Search results for: scenario-based queries

Authors: John Segars

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Built out of a real-world need to have better, more detailed, asset and infrastructure documentation, this project will lay out the case for using the database functionality of ArcGIS as a tool to track and maintain infrastructure location, status, maintenance and serviceability. Workflows and processes will be presented and detailed which may be applied to an organizations’ infrastructure needs that might allow them to make use of the robust tools which surround the ArcGIS platform. The end result is a value-added information system framework with a geographic component e.g., the spatial location of various I.T. assets, a detailed set of records which not only documents location but also captures the maintenance history for assets along with photographs and documentation of these various assets as attachments to the numerous feature class items. In addition to the asset location and documentation benefits, the staff will be able to log into the devices and pull SNMP (Simple Network Management Protocol) based query information from within the user interface. The entire collection of information may be displayed in ArcGIS, via a JavaScript based web application or via queries to the back-end database. The project is applicable to all organizations which maintain an IT infrastructure but specifically targets post-secondary educational institutions where access to ESRI resources is generally already available in house.

Keywords: ESRI, GIS, infrastructure, network documentation, PostgreSQL

Procedia PDF Downloads 181

Authors: Djelloul Nedjai

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The issue of cultural awareness triggers many controversies, especially in a context where individuals do not share the same cultural backgrounds and characteristics. The Algerian context is no exception. It has been widely documented by the literature that culture remains essential in many domains. In higher education, for instance, culture plays a pivotal role in shaping individuals’ perceptions and attitudes. Henceforth, the current paper attempts to look at the perceptions of the British culture held by students engaged in learning English as a Foreign Language (EFL) at the department of English at Banta 2 University, Algeria. It also inquires into EFL students’ perceptions of British culture. To address the aforementioned research queries, a descriptive study has been carried out wherein a questionnaire of fifteen (15) items has been deployed to collect students’ attitudes and perceptions toward British culture. Results showcase that, indeed, EFL students of the department of English at Banta 2 University hold both positive and negative perceptions towards British culture at different levels. The explanation could relate to the student's lack of acquaintance with and awareness of British culture. Consequently, this paper is an attempt to address the issue of cultural awareness from the perspective of EFL students.

Keywords: British culture, cultural awareness, EFL students’ perceptions, higher education

Procedia PDF Downloads 90

Authors: Manuela Nayantara Jeyaraj

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PostgreSQL is an Object-Relational Database Management System (ORDBMS) with an architecture that ensures optimal quality data management. But due to the shading growth of similar ORDBMS, PostgreSQL has not been renowned among the database user community. Despite having its features and in-built functionalities shadowed, PostgreSQL renders a vast range of utilities for data manipulation and hence calling for it to be upheld more among users. But introducing PostgreSQL in order to stimulate its advantageous features among users, mandates endorsing learn-ability as an add-on as the target groups considered consist of both amateur as well as professional PostgreSQL users. The scope of this paper deliberates providing easy contemplation of query formulations and flows through a visual editor designed according to user interface principles that standby to support every aspect of making PostgreSQL learn-able by self-operation and creation of queries within the visual editor. This paper tends to scrutinize the importance of choosing PostgreSQL as the working database environment, the visual perspectives that influence human behaviour and ultimately learning, the modes in which learn-ability can be provided via visualization and the advantages reaped by the implementation of the proposed system features.

Keywords: database, learn-ability, PostgreSQL, query, visual-editor

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Authors: Samira Brahimi

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Throughout Aisha, her first collection of short stories, Ahdaf Soueif draws a multilayered picture of the Other as others, picturing a series of encounters of her protagonist with this very Other as a set of binary elements. The current essay includes a comparative study between two narratives, namely The Returning and The Nativity. The Other is portrayed as a male/female binary in The Returning and as 'The Foreigner' in an exotic land vs. the local in The Nativity. The analysis is to focus on Aisha, the main female character, who figures as conforming to the portrait of the stereotyped Arab Muslim woman as a sex-subject, submissive, and maudlin character, confining her vision of the Other to the boundaries of her cocooned self, epitomizing a self-centered vision of the world. This reduced vision results in the possibility of viewing the Other as a hindrance to her attaining a clarified and centrifugal representation of the latter, herself, and the outside world. The encounters could also be considered as the character's opportunity for a less stigmatized perception of the elements set forth. The main queries to be probed are: what are the different perceptions of the Other by the author in the narratives set forth? How does the protagonist's encounter with the Other(s) impede her ability to understand the Other, herself, and the world around her? Or how does this encounter allow her an enlightened vision of the aforementioned elements to forge a new start? The possibility of imagining a dialogic relation between different perceptions of the Other opens up new perspectives for adopting magnified representations of the later, oneself, and the world, dilating one's imagination.

Keywords: dialogic, female, foreigner, local, male, other, others

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Authors: Shalitha Jayasekara, Saluk Bawantha, Dinithi Anupama, Isuru Gunarathne, Pradeepa Bandara, Hansi De Silva

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Dogs have been known as "man's best friend" for generations, providing friendship and loyalty to their human counterparts. However, due to people's busy lives, they are unaware of the ailments that can affect their pets. However, in recent years, mobile technologies have had a significant impact on our lives, and with technological improvements, a rule-based expert system allows the end-user to enable new types of healthcare systems. The advent of Android OS-based smartphones with more user-friendly interfaces and lower pricing opens new possibilities for continuous monitoring of pets' health conditions, such as healthy dogs, dangerous ingestions, and swallowed objects. The proposed ‘Best Bark’ Dog care and owner consultation system is a mobile application for dog owners. Four main components for dog owners were implemented after a questionnaire was distributed to the target group of audience and the findings were evaluated. The proposed applications are widely used to provide health and clinical support to dog owners, including suggesting exercise and diet plans and answering queries about their dogs. Additionally, after the owner uploads a photo of the dog, the application provides immediate feedback and a description of the dog's skin disease.

