Search results for: real-time data acquisition and reporting
24086 Estimating the Life-Distribution Parameters of Weibull-Life PV Systems Utilizing Non-Parametric Analysis
Authors: Saleem Z. Ramadan
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In this paper, a model is proposed to determine the life distribution parameters of the useful life region for the PV system utilizing a combination of non-parametric and linear regression analysis for the failure data of these systems. Results showed that this method is dependable for analyzing failure time data for such reliable systems when the data is scarce.Keywords: masking, bathtub model, reliability, non-parametric analysis, useful life
Procedia PDF Downloads 56224085 Digimesh Wireless Sensor Network-Based Real-Time Monitoring of ECG Signal
Authors: Sahraoui Halima, Dahani Ameur, Tigrine Abedelkader
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DigiMesh technology represents a pioneering advancement in wireless networking, offering cost-effective and energy-efficient capabilities. Its inherent simplicity and adaptability facilitate the seamless transfer of data between network nodes, extending the range and ensuring robust connectivity through autonomous self-healing mechanisms. In light of these advantages, this study introduces a medical platform harnessed with DigiMesh wireless network technology characterized by low power consumption, immunity to interference, and user-friendly operation. The primary application of this platform is the real-time, long-distance monitoring of Electrocardiogram (ECG) signals, with the added capacity for simultaneous monitoring of ECG signals from multiple patients. The experimental setup comprises key components such as Raspberry Pi, E-Health Sensor Shield, and Xbee DigiMesh modules. The platform is composed of multiple ECG acquisition devices labeled as Sensor Node 1 and Sensor Node 2, with a Raspberry Pi serving as the central hub (Sink Node). Two communication approaches are proposed: Single-hop and multi-hop. In the Single-hop approach, ECG signals are directly transmitted from a sensor node to the sink node through the XBee3 DigiMesh RF Module, establishing peer-to-peer connections. This approach was tested in the first experiment to assess the feasibility of deploying wireless sensor networks (WSN). In the multi-hop approach, two sensor nodes communicate with the server (Sink Node) in a star configuration. This setup was tested in the second experiment. The primary objective of this research is to evaluate the performance of both Single-hop and multi-hop approaches in diverse scenarios, including open areas and obstructed environments. Experimental results indicate the DigiMesh network's effectiveness in Single-hop mode, with reliable communication over distances of approximately 300 meters in open areas. In the multi-hop configuration, the network demonstrated robust performance across approximately three floors, even in the presence of obstacles, without the need for additional router devices. This study offers valuable insights into the capabilities of DigiMesh wireless technology for real-time ECG monitoring in healthcare applications, demonstrating its potential for use in diverse medical scenarios.Keywords: DigiMesh protocol, ECG signal, real-time monitoring, medical platform
Procedia PDF Downloads 7924084 Preliminary Design of Maritime Energy Management System: Naval Architectural Approach to Resolve Recent Limitations
Authors: Seyong Jeong, Jinmo Park, Jinhyoun Park, Boram Kim, Kyoungsoo Ahn
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Energy management in the maritime industry is being required by economics and in conformity with new legislative actions taken by the International Maritime Organization (IMO) and the European Union (EU). In response, the various performance monitoring methodologies and data collection practices have been examined by different stakeholders. While many assorted advancements in operation and technology are applicable, their adoption in the shipping industry stays small. This slow uptake can be considered due to many different barriers such as data analysis problems, misreported data, and feedback problems, etc. This study presents a conceptual design of an energy management system (EMS) and proposes the methodology to resolve the limitations (e.g., data normalization using naval architectural evaluation, management of misrepresented data, and feedback from shore to ship through management of performance analysis history). We expect this system to make even short-term charterers assess the ship performance properly and implement sustainable fleet control.Keywords: data normalization, energy management system, naval architectural evaluation, ship performance analysis
Procedia PDF Downloads 44924083 Geospatial Data Complexity in Electronic Airport Layout Plan
Authors: Shyam Parhi
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Airports GIS program collects Airports data, validate and verify it, and stores it in specific database. Airports GIS allows authorized users to submit changes to airport data. The verified data is used to develop several engineering applications. One of these applications is electronic Airport Layout Plan (eALP) whose primary aim is to move from paper to digital form of ALP. The first phase of development of eALP was completed recently and it was tested for a few pilot program airports across different regions. We conducted gap analysis and noticed that a lot of development work is needed to fine tune at least six mandatory sheets of eALP. It is important to note that significant amount of programming is needed to move from out-of-box ArcGIS to a much customized ArcGIS which will be discussed. The ArcGIS viewer capability to display essential features like runway or taxiway or the perpendicular distance between them will be discussed. An enterprise level workflow which incorporates coordination process among different lines of business will be highlighted.Keywords: geospatial data, geology, geographic information systems, aviation
