Search results for: data sharing
25499 Optimizing The Residential Design Process Using Automated Technologies
Authors: Martin Georgiev, Milena Nanova, Damyan Damov
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Architects, engineers, and developers need to analyse and implement a wide spectrum of data in different formats, if they want to produce viable residential developments. Usually, this data comes from a number of different sources and is not well structured. The main objective of this research project is to provide parametric tools working with real geodesic data that can generate residential solutions. Various codes, regulations and design constraints are described by variables and prioritized. In this way, we establish a common workflow for architects, geodesists, and other professionals involved in the building and investment process. This collaborative medium ensures that the generated design variants conform to various requirements, contributing to a more streamlined and informed decision-making process. The quantification of distinctive characteristics inherent to typical residential structures allows a systematic evaluation of the generated variants, focusing on factors crucial to designers, such as daylight simulation, circulation analysis, space utilization, view orientation, etc. Integrating real geodesic data offers a holistic view of the built environment, enhancing the accuracy and relevance of the design solutions. The use of generative algorithms and parametric models offers high productivity and flexibility of the design variants. It can be implemented in more conventional CAD and BIM workflow. Experts from different specialties can join their efforts, sharing a common digital workspace. In conclusion, our research demonstrates that a generative parametric approach based on real geodesic data and collaborative decision-making could be introduced in the early phases of the design process. This gives the designers powerful tools to explore diverse design possibilities, significantly improving the qualities of the building investment during its entire lifecycle.Keywords: architectural design, residential buildings, urban development, geodesic data, generative design, parametric models, workflow optimization
Procedia PDF Downloads 5425498 Migration Management in the Eastern Mediterranean: The European Union's Legacy of the Securitization and Lacking on the Principle of Solidarity and Burden Sharing
Authors: Tasawar Ashraf
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The paper argues that the European Union’s securitized recourse to migration management which is lacking on the principle of solidarity has enhanced the sufferings of the asylum seekers by influencing the asylum policies of the non-EU states in the Eastern Mediterranean. The research critically analyses the development of the Turkish Asylum Policy and advocates that due to extraordinary burden of refugees and conceivable chances of getting EU membership, Turkey is developing its asylum policy essentially on the footprints of the EU. Such political and economic domination of the EU are resulting in the development of broader securitized migration zone in the EU and MENA region. Therefore, this paper critically analyses two interconnected issues, i.e., securitization of the migration in the EU and MENA region and the deficiency of the principle of solidarity and burden sharing in the European Agenda on Migration and how it reflects on Turkish asylum policy. This paper suggests that the EU must adopt a more generous resettle scheme ensuring the division of the refugee burden on all member and regional states by considering different political, social, and economic factors. Only such corporation can increase the pool of refugee hosting states by collaborating with the regional states to develop their asylum systems in accordance with international law.Keywords: European Agenda on Migration (EAM), EU, Middle East and North Africa (MENA), Treaty on the Functioning of the European Union (TFEU)
Procedia PDF Downloads 17925497 AI-Enabled Smart Contracts for Reliable Traceability in the Industry 4.0
Authors: Harris Niavis, Dimitra Politaki
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The manufacturing industry was collecting vast amounts of data for monitoring product quality thanks to the advances in the ICT sector and dedicated IoT infrastructure is deployed to track and trace the production line. However, industries have not yet managed to unleash the full potential of these data due to defective data collection methods and untrusted data storage and sharing. Blockchain is gaining increasing ground as a key technology enabler for Industry 4.0 and the smart manufacturing domain, as it enables the secure storage and exchange of data between stakeholders. On the other hand, AI techniques are more and more used to detect anomalies in batch and time-series data that enable the identification of unusual behaviors. The proposed scheme is based on smart contracts to enable automation and transparency in the data exchange, coupled with anomaly detection algorithms to enable reliable data ingestion in the system. Before sensor measurements are fed to the blockchain component and the smart contracts, the anomaly detection mechanism uniquely combines artificial intelligence models to effectively detect unusual values such as outliers and extreme deviations in data coming from them. Specifically, Autoregressive integrated moving average, Long short-term memory (LSTM) and Dense-based autoencoders, as well as Generative adversarial networks (GAN) models, are used to detect both point and collective anomalies. Towards the goal of preserving the privacy of industries' information, the smart contracts employ techniques to ensure that only anonymized pointers to the actual data are stored on the ledger while sensitive information remains off-chain. In the same spirit, blockchain technology guarantees the security of the data storage through strong cryptography as well as the integrity of the data through the decentralization of the network and the execution of the smart contracts by the majority of the blockchain network actors. The blockchain component of the Data Traceability Software is based on the Hyperledger Fabric framework, which lays the ground for the deployment of smart contracts and APIs to expose the functionality to the end-users. The results of this work demonstrate that such a system can increase the quality of the end-products and the trustworthiness of the monitoring process in the smart manufacturing domain. The proposed AI-enabled data traceability software can be employed by industries to accurately trace and verify records about quality through the entire production chain and take advantage of the multitude of monitoring records in their databases.Keywords: blockchain, data quality, industry4.0, product quality
Procedia PDF Downloads 19025496 Key Factors for Stakeholder Engagement and Sustainable Development
Authors: Jo Rhodes, Bruce Bergstrom, Peter Lok, Vincent Cheng
