Search results for: location-based social network services

Authors: Hamza Iftikhar

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The intersex person’s social isolation condition is the leading concern in inclusive educational practices. It provides for the relevance of intersex communities with the influence of social isolation on their education and well-being. Given the underlying concern, this paper stresses the isolation-free condition of the intersex community by facilitating inclusive education. The Atkinson and Shiffrin Model and Behaviorism-Based Intersex Theory supports inclusive education by extending the desire for the significant management of stereotypes, quality teaching, parental beliefs, expressions, physique, and intersex attribution. The reducing role of social isolation for inclusive education is analyzed using the qualitative research method. The semi-structured interview research instrument is used for the data collection from the Ministry of Human Rights, Educational Institutions, and inter-sex Representatives. The results show that managing directors and heads of educational institutions frame policy management for the free social isolation of intersex persons, which is relevant through inclusive education. The implication of this paper is to provide a better social condition for intersex persons towards inclusive education through effective policy management.

Keywords: social isolation, inter-sex, relevance, inclusive education, policy management

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Authors: Juha Kettunen

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This study presents a project that tests and adjusts active European learning and teaching methods in Indonesian universities to increase their external impact on enterprises and other organizations; it also assesses the implementation of the Erasmus+ projects funded by the European Union. The project is based on the approach of innovation pedagogy that responds to regional development needs and integrates applied research and development projects into education to create capabilities for students to participate in development work after graduation. The assessment of the Erasmus+ project resulted in many improvements that can be made to achieve higher quality and innovativeness. The results of this study are useful for those who want to improve the applied research and development projects of higher education institutions.

Keywords: higher education, innovations, social network, project management

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Authors: Aphiradee Wongsiri

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The purpose of this study is to investigate the role of social capital in the relationships between community influences consisting of community attachment and community support on civic engagement among the household-header and non-household header volunteers. The data were collected from 216 household header volunteers and 204 non-household header volunteers across rural communities in seven sub-districts in Nong Khai Province, Thailand. A good fit structural equation modeling (SEM) was tested for both groups. The findings indicate that the SEM model for the group of household header volunteers, social capital had a direct effect on civic engagement, while community support had an indirect effect on civic engagement through social capital. On the other hand, the SEM model for the group of non-household header volunteers shows that social capital had a direct effect on civic engagement. Also, community attachment and community support had indirect effects on civic engagement through social capital. Therefore, social capital in this study played an important role as a mediator in the relationships between community influences and civic engagement in both groups.

Keywords: social capital, civic engagement, volunteer, rural development

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Authors: Etienne Herrick

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As an economically and ecologically feasible method for farmers to introduce greater diversity into their crop rotations, cover cropping presents a valuable opportunity for improving the sustainability of food production. Planted in-between cash crop growing seasons, cover crops serve to enhance agroecosystem functioning, rather than being destined for sale or consumption. In fact, cover crops may hold the capacity to deliver multiple ecosystem functions or services simultaneously (multifunctionality). Building upon this line of research will not only benefit society at present, but also support its continued survival through its potential for restoring depleted soils and reducing the need for energy-intensive and harmful external inputs like fertilizers and pesticides. This study utilizes a trait-based approach to explore the influence of inter- and intra-specific interactions in summer cover crop mixtures and monocultures on functional trait expression and ecosystem services. Functional traits that enhance ecosystem services related to agricultural production include height, specific leaf area (SLA), root, shoot ratio, leaf C and N concentrations, and flowering phenology. Ecosystem services include biomass production, weed suppression, reduced N leaching, N recycling, and support of pollinators. Employing a trait-based approach may allow for the elucidation of mechanistic links between plant structure and resulting ecosystem service delivery. While relationships between some functional traits and the delivery of particular ecosystem services may be readily apparent through existing ecological knowledge (e.g. height positively correlating with weed suppression), this study will begin to quantify those relationships so as to gain further understanding of whether and how measurable variation in functional trait expression across cover crop mixtures and monocultures can serve as a reliable predictor of variation in the types and abundances of ecosystem services delivered. Six cover crop species, including legume, grass, and broadleaf functional types, were selected for growth in six mixtures and their component monocultures based upon the principle of trait complementarity. The tricultures (three-way mixtures) are comprised of a legume, grass, and broadleaf species, and include cowpea/sudex/buckwheat, sunnhemp/sudex/buckwheat, and chickling vetch/oat/buckwheat combinations; the dicultures contain the same legume and grass combinations as above, without the buckwheat broadleaf. By combining species with expectedly complimentary traits (for example, legumes are N suppliers and grasses are N acquirers, creating a nutrient cycling loop) the cover crop mixtures may elicit a broader range of ecosystem services than that provided by a monoculture, though trade-offs could exist. Collecting functional trait data will enable the investigation of the types of interactions driving these ecosystem service outcomes. It also allows for generalizability across a broader range of species than just those selected for this study, which may aid in informing further research efforts exploring species and ecosystem functioning, as well as on-farm management decisions.