Procedia PDF Downloads 41624082 Anisotropic Total Fractional Order Variation Model in Seismic Data Denoising
Authors: Jianwei Ma, Diriba Gemechu
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In seismic data processing, attenuation of random noise is the basic step to improve quality of data for further application of seismic data in exploration and development in different gas and oil industries. The signal-to-noise ratio of the data also highly determines quality of seismic data. This factor affects the reliability as well as the accuracy of seismic signal during interpretation for different purposes in different companies. To use seismic data for further application and interpretation, we need to improve the signal-to-noise ration while attenuating random noise effectively. To improve the signal-to-noise ration and attenuating seismic random noise by preserving important features and information about seismic signals, we introduce the concept of anisotropic total fractional order denoising algorithm. The anisotropic total fractional order variation model defined in fractional order bounded variation is proposed as a regularization in seismic denoising. The split Bregman algorithm is employed to solve the minimization problem of the anisotropic total fractional order variation model and the corresponding denoising algorithm for the proposed method is derived. We test the effectiveness of theproposed method for synthetic and real seismic data sets and the denoised result is compared with F-X deconvolution and non-local means denoising algorithm.Keywords: anisotropic total fractional order variation, fractional order bounded variation, seismic random noise attenuation, split Bregman algorithm
Procedia PDF Downloads 20724081 Public Financial Management in Ghana: A Move beyond Reforms to Consolidation and Sustainability
Authors: Mohammed Sani Abdulai
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Ghana’s Public Financial Management reforms have been going on for some two decades now (1997/98 to 2017/18). Given this long period of reforms, Ghana in 2019 is putting together both a Public Financial Management (PFM) strategy and a Ghana Integrated Financial Management Information System (GIFMIS) strategy for the next 5-years (2020-2024). The primary aim of these dual strategies is assisting the country in moving beyond reforms to consolidation and sustainability. In this paper we, first, examined the evolution of Ghana’s PFM reforms. We, secondly, reviewed the legal and institutional reforms undertaken to strengthen the country’s key PFM institutions. Thirdly, we summarized the strengths and weaknesses identified by the 2018 Public Expenditure and Financial Accountability (PEFA) assessment of Ghana’s PFM system relating to its macro-fiscal framework, budget preparation and approval, budget execution, accounting and fiscal reporting as well as external scrutiny and audit. We, finally, considered what the country should be doing to achieve its intended goal of PFM consolidation and sustainability. Using a qualitative method of review and analysis of existing documents, we, through this paper, brought to the fore the lessons that could be learnt by other developing countries from Ghana’s PFM reforms experiences. These lessons included the need to: (a) undergird any PFM reform with a comprehensive PFM reform strategy; (b) undertake a legal and institutional reforms of the key PFM institutions; (c) assess the strengths and weaknesses of those reforms using PFM performance evaluation tools such as PEFA framework; and (d) move beyond reforms to consolidation and sustainability.Keywords: public financial management, public expenditure and financial accountability, reforms, consolidation, sustainability
Procedia PDF Downloads 23324080 NSBS: Design of a Network Storage Backup System
Authors: Xinyan Zhang, Zhipeng Tan, Shan Fan
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The first layer of defense against data loss is the backup data. This paper implements an agent-based network backup system used the backup, server-storage and server-backup agent these tripartite construction, and we realize the snapshot and hierarchical index in the NSBS. It realizes the control command and data flow separation, balances the system load, thereby improving the efficiency of the system backup and recovery. The test results show the agent-based network backup system can effectively improve the task-based concurrency, reasonably allocate network bandwidth, the system backup performance loss costs smaller and improves data recovery efficiency by 20%.Keywords: agent, network backup system, three architecture model, NSBS
Procedia PDF Downloads 45924079 A t-SNE and UMAP Based Neural Network Image Classification Algorithm
Authors: Shelby Simpson, William Stanley, Namir Naba, Xiaodi Wang
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Both t-SNE and UMAP are brand new state of art tools to predominantly preserve the local structure that is to group neighboring data points together, which indeed provides a very informative visualization of heterogeneity in our data. In this research, we develop a t-SNE and UMAP base neural network image classification algorithm to embed the original dataset to a corresponding low dimensional dataset as a preprocessing step, then use this embedded database as input to our specially designed neural network classifier for image classification. We use the fashion MNIST data set, which is a labeled data set of images of clothing objects in our experiments. t-SNE and UMAP are used for dimensionality reduction of the data set and thus produce low dimensional embeddings. Furthermore, we use the embeddings from t-SNE and UMAP to feed into two neural networks. The accuracy of the models from the two neural networks is then compared to a dense neural network that does not use embedding as an input to show which model can classify the images of clothing objects more accurately.Keywords: t-SNE, UMAP, fashion MNIST, neural networks
