Search results for: digital transformation artificial intelligence

Authors: Andrea Treviño Gavito, Diego Klabjan, Sanjiv J. Shah

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Echocardiograms serve as pivotal resources for clinicians in diagnosing cardiac conditions, offering non-invasive insights into a heart’s structure and function. When echocardiographic studies are conducted, no standardized labeling of the acquired views is performed. Employing machine learning algorithms for automated echocardiogram view detection has emerged as a promising solution to enhance efficiency in echocardiogram use for diagnosis. However, existing approaches predominantly rely on supervised learning, necessitating labor-intensive expert labeling. In this paper, we introduce a fully unsupervised echocardiographic view detection framework that leverages convolutional autoencoders to obtain lower dimensional representations and the K-means algorithm for clustering them into view-related groups. Our approach focuses on discriminative patches from echocardiographic frames. Additionally, we propose a trainable inverse average layer to optimize decoding of average operations. By integrating both public and proprietary datasets, we obtain a marked improvement in model performance when compared to utilizing a proprietary dataset alone. Our experiments show boosts of 15.5% in accuracy and 9.0% in the F-1 score for frame-based clustering, and 25.9% in accuracy and 19.8% in the F-1 score for view-based clustering. Our research highlights the potential of unsupervised learning methodologies and the utilization of open-sourced data in addressing the complexities of echocardiogram interpretation, paving the way for more accurate and efficient cardiac diagnoses.

Keywords: artificial intelligence, echocardiographic view detection, echocardiography, machine learning, self-supervised representation learning, unsupervised learning

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Authors: Muhammad Awais Kiani, Maryam Kiani

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In today's digital age, the field of electronics engineering is experiencing unprecedented growth and innovation. To keep pace with this rapidly evolving industry, effective sales and marketing strategies are crucial, especially when combined with the power of e-commerce. This study explores the significance of integrating sales and marketing techniques with e-commerce platforms in the context of electronics engineering. It highlights the benefits, challenges, and best practices in leveraging e-commerce for sales and marketing in this industry. By embracing e-commerce, electronics engineering companies can reach a wider customer base, enhance brand visibility, and personalize customer experiences. Furthermore, this abstract delves into the importance of utilizing digital marketing tools such as search engine optimization (SEO), social media marketing, and content creation to optimize online sales. Therefore, this research aims to provide insights and recommendations for electronics engineering professionals to effectively navigate the dynamic landscape of sales and marketing in conjunction with e-commerce.

Keywords: electronics engineering, marketing, sales, E-commerce

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Authors: Elvin Karaaslan Klose

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Museums are important sites of informal, often semi-structured and self-paced learning. Challenged by digital alternatives and increased expectations from their visitors, museums have to adapt to the digital age by enriching their collection and educational content with additional options for interactivity. One such option lies in the concept of the electronic book, which can be used either on dedicated devices or downloaded by visitors before entering the exhibition area. These electronic books serve as an alternative or supplement to the classic audio guide and provide visitors with information about artifacts as well as background stories and factoids about the subjects of the exhibition. Bringing such interactive elements into the museum experience has been shown to increase information retention and enjoyment among young aged visitors and adults. This article aims to bring together both theoretical frameworks and practical examples of how interactive media in the form of electronic books can be used to enhance the experience of the museum visitor.

Keywords: electronic books, interactive media, arts education, museum education

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Authors: Noriyuki Suyama

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The progress and spread of digitalization have led to the provision of a variety of new services. The recent progress in digitization can be attributed to rapid developments in science and technology. First, the research and diffusion of artificial intelligence (AI) has made dramatic progress. Around 2000, the third wave of AI research, which had been underway for about 50 years, arrived. Specifically, machine learning and deep learning were made possible in AI, and the ability of AI to acquire knowledge, define the knowledge, and update its own knowledge in a quantitative manner made the use of big data practical even for commercial PCs. On the other hand, with the spread of social media, information exchange has become more common in our daily lives, and the lending and borrowing of goods and services, in other words, the sharing economy, has become widespread. The scope of this trend is not limited to any industry, and its momentum is growing as the SDGs take root. In addition, the Social Network Service (SNS), a part of social media, has brought about the evolution of the retail business. In the past few years, social network services (SNS) involving users or companies have especially flourished. The People's Republic of China (hereinafter referred to as "China") is a country that is stimulating enormous consumption through its own unique SNS, which is different from the SNS used in developed countries around the world. This paper focuses on the effectiveness and challenges of influencer marketing by focusing on the influence of influencers on users' behavior and satisfaction with Chinese SNSs. Specifically, Conducted was the quantitative survey of Tik Tok users living in China, with the aim of gaining new insights from the analysis and discussions. As a result, we found several important findings and knowledge.