Keywords: Convolution Neural Networks, Artificial Neural Networks, Knowledgebase, Sentimental Analysis.

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Authors: Olga Kononova, Sergey Lyapin

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Global information society requirements are transparency and reliability of data, as well as ability to manage information resources independently; particularly to search, to analyze, to evaluate information, thereby obtaining new expertise. Moreover, it is satisfying the society information needs that increases the efficiency of the enterprise management and public administration. The study of structurally organized thematic and semantic contexts of different types, automatically extracted from unstructured data, is one of the important tasks for the application of information technologies in education, science, culture, governance and business. The objectives of this study are the contextual knowledge typologization, selection or creation of effective tools for extracting and analyzing contextual knowledge. Explication of various kinds and forms of the contextual knowledge involves the development and use full-text search information systems. For the implementation purposes, the authors use an e-library 'Humanitariana' services such as the contextual search, different types of queries (paragraph-oriented query, frequency-ranked query), automatic extraction of knowledge from the scientific texts. The multifunctional e-library «Humanitariana» is realized in the Internet-architecture in WWS-configuration (Web-browser / Web-server / SQL-server). Advantage of use 'Humanitariana' is in the possibility of combining the resources of several organizations. Scholars and research groups may work in a local network mode and in distributed IT environments with ability to appeal to resources of any participating organizations servers. Paper discusses some specific cases of the contextual knowledge explication with the use of the e-library services and focuses on possibilities of new types of the contextual knowledge. Experimental research base are science texts about 'e-government' and 'computer games'. An analysis of the subject-themed texts trends allowed to propose the content analysis methodology, that combines a full-text search with automatic construction of 'terminogramma' and expert analysis of the selected contexts. 'Terminogramma' is made out as a table that contains a column with a frequency-ranked list of words (nouns), as well as columns with an indication of the absolute frequency (number) and the relative frequency of occurrence of the word (in %% ppm). The analysis of 'e-government' materials showed, that the state takes a dominant position in the processes of the electronic interaction between the authorities and society in modern Russia. The media credited the main role in these processes to the government, which provided public services through specialized portals. Factor analysis revealed two factors statistically describing the used terms: human interaction (the user) and the state (government, processes organizer); interaction management (public officer, processes performer) and technology (infrastructure). Isolation of these factors will lead to changes in the model of electronic interaction between government and society. In this study, the dominant social problems and the prevalence of different categories of subjects of computer gaming in science papers from 2005 to 2015 were identified. Therefore, there is an evident identification of several types of contextual knowledge: micro context; macro context; dynamic context; thematic collection of queries (interactive contextual knowledge expanding a composition of e-library information resources); multimodal context (functional integration of iconographic and full-text resources through hybrid quasi-semantic algorithm of search). Further studies can be pursued both in terms of expanding the resource base on which they are held, and in terms of the development of appropriate tools.

Keywords: contextual knowledge, contextual search, e-library services, frequency-ranked query, paragraph-oriented query, technologies of the contextual knowledge extraction

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Authors: Mohamed S. M. Elghazal, Adel Aneiba, Essa Q. Shahra

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This study presents a comprehensive comparative analysis of REST and GraphQL API models within the context of microservices development, offering empirical insights into the strengths and limitations of each approach. The research explores the effectiveness and efficiency of GraphQL versus REST, focusing on their impact on critical software quality metrics and user experience. Using a controlled experimental setup, the study evaluates key performance indicators, including response time, data transfer efficiency, and error rates. The findings reveal that REST APIs demonstrate superior memory efficiency and faster response times, particularly under high-load conditions, making them a reliable choice for performance-critical microservices. On the other hand, GraphQL excels in offering greater flexibility for data fetching but exhibits higher response times and increased error rates when handling complex queries. This research provides a nuanced understanding of the trade-offs between REST and GraphQL API interaction models, offering actionable guidance for developers and researchers in selecting the optimal API model for microservice-based applications. The insights are particularly valuable for balancing considerations such as performance, flexibility, and reliability in real-world implementations.

Keywords: REST API, GraphQL AP, microservice, software development

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Authors: Hamdi Sana, Emna Bouazizi, Sami Faiz

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In recent years, there is a huge increase in the use of spatio-temporal applications where data and queries are continuously moving. As a result, the need to process real-time spatio-temporal data seems clear and real-time stream data management becomes a hot topic. Sliding window model and frequent itemset mining over dynamic data are the most important problems in the context of data mining. Thus, sliding window model for frequent itemset mining is a widely used model for data stream mining due to its emphasis on recent data and its bounded memory requirement. These methods use the traditional transaction-based sliding window model where the window size is based on a fixed number of transactions. Actually, this model supposes that all transactions have a constant rate which is not suited for real-time applications. And the use of this model in such applications endangers their performance. Based on these observations, this paper relaxes the notion of window size and proposes the use of a timestamp-based sliding window model. In our proposed frequent itemset mining algorithm, support conditions are used to differentiate frequents and infrequent patterns. Thereafter, a tree is developed to incrementally maintain the essential information. We evaluate our contribution. The preliminary results are quite promising.