Keywords: agroecology, cover crops, functional traits, multifunctionality, trait complementarity

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Authors: Stefan K. Behfar

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The rapid growth of the Ethereum network has brought forth the urgent need for scalable analysis methods to handle the increasing volume of blockchain data. In this research, we propose efficient methodologies for making Ethereum network analysis scalable. Our approach leverages a combination of graph-based data representation, probabilistic sampling, and parallel processing techniques to achieve unprecedented scalability while preserving critical network insights. Data Representation: We develop a graph-based data representation that captures the underlying structure of the Ethereum network. Each block transaction is represented as a node in the graph, while the edges signify temporal relationships. This representation ensures efficient querying and traversal of the blockchain data. Probabilistic Sampling: To cope with the vastness of the Ethereum blockchain, we introduce a probabilistic sampling technique. This method strategically selects a representative subset of transactions and blocks, allowing for concise yet statistically significant analysis. The sampling approach maintains the integrity of the network properties while significantly reducing the computational burden. Graph Convolutional Networks (GCNs): We incorporate GCNs to process the graph-based data representation efficiently. The GCN architecture enables the extraction of complex spatial and temporal patterns from the sampled data. This combination of graph representation and GCNs facilitates parallel processing and scalable analysis. Distributed Computing: To further enhance scalability, we adopt distributed computing frameworks such as Apache Hadoop and Apache Spark. By distributing computation across multiple nodes, we achieve a significant reduction in processing time and enhanced memory utilization. Our methodology harnesses the power of parallelism, making it well-suited for large-scale Ethereum network analysis. Evaluation and Results: We extensively evaluate our methodology on real-world Ethereum datasets covering diverse time periods and transaction volumes. The results demonstrate its superior scalability, outperforming traditional analysis methods. Our approach successfully handles the ever-growing Ethereum data, empowering researchers and developers with actionable insights from the blockchain. Case Studies: We apply our methodology to real-world Ethereum use cases, including detecting transaction patterns, analyzing smart contract interactions, and predicting network congestion. The results showcase the accuracy and efficiency of our approach, emphasizing its practical applicability in real-world scenarios. Security and Robustness: To ensure the reliability of our methodology, we conduct thorough security and robustness evaluations. Our approach demonstrates high resilience against adversarial attacks and perturbations, reaffirming its suitability for security-critical blockchain applications. Conclusion: By integrating graph-based data representation, GCNs, probabilistic sampling, and distributed computing, we achieve network scalability without compromising analytical precision. This approach addresses the pressing challenges posed by the expanding Ethereum network, opening new avenues for research and enabling real-time insights into decentralized ecosystems. Our work contributes to the development of scalable blockchain analytics, laying the foundation for sustainable growth and advancement in the domain of blockchain research and application.

Keywords: Ethereum, scalable network, GCN, probabilistic sampling, distributed computing

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Authors: Adam Bereczk

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Due to persistent socioeconomic problems regarding sustainability and labour market equilibrium in Europe, the subjects of social economy gained considerable academic attention recently. At the meantime, social enterprises pursuing the double bottom line criteria, struggling to find the proper management philosophies and strategies to make their social purpose business financially sustainable. Despite the strategic management literature was developed mainly on the bases of large corporations, in the past years, the interpretation of strategy concepts became a frequent topic in scientific discussions in the case of small and medium-sized enterprises also. The topic of strategic orientations is a good example of the trend. However, less is known about the case of social enterprises, despite the fact, the majority of them are small businesses engaged in real business activities. The main purpose of this work is to give a comprehensive summary of different perspectives regarding the interpretations of strategic orientations of social enterprises. The novelty of this work is it shows the previous outcomes and models of scholars from various fields of economic science who tried to intertwine the two spheres in different forms, methodize the findings and draw attention to the shortcomings.

Keywords: social enterprises, business sustainability, strategic orientations, literature review

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Authors: Abisha Isaac Mohanlal

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Amidst all suspicions and cynicism raised by the legal fraternity, Artificial Intelligence has found its way into the legal system and has revolutionized the conventional forms of legal services delivery. Be it legal argumentation and research or resolution of complex legal disputes; artificial intelligence has crept into all legs of modern day legal services. Its impact has been largely felt by way of big data, legal expert systems, prediction tools, e-lawyering, automated mediation, etc., and lawyers around the world are forced to upgrade themselves and their firms to stay in line with the growth of technology in law. Researchers predict that the future of legal services would belong to artificial intelligence and that the age of human lawyers will soon rust. But as far as the Judiciary is concerned, even in the developed countries, the system has not fully drifted away from the orthodoxy of preferring Natural Intelligence over Artificial Intelligence. Since Judicial decision-making involves a lot of unstructured and rather unprecedented situations which have no single correct answer, and looming questions of legal interpretation arise in most of the cases, discretion and Emotional Intelligence play an unavoidable role. Added to that, there are several ethical, moral and policy issues to be confronted before permitting the intrusion of Artificial Intelligence into the judicial system. As of today, the human judge is the unrivalled master of most of the judicial systems around the globe. Yet, scientists of Artificial Intelligence claim that robot judges can replace human judges irrespective of how daunting the complexity of issues is and how sophisticated the cognitive competence required is. They go on to contend that even if the system is too rigid to allow robot judges to substitute human judges in the recent future, Artificial Intelligence may still aid in other judicial tasks such as drafting judicial documents, intelligent document assembly, case retrieval, etc., and also promote overall flexibility, efficiency, and accuracy in the disposal of cases. By deconstructing the major challenges that Artificial Intelligence has to overcome in order to successfully invade the human- dominated judicial sphere, and critically evaluating the potential differences it would make in the system of justice delivery, the author tries to argue that penetration of Artificial Intelligence into the Judiciary could surely be enhancive and reparative, if not fully transformative.