Keywords: customer satisfaction, social networking services, influencer marketing, Chinese consumers’ behavior

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Authors: Min Jindong, Wang Mingxia

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With the widespread use of artificial intelligence in life, computer vision, especially deep convolutional neural network models, has developed rapidly. With the increase of the complexity of the real visual target detection task and the improvement of the recognition accuracy, the target detection network model is also very large. The huge deep neural network model is not conducive to deployment on edge devices with limited resources, and the timeliness of network model inference is poor. In this paper, knowledge distillation is used to compress the huge and complex deep neural network model, and the knowledge contained in the complex network model is comprehensively transferred to another lightweight network model. Different from traditional knowledge distillation methods, we propose a novel knowledge distillation that incorporates multi-faceted features, called M-KD. In this paper, when training and optimizing the deep neural network model for target detection, the knowledge of the soft target output of the teacher network in knowledge distillation, the relationship between the layers of the teacher network and the feature attention map of the hidden layer of the teacher network are transferred to the student network as all knowledge. in the model. At the same time, we also introduce an intermediate transition layer, that is, an intermediate guidance layer, between the teacher network and the student network to make up for the huge difference between the teacher network and the student network. Finally, this paper adds an exploration module to the traditional knowledge distillation teacher-student network model. The student network model not only inherits the knowledge of the teacher network but also explores some new knowledge and characteristics. Comprehensive experiments in this paper using different distillation parameter configurations across multiple datasets and convolutional neural network models demonstrate that our proposed new network model achieves substantial improvements in speed and accuracy performance.

Keywords: object detection, knowledge distillation, convolutional network, model compression

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Authors: M. Khajezadeh, M. Saied Fallah Niasar, S. Ali Asli, D. Davani Davari, M. Godarzi, Y. Asgari

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This study aims to explore the joint application of both Boston and Ansoff matrices in the operational development of the product. We conduct deep analysis, by utilizing the Artificial Neural Network, to predict the position of the product in the market while the company is interested in increasing its share. The data are gathered from two industries, called hygiene and detergent. In doing so, the effort is being made by investigating the behavior of top player companies and, recommend strategic orientations. In conclusion, this combination analysis is appropriate for operational development; as well, it plays an important role in providing the position of the product in the market for both hygiene and detergent industries. More importantly, it will elaborate on the company’s strategies to increase its market share related to a combination of the Boston Consulting Group (BCG) Matrix and Ansoff Matrix.

Keywords: artificial neural network, portfolio analysis, BCG matrix, Ansoff matrix

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Authors: Attila Kiss, Erzsébet Némedi, Zoltán Naár

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Due to the rapidly growing number of conscious customers in the recent years, more and more people look for products with positive physiological effects which may contribute to the preservation of their health. In response to these demands Food Science Research Institute of Budapest develops and introduces into the market new functional foods of guaranteed positive effect that contain bioactive agents. New, efficient technologies are also elaborated in order to preserve the maximum biological effect of the produced foods. The main objective of our work was the development of new functional biscuits fortified with physiologically beneficial ingredients. Bakery products constitute the base of the food nutrients’ pyramid, thus they might be regarded as foodstuffs of the largest consumed quantity. In addition to the well-known and certified physiological benefits of lysine, as an essential amino acid, a series of antioxidant type compounds is formed as a consequence of the occurring Maillard-reaction. Progress of the evoked Maillard-reaction was studied by applying diverse sugars (glucose, fructose, saccharose, isosugar) and lysine at several temperatures (120-170°C). Interval of thermal treatment was also varied (10-30 min). The composition and production technologies were tailored in order to reach the maximum of the possible biological benefits, so as to the highest antioxidant capacity in the biscuits. Out of the examined sugar components, theextent of the Maillard-reaction-driven transformation of glucose was the most pronounced at both applied temperatures. For the precise assessment of the antioxidant activity of the products FRAP and DPPH methods were adapted and optimised. To acquire an authentic and extensive mechanism of the occurring transformations, Maillard-reaction products were identified, and relevant reaction pathways were revealed. GC-MS and HPLC-MS techniques were applied for the analysis of the 60 generated MRPs and characterisation of actual transformation processes. 3 plausible major transformation routes might have been suggested based on the analytical result and the deductive sequence of possible occurring conversions between lysine and the sugars.

Keywords: Maillard-reaction, lysine, antioxidant activity, GC-MS and HPLC-MS techniques

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Authors: Nattapong Techarattanased

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The objectives of this research were to study the influence of market orientation and supply chain management on competitive capability in case of the automotive parts industry in Thailand. This study employed by survey research and questionnaire was used to collect the data from 400 entrepreneurs in the automotive parts industry in Thailand. The descriptive statistics and multiple regression analysis were used to analyze data. The results revealed that the overall dimensions of marketing orientation, namely, responsiveness, intelligence generation, and intelligence dissemination were rated at the high level. As well, the overall dimensions of supply chain management, namely, collaboration, communication, trust, and commitment were also rated at the high level. Furthermore, the hypothesis testing results showed that supply chain management and market orientation affected competitive capability of the automotive parts industry in Thailand which these two variables could be combined to predict competitive capability of the automotive parts industry in Thailand by 31.5 percent.

