Search results for: keyword based retrieval

Authors: Hoyeon Park, Yunhwan Keon, Kyoung-Jae Kim

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Location Based Social Network services (LBSNs) is a new term that combines location based service and social network service (SNS). Unlike traditional SNS, LBSNs emphasizes empirical elements in the user's actual physical location. Point-of-Interest (POI) is the most important factor to implement LBSNs recommendation system. POI information is the most popular spot in the area. In this study, we would like to recommend POI to users in a specific area through recommendation system using collaborative filtering. The process is as follows: first, we will use different data sets based on Seoul and New York to find interesting results on human behavior. Secondly, based on the location-based activity information obtained from the personalized LBSNs, we have devised a new rating that defines the user's preference for the area. Finally, we have developed an automated rating algorithm from massive raw data using distributed systems to reduce advertising costs of LBSNs.

Keywords: location-based social network services, point-of-interest, recommender systems, business analytics

Procedia PDF Downloads 229

Authors: F. Arıkan, Z. Karakus

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Cancer is a widespread disease in the world and is the third reason of deaths among the chronic diseases. Educating patients and caregivers has a vital role for empowering them in managing disease and treatment's symptoms. Informing of the patients about their disease and treatment process decreases patient's distress and decisional conflicts, improves wellbeing of them, increase success of the treatment and survival. In this era, technological education methods are used for patients that have different chronic disease. Many studies indicated that especially web based patient education such as chronic obstructive lung disease; heart failure is more effective than printed materials. Web based education provide easiness to patients while they are reaching health services. It also has more advantages because of it decreases health cost and requirement of staff. It is thought that web based education may be beneficial method for cancer patient's empowerment in coping with the disease's symptoms. The aim of the study is evaluate the effectiveness of web based education for cancer patients' clinical outcomes.

Keywords: cancer patients, e-learning, nursing, web based education

Procedia PDF Downloads 432

Authors: Yun Chen, Qihang Liu, Catherine Ticehurst, Chandrama Sarker, Fazlul Karim, Dave Penton, Ashmita Sengupta

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The application of ICESAT-2 altimetry data in river hydrology critically depends on the accuracy of the mean water surface elevation (WSE) at a virtual station (VS) where satellite observations intersect with water. The ICESAT-2 track generates multiple VSs as it crosses the different water bodies. The difficulties are particularly pronounced in large river basins where there are many tributaries and meanders often adjacent to each other. One challenge is to split photon segments along a beam to accurately partition them to extract only the true representative water height for individual elements. As far as we can establish, there is no automated procedure to make this distinction. Earlier studies have relied on human intervention or river masks. Both approaches are unsatisfactory solutions where the number of intersections is large, and river width/extent changes over time. We describe here an automated approach called “auto-segmentation”. The accuracy of our method was assessed by comparison with river water level observations at 10 different stations on 37 different dates along the Lower Murray River, Australia. The congruence is very high and without detectable bias. In addition, we compared different outlier removal methods on the mean WSE calculation at VSs post the auto-segmentation process. All four outlier removal methods perform almost equally well with the same R2 value (0.998) and only subtle variations in RMSE (0.181–0.189m) and MAE (0.130–0.142m). Overall, the auto-segmentation method developed here is an effective and efficient approach to deriving accurate mean WSE at river VSs. It provides a much better way of facilitating the application of ICESAT-2 ATL13 altimetry to rivers compared to previously reported studies. Therefore, the findings of our study will make a significant contribution towards the retrieval of hydraulic parameters, such as water surface slope along the river, water depth at cross sections, and river channel bathymetry for calculating flow velocity and discharge from remotely sensed imagery at large spatial scales.

Keywords: lidar sensor, virtual station, cross section, mean water surface elevation, beam/track segmentation

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Authors: Xingyu Gao, Qiang Wu