Keywords: artificial intelligence, judicial decision making, judicial systems, legal services delivery

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Authors: Selamat Muliadi

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This study aimed to explain conceptual the role of Zakat on sustainable economic development by Rumah Zakat. Rumah Zakat is a philanthropic institution that manages zakat and other social funds through community empowerment programs. In running the program, including economic empowerment and socio health services are designed for these recipients. Rumah Zakat's connection with the establisment of Sustainable Development Goals (SDGs) which is to help impoverished recipients economically and socially. It’s an important agenda that the government input into national development, even the region. The primary goal of Zakat on sustainable economic development, not only limited to economic variables but based on Islamic principles, has comprehensive characteristics. The characteristics include moral, material, spiritual, and social aspects. In other words, sustainable economic development is closely related to improving people’s living standard (Mustahiq). The findings provide empiricial evidence regarding the positive contribution and effectiveness of zakat targeting in reducing poverty and improve the welfare of people related with the management of zakat. The purpose of this study was to identify the role of Zakat on sustainable economic development, which was applied by Rumah Zakat. This study used descriptive method and qualitative analysis. The data source was secondary data collected from documents and texts related to the research topic, be it books, articles, newspapers, journals, or others. The results showed that the role of zakat on sustainable economic development by Rumah Zakat has been quite good and in accordance with the principle of Islamic economics. Rumah Zakat programs are adapted to support intended development. The contribution of the productive program implementation has been aligned with four goals in the Sustainable Development Goals, i.e., Senyum Juara (Quality Education), Senyum Lestari (Clean Water and Sanitation), Senyum Mandiri (Entrepreneur Program) and Senyum Sehat (Free Maternity Clinic). The performance of zakat in the sustainable economic empowerment community at Rumah Zakat is taking into account dimensions such as input, process, output, and outcome.

Keywords: Zakat, social welfare, sustainable economic development, charity

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Authors: Masrur Alam Khan

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The purpose of this study was to examine the dyadic interaction techniques that social media users utilize to reduce uncertainty in their day to day business engagements in the absence of their physical interaction. The study empirically tested assumptions of uncertainty reduction theory while addressing self-disclosure, seeking questions to develop consensus, and subsequently to achieve intimacy in very conducive environment. Moreover, this study examined the effect of dyadic interaction through social media among business community while identifying the strength of their reciprocity in relationships and compares it with those having no dyadic relations due to absence of social media. Using socio-metric survey, the study revealed a better understanding of their partners for upholding their professional relations more credible. A sample of unacquainted, both male and female, was randomly asked questions regarding their nature of dyadic interaction within their office while using social media (face-to-face, visual CMC (webcam) or text-only). Primary results explored that the social media users develop their better know-how about their professional obligations to reduce ambiguity and align with one to one interact.

Keywords: dyadic-interaction, social media, uncertainty reduction, socio-metric survey, self-disclosure, intimacy, reciprocity in relationship

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Authors: A. Graa, I. Ziane, F. Benhamida, S. Souag

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This paper presents a comparative analysis study of an efficient and reliable quadratic programming (QP) to solve economic load dispatch (ELD) problem with considering transmission losses in a power system. The proposed QP method takes care of different unit and system constraints to find optimal solution. To validate the effectiveness of the proposed QP solution, simulations have been performed using Algerian test system. Results obtained with the QP method have been compared with other existing relevant approaches available in literatures. Experimental results show a proficiency of the QP method over other existing techniques in terms of robustness and its optimal search.

Keywords: economic dispatch, quadratic programming, Algerian network, dynamic load

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Authors: Nonlapun Meenil, Pisitpong Intarapong, Thitima Wongsheree, Pranchalee Samanpiboon

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In Thailand, once pineapples are harvested, they must be classified into two classes based on their sweetness: sweet and unsweet. This paper has studied and developed the assessment of internal quality of pineapples using a low-cost compact spectroscopy sensor according to the Spectroscopy approach and Neural Network (NN). During the experiments, Batavia pineapples were utilized, generating 100 samples. The extracted pineapple juice of each sample was used to determine the Soluble Solid Content (SSC) labeling into sweet and unsweet classes. In terms of experimental equipment, the sensor cover was specifically designed to install the sensor and light source to read the reflectance at a five mm depth from pineapple flesh. By using a spectroscopy sensor, data on visible and near-infrared reflectance (Vis-NIR) were collected. The NN was used to classify the pineapple classes. Before the classification step, the preprocessing methods, which are Class balancing, Data shuffling, and Standardization were applied. The 510 nm and 900 nm reflectance values of the middle parts of pineapples were used as features of the NN. With the Sequential model and Relu activation function, 100% accuracy of the training set and 76.67% accuracy of the test set were achieved. According to the abovementioned information, using a low-cost compact spectroscopy sensor has achieved favorable results in classifying the sweetness of the two classes of pineapples.