Keywords: automotive parts industry, competitive capability, market orientation, supply chain management

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Authors: Sevim Ugur, Cemile Kutmec Yilmaz, Omer Us, Sevdenur Koksaldi

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Aim: This study aims to investigate the effect of digital game playing and Internet addiction on perceived stress levels in university students. Method: The descriptive study was conducted through face-to-face interview method with a total of 364 university students studying at Aksaray University between November 15 and December 30, 2017. The research data were collected using personal information form, a questionnaire to determine the characteristics of playing digital game, the Internet addiction scale and the perceived stress scale. In the evaluation of the data, Mann-Whitney U test was used for two-group comparison of the sample with non-normal distribution, Kruskal-Wallis H-test was used in the comparison of more than two groups, and the Spearman correlation test was used to determine the relationship between Internet addiction and the perceived stress level. Results: It was determined that the mean age of the students participated in the study was 20.13 ± 1.7 years, 67.6% was female, 35.7% was sophomore, and 62.1% had an income 500 TL or less. It was found that 83.5% of the students use the Internet every day and 70.6% uses the Internet for 5 hours or less per day. Of the students, 12.4% prefers digital games instead of spending time outdoors, 8% plays a game as the first activity in leisure time, 12.4% plays all day, 15.7% feels anger when he/she is prevented from playing, 14.8% prefers playing games to get away from his/her problems, 23.4% had his/her school achievement affected negatively because of game playing, and 8% argues with family members due to the time spent for gaming. Students who play games on the computer for a long time were found to feel back pain (30.8%), headache (28.6%), insomnia (26.9%), dryness and pain in the eyes (26.6%), pain in the wrist (21.2%), feeling excessive tension and anger (16.2%), humpback (12.9), vision loss (9.6%) and pain in the wrist and fingers (7.4%). In our study, students' Internet addiction scale mean score was found to be 45.47 ± 16.1 and mean perceived stress scale score was 28.56 ± 2.7. A significant and negative correlation (p=0.037) was found between the total score of the Internet addiction scale and the total score of the perceived stress scale (r=-0.110). Conclusion: It was found in the study that Internet addiction and perceived stress of the students were at a moderate level and that there was a negative correlation between Internet addiction and perceived stress levels. Internet addiction was found to increase with the increasing perceived stress levels of students, and students were found to have health problems such as back pain, dryness in the eyes, pain, insomnia, headache, and humpback. Therefore, it is recommended to inform students about different coping methods other than spending time on the Internet to cope with the stress they perceive.

Keywords: digital game, internet addiction, student, stress level

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Authors: Robert L. Fine, Zhiyong Yang, Christy Spivey, Bonnie Boardman, Maureen Courtney

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Importance: Barriers to traditional advance care planning (ACP) and advance directive (AD) creation have limited the promise of ACP/AD for individuals and families, the healthcare team, and society. Reengineering ACP by using a web-based, consumer-driven process has recently been suggested. We report early experience with such a process. Objective: Begin to analyze the potential of the creation and use of ACP/ADs as generated by a consumer-friendly, digital process by 1) assessing the likelihood that consumers would create ACP/ADs without structured intervention by medical or legal professionals, and 2) analyzing the responses to determine if the plans can help doctors better understand a person’s goals, preferences, and priorities for their medical treatments and the naming of healthcare agents. Design: The authors chose 900 users of MyDirectives.com, a digital ACP/AD tool, solely based on their state of residence in order to achieve proportional representation of all 50 states by population size and then reviewed their responses, summarizing these through descriptive statistics including treatment preferences, demographics, and revision of preferences. Setting: General United States population. Participants: The 900 participants had an average age of 50.8 years (SD = 16.6); 84.3% of the men and 91% of the women were in self-reported good health when signing their ADs. Main measures: Preferences regarding the use of life-sustaining treatments, where to spend final days, consulting a supportive and palliative care team, attempted cardiopulmonary resuscitation (CPR), autopsy, and organ and tissue donation. Results: Nearly 85% of respondents prefer cessation of life-sustaining treatments during their final days whenever those may be, 76% prefer to spend their final days at home or in a hospice facility, and 94% wanted their future doctors to consult a supportive and palliative care team. 70% would accept attempted CPR in certain limited circumstances. Most respondents would want an autopsy under certain conditions, and 62% would like to donate their organs. Conclusions and relevance: Analysis of early experience with an all-digital web-based ACP/AD platform demonstrates that individuals from a wide range of ages and conditions can engage in an interrogatory process about values, goals, preferences, and priorities for their medical treatments by developing advance directives and easily make changes to the AD created. Online creation, storage, and retrieval of advance directives has the potential to remove barriers to ACP/AD and, thus, to further improve patient-centered end-of-life care.

Keywords: Advance Care Plan, Advance Decisions, Advance Directives, Consumer; Digital, End of Life Care, Goals, Living Wills, Prefences, Universal Advance Directive, Statements

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Authors: Raghava Dhanya, Shashank S.

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This paper delves into the intersection of chess and computer science, specifically focusing on the efficient representation of chess game states. We propose two methods: the Static Method and the Dynamic Method, each offering unique advantages in terms of space efficiency and computational complexity. The Static Method aims to represent the game state using a fixedlength encoding, allocating 192 bits to capture the positions of all pieces on the board. This method introduces a protocol for ordering and encoding piece positions, ensuring efficient storage and retrieval. However, it faces challenges in representing pieces no longer in play. In contrast, the Dynamic Method adapts to the evolving game state by dynamically adjusting the encoding length based on the number of pieces in play. By incorporating Alive Bits for each piece kind, this method achieves greater flexibility and space efficiency. Additionally, it includes provisions for encoding additional game state information such as castling rights and en passant squares. Our findings demonstrate that the Dynamic Method offers superior space efficiency compared to traditional Forsyth-Edwards Notation (FEN), particularly as the game progresses and pieces are captured. However, it comes with increased complexity in encoding and decoding processes. In conclusion, this study provides insights into optimizing the representation of chess game states, offering potential applications in chess engines, game databases, and artificial intelligence research. The proposed methods offer a balance between space efficiency and computational overhead, paving the way for further advancements in the field.