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Patents play a crucial role in protecting innovation and intellectual property. Early prediction of the impact of artificial intelligence (AI) patents helps researchers and companies allocate resources and make better decisions. Understanding the key factors that influence patent impact can assist researchers in gaining a better understanding of the evolution of AI technology and innovation trends. Therefore, identifying highly impactful patents early and providing support for them holds immeasurable value in accelerating technological progress, reducing research and development costs, and mitigating market positioning risks. Despite the extensive research on AI patents, accurately predicting their early impact remains a challenge. Traditional methods often consider only single factors or simple combinations, failing to comprehensively and accurately reflect the actual impact of patents. This paper utilized the artificial intelligence patent database from the United States Patent and Trademark Office and the Len.org patent retrieval platform to obtain specific information on 35,708 AI patents. Using six machine learning models, namely Multiple Linear Regression, Random Forest Regression, XGBoost Regression, LightGBM Regression, Support Vector Machine Regression, and K-Nearest Neighbors Regression, and using early indicators of patents as features, the paper comprehensively predicted the impact of patents from three aspects: technical, social, and economic. These aspects include the technical leadership of patents, the number of citations they receive, and their shared value. The SHAP (Shapley Additive exPlanations) metric was used to explain the predictions of the best model, quantifying the contribution of each feature to the model's predictions. The experimental results on the AI patent dataset indicate that, for all three target variables, LightGBM regression shows the best predictive performance. Specifically, patent novelty has the greatest impact on predicting the technical impact of patents and has a positive effect. Additionally, the number of owners, the number of backward citations, and the number of independent claims are all crucial and have a positive influence on predicting technical impact. In predicting the social impact of patents, the number of applicants is considered the most critical input variable, but it has a negative impact on social impact. At the same time, the number of independent claims, the number of owners, and the number of backward citations are also important predictive factors, and they have a positive effect on social impact. For predicting the economic impact of patents, the number of independent claims is considered the most important factor and has a positive impact on economic impact. The number of owners, the number of sibling countries or regions, and the size of the extended patent family also have a positive influence on economic impact. The study primarily relies on data from the United States Patent and Trademark Office for artificial intelligence patents. Future research could consider more comprehensive data sources, including artificial intelligence patent data, from a global perspective. While the study takes into account various factors, there may still be other important features not considered. In the future, factors such as patent implementation and market applications may be considered as they could have an impact on the influence of patents.

Keywords: patent influence, interpretable machine learning, predictive models, SHAP

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Authors: Mannan Ahmad Rasheed, Sawera Kanwal, Mansoor Ahmad Rasheed

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The Internet of Things (IoT) has revolutionized the way we collect and process information, making it possible to gather data from a wide range of connected devices and sensors. This has led to the development of IoT-based information processing and computing systems that are capable of handling large amounts of data in real time. This paper provides a comprehensive overview of the current state of IoT-based information processing and computing, as well as the key challenges and gaps that need to be addressed. This paper discusses the potential benefits of IoT-based information processing and computing, such as improved efficiency, enhanced decision-making, and cost savings. Despite the numerous benefits of IoT-based information processing and computing, several challenges need to be addressed to realize the full potential of these systems. These challenges include security and privacy concerns, interoperability issues, scalability and reliability of IoT devices, and the need for standardization and regulation of IoT technologies. Moreover, this paper identifies several gaps in the current research related to IoT-based information processing and computing. One major gap is the lack of a comprehensive framework for designing and implementing IoT-based information processing and computing systems.

Keywords: IoT, computing, information processing, Iot computing

Procedia PDF Downloads 190

Authors: Faisal Asad Aburub

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Many organizations are investing in web applications and technologies in order to be competitive, some of them could not achieve its goals. The quality of web-based applications could play an important role for organizations to be competitive. So the aim of this study is to investigate the impact of quality of web-based applications to achieve a competitive advantage. A new model has been developed. An empirical investigation was performed on a banking sector in Jordan to test the new model. The results show that impact of web-based applications on competitive advantage is significant. Finally, further work is planned to validate and evaluate the proposed model using several domains.

Keywords: competitive advantage, web-based applications, empirical investigation, commercial banks in Jordan

Procedia PDF Downloads 341

Authors: M. S. Sreejith, Steffy Joy, Abhishesh Pal, Beom-Sahng Ryuh, V. R. Sanal Kumar

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In this paper an attempt has been made for the design of a robotic library using an intelligent system. The robot works on the ARM microprocessor, motor driver circuit with 5 degrees of freedom with Wi-Fi and GPS based communication protocol. The authenticity of the library books is controlled by RFID. The proposed robotic library system is facilitated with embedded system and ARM. In this library issuance system the previous potential readers’ authentic review reports have been taken into consideration for recommending suitable books to the deserving new users and the issuance of books or periodicals is based on the users’ decision. We have conjectured that the Wi-Fi based robotic library management system would allow fast transaction of books issuance and it also produces quality readers.