Keywords: real-time spatial big data, frequent itemset, transaction-based sliding window model, timestamp-based sliding window model, weighted frequent patterns, tree, stream query

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Authors: Vincent Ballola, Raymund Dilan, Thelma Palaoag

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The Smart Online Library Catalog System with Query Expansion seeks to address the low usage of the library because of the emergence of the Internet. Library users are not accustomed to catalog systems that need a query to have the exact words without any mistakes for decent results to appear. The graphical user interface of the current system has a rather skewed learning curve for users to adapt with. With a simple graphical user interface inspired by Google, users can search quickly just by inputting their query and hitting the search button. Because of the query expansion techniques incorporated into the new system such as stemming, thesaurus search, and weighted search, users can have more efficient results from their query. The system will be adding the root words of the user's query to the query itself which will then be cross-referenced to a thesaurus database to search for any synonyms that will be added to the query. The results will then be arranged by the number of times the word has been searched. Online queries will also be added to the results for additional references. Users showed notable increases in efficiency and usability due to the familiar interface and query expansion techniques incorporated in the system. The simple yet familiar design led to a better user experience. Users also said that they would be more inclined in using the library because of the new system. The incorporation of query expansion techniques gives a notable increase of results to users that in turn gives them a wider range of resources found in the library. Used books mean more knowledge imparted to the users.

Keywords: query expansion, catalog system, stemming, weighted search, usability, thesaurus search

Procedia PDF Downloads 388

Authors: Haitao Yang, Jianming Lv, Fei Xu, Xintong Wang, Yilin Huang, Lanting Xia, Xuewu Zhu

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Given a fixed fund, purchasing fewer hosts of higher capability or inversely more of lower capability is a must-be-made trade-off in practices for building a Hadoop big data platform. An exploratory study is presented for a Housing Big Data Platform project (HBDP), where typical big data computing is with SQL queries of aggregate, join, and space-time condition selections executed upon massive data from more than 10 million housing units. In HBDP, an empirical formula was introduced to predict the performance of host clusters potential for the intended typical big data computing, and it was shaped via a regression approach. With this empirical formula, it is easy to suggest an optimal cluster configuration. The investigation was based on a typical Hadoop computing ecosystem HDFS+Hive+Spark. A proper metric was raised to measure the performance of Hadoop clusters in HBDP, which was tested and compared with its predicted counterpart, on executing three kinds of typical SQL query tasks. Tests were conducted with respect to factors of CPU benchmark, memory size, virtual host division, and the number of element physical host in cluster. The research has been applied to practical cluster procurement for housing big data computing.

Keywords: Hadoop platform planning, optimal cluster scheme at fixed-fund, performance predicting formula, typical SQL query tasks

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Authors: Alexander Wachtel, Michael T. Franzen, Walter F. Tichy

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Programming requires years of training. With natural language and end user development methods, programming could become available to everyone. It enables end users to program their own devices and extend the functionality of the existing system without any knowledge of programming languages. In this paper, we describe an Interactive Spreadsheet Processing Module (ISPM), a natural language interface to spreadsheets that allows users to address ranges within the spreadsheet based on inferred table schema. Using the ISPM, end users are able to search for values in the schema of the table and to address the data in spreadsheets implicitly. Furthermore, it enables them to select and sort the spreadsheet data by using natural language. ISPM uses a machine learning technique to automatically infer areas within a spreadsheet, including different kinds of headers and data ranges. Since ranges can be identified from natural language queries, the end users can query the data using natural language. During the evaluation 12 undergraduate students were asked to perform operations (sum, sort, group and select) using the system and also Excel without ISPM interface, and the time taken for task completion was compared across the two systems. Only for the selection task did users take less time in Excel (since they directly selected the cells using the mouse) than in ISPM, by using natural language for end user software engineering, to overcome the present bottleneck of professional developers.

Keywords: natural language processing, natural language interfaces, human computer interaction, end user development, dialog systems, data recognition, spreadsheet

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Authors: Nir Wittenberg, Moshe Farhi

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This mixed-methods study examines the integration of artificial intelligence (AI) tools in a first-year social work course to assess their potential for enhancing professional knowledge and skills. The incorporation of digital technologies, such as AI, in social work interventions, training, and research has increased, with the expectation that AI will become as commonplace as email and mobile phones. However, policies and ethical guidelines regarding AI, as well as empirical evaluations of its usefulness, are lacking. As AI is gradually being adopted in the field, it is prudent to explore AI thoughtfully in alignment with pedagogical goals. The outcomes assessed include professional identity, course satisfaction, and motivation. AI offers unique reflective learning opportunities through personalized simulations, feedback, and queries to complement face-to-face lessons. For instance, AI simulations provide low-risk practices for situations such as client interactions, enabling students to build skills with less stress. However, it is essential to recognize that AI alone cannot ensure real-world competence or cultural sensitivity. Outcomes related to student learning, experience, and perceptions will help to elucidate the best practices for AI integration, guiding faculty, and advancing pedagogical innovation. This strategic integration of selected AI technologies is expected to diversify course methodology, improve learning outcomes, and generate new evidence on AI’s educational utility. The findings will inform faculty seeking to thoughtfully incorporate AI into teaching and learning.

Keywords: artificial intelligence (AI), social work education, students, developing a professional identity, ethical considerations

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Authors: Amadou Fall Dia, Maurras Ulbricht Togbe, Aliou Boly, Zakia Kazi Aoul, Elisabeth Metais

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Existing RDF (Resource Description Framework) Stream Processing (RSP) systems allow continuous processing of RDF data issued from different application domains such as weather station measuring phenomena, geolocation, IoT applications, drinking water distribution management, and so on. However, processing window phase often expires before finishing the entire session and RSP systems immediately delete data streams after each processed window. Such mechanism does not allow optimized exploitation of the RDF data streams as the most relevant and pertinent information of the data is often not used in a due time and almost impossible to be exploited for further analyzes. It should be better to keep the most informative part of data within streams while minimizing the memory storage space. In this work, we propose an RDF graph summarization system based on an explicit and implicit expressed needs through three main approaches: (1) an approach for user queries (SPARQL) in order to extract their needs and group them into a more global query, (2) an extension of the closeness centrality measure issued from Social Network Analysis (SNA) to determine the most informative parts of the graph and (3) an RDF graph summarization technique combining extracted user query needs and the extended centrality measure. Experiments and evaluations show efficient results in terms of memory space storage and the most expected approximate query results on summarized graphs compared to the source ones.