Keywords: chess, optimisation, encoding, bit manipulation

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Authors: Julianne Viola

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Young people are at a critical stage in their lives, developing from young participants to adult participants in democratic society. At this time, civic engagement is crucial for young people’s sense of belonging and future participation in their communities. In adolescence, individuals form their own identities and associations with others and may accomplish this with the help of technology and social media. In the Digital Age, young people and adults use technology as a platform to discuss political issues, including human rights and social justice but do not always engage in civil discourse. There is an urgent need to investigate this complex interplay of social media, identity formation, and civil discourse as it relates to how teenagers become participants in democratic society and how they engage in civil discourse. This qualitative study draws on theories of identity formation in adolescence and is situated within the literature surrounding teen civic engagement and technology use. Through in-depth interviews with participants ages 14 through 17, this study investigates the ways in which teens conceptualize their civic identities and engagement, presence online, and civil discourse. The context in which the young people in this study have grown up has the potential to impact and inform these processes. Early results of this study illustrate what it means to be a young person in today’s world, and how perceptions of others’ opinions may influence young people’s engagement in their communities and online. Participants in this study often indicated concerns of their age as a constraint on participation in their communities and in society, and a self-imposed restriction around the people with whom they engage in conversation about political and social issues. While the participants shared common concerns and experiences, each participant’s unique perspectives and beliefs are viewed with equal importance. The results from this research will help students, teachers, and community groups learn about the reasons for engagement and disengagement among this age group, and how technology has influenced teens’ dialogue about political issues. With this knowledge, academics and school leaders can devise new ways to best teach citizenship skills and civil discourse to students in the Digital Age.

Keywords: civics, digital age, discourse, sociology of youth, youth studies

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Authors: Ashkan Zakaryazad, Ekrem Duman

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A typical classification technique ranks the instances in a data set according to the likelihood of belonging to one (positive) class. A credit card (CC) fraud detection model ranks the transactions in terms of probability of being fraud. In fact, this approach is often criticized, because firms do not care about fraud probability but about the profitability or costliness of detecting a fraudulent transaction. The key contribution in this study is to focus on the profit maximization in the model building step. The artificial neural network proposed in this study works based on profit maximization instead of minimizing the error of prediction. Moreover, some studies have shown that the back propagation algorithm, similar to other gradient–based algorithms, usually gets trapped in local optima and swarm-based algorithms are more successful in this respect. In this study, we train our profit maximization ANN using the Migrating Birds optimization (MBO) which is introduced to literature recently.

Keywords: neural network, profit-based neural network, sum of squared errors (SSE), MBO, gradient descent

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Authors: Hanbey Hazar, Hakan Gul

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In this study; piston, exhaust, and suction valves of a diesel engine were coated in 300 mm thickness with Tungsten Carbide (WC) by using the HVOF coating method. Mathematical modeling of a coated and uncoated (standardized) engine was performed by using ANN (Artificial Neural Networks). The purpose was to decrease the number of repetitions of tests and reduce the test cost through mathematical modeling of engines by using ANN. The results obtained from the tests were entered in ANN and therefore engines' values at all speeds were estimated. Results obtained from the tests were compared with those obtained from ANN and they were observed to be compatible. It was also observed that, with thermal barrier coating, hydrocarbon (HC), carbon monoxide (CO), and smoke density values of the diesel engine decreased; but nitrogen oxides (NOx) increased. Furthermore, it was determined that results obtained through mathematical modeling by means of ANN reduced the number of test repetitions. Therefore, it was understood that time, fuel and labor could be saved in this way.

Keywords: Artificial Neural Network, Diesel Engine, Mathematical Modelling, Thermal Barrier Coating

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Authors: Richard W. Jelier

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This research examines the emergence of the knowledge-based economies in three world cities in a comparative context. The Australian, American and British approaches to (KBE) are analyzed through the study of three premier world cities of Sydney, New York and London. Long considered leaders in the KBE, London and New York’s pre-imminence in this race to the top is not surprising. Sydney, Australia however has seen a remarkable transformation from an old economy to an emerging success in the new economy. After an examination of national KBE indicators (GDP comparisons and Knowledge Economy indexes) the research turns to a detailed investigation of specific strategies advanced in greater Sydney, New York City and London to advance the creative sector and compete for a spot among the world leaders in the knowledge age. These intense efforts at restructuring national and local economies have led to increasingly intense competition between cities and nations and there are clear winners and losers. Overall the conclusion of this research suggests that as Australia is rising, America is struggling to keep its position as a global world leader in the new economy. London’s urban primacy has helped elevate it role in the UK new economy and recent transformations have led London to compete successfully with New York City for the top position as the premier global city.