Keywords: GPS bsed based Robotic library, library management system, robotic library, Wi-Fi library

Procedia PDF Downloads 307

Authors: Billy Zou

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Statement of the Problem: The burden of mental illness and problem behaviors in adolescence has risen worldwide. While less than 50% of teens have access to traditional mental health care, more than 73% have smartphones. Internet-based interventions offer advantages such as cost-effectiveness, availability, and flexibility. Methodology & Theoretical Orientation: A literature review was done using a PubMed search with the words mental health app yielding 2113 results. 103 articles that met inclusion criteria were reviewed, and findings were then described and synthesized. Findings: 1. Computer-based CBT was found to be effective for OCD, depression, social phobia, and panic disorder. 2. Web-based psychoeducation reduced problem behavior and improved parental well-being. 3. There is limited evidence for mobile-phone-based apps, but preliminary results suggest computer-based interventions are transferrable to mobile apps. 4. Adherence to app-based treatment was correlated with impressions about the user interface Conclusion & Significance: There is evidence for the effectiveness of computer-based programs in filling the significant gaps that currently exist in mental health delivery in the United States and internationally. There is also potential and theoretical validity for mobile-based apps to do the same, though more data is needed.

Keywords: children's mental health, mental health app, child and adolecent psychiatry, digital therapy

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Authors: Mihir Mouchum Hazarika, Maddali Ramgopal, Souvik Bhattacharyya

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The thermodynamic analysis shows that the performance of the R744 based transcritical refrigeration cycle drops drastically for higher ambient temperatures. This is due to the peculiar s-shape of the isotherm in the supercritical region. However, subcooling of the refrigerant at the gas cooler exit enhances the performance of the R744 based system. The present study is carried out to analyze the R744 based transcritical system with dedicated mechanical subcooling cycle. Based on this proposed cycle, the thermodynamic analysis is performed, and optimum operating parameters are determined. The amount of subcooling and the pressure ratio in the subcooling cycle are the parameters which are needed to be optimized to extract the maximum COP from this proposed cycle. It is expected that this study will be helpful in implementing the dedicated subcooling cycle with R744 based transcritical system to improve the performance.

Keywords: optimization, R744, subcooling, transcritical

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Authors: Wajiha Fatima

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Various approaches and methods for second language classroom teaching have been proposed since the nineteenth century. Task Based Language Teaching has been prevailing approach in a second language classroom context. It is an approach which immerses students in a naturalistic setting. Tasks are the core unit of planning and instruction. This paper aims at expounding the concept of Task Based Language Teaching and how it has been evolved. In this study, researcher will highlight the usefulness of TBLT and the role it played as a powerful tool for learning and teaching in a second language setting. The article will reflect the implementation of various tasks based activities as well as the roles played by learners and teachers and the problems faced by them. In the end, researcher will discuss how TBLT can be implemented in second language classroom pedagogy.

Keywords: implementation, second language classroom, tasks, task based language teaching

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Authors: Nadia Chagtmi, Nejla Rejab, Noureddine Boulejfen

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This paper presents a calibration approach based on artificial neural networks (ANN) to determine the envelop signal (I+jQ) of a six-port based receiver (SPR). The memory effects called also dynamic behavior and the nonlinearity brought by diode based power detector have been taken into consideration by the ANN. Experimental set-up has been performed to validate the efficiency of this method. The efficiency of this approach has been confirmed by the obtained results in terms of waveforms. Moreover, the obtained error vector magnitude (EVM) and the mean absolute error (MAE) have been calculated in order to confirm and to test the ANN’s performance to achieve I/Q recovery using the output voltage detected by the power based detector. The baseband signal has been recovered using ANN with EVMs no higher than 1 % and an MAE no higher than 17, 26 for the SPR excited different type of signals such QAM (quadrature amplitude modulation) and LTE (Long Term Evolution).

Keywords: six-port based receiver; calibration, nonlinearity, memory effect, artificial neural network

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Authors: Mohadese Oghbaee, Borna Firouzi