Keywords: centrality measures, RDF graphs summary, RDF graphs stream, SPARQL query

Procedia PDF Downloads 203

Authors: Abdul Rauf, Xiaoxing Liu, Rizwan Qaisar Danish, Waqas Amin

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The core intention of this study is to analyze the linkage of training, job attitudes and motivation through a mediation model in the banking sector of Pakistan. Moreover, this study is executed to answer a range of queries regarding the consideration of employees about training, job satisfaction, motivation and organizational commitment. Hence, the association of training with job satisfaction, job satisfaction with motivation, organizational commitment with job satisfaction, organization commitment as independently with motivation and training directly related to motivation is determined in this course of study. A questionnaire crafted for comprehending the purpose of this study by including four variables such as training, job satisfaction, motivation and organizational commitment which have to measure. A sample of 450 employees from seventeen private (17) banks and two (2) public banks was taken on the basis of convenience sampling from Pakistan. However, 357 questionnaires, completely filled were received back. AMOS used for assessing the conformity factor analysis (CFA) model and statistical techniques practiced to scan the collected data (i.e.) descriptive statistics, regression analysis and correlation analysis. The empirical findings revealed that training and organizational commitment has a significant and positive impact directly on job satisfaction and motivation as well as through the mediator (job satisfaction) also the impact sensing in the same way on the motivation of employees in the financial Banks of Pakistan. In this research study, the banking sector is under discussion, so the findings could not generalize on other sectors such as manufacturing, textiles, telecom, and medicine, etc. The low sample size is also the limitation of this study. On the foundation of these results the management fascinates to make the revised strategies regarding training program for the employees as it enhances their motivation level, and job satisfaction on a regular basis.

Keywords: job satisfaction, motivation, organizational commitment, Pakistan, training

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Authors: Premjit K. Sanjram, Gagan Jakhotiya, Apoorv Goyal, Shanu Shukla

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In psychological research, laboratory experiments often face the trade-off issue between experimental control and mundane realism. With the advent of Immersive Virtual Environment Technology (IVET), this issue seems to be at bay. However there is a growing challenge within the IVET itself to design and develop system or software that captures the psychological phenomenon of everyday lives. One such phenomena that is of growing interest is ‘media-multitasking’ To aid laboratory researches in media-multitasking this paper introduces Query Task Modulator (QTM), a computerized experimentation system to study media-multitasking behavior in a controlled laboratory environment. The system provides a computerized platform in conducting an experiment for experimenters to study media-multitasking in which participants will be involved in a query task. The system has Instant Messaging, E-mail, and Voice Call features. The answers to queries are provided on the left hand side information panel where participants have to search for it and feed the information in the respective communication media blocks as fast as possible. On the whole the system will collect multitasking behavioral data. To analyze performance there is a separate output table that records the reaction times and responses of the participants individually. Information panel and all the media blocks will appear on a single window in order to ensure multi-modality feature in media-multitasking and equal emphasis on all the tasks (thus avoiding prioritization to a particular task). The paper discusses the development of QTM in the light of current techniques of studying media-multitasking.

Keywords: experimentation system, human performance, media-multitasking, query-task

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Authors: Jinan Fiaidhi, Hashmath Shaik

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Breaking the barrier for practicing evidence-based medicine relies on effective methods for rapidly identifying relevant evidence from the body of biomedical literature. An important challenge confronted by medical practitioners is the long time needed to browse, filter, summarize and compile information from different medical resources. Deep learning can help in solving this based on automatic question answering (Q&A) and transformers. However, Q&A and transformer technologies are not trained to answer clinical queries that can be used for evidence-based practice, nor can they respond to structured clinical questioning protocols like PICO (Patient/Problem, Intervention, Comparison and Outcome). This article describes the use of deep learning techniques for Q&A that are based on transformer models like BERT and GPT to answer PICO clinical questions that can be used for evidence-based practice extracted from sound medical research resources like PubMed. We are reporting acceptable clinical answers that are supported by findings from PubMed. Our transformer methods are reaching an acceptable state-of-the-art performance based on two staged bootstrapping processes involving filtering relevant articles followed by identifying articles that support the requested outcome expressed by the PICO question. Moreover, we are also reporting experimentations to empower our bootstrapping techniques with patch attention to the most important keywords in the clinical case and the PICO questions. Our bootstrapped patched with attention is showing relevancy of the evidence collected based on entropy metrics.

Keywords: automatic question answering, PICO questions, evidence-based medicine, generative models, LLM transformers

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Authors: Kareem Adedokun

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Official secrecy is one of the colonial vestiges which upholds non – disclosure of essential information for public consumption. Information, though an indispensable tool in tax administration, is not to be divulged by any person in an official duty of the revenue agency. As a matter o fact, the Federal Inland Revenue Service (Establishment) Act, 2007 emphasizes secrecy and confidentiality in dealing with tax payer’s document, information, returns and assessment in a manner reminiscent of protecting tax payer’s privacy in all situations. It is so serious that any violation attracts criminal sanction. However, Nigeria, being a democratic and egalitarian state recently enacted Freedom of Information Act which heralded in openness in governance and takes away the confidentialities associated with official secrets Laws. Official secrecy no doubts contradicts the philosophy of freedom of information but maintaining a proper balance between protected rights of tax payers and public interest which revenue agency upholds is an uphill task. Adopting the Doctrinal method, therefore, the author of this paper probes into the real nature of the relationship between taxpayers and Revenue Agencies. It also interfaces official secrecy with the doctrine of Freedom of Information and consequently queries the retention of non – disclosure clause under Federal Inland Revenue Service (Establishment) Act (FIRSEA) 2007. The paper finds among others that non – disclosure provision in tax statutes particularly as provided for in FIRSEA is not absolute; so also is the constitutional rights and freedom of information and unless the non – disclosure clause finds justification under any recognized exemption provided under the Freedom of Information Act, its retention is antithesis to democratic ethos and beliefs as it may hinder public interest and public order.

