and analyzes its causes to construct a positive role mechanism of land use transformation on land transfer.

Keywords: land transfer, land use, rural revitalization, population loss

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Authors: Mustafa Var, Yasin Kültiğin Yaman, Elif Berna Var, Müberra Pulatkan

Abstract:

This study deals with real application of an urban transformation project in Trabzon, Turkey. It aims to highlight the significance of using native species in terms of planting design of transformation projects which will also promote sustainability of urban identity. Urban identity is a phenomenon shaped not only by physical, but also by natural, spatial, social, historical and cultural factors. Urban areas face with continuous change which can be whether positive or negative way. If it occurs in a negative way that may have some destructive effects on urban identity. To solve this problematic issue, urban renewal movements initally started after 1840s around the world especially in the cities with ports. This process later followed by the places where people suffered a lot from fires and has expanded to all over the world. In Turkey, those processes have been experienced mostly after 1980s as country experienced the worst effects of unplanned urbanization especially in 1950-1990 period. Also old squares, streets, meeting points, green areas, Ottoman bazaars have changed slowly. This change was resulted in alienation of inhabitants to their environments. As a solution, several actions were taken like Mass Housing Laws which was enacted in 1981 and 1984 or urban transformation projects. Although projects between 1990-2000 were tried to satisfy the expectations of local inhabitants by the help of several design solutions to promote cultural identity; unfortunately those modern projects has also been resulted in alienation of urban environments to the inhabitants. Those projects were initially done by TOKI (Housing Development Administration of Turkey) and later followed by the Ministry of Environment and Urbanization after 2011. Although they had significant potentials to create healthy urban environments, they could not use this opportunity in an effective way. The reason for their failure is that their architectural styles and planting designs are unrespectful to local identity and environments. Generally, it can be said that the most of the urban transformation projects implementing in Turkey nearly have no concerns about the locality. However, those projects can be used as a positive tool for enhanching the urban identity of cities by means of local planting material. For instance, Kyoto can be identified by Japanese Maple trees or Seattle can be specified by Dahlia. In the same way, in Turkey, Istanbul city can be identified by Judas and Stone Pine trees or Giresun city can be identified by Cherry trees. Thus, in this paper, the importance of conserving urban identity is discussed specificly with the help of using local planting elements. After revealing the mistakes that are made during urban transformation projects, the techniques and design criterias for preserving and promoting urban identity are examined. In the end, it is emphasized that every city should have their own original, local character and specific planting design which can be used for highlighting its identity as well as architectural elements.

Keywords: urban identity, urban transformation, planting design, landscape architecture

Procedia PDF Downloads 548