Procedia PDF Downloads 19824078 An Online Adaptive Thresholding Method to Classify Google Trends Data Anomalies for Investor Sentiment Analysis
Authors: Duygu Dere, Mert Ergeneci, Kaan Gokcesu
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Google Trends data has gained increasing popularity in the applications of behavioral finance, decision science and risk management. Because of Google’s wide range of use, the Trends statistics provide significant information about the investor sentiment and intention, which can be used as decisive factors for corporate and risk management fields. However, an anomaly, a significant increase or decrease, in a certain query cannot be detected by the state of the art applications of computation due to the random baseline noise of the Trends data, which is modelled as an Additive white Gaussian noise (AWGN). Since through time, the baseline noise power shows a gradual change an adaptive thresholding method is required to track and learn the baseline noise for a correct classification. To this end, we introduce an online method to classify meaningful deviations in Google Trends data. Through extensive experiments, we demonstrate that our method can successfully classify various anomalies for plenty of different data.Keywords: adaptive data processing, behavioral finance , convex optimization, online learning, soft minimum thresholding
Procedia PDF Downloads 16724077 Energy Efficient Assessment of Energy Internet Based on Data-Driven Fuzzy Integrated Cloud Evaluation Algorithm
Authors: Chuanbo Xu, Xinying Li, Gejirifu De, Yunna Wu
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Energy Internet (EI) is a new form that deeply integrates the Internet and the entire energy process from production to consumption. The assessment of energy efficient performance is of vital importance for the long-term sustainable development of EI project. Although the newly proposed fuzzy integrated cloud evaluation algorithm considers the randomness of uncertainty, it relies too much on the experience and knowledge of experts. Fortunately, the enrichment of EI data has enabled the utilization of data-driven methods. Therefore, the main purpose of this work is to assess the energy efficient of park-level EI by using a combination of a data-driven method with the fuzzy integrated cloud evaluation algorithm. Firstly, the indicators for the energy efficient are identified through literature review. Secondly, the artificial neural network (ANN)-based data-driven method is employed to cluster the values of indicators. Thirdly, the energy efficient of EI project is calculated through the fuzzy integrated cloud evaluation algorithm. Finally, the applicability of the proposed method is demonstrated by a case study.Keywords: energy efficient, energy internet, data-driven, fuzzy integrated evaluation, cloud model
Procedia PDF Downloads 20224076 Graph Based Traffic Analysis and Delay Prediction Using a Custom Built Dataset
Authors: Gabriele Borg, Alexei Debono, Charlie Abela
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There on a constant rise in the availability of high volumes of data gathered from multiple sources, resulting in an abundance of unprocessed information that can be used to monitor patterns and trends in user behaviour. Similarly, year after year, Malta is also constantly experiencing ongoing population growth and an increase in mobilization demand. This research takes advantage of data which is continuously being sourced and converting it into useful information related to the traffic problem on the Maltese roads. The scope of this paper is to provide a methodology to create a custom dataset (MalTra - Malta Traffic) compiled from multiple participants from various locations across the island to identify the most common routes taken to expose the main areas of activity. This use of big data is seen being used in various technologies and is referred to as ITSs (Intelligent Transportation Systems), which has been concluded that there is significant potential in utilising such sources of data on a nationwide scale. Furthermore, a series of traffic prediction graph neural network models are conducted to compare MalTra to large-scale traffic datasets.Keywords: graph neural networks, traffic management, big data, mobile data patterns
Procedia PDF Downloads 13124075 Using the Nerlovian Adjustment Model to Assess the Response of Farmers to Price and Other Related Factors: Evidence from Sierra Leone Rice Cultivation
Authors: Alhaji M. H. Conteh, Xiangbin Yan, Alfred V. Gborie
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The goal of this study was to increase the awareness of the description and assessments of rice acreage response and to offer mechanisms for agricultural policy scrutiny. The Ordinary Least Square (OLS) technique was utilized to determine the coefficients of acreage response models for the rice varieties. The magnitudes of the coefficients (λ) of both the ROK lagged and NERICA lagged acreages were found positive and highly significant, which indicates that farmers’ adjustment rate was very low. Regarding lagged actual price for both the ROK and NERICE rice varieties, the short-run price elasticities were lower than long-run, which is suggesting a long-term adjustment of the acreage, is under the crop. However, the apparent recommendations for policy transformation are to open farm gate prices and to decrease government’s involvement in agricultural sector especially in the acquisition of agricultural inputs. Impending research have to be centred on how this might be better realized. Necessary conditions should be made available to the private sector by means of minimizing price volatility. In accordance with structural reforms, it is necessary to convey output prices to farmers with minimum distortion. There is a need to eradicate price subsidies and control, which generate distortion in the market in addition to huge financial costs.Keywords: acreage response, rate of adjustment, rice varieties, Sierra Leone