Keywords: confidentiality, information, official secrecy, tax administration

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Authors: Parul Bhandari

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An image of a modern and progressive India garners the rhetoric of ‘choice’ marriages, gender egalitarian relationships, and search for ‘love’ in conjugal unions. Such an image especially resonates with the lives of young professionals, who, largely belonging to the middle class, consider themselves to be the global face India. While this rhetoric of ‘progress’ and ‘love’ is abounding in both Indian and non-Indian public discourses, it is imperative to scientifically analyse the veracity of these claims. This paper thus queries and problematises the notions of being modern and progressive, through the lens of gender roles as expected and desired in a process of matchmaking. The fieldwork conducted is based on qualitative methodology, involving in-depth interviews with 100 highly qualified professionals, (60 men and 40 women), between the age of 24-31, belonging to the Hindu religion and of varied castes and communities, who are residing in New Delhi, and are in the process of spouse-selection or have recently completed it. Further, an analysis of the structure and content of matrimonial websites, which have fast emerged as the new method of matchmaking, was also undertaken. The main finding of this paper is that gender asymmetries continue to determine a suitable match, whether in ‘arranged’ or ‘love’ marriages. This is demonstrated by analysing the expectations of gender roles and gender practices of both men and women, to construct an ideal of a ‘good match’. On the basis of the interviews and the content of matrimonial websites, the paper discusses the characteristics of a ‘suitable boy’ and a ‘suitable girl’, and the ways in which these are received (practiced or criticised) by the young men and women themselves. It is then concluded that though an ideal of ‘compatibility’ and love determines conjugal desires, traditional gender roles, that, for example, consider men as the primary breadwinner and women as responsible for the domestic sphere, continue to dictate urban Indian marriages.

Keywords: gender, India, marriage, middle class

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Authors: Laiba Amin, Rashna H. Sukhia, Mubassar Fida

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Introduction: This study evaluates the accuracy of responses from ChatGPT, Google Bard, and Microsoft Copilot regarding dentofacial orthopedic appliances. As artificial intelligence (AI) increasingly enhances various fields, including healthcare, understanding its reliability in specialized domains like orthodontics becomes crucial. By comparing the accuracy of different AI models, this study aims to shed light on their effectiveness and potential limitations in providing technical insights. Materials and Methods: A total of 110 questions focused on dentofacial orthopedic appliances were posed to each AI model. The responses were then evaluated by five experienced orthodontists using a modified 5-point Likert scale to ensure a thorough assessment of accuracy. This structured approach allowed for consistent and objective rating, facilitating a meaningful comparison between the AI systems. Results: The results revealed that Google Bard demonstrated the highest accuracy at 74%, followed by Microsoft Copilot, with an accuracy of 72.2%. In contrast, ChatGPT was found to be the least accurate, achieving only 52.2%. These results highlight significant differences in the performance of the AI models when addressing orthodontic queries. Conclusions: Our study highlights the need for caution in relying on AI for orthodontic insights. The overall accuracy of the three chatbots was 66%, with Google Bard performing best for removable Class II appliances. Microsoft Copilot was more accurate than ChatGPT, which, despite its popularity, was the least accurate. This variability emphasizes the importance of human expertise in interpreting AI-generated information. Further research is necessary to improve the reliability of AI models in specialized healthcare settings.

Keywords: artificial intelligence, large language models, orthodontics, dentofacial orthopaedic appliances, accuracy assessment.

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Authors: Clesse C., Lighezzolo-Alnot J., De Lavergne S.

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Considered as the most common surgical procedure worldwide, episiotomy can be defined as an incision around the vulva performed to enlarge it, in the aim of preventing the traumatic rupture of the perineum during childbirth. Rather mediatized, this practice raises many questions in the field of mental health, relayed by different users and health professionals. Today, is topicality is moderately hectic since many queries about the prophylactic exercise of episiotomy are subject to a relative consensus, particularly since WHO advocated in 1996 that only 10% of childbirths should involve an episiotomy. This indicator appeared after the publication of numerous results from randomized clinical trials. Unfortunately, these papers seem mostly centered about somatic impacts of episiotomy. From the side of psychological studies, they mostly integrate a major clinical methodological bias, especially considering that every primiparous woman is identical to the others face to the experience of parturition. In the aim to fill this lack of knowledge, we developed a longitudinal research starting in the 7th month of pregnancy and ending one year after delivery. We are studying in a comparative way different possible psychological consequences inherent to the use of episiotomy. To do this, we use a standardized methodology which combines semi-structured clinical interviews (IRMAG, IRMAN ...), free clinical interviews, a projective test (Rorschach) and five questionnaires (QIC, EPDS, CPQ WOMBLSQ4, SF36). Therefore, we can comprehend with shrewdness the question of psychic impacts of episiotomy in a qualitative and quantitative way by comparing it to other obstetric interventions. In this paper, we will present the first results obtained about a population of twenty-two primiparous women by focusing on body image, sexuality, quality of life, depressive affects, post-traumatic stress disorder and investment of the maternal role. Finally, we will consider the different implications and perspectives of this research which could improve the public health policies in the field of perinatal care.