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The emergence of the Internet and more specifically the formation of social media has provided the ground for paying attention to new types of content dissemination. In recent years, Social media users share information, communicate with others, and exchange opinions on social events in this space. Many of the information published in this space are suspicious and produced with the intention of deceiving others. These contents are often called "fake news". Fake news, by disrupting the circulation of the concept and similar concepts such as fake news with correct information and misleading public opinion, has the ability to endanger the security of countries and deprive the audience of the basic right of free access to real information; Competing governments, opposition elements, profit-seeking individuals and even competing organizations, knowing about this capacity, act to distort and overturn the facts in the virtual space of the target countries and communities on a large scale and influence public opinion towards their goals. This process of extensive de-truthing of the information space of the societies has created a wave of harm and worries all over the world. The formation of these concerns has led to the opening of a new path of research for the timely containment and reduction of the destructive effects of fake news on public opinion. In addition, the expansion of this phenomenon has the potential to create serious and important problems for societies, and its impact on events such as the 2016 American elections, Brexit, 2017 French elections, 2019 Indian elections, etc., has caused concerns and led to the adoption of approaches It has been dealt with. In recent years, a simple look at the growth trend of research in "Scopus" shows an increasing increase in research with the keyword "false information", which reached its peak in 2020, namely 524 cases, reached, while in 2015, only 30 scientific-research contents were published in this field. Considering that one of the capabilities of social media is to create a context for the dissemination of news and information, both true and false, in this article, the classification of strategies for spreading fake news in social networks was investigated in social events. To achieve this goal, thematic analysis research method was chosen. In this way, an extensive library study was first conducted in global sources. Then, an in-depth interview was conducted with 18 well-known specialists and experts in the field of news and media in Iran. These experts were selected by purposeful sampling. Then by analyzing the data using the theme analysis method, strategies were obtained; The strategies achieved so far (research is in progress) include unrealistically strengthening/weakening the speed and content of the event, stimulating psycho-media movements, targeting emotional audiences such as women, teenagers and young people, strengthening public hatred, calling the reaction legitimate/illegitimate. events, incitement to physical conflict, simplification of violent protests and targeted publication of images and interviews were introduced.

Keywords: fake news, social network, social events, thematic analysis

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Authors: Nada Poropat Jeletic, Gordana Hrzica

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Bilingual conversational corpora represent a meaningful and the most comprehensive data source for investigating the genuine contact phenomena in non-monitored bi-lingual speech productions. They can be particularly useful for bilingual research since some features of bilingual interaction can hardly be accessed with more traditional methodologies (e.g., elicitation tasks). The method of language sampling provides the resources for describing language interaction in a bilingual community and/or in bilingual situations (e.g. code-switching, amount of languages used, number of languages used, etc.). To capture these phenomena in genuine communication situations, such sampling should be as close as possible to spontaneous communication. Bilingual spoken corpus design is methodologically demanding. Therefore this paper aims at describing the methodological challenges that apply to the corpus design of the conversational corpus design of the Istrian Istrovenetian-Croatian Bilingual Corpus. Croatian is the first official language of the Croatian-Italian officially bilingual Istria County, while Istrovenetian is a diatopic subvariety of Venetian, a longlasting lingua franca in the Istrian peninsula, the mother tongue of the members of the Italian National Community in Istria and the primary code of informal everyday communication among the Istrian Italophone population. Within the CLARIN infrastructure, TalkBank is being used, as it provides relevant procedures for designing and analyzing bilingual corpora. Furthermore, it allows public availability allows for easy replication of studies and cumulative progress as a research community builds up around the corpus, while the tools developed within the field of corpus linguistics enable easy retrieval and analysis of information. The method of language sampling employed is kept at the level of spontaneous communication, in order to maximise the naturalness of the collected conversational data. All speakers have provided written informed consent in which they agree to be recorded at a random point within the period of one month after signing the consent. Participants are administered a background questionnaire providing information about the socioeconomic status and the exposure and language usage in the participants social networks. Recording data are being transcribed, phonologically adapted within a standard-sized orthographic form, coded and segmented (speech streams are being segmented into communication units based on syntactic criteria) and are being marked following the CHAT transcription system and its associated CLAN suite of programmes within the TalkBank toolkit. The corpus consists of transcribed sound recordings of 36 bilingual speakers, while the target is to publish the whole corpus by the end of 2020, by sampling spontaneous conversations among approximately 100 speakers from all the bilingual areas of Istria for ensuring representativeness (the participants are being recruited across three generations of native bilingual speakers in all the bilingual areas of the peninsula). Conversational corpora are still rare in TalkBank, so the Corpus will contribute to BilingBank as a highly relevant and scientifically reliable resource for an internationally established and active research community. The impact of the research of communities with societal bilingualism will contribute to the growing body of research on bilingualism and multilingualism, especially regarding topics of language dominance, language attrition and loss, interference and code-switching etc.