Procedia PDF Downloads 32324074 Learning Compression Techniques on Smart Phone
Authors: Farouk Lawan Gambo, Hamada Mohammad
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Data compression shrinks files into fewer bits than their original presentation. It has more advantage on the internet because the smaller a file, the faster it can be transferred but learning most of the concepts in data compression are abstract in nature, therefore, making them difficult to digest by some students (engineers in particular). This paper studies the learning preference of engineering students who tend to have strong, active, sensing, visual and sequential learning preferences, the paper also studies the three shift of technology-aided that learning has experienced, which mobile learning has been considered to be the feature of learning that will integrate other form of the education process. Lastly, we propose a design and implementation of mobile learning application using software engineering methodology that will enhance the traditional teaching and learning of data compression techniques.Keywords: data compression, learning preference, mobile learning, multimedia
Procedia PDF Downloads 44824073 Investigation of Delivery of Triple Play Services
Authors: Paramjit Mahey, Monica Sharma, Jasbinder Singh
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Fiber based access networks can deliver performance that can support the increasing demands for high speed connections. One of the new technologies that have emerged in recent years is Passive Optical Networks. This paper is targeted to show the simultaneous delivery of triple play service (data, voice and video). The comparative investigation and suitability of various data rates is presented. It is demonstrated that as we increase the data rate, number of users to be accommodated decreases due to increase in bit error rate.Keywords: BER, PON, TDMPON, GPON, CWDM, OLT, ONT
Procedia PDF Downloads 54124072 Inherited Eye Diseases in Africa: A Scoping Review and Strategy for an African Longitudinal Eye Study
Authors: Bawa Yusuf Muhammad, Musa Abubakar Kana, Aminatu Abdulrahman, Kerry Goetz
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Background: Inherited eye diseases are disorders that affect globally, 1 in 1000 people. The six main world populations have created databases containing information on eye genotypes. Aim: The aim of the scoping review was to mine and present the available information to date on the genetics of inherited eye diseases within the African continent. Method: Literature Search Strategy was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). PubMed and Google Scholar searched for articles on inherited eye diseases from inception to 20th June 2022. Both Original and review articles that report on inherited, genetic or developmental/congenital eye diseases within the African Continent were included in the research. Results: A total of 1162 citations were obtained, but only 37 articles were reviewed based on the inclusion and exclusion criteria. The highest output of publications on inherited eye diseases comes from South Africa and Tunisia (about 43%), followed by Morocco and Egypt (27%), then Sub-Saharan Africa and North Africa (13.50%), while the remaining articles (16.5%) originated from Nigeria, Ghana, Mauritania Cameroon, Zimbabwe and combined article between Zimbabwe and Cameroon. Glaucoma and inherited retinal disorders represent the most studied diseases, followed by Albinism and congenital cataracts, respectively. Conclusion: Despite the growing research from Tunisia, Morocco, Egypt and South Africa, Sub-Saharan Africa remains almost a virgin region to explore the genetics of eye diseases.Keywords: inherited eye diseases, Africa, scoping review, longitudinal eye study
Procedia PDF Downloads 5724071 Nazca: A Context-Based Matching Method for Searching Heterogeneous Structures
Authors: Karine B. de Oliveira, Carina F. Dorneles
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The structure level matching is the problem of combining elements of a structure, which can be represented as entities, classes, XML elements, web forms, and so on. This is a challenge due to large number of distinct representations of semantically similar structures. This paper describes a structure-based matching method applied to search for different representations in data sources, considering the similarity between elements of two structures and the data source context. Using real data sources, we have conducted an experimental study comparing our approach with our baseline implementation and with another important schema matching approach. We demonstrate that our proposal reaches higher precision than the baseline.Keywords: context, data source, index, matching, search, similarity, structure
Procedia PDF Downloads 36424070 Semiautomatic Calculation of Ejection Fraction Using Echocardiographic Image Processing
Authors: Diana Pombo, Maria Loaiza, Mauricio Quijano, Alberto Cadena, Juan Pablo Tello
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In this paper, we present a semi-automatic tool for calculating ejection fraction from an echocardiographic video signal which is derived from a database in DICOM format, of Clinica de la Costa - Barranquilla. Described in this paper are each of the steps and methods used to find the respective calculation that includes acquisition and formation of the test samples, processing and finally the calculation of the parameters to obtain the ejection fraction. Two imaging segmentation methods were compared following a methodological framework that is similar only in the initial stages of processing (process of filtering and image enhancement) and differ in the end when algorithms are implemented (Active Contour and Region Growing Algorithms). The results were compared with the measurements obtained by two different medical specialists in cardiology who calculated the ejection fraction of the study samples using the traditional method, which consists of drawing the region of interest directly from the computer using echocardiography equipment and a simple equation to calculate the desired value. The results showed that if the quality of video samples are good (i.e., after the pre-processing there is evidence of an improvement in the contrast), the values provided by the tool are substantially close to those reported by physicians; also the correlation between physicians does not vary significantly.Keywords: echocardiography, DICOM, processing, segmentation, EDV, ESV, ejection fraction