Keywords: assessment, episiotomy, mental health, psychical impacts

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Authors: Anna Stoutenburg

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With the rise of the so-called 'new left' within the United States, marked by social democratic figures such as Bernie Sanders and Alexandria Ocasio-Cortez, significant questions have been raised in response to those who would identify with the term 'socialist'. These queries typically revolve around the negatively perceived legacy of past and present countries that share the term in question, with the stark conclusion that not only is socialism a structure that does not work economically, but that it also tends to inflict more harm on those living under it that would be endured in a country functioning under capitalism. In order to examine these claims, the goal of this paper is to examine the legacy of anti-communist historiography in a western context, with the Union of Soviet Socialist Republics, China, and modern Venezuela used as case studies for how this phenomenon operates. Not only will key portions of each nation’s history be re-examined, but there will also be a critical analysis of source cultivation and usage among western historians. The intent of this paper is not merely to deride previous attempts at historicizing and reporting on the events of the nations, but rather to attempt to glean a clearer picture that is free from anti-communist sentiments. Theoretical works that will be consulted in order to define this project are 'The Historiography of Communism' by Michael Brown, as well as 'Beyond Philosophy: Ethics, History, Marxism, and Liberation Theology' by Enrique Dussel. The latter will provide insights concerning why these questions are relevant in a larger context, namely by articulating how the means of liberation understood through an analectic method can be achieved structurally. For a majority of leftists, this question is integral, and by using history as a tool, the ways that political organizing can be used can be better understood, bridging the gap between the common assumption that the communist legacy is a dire one and the idea that it is something which needs to be completely lauded.

Keywords: anti-communism, history, ideology, Marxism

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Authors: L. Sun, C. Hardacre, A. Garforth, N. Zhang

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Higher Education (HE) degrees in the UK are attractive for international students. The recognized reputation of the HE and the world-leading researchers in some areas in the UK imply that the HE degree from the UK might be a passport to a successful career for abroad students. However, it is a challenge to inspire outstanding students applying for the universities in the UK. The incentives should be country-specific for undergraduates and postgraduates. The potential obstacles to stop students applying for the study in the UK mainly lie in these aspects: different HE systems between the UK and other countries, such as China; less information for the application procedures; worries for the study in English for those non-native speakers; and expensive international tuition fees. The hybrid incentives have been proposed by the efforts from the institutions, stuffs, and students themselves. For example, excellent students from top universities would join us based on the abroad exchange programs or ‘2+2 programme’ with discount tuition. They are potential PhD candidates in the further study in the UK. Diversity promotions are implemented to share information and answer queries for potential students and their guardians. Face to face presentations, workshops, and seminars deliver chances for students to admire teaching and learning in the UK, and give students direct answers for their confusions. WeChat official account and Twitter as the online information platform are set up to post messages of recruitment, the guidance for the application procedures, and international collaboration in teaching and research as well. Students who are studying in the UK and the alumni would share their experiences in the study and lives in the UK and their careers after obtaining the HE degree would play as a positive stimulus to our potential students. Short term modules in the UK with exchangeable credits in summer holidays would give abroad students firsthand experiences of the study in the reputable schools with excellent academics, different cultures and the network with international students. Successful cases at the University of Manchester illustrated the effectiveness of these presented methodologies.

Keywords: abroad students, degree study, high education, hybrid incentives

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Authors: Durga Toshniwal, Lokesh Agrawal

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As the web continues to play an increasing role in information exchange, and conducting daily activities, computer users have become the target of miscreants which infects hosts with malware or adware for financial gains. Unfortunately, even a single visit to compromised web site enables the attacker to detect vulnerabilities in the user’s applications and force the downloading of multitude of malware binaries. We provide an approach to effectively scan the so-called drive-by downloads on the Internet. Drive-by downloads are result of URLs that attempt to exploit their visitors and cause malware to be installed and run automatically. To scan the web for malicious pages, the first step is to use a crawler to collect URLs that live on the Internet, and then to apply fast prefiltering techniques to reduce the amount of pages that are needed to be examined by precise, but slower, analysis tools (such as honey clients or antivirus programs). Although the technique is effective, it requires a substantial amount of resources. A main reason is that the crawler encounters many pages on the web that are legitimate and needs to be filtered. In this paper, to characterize the nature of this rising threat, we present implementation of a web crawler on Python, an approach to search the web more efficiently for pages that are likely to be malicious, filtering benign pages and passing remaining pages to antivirus program for detection of malwares. Our approaches starts from an initial seed of known, malicious web pages. Using these seeds, our system generates search engines queries to identify other malicious pages that are similar to the ones in the initial seed. By doing so, it leverages the crawling infrastructure of search engines to retrieve URLs that are much more likely to be malicious than a random page on the web. The results shows that this guided approach is able to identify malicious web pages more efficiently when compared to random crawling-based approaches.

Keywords: web crawler, malwares, seeds, drive-by-downloads, security

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Authors: April Hueimin Lu, Liangj-Ju Yao, Jun-Tin Lin, Susan Siru Liu

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This paper discusses the application of aerial survey technology and 3D laser scanning technology in the surveying and mapping work of the settlements and slate houses of the old Taiwanese aborigines. The relics of old Taiwanese aborigines with thousands of history are widely distributed in the deep mountains of Taiwan, with a vast area and inconvenient transportation. When constructing the basic data of cultural assets, it is necessary to apply new technology to carry out efficient and accurate settlement mapping work. In this paper, taking the old Paiwan as an example, the aerial survey of the settlement of about 5 hectares and the 3D laser scanning of a slate house were carried out. The obtained orthophoto image was used as an important basis for drawing the settlement map. This 3D landscape data of topography and buildings derived from the aerial survey is important for subsequent preservation planning as well as building 3D scan provides a more detailed record of architectural forms and materials. The 3D settlement data from the aerial survey can be further applied to the 3D virtual model and animation of the settlement for virtual presentation. The information from the 3D scanning of the slate house can also be used for further digital archives and data queries through network resources. The results of this study show that, in large-scale settlement surveys, aerial surveying technology is used to construct the topography of settlements with buildings and spatial information of landscape, as well as the application of 3D scanning for small-scale records of individual buildings. This application of 3D technology, greatly increasing the efficiency and accuracy of survey and mapping work of aboriginal settlements, is much helpful for further preservation planning and rejuvenation of aboriginal cultural heritage.