Keywords: conversational corpora, bilingual corpora, code-switching, language sampling, corpus design methodology

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Authors: Boon Yih Mah

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Web-based Cognitive Writing Instruction (WeCWI) is a hybrid e-framework that consolidates instructional design and language development towards the development of a web-based instruction (WBI). WeCWI divides instructional design into macro and micro perspectives. In macro perspective, a 21st century educator is encouraged to disseminate knowledge and share ideas with in-class and global learners. By leveraging the virtue of technology, WeCWI aims to transform the educator into an aggregator, curator, publisher, social networker and finally, a web-based instructor. Since the most notable contribution of integrating technology is being a tool of teaching as well as a stimulus for learning, WeCWI focuses on the use of contemporary web tools based on the multiple roles played by the 21st century educator. The micro perspective draws attention to the pedagogical approaches focussing on three main aspects: reading, discussion, and writing. With the effective use of pedagogical approaches, technology adds new dimensions and expands the bounds of learning capacity. Lastly, WeCWI also imparts the fundamental theoretical concepts for web-based instructors’ awareness such as interactionism, e-learning interactional-based model, computer-mediated communication (CMC), cognitive theories, and learning style model.

Keywords: web-based cognitive writing instruction, WeCWI, instructional design, e-framework, web-based instructor

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Authors: Anna Czarczynska

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Creativity is taken as a requirement for a personal anti-fragile career path in the context of regional competitive advantage in the terms of socio-economics creative environment. At the personal level, the competence and value-based approach to creativity are proposed, is an elaboration of the resource-based view of the group of individuals selected from given country. Entrepreneurial creativity competence (measured by the Schein anchor questionnaire) is based on an independent way of thinking and empowerment presents one aspect of creative capability, however quickly verified by the market, that’s why we treat this as a basic exemplification of average creative attitude combine with the entrepreneurial attitude. This introductory instrument enables further scientific research based on the same group in the context of multi-cultural external creative or the non-creative environment.

Keywords: creativity, value-based approach, entrepreneurship, regional culture

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Authors: Bahareh Ansari

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Background: The Open Government Data (OGD) movement in the last decade has encouraged many government organizations around the world to make their data publicly available to advance democratic processes. But current open data platforms have not yet reached to their full potential in supporting all interested parties. To make the data useful and understandable for everyone, scholars suggested that opening the data should be supplemented by visualization. However, different visualizations of the same information can dramatically change an individual’s cognitive and emotional experience in working with the data. This study reviews the data visualization literature to create a list of the methods empirically tested to enhance users’ performance and experience in working with a visualization tool. This list can be used in evaluating the OGD visualization practices and informing the future open data initiatives. Methods: Previous reviews of visualization literature categorized the visualization outcomes into four categories including recall/memorability, insight/comprehension, engagement, and enjoyment. To identify the papers, a search for these outcomes was conducted in the abstract of the publications of top-tier visualization venues including IEEE Transactions for Visualization and Computer Graphics, Computer Graphics, and proceedings of the CHI Conference on Human Factors in Computing Systems. The search results are complemented with a search in the references of the identified articles, and a search for 'open data visualization,' and 'visualization evaluation' keywords in the IEEE explore and ACM digital libraries. Articles are included if they provide empirical evidence through conducting controlled user experiments, or provide a review of these empirical studies. The qualitative synthesis of the studies focuses on identification and classifying the methods, and the conditions under which they are examined to positively affect the visualization outcomes. Findings: The keyword search yields 760 studies, of which 30 are included after the title/abstract review. The classification of the included articles shows five distinct methods: interactive design, aesthetic (artistic) style, storytelling, decorative elements that do not provide extra information including text, image, and embellishment on the graphs), and animation. Studies on decorative elements show consistency on the positive effects of these elements on user engagement and recall but are less consistent in their examination of the user performance. This inconsistency could be attributable to the particular data type or specific design method used in each study. The interactive design studies are consistent in their findings of the positive effect on the outcomes. Storytelling studies show some inconsistencies regarding the design effect on user engagement, enjoyment, recall, and performance, which could be indicative of the specific conditions required for the use of this method. Last two methods, aesthetics and animation, have been less frequent in the included articles, and provide consistent positive results on some of the outcomes. Implications for e-government: Review of the visualization best-practice methods show that each of these methods is beneficial under specific conditions. By using these methods in a potentially beneficial condition, OGD practices can promote a wide range of individuals to involve and work with the government data and ultimately engage in government policy-making procedures.

Keywords: best practices, data visualization, literature review, open government data

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Authors: Tudor Barbu

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An automatic moment-based texture segmentation approach is proposed in this paper. First, we describe the related work in this computer vision domain. Our texture feature extraction, the first part of the texture recognition process, produces a set of moment-based feature vectors. For each image pixel, a texture feature vector is computed as a sequence of area moments. Second, an automatic pixel classification approach is proposed. The feature vectors are clustered using some unsupervised classification algorithm, the optimal number of clusters being determined using a measure based on validation indexes. From the resulted pixel classes one determines easily the desired texture regions of the image.