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The aim of this study is to determine key factors and processes for multinationals (MNCs) to develop an effective stakeholder engagement and sustainable development framework. A qualitative multiple-case approach was used. A triangulation method was adopted (interviews, archival documents and observations) to collect data on three global firms (MNCs). 9 senior executives were interviewed for this study (3 from each firm). An initial literature review was conducted to explore possible practices and factors (the deductive approach) to sustainable development. Interview data were analysed using Nvivo to obtain appropriate nodes and themes for the framework. A comparison of findings from interview data and themes, factors developed from the literature review and cross cases comparison were used to develop the final conceptual framework (the inductive approach). The results suggested that stakeholder engagement is a key mediator between ‘stakeholder network’ (internal and external factors) and outcomes (corporate social responsibility, social capital, shared value and sustainable development). Key internal factors such as human capital/talent, technology, culture, leadership and processes such as collaboration, knowledge sharing and co-creation of value with stakeholders were identified. These internal factors and processes must be integrated and aligned with external factors such as social, political, cultural, environment and NGOs to achieve effective stakeholder engagement.Keywords: stakeholder, engagement, sustainable development, shared value, corporate social responsibility
Procedia PDF Downloads 51525495 Information Sharing with Potential Users of Traditional Knowledge under Provisions of Nagoya Protocol: Issues of Participation of Indigenous People and Local Communities
Authors: Hasrat Arjjumend, Sabiha Alam
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The Nagoya Protocol is landmark international legislation governing access to genetic resources and benefit sharing from utilization of genetic resource and traditional knowledge. The field implications of the international law have been assessed by surveying academic/ research institutions, civil society organizations (CSOs) and concerned individuals, who gave their opinions on whether the provider parties (usually developing countries) would ensure effective participation of Indigenous people and local communities (ILCs) in establishing the mechanisms to inform the potential users of traditional knowledge (TK) about their obligations under art. 12.2 of Nagoya Protocol. First of all, involvement and participation of ILCs in suggested clearing-house mechanisms of the Parties are seldom witnessed. Secondly, as respondents expressed, it is doubtful that developing countries would ensure effective participation of ILCs in establishing the mechanisms to inform the potential users of TK about their obligations. Yet, as most of ILCs speak and understand local or indigenous languages, whether the Nagoya Protocol provides or not, it is a felt need that the Parties should disclose information in a language understandable to ILCs. Alternative opinions indicate that if TK held by ILCs is disclosed, the value is gone. Therefore, it should be protected by the domestic law first and should be disclosed then.Keywords: genetic resources, indigenous people, language, Nagoya protocol, participation, traditional knowledge
Procedia PDF Downloads 15125494 Two-stage Robust Optimization for Collaborative Distribution Network Design Under Uncertainty
Authors: Reza Alikhani
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This research focuses on the establishment of horizontal cooperation among companies to enhance their operational efficiency and competitiveness. The study proposes an approach to horizontal collaboration, called coalition configuration, which involves partnering companies sharing distribution centers in a network design problem. The paper investigates which coalition should be formed in each distribution center to minimize the total cost of the network. Moreover, potential uncertainties, such as operational and disruption risks, are considered during the collaborative design phase. To address this problem, a two-stage robust optimization model for collaborative distribution network design under surging demand and facility disruptions is presented, along with a column-and-constraint generation algorithm to obtain exact solutions tailored to the proposed formulation. Extensive numerical experiments are conducted to analyze solutions obtained by the model in various scenarios, including decisions ranging from fully centralized to fully decentralized settings, collaborative versus non-collaborative approaches, and different amounts of uncertainty budgets. The results show that the coalition formation mechanism proposes some solutions that are competitive with the savings of the grand coalition. The research also highlights that collaboration increases network flexibility and resilience while reducing costs associated with demand and capacity uncertainties.Keywords: logistics, warehouse sharing, robust facility location, collaboration for resilience
Procedia PDF Downloads 7025493 Performance Analysis of IDMA Scheme Using Quasi-Cyclic Low Density Parity Check Codes
Authors: Anurag Saxena, Alkesh Agrawal, Dinesh Kumar
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The next generation mobile communication systems i.e. fourth generation (4G) was developed to accommodate the quality of service and required data rate. This project focuses on multiple access technique proposed in 4G communication systems. It is attempted to demonstrate the IDMA (Interleave Division Multiple Access) technology. The basic principle of IDMA is that interleaver is different for each user whereas CDMA employs different signatures. IDMA inherits many advantages of CDMA such as robust against fading, easy cell planning; dynamic channel sharing and IDMA increase the spectral efficiency and reduce the receiver complexity. In this, performance of IDMA is analyzed using QC-LDPC coding scheme further it is compared with LDPC coding and at last BER is calculated and plotted in MATLAB.Keywords: 4G, QC-LDPC, CDMA, IDMA
Procedia PDF Downloads 32325492 Web-GIS Technology: A Tool for Farm-to-Market Road Project Profiling and Proposal Prioritization of the Philippines’ Department of Agriculture
Authors: Elbert S. Moyon, Edsel Matt O. Morales, Jaymer M. Jayoma, Kent C. Espejon, Jayson C. Dollete, Mark Phil B. Pacot
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This research paper focuses on the potential of using Web-GIS technology in prioritizing farm-to-market road projects by the Philippines’ Department of Agriculture (DA). The study aimed to explore the benefits of Web-GIS in addressing the limitations faced by the DA in terms of Farm to Market Road profiling and project prioritization, which include a lack of access to updated data, limited spatial analysis capabilities, and difficulties in sharing information between stakeholders. The research methodology involves a comprehensive literature review and a case study of a Web-GIS application developed for the DA, which was used to profile and prioritize farm-to-market road projects in the Philippines. The results showed that the Web-GIS technology provides the DA with an effective tool for analyzing and visualizing data, which can help in profiling and prioritizing road projects based on various criteria such as economic, social, and environmental impacts. The study also showed that Web-GIS technology could help in reducing the time and effort required for road project prioritization and improve communication between stakeholders.Keywords: GIS, web application, farm-to-market road, FMR prioritization, Django, GeoServer
Procedia PDF Downloads 8325491 Lies of Police Interrogators in the Ultimatum Game
Authors: Eitan Elaad