Procedia PDF Downloads 42624069 Spatially Random Sampling for Retail Food Risk Factors Study
Authors: Guilan Huang
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In 2013 and 2014, the U.S. Food and Drug Administration (FDA) collected data from selected fast food restaurants and full service restaurants for tracking changes in the occurrence of foodborne illness risk factors. This paper discussed how we customized spatial random sampling method by considering financial position and availability of FDA resources, and how we enriched restaurants data with location. Location information of restaurants provides opportunity for quantitatively determining random sampling within non-government units (e.g.: 240 kilometers around each data-collector). Spatial analysis also could optimize data-collectors’ work plans and resource allocation. Spatial analytic and processing platform helped us handling the spatial random sampling challenges. Our method fits in FDA’s ability to pinpoint features of foodservice establishments, and reduced both time and expense on data collection.Keywords: geospatial technology, restaurant, retail food risk factor study, spatially random sampling
Procedia PDF Downloads 35024068 Automatic MC/DC Test Data Generation from Software Module Description
Authors: Sekou Kangoye, Alexis Todoskoff, Mihaela Barreau
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Modified Condition/Decision Coverage (MC/DC) is a structural coverage criterion that is highly recommended or required for safety-critical software coverage. Therefore, many testing standards include this criterion and require it to be satisfied at a particular level of testing (e.g. validation and unit levels). However, an important amount of time is needed to meet those requirements. In this paper we propose to automate MC/DC test data generation. Thus, we present an approach to automatically generate MC/DC test data, from software module description written over a dedicated language. We introduce a new merging approach that provides high MC/DC coverage for the description, with only a little number of test cases.Keywords: domain-specific language, MC/DC, test data generation, safety-critical software coverage
Procedia PDF Downloads 44124067 Blockchain-Based Approach on Security Enhancement of Distributed System in Healthcare Sector
Authors: Loong Qing Zhe, Foo Jing Heng
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A variety of data files are now available on the internet due to the advancement of technology across the globe today. As more and more data are being uploaded on the internet, people are becoming more concerned that their private data, particularly medical health records, are being compromised and sold to others for money. Hence, the accessibility and confidentiality of patients' medical records have to be protected through electronic means. Blockchain technology is introduced to offer patients security against adversaries or unauthorised parties. In the blockchain network, only authorised personnel or organisations that have been validated as nodes may share information and data. For any change within the network, including adding a new block or modifying existing information about the block, a majority of two-thirds of the vote is required to confirm its legitimacy. Additionally, a consortium permission blockchain will connect all the entities within the same community. Consequently, all medical data in the network can be safely shared with all authorised entities. Also, synchronization can be performed within the cloud since the data is real-time. This paper discusses an efficient method for storing and sharing electronic health records (EHRs). It also examines the framework of roles within the blockchain and proposes a new approach to maintain EHRs with keyword indexes to search for patients' medical records while ensuring data privacy.Keywords: healthcare sectors, distributed system, blockchain, electronic health records (EHR)
Procedia PDF Downloads 19124066 Demographic Factors Influencing Employees’ Salary Expectations and Labor Turnover
Authors: M. Osipova
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Thanks to informational technologies development every sphere of economics is becoming more and more data-centralized as people are generating huge datasets containing information on any aspect of their life. Applying research of such data to human resources management allows getting scarce statistics on labor market state including salary expectations and potential employees’ typical career behavior, and this information can become a reliable basis for management decisions. The following article presents results of career behavior research based on freely accessible resume data. Information used for study is much wider than one usually uses in human resources surveys. That is why there is enough data for statistically significant results even for subgroups analysis.Keywords: human resources management, salary expectations, statistics, turnover
Procedia PDF Downloads 34924065 A Systematic Literature Review on the Prevalence of Academic Plagiarism and Cheating in Higher Educational Institutions
Authors: Sozon, Pok Wei Fong, Sia Bee Chuan, Omar Hamdan Mohammad