Keywords: aerial survey, 3D scanning, aboriginal settlement, settlement architecture cluster, ecological landscape area, old Paiwan settlements, slat house, photogrammetry, SfM, MVS), Point cloud, SIFT, DSM, 3D model

Procedia PDF Downloads 173

Authors: Kavian Khosravinia, Mohd Khair Hassan, Ribhan Zafira Abdul Rahman, Syed Abdul Rahman Al-Haddad

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The CAN (controller area network) bus is introduced as a multi-master, message broadcast system. The messages sent on the CAN are used to communicate state information, referred as a signal between different ECUs, which provides data consistency in every node of the system. OBD-II Dongles that are based on request and response method is the wide-spread solution for extracting sensor data from cars among researchers. Unfortunately, most of the past researches do not consider resolution and quantity of their input data extracted through OBD-II technology. The maximum feasible scan rate is only 9 queries per second which provide 8 data points per second with using ELM327 as well-known OBD-II dongle. This study aims to develop and design a programmable, and latency-sensitive vehicle data acquisition system that improves the modularity and flexibility to extract exact, trustworthy, and fresh car sensor data with higher frequency rates. Furthermore, the researcher must break apart, thoroughly inspect, and observe the internal network of the vehicle, which may cause severe damages to the expensive ECUs of the vehicle due to intrinsic vulnerabilities of the CAN bus during initial research. Desired sensors data were collected from various vehicles utilizing Raspberry Pi3 as computing and processing unit with using OBD (request-response) and direct CAN method at the same time. Two types of data were collected for this study. The first, CAN bus frame data that illustrates data collected for each line of hex data sent from an ECU and the second type is the OBD data that represents some limited data that is requested from ECU under standard condition. The proposed system is reconfigurable, human-readable and multi-task telematics device that can be fitted into any vehicle with minimum effort and minimum time lag in the data extraction process. The standard operational procedure experimental vehicle network test bench is developed and can be used for future vehicle network testing experiment.

Keywords: CAN bus, OBD-II, vehicle data acquisition, connected cars, telemetry, Raspberry Pi3

Procedia PDF Downloads 208

Authors: Mariana Damova, Stanko Stankov, Emil Stoyanov, Hristo Hristov, Hermand Pessek, Plamen Chernev

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We will present one of the first use cases on the DestinE platform, a joint initiative of the European Commission, European Space Agency and EUMETSAT, providing access to global earth observation, meteorological and statistical data, and emphasize the good practice of intergovernmental agencies acting in concert. Further, we will discuss the importance of space-bound disruptive solutions for improving the balance between the ever-increasing water-related disasters coming from climate change and minimizing their economic and societal impact. The use case focuses on forecasting floods and estimating the impact of flood events on the urban environment and the ecosystems in the affected areas with the purpose of helping municipal decision-makers to analyze and plan resource needs and to forge human-environment relationships by providing farmers with insightful information for improving their agricultural productivity. For the forecast, we will adopt an EO4AI method of our platform ISME-HYDRO, in which we employ a pipeline of neural networks applied to in-situ measurements and satellite data of meteorological factors influencing the hydrological and hydrodynamic status of rivers and dams, such as precipitations, soil moisture, vegetation index, snow cover to model flood events and their span. ISME-HYDRO platform is an e-infrastructure for water resources management based on linked data, extended with further intelligence that generates forecasts with the method described above, throws alerts, formulates queries, provides superior interactivity and drives communication with the users. It provides synchronized visualization of table views, graphviews and interactive maps. It will be federated with the DestinE platform.

Keywords: flood simulation, AI, Earth observation, e-Infrastructure, flood forecasting, flood areas localization, response planning, resource estimation

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Authors: Dirson Santos De Campos, Deller James Ferreira, Anderson Cavalcante Gonçalves, Uyara Ferreira Silva

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Rubrics to learning research provide many evaluation criteria and expected performance standards linked to defined student activity for learning and pedagogical objectives. Despite the rubric being used in education at all levels, academic literature on rubrics as a tool to support research in SQL Education is quite rare. There is a large class of SQL queries is syntactically correct, but certainly, not all are semantically correct. Detecting and correcting errors is a recurring problem in SQL education. In this paper, we usthe Rubric Abstract Framework (RAF), which consists of steps, that allows us to map the information to measure student performance guided by didactic objectives defined by the teacher as long as it is contextualized domain modeling by rubric. An empirical study was done that demonstrates how rubrics can mitigate student difficulties in finding logical errors and easing teacher workload in SQL education. Detecting and correcting logical errors is an important skill for students. Researchers have proposed several ways to improve SQL education because understanding this paradigm skills are crucial in software engineering and computer science. The RAF instantiation was using in an empirical study developed during the COVID-19 pandemic in database course. The pandemic transformed face-to-face and remote education, without presential classes. The lab activities were conducted remotely, which hinders the teaching-learning process, in particular for this research, in verifying the evidence or statements of knowledge, skills, and abilities (KSAs) of students. Various research in academia and industry involved databases. The innovation proposed in this paper is the approach used where the results obtained when using rubrics to map logical errors in query formulation have been analyzed with gains obtained by students empirically verified. The research approach can be used in the post-pandemic period in both classroom and distance learning.