Keywords: knowledge-based economy, knowledge economy indexes, sustainable transformation, creative economies, New York, London and Sydney

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Authors: Javad Abdi, Azam Famil Khalili

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Modeling emotions have attracted much attention in recent years, both in cognitive psychology and design of artificial systems. However, it is a negative factor in decision-making; emotions have shown to be a strong faculty for making fast satisfying decisions. In this paper, we have adapted a computational model based on the limbic system in the mammalian brain for control engineering applications. Learning in this model based on Temporal Difference (TD) Learning, we applied the proposed controller (termed BELBIC) for a simple model of a submarine. The model was supposed to reach the desired depth underwater. Our results demonstrate excellent control action, disturbance handling, and system parameter robustness for TDBELBIC. The proposal method, regarding the present conditions, the system action in the part and the controlling aims, can control the system in a way that these objectives are attained in the least amount of time and the best way.

Keywords: artificial neural networks, temporal difference, brain emotional learning based intelligent controller, heating- ventilating and air conditioning

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Authors: Bliss Singhal

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Machine learning (ML) is a branch of Artificial Intelligence (AI) where computers analyze data and find patterns in the data. The study focuses on the detection of metastatic cancer using ML. Metastatic cancer is the stage where cancer has spread to other parts of the body and is the cause of approximately 90% of cancer-related deaths. Normally, pathologists spend hours each day to manually classifying whether tumors are benign or malignant. This tedious task contributes to mislabeling metastasis being over 60% of the time and emphasizes the importance of being aware of human error and other inefficiencies. ML is a good candidate to improve the correct identification of metastatic cancer, saving thousands of lives and can also improve the speed and efficiency of the process, thereby taking fewer resources and time. So far, the deep learning methodology of AI has been used in research to detect cancer. This study is a novel approach to determining the potential of using preprocessing algorithms combined with classification algorithms in detecting metastatic cancer. The study used two preprocessing algorithms: principal component analysis (PCA) and the genetic algorithm, to reduce the dimensionality of the dataset and then used three classification algorithms: logistic regression, decision tree classifier, and k-nearest neighbors to detect metastatic cancer in the pathology scans. The highest accuracy of 71.14% was produced by the ML pipeline comprising of PCA, the genetic algorithm, and the k-nearest neighbor algorithm, suggesting that preprocessing and classification algorithms have great potential for detecting metastatic cancer.

Keywords: breast cancer, principal component analysis, genetic algorithm, k-nearest neighbors, decision tree classifier, logistic regression

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Authors: R. Chinnaiyaprabhu, S. Bharanidharan, V. Dharsana, Rajalavanya

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The concept of the Metaverse represents a potential evolution in the realm of cyberspace. In the early stages of Web 2.0, we observed a proliferation of online pseudonyms or 'nyms,' which increased the prevalence of fake accounts and made it challenging to establish unique online identities for various roles. However, in the era of Web 3.0, particularly in the context of the Metaverse, an individual's digital identity is intrinsically linked to their real-world identity. Consequently, actions taken in the Metaverse can carry significant consequences in the physical world. In light of these considerations, we propose the development of an innovative authentication system known as 'Metasec.' This system is designed to enhance security for digital assets, online identities, avatars, and user accounts within the Metaverse. Notably, Metasec operates as a password less authentication solution, relying on a multifaceted approach to security, encompassing device attestation, facial recognition, and pattern-based security keys.

Keywords: metaverse, multifactor authentication, security, facial recognition, patten password

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Authors: Delana Theiventhiran, Wally J. Bartfay

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Background and Significance: As the Internet is becoming the epitome of modern communications, there are many pragmatic reasons why the digital divide matters in terms of accessing and using E-health based technologies. With the rise of technology usage globally, those in the older adult generation may not be as familiar and comfortable with technology usage and are thus put at a disadvantage compared to other generations such as millennials when examining and using E-health based platforms and technology. Currently, little is known about how older adults and millennials access and use e-health based technologies. Methods: A systemic review of the literature was undertaken employing the following three databases: (i) PubMed, (ii) ERIC, and (iii) CINAHL; employing the search term 'digital divide and generations' to identify potential articles. To extract required data from the studies, a data abstraction tool was created to obtain the following information: (a) author, (b) year of publication, (c) sample size, (d) country of origin, (e) design/methods, (f) major findings/outcomes obtained. Inclusion criteria included publication dates between the years of Jan 2009 to Aug 2018, written in the English language, target populations of older adults aged 65 and above and millennials, and peer reviewed quantitative studies only. Major Findings: PubMed provided 505 potential articles, where 23 of those articles met the inclusion criteria. Specifically, ERIC provided 53 potential articles, where no articles met criteria following data extraction. CINAHL provided 14 potential articles, where eight articles met criteria following data extraction. Conclusion: Practically speaking, identifying how newer E-health based technologies can be integrated into society and identifying why there is a gap with digital technology will help reduce the impact on generations and individuals who are not as familiar with technology and Internet usage. The largest concern of all is how to prepare older adults for new and emerging E-health technologies. Currently, there is a dearth of literature in this area because it is a newer area of research and little is known about it. The benefits and consequences of technology being integrated into daily living are being investigated as a newer area of research. Several of the articles (N=11) indicated that age is one of the larger factors contributing to the digital divide. Similarly, many of the examined articles (N=5) identify that privacy concerns were one of the main deterrents of technology usage for elderly individuals aged 65 and above. The older adult generation feels that privacy is one of the major concerns, especially in regards to how data is collected, used and possibly sold to third party groups by various websites. Additionally, access to technology, the Internet, and infrastructure also plays a large part in the way that individuals are able to receive and use information. Lastly, a change in the way that healthcare is currently used, received and distributed would also help attribute to the change to ensure that no generation is left behind in a technologically advanced society.