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Owing to the widespread phenomenon of plagiarism and cheating in higher education institutions (HEIs), it is now difficult to ensure academic integrity and quality education. Moreover, the COVID-19 pandemic has intensified the issue by shifting educational institutions into virtual teaching and assessment mode. Thus, there is a need to carry out an extensive and holistic systematic review of the literature to highlight plagiarism and cheating in both prevalence and form among HEIs. This paper systematically reviews the literature concerning academic plagiarism and cheating in HEIs to determine the most common forms and suggest strategies for resolution and boosting the academic integrity of students. The review included 45 articles and publications for the period from February 12, 2018, to September 12, 2022, in the Scopus database aligned with the Systematic Review and Meta-Analysis (PRISMA) guidelines in the selection, filtering, and reporting of the papers for review from which a conclusion can be drawn. Based on the results, out of the studies reviewed, 48% of the quantitative results of students were plagiarized and obtained through cheating, with 84% coming from the fields of Humanities. Moreover, Psychology and Social Sciences studies accumulated 9% and 7% articles respectively. Based on the results, individual factors, institutional factors, and social and cultural factors have contributed to plagiarism and cheating cases in HEIs. The resolution of this issue can be the establishment of ethical and moral development initiatives and modern academic policies and guidelines supported by technological strategies of testing.Keywords: plagiarism, cheating, systematic review, academic integrity
Procedia PDF Downloads 7424064 An Optimal Path for Virtual Reality Education using Association Rules
Authors: Adam Patterson
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This study analyzes the self-reported experiences of virtual reality users to develop insight into an optimal learning path for education within virtual reality. This research uses a sample of 1000 observations to statistically define factors influencing (i) immersion level and (ii) motion sickness rating for virtual reality experience respondents of college age. This paper recommends an efficient duration for each virtual reality session, to minimize sickness and maximize engagement, utilizing modern machine learning methods such as association rules. The goal of this research, in augmentation with previous literature, is to inform logistical decisions relating to implementation of pilot instruction for virtual reality at the collegiate level. Future research will include a Randomized Control Trial (RCT) to quantify the effect of virtual reality education on student learning outcomes and engagement measures. Current research aims to maximize the treatment effect within the RCT by optimizing the learning benefits of virtual reality. Results suggest significant gender heterogeneity amongst likelihood of reporting motion sickness. Females are 1.7 times more likely, than males, to report high levels of motion sickness resulting from a virtual reality experience. Regarding duration, respondents were 1.29 times more likely to select the lowest level of motion sickness after an engagement lasting between 24.3 and 42 minutes. Conversely, respondents between 42 to 60 minutes were 1.2 times more likely to select the higher levels of motion sickness.Keywords: applications and integration of e-education, practices and cases in e-education, systems and technologies in e-education, technology adoption and diffusion of e-learning
Procedia PDF Downloads 6724063 Exploring Electroactive Polymers for Dynamic Data Physicalization
Authors: Joanna Dauner, Jan Friedrich, Linda Elsner, Kora Kimpel
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Active materials such as Electroactive Polymers (EAPs) are promising for the development of novel shape-changing interfaces. This paper explores the potential of EAPs in a multilayer unimorph structure from a design perspective to investigate the visual qualities of the material for dynamic data visualization and data physicalization. We discuss various concepts of how the material can be used for this purpose. Multilayer unimorph EAPs are of particular interest to designers because they can be easily prototyped using everyday materials and tools. By changing the structure and geometry of the EAPs, their movement and behavior can be modified. We present the results of our preliminary user testing, where we evaluated different movement patterns. As a result, we introduce a prototype display built with EAPs for dynamic data physicalization. Finally, we discuss the potentials and drawbacks and identify further open research questions for the design discipline.Keywords: electroactive polymer, shape-changing interfaces, smart material interfaces, data physicalization
Procedia PDF Downloads 9924062 The Influence of English Immersion Program on Academic Performance: Case Study at a Sino-US Cooperative University in China
Authors: Leah Li Echiverri, Haoyu Shang, Yue Li
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Wenzhou-Kean University (WKU) is a Sino-US Cooperative University in China. It practices the English Immersion Program (EIP), where all the courses are taught in English. Class discussions and presentations are pervasively interwoven in designing students’ learning experiences. This WKU model has brought positive influences on students and is in some way ahead of traditional college English majors. However, literature to support the perceptions on the positive outcomes of this teaching and learning model remain scarce. The distinctive profile of Chinese-ESL students in an English Medium of Instruction (EMI) environment contributes further to the scarcity of literature compared to existing studies conducted among ESL learners in Western educational settings. Hence, the study investigated the students’ perceptions towards the English Immersion Program and determine how it influences Chinese-ESL students’ academic performance (AP). This research can provide