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The present study's purpose was to examine lyingand pretend fairness by police interrogators in sharing situations. Forty police officers and 40 laypeople from the community, all males, self-assessed their lie-telling ability, rated the frequency of their lies, evaluated the acceptability of lying, and indicated using rational and intuitive thinking while lying. Next, according to the ultimatum game procedure, participants were asked to share 100 points with a virtual target, either a male police interrogator or a male layman. Participantsallocated points to the target person bearing in mind that the other person must accept their offer. Participants' goal was to retain as many points as possible, and to this end, they could tell the target person that fewer than 100 points were available for distribution. The difference between the available 100 points and the sum of points designated for sharing defines lying. The ratio of offered and designated points defines pretend fairness. Results indicate that those police officers lied more than laypeople. Similar results emergedeven when the target person was a police interrogator. However, police interrogators presented higher pretend fairness than laypeople. The higher pretend fairness may be in line with interrogation tactics of persuasion used in the criminal interrogation. Higher-lying frequency reported by police interrogators compared with laypeople support the present results. Finally, lie acceptability predicted lying in the ultimatum game. Specifically, participants who rated lying as more acceptable tended to lie more than low acceptability raters.Keywords: lying, police interrogators, lie acceptability, ultimatum game, pretend fairness
Procedia PDF Downloads 15425490 A Study of Relational Factors Associated with Online Celebrity Business and Consumer Purchase Intention
Authors: Sixing Chen, Shuai Yang
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Online celebrity business, also known as Internet celebrity business (or Wanghong business in Chinese), is an emerging relational C2C business model, and an alternative to traditional C2C transactional business models. There are already millions of these consumers, and this number is growing. In this model, consumer purchase decisions are driven by recommendations and endorsements in videos posted online by celebrities. The purpose of this paper is to determine the relational constructs within consumer relationships in the Internet celebrity business model and to investigate relationships between the constructs and consumer purchase intention. A questionnaire-based study was conducted with consumers who had an awareness of, or prior purchase experience with online celebrities. The results of exploratory factor analysis (EFA) and multiple regression analysis revealed three valid relational constructs: product experience sharing, lifestyle association, and real-time interaction. This study indicated that these constructs had the direct effect on consumer preference and purchase intention. The findings of this study provide insight into a business model in which online shopping is driven by celebrities. They suggest that online celebrities should pay more attention to product experience sharing, life style association and real-time interaction for managing their product promotions. These are the most salient factors with respect to the relational constructs identified in this study.Keywords: customer relationship, customer to customer, Internet celebrity, online celebrity, online marketing, purchase intention
Procedia PDF Downloads 31925489 Mobile Traffic Management in Congested Cells using Fuzzy Logic
Authors: A. A. Balkhi, G. M. Mir, Javid A. Sheikh
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To cater the demands of increasing traffic with new applications the cellular mobile networks face new changes in deployment in infrastructure for making cellular networks heterogeneous. To reduce overhead processing the densely deployed cells require smart behavior with self-organizing capabilities with high adaptation to the neighborhood. We propose self-organization of unused resources usually excessive unused channels of neighbouring cells with densely populated cells to reduce handover failure rates. The neighboring cells share unused channels after fulfilling some conditional candidature criterion using threshold values so that they are not suffered themselves for starvation of channels in case of any abrupt change in traffic pattern. The cells are classified as ‘red’, ‘yellow’, or ‘green’, as per the available channels in cell which is governed by traffic pattern and thresholds. To combat the deficiency of channels in red cell, migration of unused channels from under-loaded cells, hierarchically from the qualified candidate neighboring cells is explored. The resources are returned back when the congested cell is capable of self-contained traffic management. In either of the cases conditional sharing of resources is executed for enhanced traffic management so that User Equipment (UE) is provided uninterrupted services with high Quality of Service (QoS). The fuzzy logic-based simulation results show that the proposed algorithm is efficiently in coincidence with improved successful handoffs.Keywords: candidate cell, channel sharing, fuzzy logic, handover, small cells
Procedia PDF Downloads 12125488 Copyright Clearance for Artificial Intelligence Training Data: Challenges and Solutions
Authors: Erva Akin
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– The use of copyrighted material for machine learning purposes is a challenging issue in the field of artificial intelligence (AI). While machine learning algorithms require large amounts of data to train and improve their accuracy and creativity, the use of copyrighted material without permission from the authors may infringe on their intellectual property rights. In order to overcome copyright legal hurdle against the data sharing, access and re-use of data, the use of copyrighted material for machine learning purposes may be considered permissible under certain circumstances. For example, if the copyright holder has given permission to use the data through a licensing agreement, then the use for machine learning purposes may be lawful. It is also argued that copying for non-expressive purposes that do not involve conveying expressive elements to the public, such as automated data extraction, should not be seen as infringing. The focus of such ‘copy-reliant technologies’ is on understanding language rules, styles, and syntax and no creative ideas are being used. However, the non-expressive use defense is within the framework of the fair use doctrine, which allows the use of copyrighted material for research or educational purposes. The questions arise because the fair use doctrine is not available in EU law, instead, the InfoSoc Directive provides for a rigid system of exclusive rights with a list of exceptions and limitations. One could only argue that non-expressive uses of copyrighted material for machine learning purposes do not constitute a ‘reproduction’ in the first place. Nevertheless, the use of machine learning with copyrighted material is difficult because EU copyright law applies to the mere use of the works. Two solutions can be proposed to address the problem of copyright clearance for AI training data. The first is to introduce a broad exception for text and data mining, either mandatorily or for commercial and scientific purposes, or to permit the reproduction of works for non-expressive purposes. The second is that copyright laws should permit the reproduction of works for non-expressive purposes, which opens the door to discussions regarding the transposition of the fair use principle from the US into EU law. Both solutions aim to provide more space for AI developers to operate and encourage greater freedom, which could lead to more rapid innovation in the field. The Data Governance Act presents a significant opportunity to advance these debates. Finally, issues concerning the balance of general public interests and legitimate private interests in machine learning training data must be addressed. In my opinion, it is crucial that robot-creation output should fall into the public domain. Machines depend on human creativity, innovation, and expression. To encourage technological advancement and innovation, freedom of expression and business operation must be prioritised.Keywords: artificial intelligence, copyright, data governance, machine learning