Keywords: image segmentation, moment-based, texture analysis, automatic classification, validation indexes

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Authors: Gebeyaw Molla Wondim, Damen Haile Mariam, Wubegzier Mekonnen, Catherine Arsenault

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Introduction: Maternal depression is a common psychological disorder that mostly occurs during pregnancy and after childbirth. It affects approximately one in four women worldwide. There is inconsistent evidence regarding the association between anemia and maternal depression. The objective of this systematic review was to examine the association between anemia and depression during pregnancy. Method: A comprehensive search of articles published before March 8, 2024, was conducted in seven databases such as PubMed, Scopus, Web of Science, PsycINFO, CINAHL, Cochrane Library, and Google Scholar. The Boolean operators “AND” or “OR” and “NOT” were used to connect the MeSH terms and keywords. Rayyan software was used to screen articles for final retrieval, and the PRISMA diagram was used to show the article selection process. Data extraction and risk bias assessment were done by two reviewers independently. JBI critical appraisal tool was used to assess the methodological quality of the retrieved articles. Heterogenicity was assessed through visual inspection of the extracted result, and narrative analysis was used to synthesize the result. Result: A total of 2,413 articles were obtained from seven electronic databases. Among these articles, a total of 2,398 were removed due to duplication (702 articles), by title and abstract selection criteria (1,678 articles), and by full-text review (18 articles). Finally, in this systematic review, 15 articles with a total of 628,781 pregnant women were included: seven articles were cohort studies, two were case-control, and six studies were cross-sectional. All included studies were published between 2013 and 2022. Studies conducted in the United States, South Korea, Finland, and one in South India found no significant association between anemia and maternal depression during pregnancy. On the other hand, studies conducted in Australia, Canada, Finland, Israel, Turkey, Vietnam, Ethiopia, and South India showed a significant association between anemia and depression during pregnancy. Conclusion: The overall finding of the systematic review shows the burden of anemia and antenatal depression is much higher among pregnant women in developing countries. Around three-fourths of the studies show that anemia is positively associated with antenatal depression. Almost all studies conducted in LMICs show anemia positively associated with antenatal depression.

Keywords: pregnant, women, anemia, depression

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Authors: Leon Pan

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The first programming course within post-secondary education has long been recognized as a challenging endeavor for both educators and students alike. Historically, these courses have exhibited high failure rates and a notable number of dropouts. Instructors often lament students' lack of effort in their coursework, and students often express frustration that the teaching methods employed are not effective. Drawing inspiration from the successful principles of Extreme Programming, this study introduces an approach—the Extremes-based teaching model — aimed at enhancing the teaching of introductory programming courses. To empirically determine the effectiveness of the model, a comparison was made between a section taught using the extreme-based model and another utilizing traditional teaching methods. Notably, the extreme-based teaching class required students to work collaboratively on projects while also demanding continuous assessment and performance enhancement within groups. This paper details the application of the extreme-based model within the post-secondary online classroom context and presents the compelling results that emphasize its effectiveness in advancing the teaching and learning experiences. The extreme-based model led to a significant increase of 13.46 points in the weighted total average and a commendable 10% reduction in the failure rate.

Keywords: extreme-based teaching model, innovative pedagogical methods, project-based learning, team-based learning

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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: Ali Ganoun, Wesam Algablawi, Wasim BenAnaif

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Video based traffic surveillance based on License Plate Recognition (LPR) system is an essential part for any intelligent traffic management system. The LPR system utilizes computer vision and pattern recognition technologies to obtain traffic and road information by detecting and recognizing vehicles based on their license plates. Generally, the video based LPR system is a challenging area of research due to the variety of environmental conditions. The LPR systems used in a wide range of commercial applications such as collision warning systems, finding stolen cars, controlling access to car parks and automatic congestion charge systems. This paper presents an automatic LPR system of Libyan license plate. The performance of the proposed system is evaluated with three video sequences.

Keywords: license plate recognition, localization, segmentation, recognition

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Authors: Emily Stamm, Neil Smyth, Elizabeth O'Sullivan

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In Identity-Based Encryption (IBE), an identity, such as a username, email address, or domain name, acts as the public key. IBE consolidates the PKI by eliminating the repetitive process of requesting public keys for each message encryption. Two of the most popular schemes are Sakai-Kasahara (SAKKE), which is based on elliptic curve pairings, and the Ducas, Lyubashevsky, and Prest lattice scheme (DLP- Lattice), which is based on quantum-secure lattice cryptography. In or- der to embed the schemes in a standard enterprise setting, both schemes are implemented as shared system libraries and integrated into a REST service that functions at the enterprise level. The performance of both schemes as libraries and services is compared, and the practicalities of implementation and application are discussed. Our performance results indicate that although SAKKE has the smaller key and ciphertext sizes, DLP-Lattice is significantly faster overall and we recommend it for most enterprise use cases.