empirical data that would be helpful to educators, teaching practitioners, university administrators, and other researchers in making informed decisions when developing curricular reforms, instructional and pedagogical methods, and university-wide support programs using this educational model. The purpose of the study was to establish the relationship between the English Immersion Program and Academic Performance among Chinese-ESL students enrolled at WKU for the academic year 2020-2021. Course length, immersion location, course type, and instructional design were the constructs of the English immersion program. English language learning, learning efficiency, and class participation were used to measure academic performance. Descriptive-correlational design was used in this cross-sectional research project. A quantitative approach for data analysis was applied to determine the relationship between the English immersion program and Chinese-ESL students’ academic performance. The research was conducted at WKU; a Chinese-American jointly established higher educational institution located in Wenzhou, Zhejiang province. Convenience, random, and snowball sampling of 283 students, a response rate of 10.5%, were applied to represent the WKU student population. The questionnaire was posted through the survey website named Wenjuanxing and shared to QQ or WeChat. Cronbach’s alpha was used to test the reliability of the research instrument. Findings revealed that when professors integrate technology (PowerPoint, videos, and audios) in teaching, students pay more attention. This contributes to the acquisition of more professional knowledge in their major courses. As to course immersion, students perceive WKU as a good place to study, providing them a high degree of confidence to talk with their professors in English. This also contributes to their English fluency and better pronunciation in their communication. In the construct of designing instruction, the use of pictures, video clips, and professors’ non-verbal communication, and demonstration of concern for students encouraged students to be more active in-class participation. Findings on course length and academic performance indicated that students’ perception regarding taking courses during fall and spring terms can moderately contribute to their academic performance. In conclusion, the findings revealed a significantly strong positive relationship between course type, immersion location, instructional design, and academic performance.Keywords: class participation, English immersion program, English language learning, learning efficiency
Procedia PDF Downloads 17424061 Heat Waves and Hospital Admissions for Mental Disorders in Hanoi Vietnam
Authors: Phan Minh Trang, Joacim Rocklöv, Kim Bao Giang, Gunnar Kullgren, Maria Nilsson
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There are recent studies from high income countries reporting an association between heat waves and hospital admissions for mental health disorders. It is not previously studied if such relations exist in sub-tropical and tropical low- and middle-income countries. In this study from Vietnam, the assumption was that hospital admissions for mental disorders may be triggered, or exacerbated, by heat exposure and heat waves. A database from Hanoi Mental Hospital with mental disorders diagnosed by the International Classification of Diseases 10, spanning over five years, was used to estimate the heatwave-related impacts on admissions for mental disorders. The relationship was analysed by a Negative Binomial regression model accounting for year, month, and days of week. The focus of the study was heat-wave events with periods of three or seven consecutive days above the threshold of 35oC daily maximum temperature. The preliminary study results indicated that heat-waves increased the risks for hospital admission for mental disorders (F00-79) from heat-waves of three and seven days with relative risks (RRs) of 1.16 (1.01–1.33) and 1.42 (1.02–1.99) respectively, when compared with non-heat-wave periods. Heatwave-related admissions for mental disorders increased statistically significantly among men, among residents in rural communities and in elderly. Moreover, cases for organic mental disorders including symptomatic illnesses (F0-9) and mental retardation (F70-79) raised in high risks during heat waves. The findings are novel studying a sub-tropical middle-income city, facing rapid urbanisation and epidemiological and demographic transitions.Keywords: mental disorders, admissions for F0-9 or F70-79, maximum temperature, heat waves
Procedia PDF Downloads 24424060 Research and Implementation of Cross-domain Data Sharing System in Net-centric Environment
Authors: Xiaoqing Wang, Jianjian Zong, Li Li, Yanxing Zheng, Jinrong Tong, Mao Zhan
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With the rapid development of network and communication technology, a great deal of data has been generated in different domains of a network. These data show a trend of increasing scale and more complex structure. Therefore, an effective and flexible cross-domain data-sharing system is needed. The Cross-domain Data Sharing System(CDSS) in a net-centric environment is composed of three sub-systems. The data distribution sub-system provides data exchange service through publish-subscribe technology that supports asynchronism and multi-to-multi communication, which adapts to the needs of the dynamic and large-scale distributed computing environment. The access control sub-system adopts Attribute-Based Access Control(ABAC) technology to uniformly model various data attributes such as subject, object, permission and environment, which effectively monitors the activities of users accessing resources and ensures that legitimate users get effective access control rights within a legal time. The cross-domain access security negotiation subsystem automatically determines the access rights between different security domains in the process of interactive disclosure of digital certificates and access control policies through trust policy management and negotiation algorithms, which provides an effective means for cross-domain trust relationship establishment and access control in a distributed environment. The CDSS’s asynchronous,multi-to-multi and loosely-coupled communication features can adapt well to data exchange and sharing in dynamic, distributed and large-scale network environments. Next, we will give CDSS new features to support the mobile computing environment.Keywords: data sharing, cross-domain, data exchange, publish-subscribe