Procedia PDF Downloads 8525487 Applications of Big Data in Education
Authors: Faisal Kalota
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Big Data and analytics have gained a huge momentum in recent years. Big Data feeds into the field of Learning Analytics (LA) that may allow academic institutions to better understand the learners’ needs and proactively address them. Hence, it is important to have an understanding of Big Data and its applications. The purpose of this descriptive paper is to provide an overview of Big Data, the technologies used in Big Data, and some of the applications of Big Data in education. Additionally, it discusses some of the concerns related to Big Data and current research trends. While Big Data can provide big benefits, it is important that institutions understand their own needs, infrastructure, resources, and limitation before jumping on the Big Data bandwagon.Keywords: big data, learning analytics, analytics, big data in education, Hadoop
Procedia PDF Downloads 42725486 Traffic Congestions Modeling and Predictions by Social Networks
Authors: Bojan Najdenov, Danco Davcev
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Reduction of traffic congestions and the effects of pollution and waste of resources that come with them has been a big challenge in the past decades. Having reliable systems to facilitate the process of modeling and prediction of traffic conditions would not only reduce the environmental pollution, but will also save people time and money. Social networks play big role of people’s lives nowadays providing them means of communicating and sharing thoughts and ideas, that way generating huge knowledge bases by crowdsourcing. In addition to that, crowdsourcing as a concept provides mechanisms for fast and relatively reliable data generation and also many services are being used on regular basis because they are mainly powered by the public as main content providers. In this paper we present the Social-NETS-Traffic-Control System (SNTCS) that should serve as a facilitator in the process of modeling and prediction of traffic congestions. The main contribution of our system is to integrate data from social networks as Twitter and also implements a custom created crowdsourcing subsystem with which users report traffic conditions using an android application. Our first experience of the usage of the system confirms that the integrated approach allows easy extension of the system with other social networks and represents a very useful tool for traffic control.Keywords: traffic, congestion reduction, crowdsource, social networks, twitter, android
Procedia PDF Downloads 48325485 Erosion of Culture through Democratization
Authors: Mladen Milicevic
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This paper explores how the explosion of computer technologies has allowed for the democratization of many aspects of human activities, which were in the past only available through the institutionalized channels of production and distribution. We will going to use as an example the music recording industries, just to illustrate this process, but the analogies to other activities and aspects of human life can easily be extrapolated from it.Keywords: aura, democratization, music industry, music sharing, paradigm-shift
Procedia PDF Downloads 23625484 How Whatsappization of the Chatbot Affects User Satisfaction, Trust, and Acceptance in a Drive-Sharing Task
Authors: Nirit Gavish, Rotem Halutz, Liad Neta
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Nowadays, chatbots are gaining more and more attention due to the advent of large language models. One of the important considerations in chatbot design is how to create an interface to achieve high user satisfaction, trust, and acceptance. Since WhatsApp conversations sometimes substitute for face-to-face communication, we studied whether WhatsAppization of the chatbot -making the conversation resemble a WhatsApp conversation more- will improve user satisfaction, trust, and acceptance, or whether the opposite will occur due to the Uncanny Valley (UV) effect. The task was a drive-sharing task, in which participants communicated with a textual chatbot via WhatsApp and could decide whether to participate in a ride to college with a driver suggested by the chatbot. WhatsAppization of the chatbot was done in two ways: By a dialog-style conversation (Dialog versus No Dialog), and by adding WhatsApp indicators – “Last Seen”, “Connected”, “Read Receipts”, and “Typing…” (Indicators versus No Indicators). Our 120 participants were randomly assigned to one of the four 2 by 2 design groups, with 30 participants in each. They interacted with the WhatsApp chatbot and then filled out a questionnaire. The results demonstrated that, as expected from the manipulation, the interaction with the chatbot was longer for the dialog condition compared to the no dialog. This extra interaction, however, did not lead to higher acceptance -quite the opposite, since participants in the dialog condition were less willing to implement the decision made at the end of the conversation with the chatbot and continue the interaction with the driver they chose. The results are even more striking when considering the Indicators condition. Both for the satisfaction measures and the trust measures, participants’ ratings were lower in the Indicators condition compared to the No Indicators. Participants in the Indicators condition felt that the ride search process was harder to operate, and slower (even though the actual interaction time was similar). They were less convinced that the chatbot suggested real trips and they trusted the person offering the ride and referred to them by the chatbot less. These effects were more evident for participants who preferred to share their rides using WhatsApp compared to participants who preferred chatbots for that purpose. Considering our findings, we can say that the WhatsAppization of the chatbot was detrimental. This is true for the both chatbot WhatsAppization methods – by making the conversation more a dialog and adding WhatsApp indicators. For the chosen drive-sharing task, the results were, in addition to lower satisfaction, less trust in the chatbot’s suggestion and even in the driver suggested by the chatbot, and lower willingness to actually undertake the suggested ride. In addition, it seems that the most problematic WhatsAppization method was using WhatsApp’s indicators during the interaction with the chatbot. The current study suggests that a conversation with an artificial agent should also not imitate a WhatsApp conversation very closely. With the proliferation of WhatsApp use, the emotional and social aspect of face-to face commination are moving to WhatsApp communication. Based on the current study’s findings, it is possible that the UV effect also occurs in WhatsAppization, and not only in humanization, of the chatbot, with a similar feeling of eeriness, and is more pronounced for people who prefer to use WhatsApp over chatbots. The current research can serve as a starting point to study the very interesting and important topic of chatbots WhatsAppization. More methods of WhatsAppization and other tasks could be the focus of further studies.Keywords: chatbot, WhatsApp, humanization, Uncanny Valley, drive sharing