Keywords: digital divide, e-health, millennials, older adults

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Authors: Remy Kulagowski, Tobias Sturm, Audrey Leopold, Aurelie Metay, Josephine Peigne, Alexis Thoumazeau, Alain Brauman, Bruno Fogliani, Florent Tivet

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A major challenge for agriculture is to enhance productivity while limiting the impact on the environment. Conservation agriculture (CA) is one strategy whereby both sustainability and productivity can be achieved by preserving and improving the soil quality. Soils provide and regulate a large number of ecosystem services (ES) such as agricultural productivity and climate change adaptation and mitigation. The aim of this study is to assess the impacts of contrasted CA crop management on soil functions for maize (Zea mays L.) cultivation in an eight years field experiment (2010-2018). The study included two CA practices: direct seeding in dead mulch (DM) and living mulch (LM), and conventional plough-based tillage (CT) practices on a fluvisol in New Caledonia (French Archipelago in the South Pacific). In 2018, soil quality of the cropping systems were evaluated with the Biofunctool® set of indicators, that consists in twelve integrative, in-field, and low-tech indicators assessing the biological, physical and chemical properties of soils. Main soil functions were evaluated including (i) carbon transformation, (ii) structure maintenance, and (iii) nutrient cycling in the ten first soil centimeters. The results showed significant higher score for soil structure maintenance (e.g., aggregate stability, water infiltration) and carbon transformation function (e.g., soil respiration, labile carbon) under CA in DM and LM when compared with CT. Score of carbon transformation index was higher in DM compared with LM. However, no significant effect of cropping systems was observed on nutrient cycling (i.e., nitrogen and phosphorus). In conclusion, the aggregated synthetic scores of soil multi-functions evaluated with Biofunctool® demonstrate that CA cropping systems lead to a better soil functioning. Further analysis of the results with agronomic performance of the soil-crop systems would allow to better understand the links between soil functioning and production ES of CA.

Keywords: conservation agriculture, cropping systems, ecosystem services, soil functions

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Authors: Erfan Asghari Fesaghandis, Reza Ghaffari Adli, Abbas Kianvash, Hossein Aghajani, Homa Homaie

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NiTi alloys possess magnificent superelastic, shape memory, high strength and biocompatible properties. For improving mechanical properties, foremost, superelasticity behavior, heat treatment process is carried out. In this paper, two different heat treatment methods were undertaken: (1) solid solution, and (2) aging. The effect of each treatment in a constant time is investigated. Five samples were prepared to study the structure and optimize mechanical properties under different time and temperature. For measuring the upper plateau stress, lower plateau stress and residual strain, tensile test is carried out. The samples were aged at two different temperatures to see difference between aging temperatures. The sample aged at 500 °C has a bigger crystallite size and lower amount of Ni which causes the mentioned sample to possess poor pseudo elasticity behaviour than the other aged sample. The sample aged at 460 °C has shown remarkable superelastic properties. The mentioned sample’s higher plateau is 580 MPa with the lowest residual strain (0.17%) while other samples have possessed higher residual strains. X-ray diffraction was used to investigate the produced phases.

Keywords: heat treatment, phase transformation, superelasticity, NiTi alloy

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Authors: Halkiopoulos Constantinos, Gkintoni Evgenia, Koutsopoulou Ioanna, Antonopoulou Hera

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E-sports and e-gaming have emerged in recent years since the increase in internet use have become universal and e-gamers are the new reality in our homes. The excessive involvement of young adults with e-sports has already been revealed and the adverse consequences have been reported in researches in the past few years, but the issue has not been fully studied yet. The present research is conducted in Greece and studies the psychological profile of video game players and provides information on personality traits, habits and emotional status that affect online gamers’ behaviors in order to help professionals and policy makers address the problem. Three standardized self-report questionnaires were administered to participants who were young male and female adults aged from 19-26 years old. The Profile of Mood States (POMS) scale was used to evaluate people’s perceptions of their everyday life mood; the personality features that can trace back to people’s habits and anticipated reactions were measured by Eysenck Personality Questionnaire (EPQ), and the Trait Emotional Intelligence Questionnaire (TEIQue) was used to measure which cognitive (gamers’ beliefs) and emotional parameters (gamers’ emotional abilities) mainly affected/ predicted gamers’ behaviors and leisure time activities?/ gaming behaviors. Data mining techniques were used to analyze the data, which resulted in machine learning algorithms that were included in the software package R. The research findings attempt to designate the effect of personality traits, emotional status and emotional intelligence influence and correlation with e-sports, gamers’ behaviors and help policy makers and stakeholders take action, shape social policy and prevent the adverse consequences on young adults. The need for further research, prevention and treatment strategies is also addressed.