Keywords: identity-based encryption, post-quantum cryptography, lattice-based cryptography, IBE

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Authors: Lamyaa Gamal El-Deen Taha, Ashraf Sharawi

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China launched satellite GF-2 in 2014. This study deals with comparing nearest neighbor object-based classification and neural network classification methods for classification of the fused GF-2 image. Firstly, rectification of GF-2 image was performed. Secondly, a comparison between nearest neighbor object-based classification and neural network classification for classification of fused GF-2 was performed. Thirdly, the overall accuracy of classification and kappa index were calculated. Results indicate that nearest neighbor object-based classification is better than neural network classification for urban mapping.

Keywords: GF-2 images, feature extraction-rectification, nearest neighbour object based classification, segmentation algorithms, neural network classification, multilayer perceptron

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Authors: Nuur Ezaini Akmar Ismail, Norbazilah Rahim, Norul Huda Md Rasdi, Maslina Daud

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A web application is the most targeted by the attacker because the web application is accessible by the end users. It has become more advantageous to the attacker since not all the end users aware of what kind of sensitive data already leaked by them through the Internet especially via social network in shake on ‘sharing’. The attacker can use this information such as personal details, a favourite of artists, a favourite of actors or actress, music, politics, and medical records to customize phishing attack thus trick the user to click on malware-laced attachments. The Phishing attack is one of the most popular attacks for social engineering technique against web applications. There are several methods to detect phishing websites such as Blacklist/Whitelist based detection, heuristic-based, and visual similarity-based detection. This paper illustrated a comparison between the heuristic-based technique using features of a uniform resource locator (URL) and visual similarity-based detection techniques that compares the content of a suspected phishing page with the legitimate one in order to detect new phishing sites based on the paper reviewed from the past few years. The comparison focuses on three indicators which are false positive and negative, accuracy of the method, and time consumed to detect phishing website.

Keywords: heuristic-based technique, phishing detection, social engineering and visual similarity-based technique

Procedia PDF Downloads 177

Authors: K. W. Lee, C. M. Choi, H. C. Tsang, W. K. Fong, Y. K. Cheng, L. Y. Chan, C. K. Yuen, P. W. Lau, Y. L. To, K. C. Chow

Abstract:

QR (Quick Response) Code is a matrix barcode. It enables users to open websites, photos and other information with mobile devices by just snapping the code. In usual Long Term Oxygen Therapy arrangement, piles of LTOT related information like leaflets from different oxygen service providers are given to patients to choose an appropriate plan according to their needs. If these printed materials are transformed into electronic format (QR Code), it would be more environmentally-friendly. More importantly, electronic materials including LTOT equipment operation and dyspnoea relieving techniques also empower patients in long-term disease management. The objective to this study is to investigate the effect of QR code in patient education on new LTOT users. This study was carried out in medical wards of North District Hospital. Adult patients and relatives who followed commands, were able to use smartphones with internet services and required LTOT arrangement on hospital discharge were recruited. In LTOT arrangement, apart from the usual LTOT education booklets which included patients’ personal information (e.g. oxygen titration and six-minute walk test results etc.), extra leaflets consisted of 1. QR codes of LTOT plans from different oxygen service providers, 2. Education materials of dyspnoea management and 3. Instructions on LTOT equipment operation were given. Upon completion of LTOT arrangement, a questionnaire about the use of QR code on patient education was filled in by patients or relatives. A total of 10 new LTOT users were recruited from November 2017 to January 2018. Initially, 70% of them did not know anything about the QR code, but all of them understood its operation after a simple demonstration. 70% of them agreed that it was convenient to use (20% strongly agree, 40% agree, 10% somewhat agree). 80% of them agreed that QR code could facilitate the retrieval of more LTOT related information (10% strongly agree, 70% agree) while 90% agreed that we should continue delivering QR code leaflets to new LTOT users in the future (30% strongly agree, 40% agree, 20% somewhat agree). It is proven that QR code is a convenient and environmentally-friendly tool to deliver information. It is also relatively easy to be introduced to new users. It has received welcoming feedbacks from current users.