Procedia PDF Downloads 4925483 Language in International Students’ Cross-Cultural Adaptation: Case Study of Ukrainian Students in Taiwan and Lithuania
Authors: Min-Hsun Liao
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Since the outbreak of war between Russia and Ukraine in February 2022, universities around the world have extended their helping hands to welcome Ukrainian students whose academic careers have been unexpectedly interrupted. Tunghai University (THU) in Taiwan and Mykolas Romeris University (MRU) in Lithuania are among the many other universities offering short- and long-term scholarships to host Ukrainian students in the midst of the war crisis. This mixed-methods study examines the cross-cultural adjustment processes of Ukrainian students in Taiwan. The research team at MRU will also conduct a parallel study with their Ukrainian students. Both institutions are committed to gaining insights into the adjustment processes of these students through cross-institutional collaboration. Studies show that while international students come from different cultural backgrounds, the difficulties they face while studying abroad are comparable and vary in intensity. These difficulties range from learning the language of the host country, adopting cultural customs, and adapting culinary preferences to the sociocultural shock of being separated from family and friends. These problems have been the subject of numerous studies. Study findings indicate that these challenges, if not properly addressed, can lead to significant stress, despair, and failure in academics or other endeavors for international students, not to mention those who have had to leave home involuntarily and settle into a completely new environment. Among these challenges, the language of the host country is foremost. The issue of international students' adjustment, particularly language acquisition, is critical to the psychological, academic, and sociocultural well-being of individuals. Both quantitative and qualitative data will be collected: 1) the International Student Cross-cultural Adaptation Survey (ISCAS) will be distributed to all Ukrainian students in both institutions; 2) one-on-one interviews will be conducted to gain a deeper understanding of their adaptations; and 3) t-tests or ANOVA will be calculated to determine significant differences between the languages used and the adaptation patterns of Ukrainian students. The significance of this study is consistent with three SDGs, namely quality education, peace/justice, and strong institutions and partnerships for the goals. The THU and MRU research teams believe that through partnership, both institutions can benefit exponentially from sharing the data, avoiding fixed interpretation, and sharing contextual insights, which will help improve the overall quality of education for international students and promote peace/justice through strong institutions. The impact of host country language proficiency on academic and sociocultural adjustments remains inconclusive. Therefore, the outcome of the study will shed new light on the relationship between language and various adjustments. In addition, the feedback from Ukrainian students will help other host countries better serve international students who must flee their home countries for an undisturbed education.Keywords: international students, ukrainian students, cross-cultural adaptation, host country language, acculturation theory
Procedia PDF Downloads 7825482 Re-identification Risk and Mitigation in Federated Learning: Human Activity Recognition Use Case
Authors: Besma Khalfoun
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In many current Human Activity Recognition (HAR) applications, users' data is frequently shared and centrally stored by third parties, posing a significant privacy risk. This practice makes these entities attractive targets for extracting sensitive information about users, including their identity, health status, and location, thereby directly violating users' privacy. To tackle the issue of centralized data storage, a relatively recent paradigm known as federated learning has emerged. In this approach, users' raw data remains on their smartphones, where they train the HAR model locally. However, users still share updates of their local models originating from raw data. These updates are vulnerable to several attacks designed to extract sensitive information, such as determining whether a data sample is used in the training process, recovering the training data with inversion attacks, or inferring a specific attribute or property from the training data. In this paper, we first introduce PUR-Attack, a parameter-based user re-identification attack developed for HAR applications within a federated learning setting. It involves associating anonymous model updates (i.e., local models' weights or parameters) with the originating user's identity using background knowledge. PUR-Attack relies on a simple yet effective machine learning classifier and produces promising results. Specifically, we have found that by considering the weights of a given layer in a HAR model, we can uniquely re-identify users with an attack success rate of almost 100%. This result holds when considering a small attack training set and various data splitting strategies in the HAR model training. Thus, it is crucial to investigate protection methods to mitigate this privacy threat. Along this path, we propose SAFER, a privacy-preserving mechanism based on adaptive local differential privacy. Before sharing the model updates with the FL server, SAFER adds the optimal noise based on the re-identification risk assessment. Our approach can achieve a promising tradeoff between privacy, in terms of reducing re-identification risk, and utility, in terms of maintaining acceptable accuracy for the HAR model.Keywords: federated learning, privacy risk assessment, re-identification risk, privacy preserving mechanisms, local differential privacy, human activity recognition
Procedia PDF Downloads 1325481 Development of mHealth Information in Community Based on Geographical Information: A Case Study from Saraphi District, Chiang Mai, Thailand
Authors: Waraporn Boonchieng, Ekkarat Boonchieng, Wilawan Senaratana, Jaras Singkaew
