Search results for: survival data analysis

Authors: Osama Moustafa Zayed

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Aim of the work: To evaluate the effectiveness of venous glucose, levels of serum lactate and base deficit in polytraumatized patients as simple parameters to predict the mortality in these patients. Compared to the predictive value of Trauma and injury severity (TRISS) and Acute Physiology And Chronic Health Evaluation IV (APACHE IV). Introduction: Trauma is a serious global health problem, accounting for approximately one in 10 deaths worldwide. Trauma accounts for 5 million deaths per year. Prediction of mortality in trauma patients is an important part of trauma care. Several trauma scores have been devised to predict injury severity and risk of mortality. The trauma and injury severity score (TRISS) was most common used. Regardless of the accuracy of trauma scores, is based on an anatomical description of every injury and cannot be assigned to the patients until a full diagnostic procedure has been performed. So we hypothesized that alterations in admission glucose, lactate levels and base deficit would be an early and easy rapid predictor of mortality. Patient and Method: a comparative cross-sectional study. 282 Polytraumatized patients attended to the Emergency Department(ED) of the Suez Canal university Hospital constituted. The period from 1/1/2012 to 1/4/2013 was included. Results: We found that the best cut off value of TRISS probability of survival score for prediction of mortality among poly-traumatized patients is = 90, with 77% sensitivity and 89% specificity using area under the ROC curve (0.89) at (95%CI). APACHE IV demonstrated 67% sensitivity and 95% specificity at 95% CI at cut off point 99. The best cutoff value of Random Blood Sugar (RBS) for prediction of mortality was>140 mg/dl, with 89%, sensitivity, 49% specificity. The best cut off value of base deficit for prediction of mortality was less than -5.6 with 64% sensitivity, 93% specificity. The best cutoff point of lactate for prediction of mortality was > 2.6 mmol/L with 92%, sensitivity, 42% specificity. Conclusion: According to our results from all evaluated predictors of mortality (laboratory and scores) and mortality based on the estimated cutoff values using ROC curves analysis, the highest risk of mortality was found using a cutoff value of 90 in TRISS score while with laboratory parameters the highest risk of mortality was with serum lactate > 2.6 . Although that all of the three parameter are accurate in predicting mortality in poly-traumatized patients and near with each other, as in serum lactate the area under the curve 0.82, in BD 0.79 and 0.77 in RBS.

Keywords: APACHE IV, emergency department, polytraumatized patients, serum lactate

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Authors: Katarina Ott, Velibor Mačkić, Mihaela Bronić, Branko Stanić

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The determinants of national budget transparency have been widely discussed in the literature, while research on determinants of local budget transparency are scarce and empirically inconclusive, particularly in the new, fiscally centralised, EU member states. To fill the gap, we combine two strands of the literature: that concerned with public administration and public finance, shedding light on the economic and financial determinants of local budget transparency, and that on the political economy of transparency (principal agent theory), covering the relationships among politicians and between politicians and voters. Our main hypothesis states that variables describing residents’ capacity have a greater impact on local budget transparency than variables indicating the institutional capacity of local government units (LGUs). Additional subhypotheses test the impact of each variable analysed on local budget transparency. We address the determinants of local budget transparency in Croatia, measured by the number of key local budget documents published on the LGUs’ websites. By using a data set of 128 cities and 428 municipalities over the 2015-2017 period and by applying panel data analysis based on Poisson and negative binomial distribution, we test our main hypothesis and sub-hypotheses empirically. We measure different characteristics of institutional and residents’ capacity for each LGU. Age, education and ideology of the mayor/municipality head, political competition indicators, number of employees, current budget revenues and direct debt per capita have been used as a measure of the institutional capacity of LGU. Residents’ capacity in each LGU has been measured through the numbers of citizens and their average age as well as by average income per capita. The most important determinant of local budget transparency is average residents' income per capita at both city and municipality level. The results are in line with most previous research results in fiscally decentralised countries. In the context of a fiscally centralised country with numerous small LGUs, most of whom have low administrative and fiscal capacity, this has a theoretical rationale in the legitimacy and principal-agent theory (opportunistic motives of the incumbent). The result is robust and significant, but because of the various other results that change between city and municipality levels (e.g. ideology and political competition), there is a need for further research (both on identifying other determinates and/or methods of analysis). Since in Croatia the fiscal capacity of a LGU depends heavily on the income of its residents, units with higher per capita incomes in many cases have also higher budget revenues allowing them to engage more employees and resources. In addition, residents’ incomes might be also positively associated with local budget transparency because of higher citizen demand for such transparency. Residents with higher incomes expect more public services and have more access to and experience in using the Internet, and will thus typically demand more budget information on the LGUs’ websites.

Keywords: budget transparency, count data, Croatia, local government, political economy

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Authors: Wanida Suwunniponth

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The purpose of this research was to study the factors of characteristic of business, website quality and trust affected intention to use electronic payment systems for online purchasing. This survey research used questionnaire as a tool to collect the data of 300 customers who purchased online products and used an electronic payment system. The descriptive statistics and multiple regression analysis were used to analyze data. The results revealed that customers had a good opinion towards the characteristic of the business and website quality. However, they have a moderate opinion towards trust and intention to repurchase. In addition, the characteristics of the business affected the purchase intention the most, followed by website quality and the trust with statistical significance at 0.05 level. For particular, the terms of reputation, communication, information quality, perceived risk and word of mouth affected the intention to use the electronic payment system. In contrast, the terms of size, system quality and service quality did not affect intention to use an electronic payment system.