Keywords: neural network, pineapple, soluble solid content, spectroscopy

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Authors: Ahmad Mansoor Stanikzai, Yoshitaka Kajita

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This research is a very essential towards transportation planning of Kabul New City. In this research, the travel demand of Kabul metropolitan area (Existing and Kabul New City) are evaluated for three different target years (2015, current, 2025, mid-term, 2040, long-term). The outcome of this study indicates that, though currently the vehicle volume is less the capacity of existing road networks, Kabul city is suffering from daily traffic congestions. This is mainly due to lack of transportation management, the absence of proper policies, improper public transportation system and violation of traffic rules and regulations by inhabitants. On the other hand, the observed result indicates that the current vehicle to capacity ratio (VCR) which is the most used index to judge traffic status in the city is around 0.79. This indicates the inappropriate traffic condition of the city. Moreover, by the growth of population in mid-term (2025) and long-term (2040) and in the case of no development in the road network and transportation system, the VCR value will dramatically increase to 1.40 (2025) and 2.5 (2040). This can be a critical situation for an urban area from an urban transportation perspective. Thus, by introducing high-capacity public transportation system and the development of road network in Kabul New City and integrating these links with the existing city road network, significant improvements were observed in the value of VCR.

Keywords: Afghanistan, Kabul new city, planning, policy, urban transportation

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Authors: Hye Rim Lee, Eui Jun Jeong, Ju Woo Kim

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This study will examine how the therapeutic factors (therapeutic catharsis-seeking and game-efficacy of the game player) and self-construal factors (independent and interdependent self-construal of the game player) as well as social capital factors (bonding and bridging social capital of the game player) affect trait aggression in the game. Results show that both therapeutic catharsis-seeking and game self-efficacy are particularly important to the players since they cause the game players’ aggressive tendencies to be greatly diminished. Independent self-construal reduces the level of the players’ aggression. Interestingly enough, the bonding social capital enhances the level of the players’ aggression, while individuals with bridging social capital did not show any significant effects. The results and implications will be discussed herein.

Keywords: aggression catharsis, game self-efficacy, self-construal, social capital, therapeutic catharsis seeking

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Authors: Zixian Zhang, Shanliang Yao, Zile Huang, Zhaodong Wu, Xiaohui Zhu, Yong Yue, Jieming Ma

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Unmanned Surface Vehicles (USVs) are valuable due to their ability to perform dangerous and time-consuming tasks on the water. Object detection tasks are significant in these applications. However, inherent challenges, such as the complex distribution of obstacles, reflections from shore structures, water surface fog, etc., hinder the performance of object detection of USVs. To address these problems, this paper provides a fusion method for USVs to effectively detect objects in the inland surface environment, utilizing vision sensors and 3+1D Millimeter-wave radar. MMW radar is complementary to vision sensors, providing robust environmental information. The radar 3D point cloud is transferred to 2D radar pseudo image to unify radar and vision information format by utilizing the point transformer. We propose a multi-source object detection network (RV-YOLOX )based on radar-vision fusion for inland waterways environment. The performance is evaluated on our self-recording waterways dataset. Compared with the YOLOX network, our fusion network significantly improves detection accuracy, especially for objects with bad light conditions.

Keywords: inland waterways, YOLO, sensor fusion, self-attention

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Authors: Monika Florczak-Wątor

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The main purpose of this paper is to determine the applicability of the constitutional social rights in the so-called horizontal relations, i.e. the relations between private entities. Nowadays the constitutional rights are more and more often violated by private entities and not only by the state. The private entities interfere with the privacy of individuals, limit their freedom of expression or disturb their peaceful gatherings. International corporations subordinate individuals in a way which may limit their constitutional rights. These new realities determine the new role of the constitution in protecting human rights. The paper will aim at answering two important questions. Firstly, are the private entities obliged to respect the constitutional social rights of other private entities and can they be liable for violation of these rights? Secondly, how the constitutional social rights can receive horizontal effect? Answers to these questions will have a significant meaning for the popularization of the practice of applying the Constitution among the citizens as well as for the courts which settle disputes between them.