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Geographical information system (GIS) is a designated system widely used for collecting and analyzing geographical data. Since the introduction of ultra-mobile, 'smart' devices, investigators, clinicians, and even the general public have had powerful new tools for collecting, uploading and accessing information in the field. Epidemiology paired with GIS will increase the efficacy of preventive health care services. The objective of this study is to apply GPS location services that are available on the common mobile device with district health systems, storing data on our private cloud system. The mobile application has been developed for use on iOS, Android, and web-based platforms. The system consists of two parts of district health information, including recorded resident data forms and individual health recorded data forms, which were developed and approved by opinion sharing and public hearing. The application's graphical user interface was developed using HTML5 and PHP with MySQL as a database management system (DBMS). The reporting module of the developed software displays data in a variety of views, from traditional tables to various types of high-resolution, layered graphics, incorporating map location information with street views from Google Maps. Multi-extension exporting is also supported, utilizing standard platforms such as PDF, PNG, JPG, and XLS. The data were collected in the database beginning in March 2013, by district health volunteers and district youth volunteers who had completed the application training program. District health information consisted of patients’ household coordinates, individual health data, social and economic information. This was combined with Google Street View data, collected in March 2014. Studied groups consisted of 16,085 (67.87%) and 47,811 (59.87%) of the total 23,701 households and 79,855 people were collected by the system respectively, in Saraphi district, Chiang Mai Province. The report generated from the system has had a major benefit directly to the Saraphi District Hospital. Healthcare providers are able to use the basic health data to provide a specific home health care service and also to create health promotion activities according to medical needs of the people in the community.Keywords: health, public health, GIS, geographic information system
Procedia PDF Downloads 33725480 Research on Innovation Service based on Science and Technology Resources in Beijing-Tianjin-Hebei
Authors: Runlian Miao, Wei Xie, Hong Zhang
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In China, Beijing-Tianjin-Hebei is regarded as a strategically important region because itenjoys highest development in economic development, opening up, innovative capacity and andpopulation. Integrated development of Beijing-Tianjin-Hebei region is increasingly emphasized by the government recently years. In 2014, it has ascended to one of the national great development strategies by Chinese central government. In 2015, Coordinated Development Planning Compendium for Beijing-Tianjin-Hebei Region was approved. Such decisions signify Beijing-Tianjin-Hebei region would lead innovation-driven economic development in China. As an essential factor to achieve national innovation-driven development and significant part of regional industry chain, the optimization of science and technology resources allocation will exert great influence to regional economic transformation and upgrading and innovation-driven development. However, unbalanced distribution, poor sharing of resources and existence of information isolated islands have contributed to different interior innovation capability, vitality and efficiency, which impeded innovation and growth of the whole region. Under such a background, to integrate and vitalize regional science and technology resources and then establish high-end, fast-responding and precise innovation service system basing on regional resources, would be of great significance for integrated development of Beijing-Tianjin-Hebei region and even handling of unbalanced and insufficient development problem in China. This research uses the method of literature review and field investigation and applies related theories prevailing home and abroad, centering service path of science and technology resources for innovation. Based on the status quo and problems of regional development of Beijing-Tianjin-Hebei, theoretically, the author proposed to combine regional economics and new economic geography to explore solution to problem of low resource allocation efficiency. Further, the author puts forward to applying digital map into resource management and building a platform for information co-building and sharing. At last, the author presents the thought to establish a specific service mode of ‘science and technology plus digital map plus intelligence research plus platform service’ and suggestion on co-building and sharing mechanism of 3 (Beijing, Tianjin and Hebei ) plus 11 (important cities in Hebei Province).Keywords: Beijing-Tianjin-Hebei, science and technology resources, innovation service, digital platform
Procedia PDF Downloads 16125479 Utilizing Experiential Teaching Strategies to Reduce the Incidence of Falls in Patients in Orthopedic Wards
Authors: Yu-Shi Ye, Jia-Min Wu, Jhih-Ci Li
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Background: Most orthopedic inpatients and primary caregivers are elderly, and patients are at high risk of falls. We set up a quality control team to analyze the root cause and found the following issues: 1. The nursing staff did not conduct cognitive assessments of patients and their primary caregivers to ensure that health education content was understood. 2. Nurses prefer to use spoken language in health education but lack the skills to use diverse teaching materials. 3. Newly recruited nurses have insufficient awareness of fall prevention. Methods: The study subjects were 16 nurses in the orthopedic ward of a teaching hospital in central Taiwan. We implemented the following strategies: 1. Developed a fall simulation teaching plan and conducted teaching courses and assessments in the morning meeting; 2. Designed and used a "fall prevention awareness card" to improve the prevention awareness of elderly patients; 3. All staff (including new staff) received experiential education training. Results: In 2021, 40% of patients in the orthopedic wards were aged 60-79 years (792/1979) with a high risk of falls. According to data collection, the incidence of falls in hospitalized patients was 0.04% (5/12651), which exceeded the threshold of 0.02% in our ward. After completing the on-the-job education training in October, the nursing staff expressed that they were more aware of the special situation of fall prevention. Through practical sharing and drills, combined with experiential teaching strategies, nurses can reconstruct the safety awareness of fall prevention and deepen their cognitive memory. Participants scored between 30 and 80 on the pretest (16 students, mean: 72.6) and between 90 and 100 on the post-test (16 students, mean: 92.6), resulting in a 73.8% improvement in overall scores. We have a total of 4 new employees who have all completed the first 3 months of compulsory PGY courses. From January to April 2022, the incidence of falls in hospitalized patients was 0.025% (1/3969). We have made good improvements and will continue to track the outcome. Discussion: In addition to enhancing the awareness of falls among nursing staff, how-to guide patients and primary caregivers to prevent falls is also the focus of improvement. The proper way of health education can be better understood through practical exercises and case sharing.Keywords: experiential teaching strategies, fall prevention, cognitive card, elderly patients, orthopedic wards
Procedia PDF Downloads 5325478 Role of Social Media in Imparting Climate Change through Diffusion of Innovation
Authors: Zahra Ali Abbasi, Syed Muhammad Saqib Saleem