Procedia PDF Downloads 12424059 The Effectiveness of Summative Assessment in Practice Learning
Authors: Abdool Qaiyum Mohabuth, Syed Munir Ahmad
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Assessment enables students to focus on their learning, assessment. It engages them to work hard and motivates them in devoting time to their studies. Student learning is directly influenced by the type of assessment involved in the programme. Summative Assessment aims at providing measurement of student understanding. In fact, it is argued that summative assessment is used for reporting and reviewing, besides providing an overall judgement of achievement. While summative assessment is a well defined process for learning that takes place in the classroom environment, its application within the practice environment is still being researched. This paper discusses findings from a mixed-method study for exploring the effectiveness of summative assessment in practice learning. A survey questionnaire was designed for exploring the perceptions of mentors and students about summative assessment in practice learning. The questionnaire was administered to the University of Mauritius students and mentors who supervised students for their Work-Based Learning (WBL) practice at the respective placement settings. Some students, having undertaken their WBL practice, were interviewed, for capturing their views and experiences about the application of summative assessment in practice learning. Semi-structured interviews were also conducted with three experienced mentors who have assessed students on practice learning. The findings reveal that though learning in the workplace is entirely different from learning at the University, most students had positive experiences about their summative assessments in practice learning. They felt comfortable and confident to be assessed by their mentors in their placement settings and wished that the effort and time that they devoted to their learning be recognised and valued. Mentors on their side confirmed that the summative assessment is valid and reliable, enabling them to better monitor and coach students to achieve the expected learning outcomes.Keywords: practice learning, judgement, summative assessment, knowledge, skills, workplace
Procedia PDF Downloads 34124058 Routing Protocol in Ship Dynamic Positioning Based on WSN Clustering Data Fusion System
Authors: Zhou Mo, Dennis Chow
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In the dynamic positioning system (DPS) for vessels, the reliable information transmission between each note basically relies on the wireless protocols. From the perspective of cluster-based routing protocols for wireless sensor networks, the data fusion technology based on the sleep scheduling mechanism and remaining energy in network layer is proposed, which applies the sleep scheduling mechanism to the routing protocols, considering the remaining energy of node and location information when selecting cluster-head. The problem of uneven distribution of nodes in each cluster is solved by the Equilibrium. At the same time, Classified Forwarding Mechanism as well as Redelivery Policy strategy is adopted to avoid congestion in the transmission of huge amount of data, reduce the delay in data delivery and enhance the real-time response. In this paper, a simulation test is conducted to improve the routing protocols, which turn out to reduce the energy consumption of nodes and increase the efficiency of data delivery.Keywords: DPS for vessel, wireless sensor network, data fusion, routing protocols
Procedia PDF Downloads 52424057 Advanced Data Visualization Techniques for Effective Decision-making in Oil and Gas Exploration and Production
Authors: Deepak Singh, Rail Kuliev
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This research article explores the significance of advanced data visualization techniques in enhancing decision-making processes within the oil and gas exploration and production domain. With the oil and gas industry facing numerous challenges, effective interpretation and analysis of vast and diverse datasets are crucial for optimizing exploration strategies, production operations, and risk assessment. The article highlights the importance of data visualization in managing big data, aiding the decision-making process, and facilitating communication with stakeholders. Various advanced data visualization techniques, including 3D visualization, augmented reality (AR), virtual reality (VR), interactive dashboards, and geospatial visualization, are discussed in detail, showcasing their applications and benefits in the oil and gas sector. The article presents case studies demonstrating the successful use of these techniques in optimizing well placement, real-time operations monitoring, and virtual reality training. Additionally, the article addresses the challenges of data integration and scalability, emphasizing the need for future developments in AI-driven visualization. In conclusion, this research emphasizes the immense potential of advanced data visualization in revolutionizing decision-making processes, fostering data-driven strategies, and promoting sustainable growth and improved operational efficiency within the oil and gas exploration and production industry.Keywords: augmented reality (AR), virtual reality (VR), interactive dashboards, real-time operations monitoring
Procedia PDF Downloads 86