Keywords: long-term oxygen therapy, physiotherapy, patient education, QR code

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Authors: T. Turan, Ç. Erdoğan

Abstract:

As far as is known, general nursing care practices do not include specific evidence-based practices related to oral care in children. This study aimed to evaluate the evidence based nursing practice for oral care in children. This article is planned as a review article by searching the literature in this field. According to all age groups and the oral care in various specific situations located evidence in the literature were examined. It has been determined that the methods and frequency used in oral care practices performed by nurses in clinics differ from one hospital to another. In addition, it is seen that different solutions are used in basic oral care, oral care practices to prevent ventilator-associated pneumonia and evidence-based practice in mucositis management in children. As a result, a standard should be established in oral care practices for children and education for children is recommended.

Keywords: evidence-based practice, oral care, nursing, children

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Authors: Sangita Bharati

Abstract:

Violence against women is now well recognised as a public health problem and human rights violation of worldwide significance. It is an important risk factor for women's ill health, with far reaching consequences for both their physical and mental health. Gender based violence takes many forms and results in physical, sexual and psychological harm to the women throughout their lives. Gender based violence often manifests unequal power relation between men and women in society and the secondary status of the women because of which women have to suffer a range of health problems in silence. This paper will aim at describing a few problems related to women’s health which are directly linked to their experience as victims of gender based violence.

Keywords: violence, health, women, society

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Authors: Dev Ras Pandey, Bharat Mishra, S. K. Tripathi

Abstract:

Cloud computing is ready to transform the structure of businesses and learning through supplying the real-time applications and provide an immediate help for small to medium sized businesses. The ability to run a hypervisor inside a virtual machine is important feature of virtualization and it is called nested virtualization. In today’s growing field of information technology, many of the virtualization models are available, that provide a convenient approach to implement, but decision for a single model selection is difficult. This paper explains the applications of operating system based virtualization in cloud computing with an appropriate/suitable model with their different specifications and user’s requirements. In the present paper, most popular models are selected, and the selection was based on container and hypervisor based virtualization. Selected models were compared with a wide range of user’s requirements as number of CPUs, memory size, nested virtualization supports, live migration and commercial supports, etc. and we identified a most suitable model of virtualization.

Keywords: virtualization, OS based virtualization, container based virtualization, hypervisor based virtualization

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Authors: Abderrahmane Khiat, Moussa Benaissa

Abstract:

Due to the increasing number of sources of information available on the web and their distribution and heterogeneity, ontology alignment became a very important and inevitable problem to ensure semantic interoperability. Instance-based ontology alignment is based on the comparison of the extensions of concepts; and represents a very promising technique to find semantic correspondences between entities of different ontologies. In practice, two situations may arise: ontologies that share many common instances and ontologies that share few or do not share common instances. In this paper, we describe an approach to manage the latter case. This approach exploits the reasoning on ontologies in order to create a corpus of common instances. We show that it is theoretically powerful because it is based on description logics and very useful in practice. We present the experimental results obtained by running our approach on ontologies of OAEI 2012 benchmark test. The results show the performance of our approach.

Keywords: description logic inference, instance-based ontology alignment, semantic interoperability, semantic web

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Authors: Yunpeng Xia, Jiajia Zha, Haoxin Huang, Hau Ping Chan, Chaoliang Tan

Abstract:

Although the crystal phase of two-dimensional (2D) transition metal dichalcogenides (TMDs) has been proven to play an essential role in fabricating high-performance electronic devices in the past decade, its effect on the performance of 2D material-based flash memory devices still remains unclear. Here, we report the exploration of the effect of MoTe₂ in different phases as the charge trapping layer on the performance of 2D van der Waals (vdW) heterostructure-based flash memory devices, where the metallic 1T′-MoTe₂ or semiconducting 2H-MoTe₂ nanoflake is used as the floating gate. By conducting comprehensive measurements on the two kinds of vdW heterostructure-based devices, the memory device based on MoS2/h-BN/1T′-MoTe₂ presents much better performance, including a larger memory window, faster switching speed (100 ns) and higher extinction ratio (107), than that of the device based on MoS₂/h-BN/2H-MoTe₂ heterostructure. Moreover, the device based on MoS₂/h-BN/1T′-MoTe₂ heterostructure also shows a long cycle (>1200 cycles) and retention (>3000 s) stability. Our study clearly demonstrates that the crystal phase of 2D TMDs has a significant impact on the performance of nonvolatile flash memory devices based on 2D vdW heterostructures, which paves the way for the fabrication of future high-performance memory devices based on 2D materials.

Keywords: crystal Phase, 2D van der Waals heretostructure, flash memory device, floating gate

Procedia PDF Downloads 55