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This research explores the relationship between social media and awareness about climate change amongst the university students of Lahore, Pakistan. The aim is to understand how the people of Pakistan perceive climate change, especially on the social media. A deductive and quantitative method is applied on the research to find out the awareness of climate change in the people using social media. For this purpose, a survey method is used, to analyze the response from 167 online respondents through stratified random sampling technique. The relation between multiple variables including awareness about important climatic events like Paris agreement, GreenTube, Smog in Lahore, Floods in Pakistan and other eminent incidents of climate change and social media are calculated by analyzing social media as a source to impart information about climate change. The results show that as people get aware of climate change, they post about different national and international events/incidents of climate which reveal a significant relationship between respondents' awareness about climate change and their posting and sharing of content about climate change. Another test indicates that respondents’ post/share/comment (impart) information about climate change when there is a shift in the climate both globally and nationally. However, the significance of both these correlations has been found to be negligible. Social media being an independent platform holds greater influencing power, hence, as consumers of the environment the users hold the responsibility of producing and sharing content at a global platform about climate. However, matters of politics, economy and religion seem to have overshadowed the significance of climate.Keywords: climate change, diffusion of innovation, environment, social media, Pakistan
Procedia PDF Downloads 19725477 Resources-Based Ontology Matching to Access Learning Resources
Authors: A. Elbyed
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Nowadays, ontologies are used for achieving a common understanding within a user community and for sharing domain knowledge. However, the de-centralized nature of the web makes indeed inevitable that small communities will use their own ontologies to describe their data and to index their own resources. Certainly, accessing to resources from various ontologies created independently is an important challenge for answering end user queries. Ontology mapping is thus required for combining ontologies. However, mapping complete ontologies at run time is a computationally expensive task. This paper proposes a system in which mappings between concepts may be generated dynamically as the concepts are encountered during user queries. In this way, the interaction itself defines the context in which small and relevant portions of ontologies are mapped. We illustrate application of the proposed system in the context of Technology Enhanced Learning (TEL) where learners need to access to learning resources covering specific concepts.Keywords: resources query, ontologies, ontology mapping, similarity measures, semantic web, e-learning
Procedia PDF Downloads 31325476 Analysis of Big Data
Authors: Sandeep Sharma, Sarabjit Singh
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As per the user demand and growth trends of large free data the storage solutions are now becoming more challenge-able to protect, store and to retrieve data. The days are not so far when the storage companies and organizations are start saying 'no' to store our valuable data or they will start charging a huge amount for its storage and protection. On the other hand as per the environmental conditions it becomes challenge-able to maintain and establish new data warehouses and data centers to protect global warming threats. A challenge of small data is over now, the challenges are big that how to manage the exponential growth of data. In this paper we have analyzed the growth trend of big data and its future implications. We have also focused on the impact of the unstructured data on various concerns and we have also suggested some possible remedies to streamline big data.Keywords: big data, unstructured data, volume, variety, velocity
Procedia PDF Downloads 54825475 The Lived Experiences of Stigma in Non-offending Pedophiles
Authors: Rebecca Heron, Steal Adcock, Karen Parsonson
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Non-offending pedophiles are an under- researched, hard to reach population. This group of individuals are often hesitant to come forward and fail to seek help ongoing stigma experienced in society.In order to better understand non-offending pedophiles experiences of their identity and the stigma they face, semi-structured qualitative interviews were conducted with 10 non-offending pedophiles, who were recruited through online support groups for individuals who have sexual attractions towards children. Participants were interviewed over skype, and the data was analysed using interpretative phenomenological analysis (IPA) approach, anda number of themes were generated from the rich data set produced. Four main themes emerged, providing insight into how non-offending pedophiles experience stigma. The themes included ‘stigma in relation to themselves’, ‘others’, ‘the media portrayal’and ‘impact of the stigma of MAP’s seeking treatment’. Findings are discussed in relation to existing literature, and practical recommendations are proposed to hopefully allow this population to feel more comfortable sharing their sexual interests, which will allow them to seek help resulting in them not offending and, ultimately, the prevention of sexual abuse. This study fills the void in terms of lack of research with this population, especially when it comes to qualitative in depth studies, including not just male minor attracted persons but female minor attracted persons as well.Keywords: pedophillia, stigma, non-offending pedophiles, minor attracted persons, prevention
Procedia PDF Downloads 12825474 Research of Data Cleaning Methods Based on Dependency Rules
Authors: Yang Bao, Shi Wei Deng, WangQun Lin
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This paper introduces the concept and principle of data cleaning, analyzes the types and causes of dirty data, and proposes several key steps of typical cleaning process, puts forward a well scalability and versatility data cleaning framework, in view of data with attribute dependency relation, designs several of violation data discovery algorithms by formal formula, which can obtain inconsistent data to all target columns with condition attribute dependent no matter data is structured (SQL) or unstructured (NoSQL), and gives 6 data cleaning methods based on these algorithms.Keywords: data cleaning, dependency rules, violation data discovery, data repair
Procedia PDF Downloads 56425473 Integrating Cost-Benefit Assessment and Contract Design to Support Industrial Symbiosis Deployment
Authors: Robin Molinier
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Industrial symbiosis (I.S) is the realization of Industrial Ecology (I.E) principles in production systems in function. I.S consists in the use of waste materials, fatal energy, recirculated utilities and infrastructure/service sharing as resources for production. Environmental benefits can be achieved from resource conservation but economic profitability is required by the participating actors. I.S indeed involves several actors with their own objectives and resources so that each one must be satisfied by ex-ante arrangements to commit toward I.S execution (investments and transactions). Following the Resource-Based View of transactions we build a modular framework to assess global I.S profitability and to specify each actor’s contributions to costs and benefits in line with their resource endowments and performance requirements formulations. I.S projects specificities implied by the need for customization (asset specificity, non-homogeneity) induce the use of long-term contracts for transactions following Transaction costs economics arguments. Thus we propose first a taxonomy of costs and value drivers for I.S and an assignment to each actor of I.S specific risks that we identified as load profiles mismatch, quality problems and value fluctuations. Then appropriate contractual guidelines (pricing, cost sharing and warranties) that support mutual profitability are derived from the detailed identification of contributions by the cost-benefits model. This analytical framework helps identifying what points to focus on when bargaining over contracting for transactions and investments. Our methodology is applied to I.S archetypes raised from a literature survey on eco-industrial parks initiatives and practitioners interviews.Keywords: contracts, cost-benefit analysis, industrial symbiosis, risks