Keywords: rubric, logical error, structured query language (SQL), empirical study, SQL education

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Authors: Ahlem Bouziri, Chiraz Latiri, Eric Gaussier

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The steady growth in the size of textual document collections is a key progress-driver for modern information retrieval techniques whose effectiveness and efficiency are constantly challenged. Given a user query, the number of retrieved documents can be overwhelmingly large, hampering their efficient exploitation by the user. In addition, retaining only relevant documents in a query answer is of paramount importance for an effective meeting of the user needs. In this situation, the query expansion technique offers an interesting solution for obtaining a complete answer while preserving the quality of retained documents. This mainly relies on an accurate choice of the added terms to an initial query. Interestingly enough, query expansion takes advantage of large text volumes by extracting statistical information about index terms co-occurrences and using it to make user queries better fit the real information needs. In this respect, a promising track consists in the application of data mining methods to extract dependencies between terms, namely a generic basis of association rules between terms. The key feature of our approach is a better trade off between the size of the mining result and the conveyed knowledge. Thus, face to the huge number of derived association rules and in order to select the optimal combination of query terms from the generic basis, we propose to model the problem as a classification problem and solve it using a supervised learning algorithm such as SVM or k-means. For this purpose, we first generate a training set using a genetic algorithm based approach that explores the association rules space in order to find an optimal set of expansion terms, improving the MAP of the search results. The experiments were performed on SDA 95 collection, a data collection for information retrieval. It was found that the results were better in both terms of MAP and NDCG. The main observation is that the hybridization of text mining techniques and query expansion in an intelligent way allows us to incorporate the good features of all of them. As this is a preliminary attempt in this direction, there is a large scope for enhancing the proposed method.

Keywords: supervised leaning, classification, query expansion, association rules

Procedia PDF Downloads 325

Authors: Alice Brites, Gerd Sparovek, Jean Paul Metzger, Ricardo Rodrigues

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The segregation between science and policy in decision making process hinders nature conservation efforts worldwide. Scientists have been criticized for not producing information that leads to effective solutions for environmental problems. In an attempt to bridge this gap between science and practice, we conducted a project aimed at supporting the implementation of the Brazilian Native Vegetation Protection Law (NVPL) implementation in São Paulo State (SP), Brazil. To do so, we conducted multiple open meetings with the stakeholders involved in this discussion. Throughout this process, we raised stakeholders' demands for scientific information and brought feedbacks about our findings. However, our main scientific advice was not taken into account during the NVPL implementation in SP. The NVPL has a mechanism that exempts landholders who converted native vegetation without offending the legislation in place at the time of the conversion from restoration requirements. We found out that there were no accurate spatialized data for native vegetation cover before the 1960s. Thus, the initial benchmark for the mechanism application should be the 1965 Brazilian Forest Act. Even so, SP kept the 1934 Brazilian Forest Act as the initial legal benchmark for the law application. This decision implies the use of a probabilistic native vegetation map that has uncertainty and subjectivity as its intrinsic characteristics, thus its use can lead to legal queries, corruption, and an unfair benefit application. But why this decision was made even after the scientific advice was vastly divulgated? We raised some possible reasons to explain it. First, the decision was made during a government transition, showing that circumstantial political events can overshadow scientific arguments. Second, the debate about the NVPL in SP was not pacified and powerful stakeholders could benefit from the confusion created by this decision. Finally, the native vegetation protection mechanism is a complex issue, with many technical aspects that can be hard to understand for a non-specialized courtroom, such as the one that made the final decision at SP. This example shows that science and decision-makers still have a long way ahead to improve their way to interact and that science needs to find its way to be heard above the political buzz.

Keywords: Brazil, forest act, science-based dialogue, science-policy interface

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Authors: Iseoluwa Bukunmi Kolawole, Omowunmi Precious Isreal

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Social media has completely revolutionized the ways communication used to take place even a decade ago. It makes use of computer mediated technologies which helps in the creation of information and sharing. Social media may be defined as the production, consumption and exchange of information across platforms for social interaction. The social media has become a forum in which customer’s look for information about companies to do business with and request answers to questions about their products and services. Customer service may be termed as a process of ensuring customer’s satisfaction by meeting and exceeding their wants. In delivering excellent customer service, knowing customer’s expectations and where they are reaching out is important in meeting and exceeding customer’s want. Facebook is one of the most used social media platforms among others which also include Twitter, Instagram, Whatsapp and LinkedIn. This indicates customers are spending more time on social media platforms, therefore calls for improvement in customer service delivery over the social media pages. Millions of people channel their issues, complaints, complements and inquiries through social media. This study have being able to identify what social media customers want, their expectations and how they want to be responded to by brands and companies. However, the applied research methodology used in this paper was a mixed methods approach. The authors of d paper used qualitative method such as gathering critical views of experts on social media and customer relationship management to analyse the impacts of social media on customer's satisfaction through interviews. The authors also used quantitative such as online survey methods to address issues at different stages and to have insight about different aspects of the platforms i.e. customer’s and company’s perception about the effects of social media. Thereby exploring and gaining better understanding of how brands make use of social media as a customer relationship management tool. And an exploratory research approach strategy was applied analysing how companies need to create good customer support using social media in order to improve good customer service delivery, customer retention and referrals. Therefore many companies have preferred social media platform application as a medium of handling customer’s queries and ensuring their satisfaction, this is because social media tools are considered more transparent and effective in its operations when dealing with customer relationship management.

Keywords: brands, customer service, information, social media

Procedia PDF Downloads 270