Keywords: e-sports, e-gamers, personality traits, POMS, emotional intelligence, data mining, R

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Authors: Jerald Ruta, Ricardo Villar, Jojemar Bantugan, Nycel Barbadillo, Jigg Pelayo

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Streams are important in providing water supply for industrial, agricultural and human consumption, In short when there are streams there are lives. Identifying streams are essential since many developed cities are situated in the vicinity of these bodies of water and in flood management, it serves as basin for surface runoff within the area. This study aims to process and generate features from high-resolution digital terrain model (DTM) with 1-meter resolution using Hydrology Tools of ArcGIS. The raster was then filled, processed flow direction and accumulation, then raster calculate and provide stream order, converted to vector, and clearing undesirable features using the ancillary or google earth. In field validation streams were classified whether perennial, intermittent or ephemeral. Results show more than 90% of the extracted feature were accurate in assessment through field validation.

Keywords: digital terrain models, hydrology tools, strahler method, stream classification

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Authors: Jason Sheng-Hong Tsai, Faezeh Ebrahimzadeh, Min-Ching Chung, Shu-Mei Guo, Leang-San Shieh, Tzong-Jiy Tsai, Li Wang

Abstract:

In this paper, we first construct a new state and disturbance estimator using discrete-time proportional plus integral observer to estimate the system state and the unknown external disturbance for the discrete-time system with an input-to-output direct-feedthrough term. Then, the generalized optimal linear quadratic digital tracker design is applied to construct a proportional plus integral observer-based tracker for the system with an unknown external disturbance to have a desired tracking performance. Finally, a numerical simulation is given to demonstrate the effectiveness of the new application of our proposed approach.

Keywords: non-minimum phase system, optimal linear quadratic tracker, proportional plus integral observer, state and disturbance estimator

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Authors: Kannan Subramani, Twinkle Sara Joseph

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Virtual Reality (VR) has emerged as a promising tool to create immersive experiences for social impact. This study examines the capacity of virtual reality (VR) as a means of creating social change. It does so by analyzing a 360-degree VR documentary called ‘The Hidden,’ which specifically addresses the problem of bonded labour in India. Bonded labour is a contemporary manifestation of slavery in which individuals are coerced into working to repay debts that can endure for many generations. The documentary seeks to enhance awareness and elicit empathy towards this matter. The study utilizes a combination of qualitative and quantitative methodologies to investigate the influence of ‘The Hidden’ on the audience's views and their inclination to combat bonded labour. A total of ninety-six individuals used Oculus Quest 2 VR headsets to watch the documentary and subsequently engaged in interviews to discuss their encounters. The data underwent analysis using linear regression to discover any noteworthy trends in the replies. The results indicate that virtual reality (VR) has the potential to greatly amplify viewers' emotional involvement and facilitate societal transformation by offering immersive, direct encounters with crucial social matters.

Keywords: virtual reality, societal influence, indentured servitude, 360-degree virtual reality documentary, immersive media, societal transformation

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Authors: A. Shirazibeheshti, T. Radwan, A. Ettefaghian, G. Wilson, C. Luca, Farbod Khanizadeh

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Anticholinergic medication has been associated with events such as falls, delirium, and cognitive impairment in older patients. To further assess this, anticholinergic burden scores have been developed to quantify risk. A risk model based on clustering was deployed in a healthcare management system to cluster patients into multiple risk groups according to anticholinergic burden scores of multiple medicines prescribed to patients to facilitate clinical decision-making. To do so, anticholinergic burden scores of drugs were extracted from the literature, which categorizes the risk on a scale of 1 to 3. Given the patients’ prescription data on the healthcare database, a weighted anticholinergic risk score was derived per patient based on the prescription of multiple anticholinergic drugs. This study was conducted on over 300,000 records of patients currently registered with a major regional UK-based healthcare provider. The weighted risk scores were used as inputs to an unsupervised learning algorithm (mean-shift clustering) that groups patients into clusters that represent different levels of anticholinergic risk. To further evaluate the performance of the model, any association between the average risk score within each group and other factors such as socioeconomic status (i.e., Index of Multiple Deprivation) and an index of health and disability were investigated. The clustering identifies a group of 15 patients at the highest risk from multiple anticholinergic medication. Our findings also show that this group of patients is located within more deprived areas of London compared to the population of other risk groups. Furthermore, the prescription of anticholinergic medicines is more skewed to female than male patients, indicating that females are more at risk from this kind of multiple medications. The risk may be monitored and controlled in well artificial intelligence-equipped healthcare management systems.

Keywords: anticholinergic medicines, clustering, deprivation, socioeconomic status

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Authors: Amien Rahardjo, Faiz Husnayain, Iwa Garniwa

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PLN used the kWh meter to determine the amount of energy consumed by the household customers. High precision of kWh meter is needed in order to give accuracy results as the accuracy can be decreased due to the presence of harmonic. In this study, an estimation of active power consumed was developed. Based on the first year study results, the largest deviation due to harmonics can reach up to 9.8% in 2200VA and 12.29% in 3500VA with kWh meter analog. In the second year of study, deviation of digital customer meter reaches 2.01% and analog meter up to 9.45% for 3500VA household customers. The aim of this research is to produce an estimation system to calculate the total energy consumed by household customer using analog meter so the losses due to irregularities PLN recording of energy consumption based on the measurement used Analog kWh-meter installed is avoided.