Keywords: social rights, private relations, horizontality, constitutional rights

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Authors: Mohsen Noroozi, Maryam Khalili

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Creating cities, objects and spaces that are economically, environmentally and socially sustainable and which meet the challenge of social interaction and generation change will be one of the biggest tasks of designers. Social sustainability is about how individuals, communities and societies live with each other and set out to achieve the objectives of development model which they have chosen for themselves. Urban lightning as one of the most important elements of urban furniture that people constantly interact with it in public spaces; can be a significant object for designers. Using intelligence by internet of things for urban lighting makes it more interactive in public environments. It can encourage individuals to carry out appropriate behaviors and provides them the social awareness through new interactions. The greatest strength of this technology is its strong impact on many aspects of everyday life and users' behaviors. The analytical phase of the research is based on a multiple method survey strategy. Smart lighting proposed in this paper is an urban lighting designed on results obtained from a collective point of view about the social sustainability. In this paper, referring to behavioral design methods, the social behaviors of the people has been studied. Data show that people demands for a deeper experience of social participation, safety perception and energy saving with the meaningful use of interactive and colourful lighting effects. By using intelligent technology, some suggestions are provided in the field of future lighting to consider the new forms of social sustainability.

Keywords: behavior pattern, internet of things, social sustainability, urban lighting

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Authors: Charitha Harshani Perera, Rajkishore Nayak, Long Thang Van Nguyen

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With the advent of social media, Vietnam has changed the way customers perceive the information about the brand. In the context of higher education, the adoption of social media has received attention with the increasing rate of social media usage among undergraduates. Brand-related user-generated content (UGC) on social media emphasizes the social ties between users and users’ participation, which promotes the communication to build and maintain the relationship with the brands. Although brand positioning offers a significant competitive advantage, the association with brand-related user-generated content in social media with brand positioning in the context of higher education is still an under-researched area. Accordingly, using social identity theory and social exchange theory, this research aims to deepen our understanding of the influence of brand-related user-generated content on brand positioning and purchase intention. Employing a quantitative survey design,384 Vietnamese undergraduates were selected based on purposive sampling. The findings suggest that brand-related user-generated content influence brand positioning and brand choice intention. However, there is a significant mediating effect of the reliability and understandability of the content.

Keywords: brand positioning, brand-related user-generated content, emerging countries, higher education

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Authors: Evan Lowhorn, Rocio Alba-Flores

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The purpose of this work is to develop a method for classifying hand signals and using the output in a drone control algorithm. To achieve this, methods based on Convolutional Neural Networks (CNN) were applied. CNN's are a subset of deep learning, which allows grid-like inputs to be processed and passed through a neural network to be trained for classification. This type of neural network allows for classification via imaging, which is less intrusive than previous methods using biosensors, such as EMG sensors. Classification CNN's operate purely from the pixel values in an image; therefore they can be used without additional exteroceptive sensors. A development bench was constructed using a desktop computer connected to a high-definition webcam mounted on a scissor arm. This allowed the camera to be pointed downwards at the desk to provide a constant solid background for the dataset and a clear detection area for the user. A MATLAB script was created to automate dataset image capture at the development bench and save the images to the desktop. This allowed the user to create their own dataset of 12,000 images within three hours. These images were evenly distributed among seven classes. The defined classes include forward, backward, left, right, idle, and land. The drone has a popular flip function which was also included as an additional class. To simplify control, the corresponding hand signals chosen were the numerical hand signs for one through five for movements, a fist for land, and the universal “ok” sign for the flip command. Transfer learning with PyTorch (Python) was performed using a pre-trained 18-layer residual learning network (ResNet-18) to retrain the network for custom classification. An algorithm was created to interpret the classification and send encoded messages to a Ryze Tello drone over its 2.4 GHz Wi-Fi connection. The drone’s movements were performed in half-meter distance increments at a constant speed. When combined with the drone control algorithm, the classification performed as desired with negligible latency when compared to the delay in the drone’s movement commands.

Keywords: classification, computer vision, convolutional neural networks, drone control

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Authors: Emmanuel Benjamin, Matthias Blum

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Purpose – We address smallholder farmers’ restricted possibilities to adopt sustainable technologies which have direct and indirect benefits. Smallholders often face little asset endowment due to small farm size und insecure property rights, therefore experiencing constraints in adopting agricultural innovation. A program involving payments for ecosystem services (PES) benefits poor smallholder farmers in developing countries in many ways and has been suggested as a means of easing smallholder farmers’ financial constraints. PES may also provide additional mainstay which can eventually result in more favorable credit contract terms due to the availability of collateral substitute. Results of this study may help to understand the barriers, motives and incentives for smallholders’ participation in PES and help in designing a strategy to foster participation in beneficial programs. Design/methodology/approach – This paper uses a random utility model and a logistic regression approach to investigate factors that influence agroforestry adoption. We investigate non-monetary factors, such as information spillover, that influence the decision to adopt such conservation strategies. We collected original data from non-government-run agroforestry mitigation programs with PES that have been implemented in the Mount Kenya region. Preliminary Findings – We find that spread of information, existing networks and peer involvement in such programs drive participation. Conversely, participation by smallholders does not seem to be influenced by education, land or asset endowment. Contrary to some existing literature, we found weak evidence for a positive correlation between the adoption of agroforestry with PES and age of smallholder, e.g., one increases with the other, in the Mount Kenyan region. Research implications – Poverty alleviation policies for developing countries should target social capital to increase the adoption rate of modern technologies amongst smallholders.