Procedia PDF Downloads 34025472 Volunteered Geographic Information Coupled with Wildfire Fire Progression Maps: A Spatial and Temporal Tool for Incident Storytelling
Authors: Cassandra Hansen, Paul Doherty, Chris Ferner, German Whitley, Holly Torpey
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Wildfire is a natural and inevitable occurrence, yet changing climatic conditions have increased the severity, frequency, and risk to human populations in the wildland/urban interface (WUI) of the Western United States. Rapid dissemination of accurate wildfire information is critical to both the Incident Management Team (IMT) and the affected community. With the advent of increasingly sophisticated information systems, GIS can now be used as a web platform for sharing geographic information in new and innovative ways, such as virtual story map applications. Crowdsourced information can be extraordinarily useful when coupled with authoritative information. Information abounds in the form of social media, emergency alerts, radio, and news outlets, yet many of these resources lack a spatial component when first distributed. In this study, we describe how twenty-eight volunteer GIS professionals across nine Geographic Area Coordination Centers (GACC) sourced, curated, and distributed Volunteered Geographic Information (VGI) from authoritative social media accounts focused on disseminating information about wildfires and public safety. The combination of fire progression maps with VGI incident information helps answer three critical questions about an incident, such as: where the first started. How and why the fire behaved in an extreme manner and how we can learn from the fire incident's story to respond and prepare for future fires in this area. By adding a spatial component to that shared information, this team has been able to visualize shared information about wildfire starts in an interactive map that answers three critical questions in a more intuitive way. Additionally, long-term social and technical impacts on communities are examined in relation to situational awareness of the disaster through map layers and agency links, the number of views in a particular region of a disaster, community involvement and sharing of this critical resource. Combined with a GIS platform and disaster VGI applications, this workflow and information become invaluable to communities within the WUI and bring spatial awareness for disaster preparedness, response, mitigation, and recovery. This study highlights progression maps as the ultimate storytelling mechanism through incident case studies and demonstrates the impact of VGI and sophisticated applied cartographic methodology make this an indispensable resource for authoritative information sharing.Keywords: storytelling, wildfire progression maps, volunteered geographic information, spatial and temporal
Procedia PDF Downloads 17925471 Knowledge Transfer among Cross-Functional Teams as a Continual Improvement Process
Authors: Sergio Mauricio Pérez López, Luis Rodrigo Valencia Pérez, Juan Manuel Peña Aguilar, Adelina Morita Alexander
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The culture of continuous improvement in organizations is very important as it represents a source of competitive advantage. This article discusses the transfer of knowledge between companies which formed cross-functional teams and used a dynamic model for knowledge creation as a framework. In addition, the article discusses the structure of cognitive assets in companies and the concept of "stickiness" (which is defined as an obstacle to the transfer of knowledge). The purpose of this analysis is to show that an improvement in the attitude of individual members of an organization creates opportunities, and that an exchange of information and knowledge leads to generating continuous improvements in the company as a whole. This article also discusses the importance of creating the proper conditions for sharing tacit knowledge. By narrowing gaps between people, mutual trust can be created and thus contribute to an increase in sharing. The concept of adapting knowledge to new environments will be highlighted, as it is essential for companies to translate and modify information so that such information can fit the context of receiving organizations. Adaptation will ensure that the transfer process is carried out smoothly by preventing "stickiness". When developing the transfer process on cross-functional teams (as opposed to working groups), the team acquires the flexibility and responsiveness necessary to meet objectives. These types of cross-functional teams also generate synergy due to the array of different work backgrounds of their individuals. When synergy is established, a culture of continuous improvement is created.Keywords: knowledge transfer, continuous improvement, teamwork, cognitive assets
Procedia PDF Downloads 32425470 “Referral for re-submission” – The Case of EFL Applied Linguistics Doctoral Defense Sessions
Authors: Alireza Jalilifar, Nadia Mayahi
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An oral defense is the examination of a doctoral program in which the candidates display their academic capacity through sharing and disseminating the findings of their study and defending their position. In this challenging criticism-generating context, the examiners evaluate the PhD dissertation critically so as to confirm its scholarly merit or lack of it. To identify the examiners’ expectations of the viva, this study used a conversation analytic approach for analyzing the data. The research is inductive in that it seeks to develop theory that is grounded in the data. The data comprised transcripts of the question and answer section of two applied linguistics doctoral defense sessions from two accredited Iranian state universities in 2019, both of which are among the top Iranian universities on the list of Times Higher Education World University Rankings. In spite of the similar shortcomings and deficiencies, for instance, in terms of innovation, development, sampling, and treatment, raised by the examiners, one of these defenses passed with distinction while the other was referred for re-submission. It seems that the outcome of a viva, in an EFL context, not only depends on adherence to the rules and regulations of doctoral research but is also influenced to a certain extent by the strictness of the examiners and the candidates’ language proficiency and effective negotiation and communication skills in this confrontational communicative event. The findings of this study provide evidence for the issues determining the success or failure of PhD candidates in displaying their claims of scholarship during their defense sessions. This study has implications for both applied linguistics doctoral students and academics in EFL contexts who try to prove and authenticate the doctorateness of a dissertation.Keywords: academic discourse, conversation analysis, doctoral defense, doctorateness, EFL
Procedia PDF Downloads 157