Keywords: harmonics estimation, harmonic distortion, kWh meters analog and digital, THD, household customers

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Authors: Claudia Rodriguez-Espinosa, Erika Elizabeth Pérez Múzquiz

Abstract:

Since the creation of the “Pueblos Mágicos” program in 2001, a series of social and cultural events had directly affected the heritage conservation of the 121 registered localities until 2018, when the federal government terminated the program. Many studies have been carried out that seek to analyze from different perspectives and disciplines the consequences that these appointments have generated in the “Pueblos Mágicos.” Multidisciplinary groups such as the one headed by Carmen Valverde and Liliana López Levi, have brought together specialists from all over the Mexican Republic to create a set of diagnoses of most of these settlements, and although each one has unique specificities, there is a constant in most of them that has to do with the loss of cultural heritage and that is related to transculturality. There are several factors identified that have fostered a cultural loss, as a direct reflection of the economic crisis that prevails in Mexico. It is important to remember that the origin of this program had as its main objective to promote the growth and development of local economies since one of the conditions for entering the program is that they have less than 20,000 inhabitants. With this goal in mind, one of the first actions that many “Pueblos Mágicos” carried out was to improve or create an infrastructure to receive both national and foreign tourists since this was practically non-existent. Creating hotels, restaurants, cafes, training certified tour guides, among other actions, have led to one of the great problems they face: globalization. Although by itself it is not bad, its impact in many cases has been negative for heritage conservation. The entry into and contact with new cultures has led to the undervaluation of cultural traditions, their transformation and even their total loss. This work seeks to present specific cases of transformation and loss of cultural heritage, as well as to reflect on the problem and propose scenarios in which the negative effects can be reversed. For this text, 36 “Pueblos Mágicos” have been selected for study, based on those settlements that are cited in volumes I and IV (the first and last of the collection) of the series produced by the multidisciplinary group led by Carmen Valverde and Liliana López Levi (researchers from UNAM and UAM Xochimilco respectively) in the project supported by CONACyT entitled “Pueblos Mágicos. An interdisciplinary vision”, of which we are part. This sample is considered representative since it forms 30% of the total of 121 “Pueblos Mágicos” existing at that moment. With this information, the elements of its intangible heritage loss or transformation have been identified in every chapter based on the texts written by the participants of that project. Finally, this text shows an analysis of the effects that this federal program, as a public policy applied to 132 populations, has had on the conservation or transformation of the intangible cultural heritage of the “Pueblos Mágicos.” Transculturality, globalization, the creation of identities and the desire to increase the flow of tourists have impacted the changes that traditions (main intangible cultural heritage) have had in the 18 years that the federal program lasted.

Keywords: public policies, cultural tourism, heritage preservation, pueblos mágicos program

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Authors: L. Krpalkova, N. O' Mahony, A. Carvalho, S. Campbell, G. Corkery, E. Broderick, J. Walsh

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Farm management and operations will drastically change due to access to real-time data, real-time forecasting, and tracking of physical items in combination with Internet of Things developments to further automate farm operations. Dairy farms have embraced technological innovations and procured vast amounts of permanent data streams during the past decade; however, the integration of this information to improve the whole farm-based management and decision-making does not exist. It is now imperative to develop a system that can collect, integrate, manage, and analyse on-farm and off-farm data in real-time for practical and relevant environmental and economic actions. The developed systems, based on machine learning and artificial intelligence, need to be connected for useful output, a better understanding of the whole farming issue, and environmental impact. Evolutionary computing can be very effective in finding the optimal combination of sets of some objects and, finally, in strategy determination. The system of the future should be able to manage the dairy farm as well as an experienced dairy farm manager with a team of the best agricultural advisors. All these changes should bring resilience and sustainability to dairy farming as well as improving and maintaining good animal welfare and the quality of dairy products. This review aims to provide an insight into the state-of-the-art of big data applications and evolutionary computing in relation to smart dairy farming and identify the most important research and development challenges to be addressed in the future. Smart dairy farming influences every area of management, and its uptake has become a continuing trend.

Keywords: big data, evolutionary computing, cloud, precision technologies

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Authors: Hosamuddin Hamza

Abstract:

The major concept of 4D printing is self-folding under thermal and humidity changes. This concept relies on understanding how the microstructures of 3D-printed models can undergo spontaneous shape transformation under thermal and moisture changes. The transformation mechanism could be achieved by mixing, in a controllable pattern, a number of materials within the printed model, each with known strain/shrinkage properties. 4D printing has a strong potential to be applied in dentistry as the technology could produce dynamic and adaptable materials to be used as functional objects in the oral environment under the continuously changing thermal and humidity conditions. The motion criteria could override the undesired dimensional changes, thermal instability, polymerization shrinkage and microleakage. 4D printing could produce restorative materials being self-adjusted spontaneously without further intervention from the dentist or patient; that is, the materials could be capable of fixing its failed portions, compensating for some lost tooth structure, while avoiding microleakage or overhangs at the margins. In prosthetic dentistry, 4D printing could provide an option to manage the influence of bone and soft tissue imbalance during mastication (and at rest) with high predictability of the type/direction of forces. It can also produce materials with better fitting and retention characteristics than conventional or 3D-printed materials. Nevertheless, it is important to highlight that 4D-printed objects, having dynamic properties, could provide some cushion as they undergo self-folding compensating for any thermal changes or mechanical forces such as traumatic forces.

Keywords: functional material, self-folding material, 3D printing, 4D printing

Procedia PDF Downloads 482