Keywords: agriculture innovation, agroforestry adoption, smallholders, payment for ecosystem services, Sub-Saharan Africa

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Authors: Cheryl M. Bowen

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Understanding that children thrive in a multi-systems approach to mental health development, a growing number of schools often promote school-based positive youth development however, there is scant empirical evidence investigating effective school-based “wraparound” mental health services for low income, Latinx children and their families. This 10-month case study utilizes a sample of 281 low-income, Latinx parents and their children, and 23 K-5th grade teachers living in northern California to test the hypothesis that a school-based mental health program can strengthen students’ developmental asset attainment and positively impact the school environment. The study utilized triangulated data to ascertain the effects of two program levels - (a) mental health and (b) positive child development services. All services were site-based and meant to target a wide variety of families. Findings from the study report that the universal mental health program increased the developmental asset attainment in 5 out of 8 thriving indicators thus transforming the child within his/her environment. Data collected from the administrative referral report demonstrate that the project also positively impacted the school climate. Parents and teachers felt more connected to the school, and referrals were down for discipline (35%), academics (66%), and suspensions (51%). The study concludes that a transformational ecology model of positive child development is the most effective means to nurture connections to all socializing agencies in a child’s ecosystem.

Keywords: case study, child development, positive youth development, developmental assets, ecological systems theory

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Authors: Maximilian Richter

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Implementing shared autonomous electric vehicles (SAEVs) has many advantages. The main advantages are achieved when SAEVs are offered as on-demand services by a fleet operator. However, autonomous mobility on demand (AMoD) will be distributed nationwide only if a fleet operation is economically profitable for the operator. This paper proposes a microscopic approach to modeling two implementation scenarios of an AMoD fleet. The city of Zurich is used as a case study, with the results and findings being generalizable to other similar European and North American cities. The data are based on the traffic model of the canton of Zurich (Gesamtverkehrsmodell des Kantons Zürich (GVM-ZH)). To determine financial profitability, demand is based on the simulation results and combined with analyzing the costs of a SAEV per kilometer. The results demonstrate that depending on the scenario; journeys can be offered profitably to customers for CHF 0.3 up to CHF 0.4 per kilometer. While larger fleets allowed for lower price levels and increased profits in the long term, smaller fleets exhibit elevated efficiency levels and profit opportunities per day. The paper concludes with recommendations for how fleet operators can prepare themselves to maximize profit in the autonomous future.

Keywords: autonomous vehicle, mobility on demand, traffic simulation, fleet provider

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Authors: Mustafa Hyder, Shamaila Burney, Roohi Mumtaz

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The aim of this study is to determine the consequences of silent or hidden messages and their effectiveness in deteriorating or altering our ethical norms and values. The study also focuses the repercussions of subconscious messages and possibilities of ethical diffusion in our society. The research based on the question that what are the different factors that motivate advertisers to include subliminal messages and how much these unspoken truths affecting our ethical values silently. What are the causes and effects of the subliminal messages in general and the level of ethical diffusion and its acceptance? The concept of advertising is to promote and highlight the salient features of the products and services, a company offers. Advertising is the best option nowadays to convey the related information to the consumers so that they attracted more towards the products or services proposed. The other thing advertisers concentrate, is the psychological characteristics using to persuade consumers choice. Using skills and tactics of advertising to promote a product in such a way that it creates a sensation, controversy or brand consciousness among the consumers or customers. The purpose to have increase purchase or to gain popularity in comparison to their competitors, they sometimes use such tactics and techniques, which is highly unethical and immoral for any society. These kinds of stuff used very smartly within the ads that only the conscious mind subconsciously catches the meaning of those glittery images, posters, phrases, tag lines and non-verbal clues. This study elucidates the subliminal advertising their repercussions and impact on consumer’s behaviour in our society with the help of few ads embedded subliminally and the trends of profitability. The methods used to accomplish our research are based on qualitative research along with the research articles, books and feedback from focused groups regarding the topic. The basic objective of this study was that, there is no significant change in the behaviour and attitude observed. These messages capture very short-term life on the viewer’s subconscious mind but in long run people get used to it and hence not only have the diffusion power but also has the high level of acceptance as well that reflects mostly through their social behaviours and attitudes.

Keywords: ethical diffusion, subconscious, subliminal advertising, unspoken facts

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Authors: Jiaqi Dong, Qing-Hua Qin, Yi Xiao

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Some of the most fundamental challenges of elastic metamaterials (EMMs) optimization can be attributed to the high consumption of computational power resulted from finite element analysis (FEA) simulations that render the optimization process inefficient. Furthermore, due to the inherent mesh dependence of FEA, minuscule geometry features, which often emerge during the later stages of optimization, induce very fine elements, resulting in enormously high time consumption, particularly when repetitive solutions are needed for computing the objective function. In this study, a surrogate modelling algorithm is developed to reduce computational time in structural optimization of EMMs. The surrogate model is constructed based on a multilayer feedforward artificial neural network (ANN) architecture, trained with prepopulated eigenfrequency data prepopulated from FEA simulation and optimized through regime selection with genetic algorithm (GA) to improve its accuracy in predicting the location and width of the primary elastic band gap. With the optimized ANN surrogate at the core, a Nelder-Mead (NM) algorithm is established and its performance inspected in comparison to the FEA solution. The ANNNM model shows remarkable accuracy in predicting the band gap width and a reduction of time consumption by 47%.

Keywords: artificial neural network, machine learning, mechanical metamaterials, Nelder-Mead optimization

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Authors: Tunde Ope-Davies

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Transmediality and platformization as online content-sharing protocols have continued to accentuate the growing impact of the unprecedented digital revolution across the world. The rapid transformation across all sectors as a result of this revolution has continued to spotlight the increasing importance of new media technologies in redefining and reshaping the rhythm and dynamics of our private and public discursive practices. Equally, social and political activities are being impacted daily through the creation and transmission of political discourse content through multi-channel platforms such as mobile telephone communication, social media networks and the internet. It has been observed that digital platforms have become central to the production, processing, and distribution of multimodal social data and cultural content. The platformization paradigm thus underpins our understanding of how digital platforms enhance the production and heterogenous distribution of media and cultural content through these platforms and how this process facilitates socioeconomic and political activities. The use of multiple digital platforms to share and transmit political discourse material synchronously and asynchronously has gained some exciting momentum in the last few years. Nigeria’s 2023 general elections amplified the usage of social media and other online platforms as tools for electioneering campaigns, socio-political mobilizations and civic engagement. The study, therefore, focuses on transmedia and platformed political discourse as a new strategy to promote political candidates and their manifesto in order to mobilize support and woo voters. This innovative transmedia digital discourse model involves a constellation of online texts and images transmitted through different online platforms almost simultaneously. The data for the study was extracted from the 2023 general elections campaigns in Nigeria between January- March 2023 through media monitoring, manual download and the use of software to harvest the online electioneering campaign material. I adopted a discursive-analytic qualitative technique with toolkits drawn from a computer-mediated multimodal discourse paradigm. The study maps the progressive development of digital political discourse in this young democracy. The findings also demonstrate the inevitable transformation of modern democratic practice through platform-dependent and transmedia political discourse. Political actors and media practitioners now deploy layers of social media network platforms to convey messages and mobilize supporters in order to aggregate and maximize the impact of their media campaign projects and audience reach.

Keywords: social media, digital humanities, political discourse, platformized discourse, multimodal discourse

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Authors: Thrivikraman Aswathi, S. Advaith

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As there can be cases where the use of real data is somehow limited, such as when it is hard to get access to a large volume of real data, we need to go for synthetic data generation. This produces high-quality synthetic data while maintaining the statistical properties of a specific dataset. In the present work, a generative adversarial network (GAN) is trained to produce multivariate time series (MTS) data since the MTS is now being gathered more often in various real-world systems. Furthermore, the GAN-generated MTS data is fed into a transformer-based deep learning architecture that carries out the data categorization into predefined classes. Further, the model is evaluated across various distinct domains by generating corresponding MTS data.

Keywords: GAN, transformer, classification, multivariate time series

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Authors: Airy Huang, Fuji Foo, Aries Prasetya Wibowo

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In recent years, the focus of Natural Language Processing (NLP) development has been gradually shifting from the semantics-based approach to deep learning one, which performs faster with fewer resources. Although it performs well in many applications, the deep learning approach, due to the lack of semantics understanding, has difficulties in noticing and expressing a novel business case with a pre-defined scope. In order to meet the requirements of specific robotic services, deep learning approach is very labor-intensive and time consuming. It is very difficult to improve the capabilities of conversational AI in a short time, and it is even more difficult to self-learn from experiences to deliver the same service in a better way. In this paper, we present an adaptive conversational AI algorithm that combines both semantic knowledge and deep learning to address this issue by learning new business cases through conversations. After self-learning from experience, the robot adapts to the business cases originally out of scope. The idea is to build new or extended robotic services in a systematic and fast-training manner with self-configured programs and constructed dialog flows. For every cycle in which a chat bot (conversational AI) delivers a given set of business cases, it is trapped to self-measure its performance and rethink every unknown dialog flows to improve the service by retraining with those new business cases. If the training process reaches a bottleneck and incurs some difficulties, human personnel will be informed of further instructions. He or she may retrain the chat bot with newly configured programs, or new dialog flows for new services. One approach employs semantics analysis to learn the dialogues for new business cases and then establish the necessary ontology for the new service. With the newly learned programs, it completes the understanding of the reaction behavior and finally uses dialog flows to connect all the understanding results and programs, achieving the goal of self-learning process. We have developed a chat bot service mounted on a kiosk, with a camera for facial recognition and a directional microphone array for voice capture. The chat bot serves as a concierge with polite conversation for visitors. As a proof of concept. We have demonstrated to complete 90% of reception services with limited self-learning capability.

Keywords: conversational AI, chatbot, dialog management, semantic analysis

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Authors: Lynne Soon-Chean Park

Abstract:

Critical Realism (CR) has emerged as an alternative to both the positivist and constructivist perspectives that have long dominated social work research. By unpacking the epistemic weakness of two dogmatic perspectives, CR provides a useful philosophical approach that incorporates the ontological objectivist and subjectivist stance. The CR perspective suggests an alternative approach for social work researchers who have long been looking to engage in the complex interplay between perceived reality at the empirical level and the objective reality that lies behind the empirical event as a causal mechanism. However, despite the usefulness of CR in informing social work research, little practical guidance is available about how CR can inform methodological considerations in social work research studies. This presentation aims to provide a detailed description of CR-informed thematic analysis by drawing examples from a social work doctoral research of Korean migrants’ experiences and understanding of trust associated with their settlement experience in New Zealand. Because of its theoretical flexibility and accessibility as a qualitative analysis method, thematic analysis can be applied as a method that works both to search for the demi-regularities of the collected data and to identify the causal mechanisms that lay behind the empirical data. In so doing, this presentation seeks to provide a concrete and detailed exemplar for social work researchers wishing to employ CR in their qualitative thematic analysis process.

Keywords: critical Realism, data analysis, epistemology, research methodology, social work research, thematic analysis

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Authors: Choumous Mannoubi, Dahlia Kairy, Brigitte Vachon

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The use of technology allows clinicians to provide an individualized approach in a cost-effective manner and to reach a broader client base more easily. Such interventions can be effective in ensuring self-management and follow-up of people with diabetes, reducing the risk of complications by improving accessibility to care services, and better adherence to health recommendations. Consideration of users' opinions and fears to inform the design and implementation stages of these telehealth services seems to be essential to improve their acceptance and usability. The objective of this study is to describe the telepractice of nutritionists supporting the therapeutic management of diabetic patients and document the functional requirements of nutritionists for the design of a tele-nutrition platform. To best identify the requirements and constraints of nutritionists, we conducted individual semi-structured interviews with 10 nutritionists who offered tele-nutrition services. Using a qualitative design with a descriptive approach based on the Nutrition Care Process Model (mNCP) framework, we explored in depth the state of nutritionists' telepractice in public and private health care settings, as well as their requirements for teleconsultation. Qualitative analyses revealed that nutritionists primarily used telephone calls during the COVID 19 pandemic to provide teleconsultations. Nutritionists identified the following important features for the design of a tele-nutrition platform: it should support interprofessional collaboration, allow for the development and monitoring of a care plan, integrate with the existing IT environment, be easy to use, accommodate different levels of patient literacy, and allow for easy sharing of educational materials to support nutrition education.

Keywords: telehealth, nutrition, diabetes, telenutrition, teleconsultation, telemonitoring

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Authors: Thirakorn Maneerat, Darunee Jongudomkarn, Jiraporn Khiewyoo

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Family quality of life of families who have persons with disabilities is a core concern in government services and community health promotion to deal with the multidimensionality of today’s health and societal issues. The number of families who have persons with disabilities in Thailand is gradually increasing. However, facilitation and evaluation of such family quality of life are limited by the lack of feasible tools. As a consequence, service provided for the families is not optimally facilitated and evaluated. This paper is part of a larger project which is aimed to develop a scale for measuring of family quality of life of families who have persons with developmental disabilities in Thailand, presenting the results of a three-round Delphi method involving 11 experts. The study was obtained during December 2013 to May 2014. The first round consisted of open-ended questionnaire and content analysis of the answers. The second round comprised a 5-point Likert scale structured questionnaire based on the first round analysis, with required the experts to identify the most relevant studied tool aspects. Their feedbacks levels of agreements were statistic analysis using the median, interquartile range and quartile deviation. The included criteria for items acceptance were greater than 3.50 of the median, lesser than 1.50 of interquartile range, and 0.65 or less of a quartile deviation. Finally, the proposed questionnaire was structured and validated by the experts in the third round. The results found that across all three rounds, the experts achieved 100% agreement on the five factors regarding to quality of life of a family who have person with disability were considered. These five factors with 38 items were included: 1) 10 items of family interactions; 2) 9 items of child rearing; 3) 7 items of physical and material resources; 4) 5 items of social-emotional status; and 7 items of disability-related services and welfare. Next step of the study was examined the construct validity by using factor analysis methods.

Keywords: tool development, family quality of life scale, person with disability, Delphi study

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Authors: Sedigheh Zarei

Abstract:

The aim of this research is to identify the key factors in shipping company’s port selection in order to providing their requirement. To identify and rank factors that are play the main role in selecting port for providing the ship supplies. At the first step, Data were collected via Semi-structured interviews, The aim was to generate knowledge on how shipping company select the port and suppliers for providing their needs. 37 port selection factors were chosen from the previous researches and field interviews and have been categorized into two groups of port's factor and the factors of services of suppliers companies. The current study adopts a questionnaire survey to the main shipping companies' operators in Iran. Their responses reveal that level of services of supplying companies and customs rules play the important role in selecting the ports. Our findings could affect decisions made by port authorities to consider that supporting the privet sections for ship chandelling business could have the best result in attracting ships.

Keywords: ship supplier, port selection, ship chandler, provision

Procedia PDF Downloads 445