Keywords: electronic payment, intention, online purchasing, trust

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Authors: Yao Wu

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In the context of financial globalization, China has put forward the policy goal of high-quality development, and the digital economy, with its advantage of information resources, is driving China's export trade to achieve high-quality development. Due to the long-standing financing constraints of small and medium-sized export enterprises, how to expand the export scale of small and medium-sized enterprises has become a major threshold for the development of China's export trade. This paper firstly adopts the hierarchical analysis method to establish the evaluation system of high-quality development of China's export trade; secondly, the panel data of 30 provinces in China from 2011 to 2018 are selected for empirical analysis to establish the impact model of digital inclusive finance on the high-quality development of China's export trade; based on the analysis of heterogeneous enterprise trade model, a mediating effect model is established to verify the mediating role of credit constraint in the development of high-quality export trade in China. Based on the above analysis, this paper concludes that inclusive digital finance, with its unique digital and inclusive nature, alleviates the credit constraint problem among SMEs, enhances the binary marginal effect of SMEs' exports, optimizes their export scale and structure, and promotes the high-quality development of regional and even national export trade. Finally, based on the findings of this paper, we propose insights and suggestions for inclusive digital finance to promote the high-quality development of export trade.

Keywords: digital inclusive finance, high-quality development of export trade, fixed effects, binary marginal effects

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Authors: Gunasekaran Raja, Kottilingam Kottursamy, Rajakumar Arul, Ramkumar Jayaraman, Krithika Sairam, Lakshmi Ravi

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The synchronization server maintains a dynamically changing cache, which contains the data items which were requested and collected by the mobile node from the server. The order and presence of tuples in the cache changes dynamically according to the frequency of updates performed on the data, by the server and client. To synchronize, the data which has been modified by client and the server at an instant are collected, batched together by the type of modification (insert/ update/ delete), and sorted according to their update frequencies. This ensures that the DCASH (Dynamic Cache Synchronization Algorithm for Heterogeneous Reverse Y synchronizing Mobile Database Systems) gives priority to the frequently accessed data with high usage. The optimal memory management algorithm is proposed to manage data items according to their frequency, theorems were written to show the current mobile data activity is reverse Y in nature and the experiments were tested with 2g and 3g networks for various mobile devices to show the reduced response time and energy consumption.

Keywords: mobile databases, synchronization, cache, response time

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Authors: Stefano Fantin

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The present analysis outcomes from the research undertaken in the course of the European-funded project EUNITY, which targets the gaps in research and development on cybersecurity and privacy between Europe and Japan. Under these auspices, the research presents a study on the policy approach of Japan, the EU and a number of Member States of the Union with regard to the handling and discovery of software vulnerabilities, with the aim of identifying methodological differences and similarities. This research builds upon a functional comparative analysis of both public policies and legal instruments from the identified jurisdictions. The result of this analysis is based on semi-structured interviews with EUNITY partners, as well as by the participation of the researcher to a recent report from the Center for EU Policy Study on software vulnerability. The European Union presents a rather fragmented legal framework on software vulnerabilities. The presence of a number of different legislations at the EU level (including Network and Information Security Directive, Critical Infrastructure Directive, Directive on the Attacks at Information Systems and the Proposal for a Cybersecurity Act) with no clear focus on such a subject makes it difficult for both national governments and end-users (software owners, researchers and private citizens) to gain a clear understanding of the Union’s approach. Additionally, the current data protection reform package (general data protection regulation), seems to create legal uncertainty around security research. To date, at the member states level, a few efforts towards transparent practices have been made, namely by the Netherlands, France, and Latvia. This research will explain what policy approach such countries have taken. Japan has started implementing a coordinated vulnerability disclosure policy in 2004. To date, two amendments can be registered on the framework (2014 and 2017). The framework is furthermore complemented by a series of instruments allowing researchers to disclose responsibly any new discovery. However, the policy has started to lose its efficiency due to a significant increase in reports made to the authority in charge. To conclude, the research conducted reveals two asymmetric policy approaches, time-wise and content-wise. The analysis therein will, therefore, conclude with a series of policy recommendations based on the lessons learned from both regions, towards a common approach to the security of European and Japanese markets, industries and citizens.

Keywords: cybersecurity, vulnerability, European Union, Japan

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Authors: Bar Shapira-Youngster, Sima Amram-Vaknin, Yuliya Lipshits-Braziler

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The study examined how 811 Israelis experienced and coped with the COVID-19 lockdown. Stress, uncertainty, and loss of control were reported as common emotional experiences. Two main difficulties were reported: Loneliness and health and emotional concerns. Frequent explanations for the virus's emergence were: scientific or faith reasoning. The most prevalent coping strategies were distraction activities and acceptance. Reducing the use of maladaptive coping strategies has important implications for mental health outcomes. Objectives: COVID-19 has been recognized as a collective, continuous traumatic stressor. The present study examined how individuals experienced, perceived, and coped with this traumatic event during the lockdown in Israel in April 2020. Method: 811 Israelis (71.3% were women; mean age 43.7, SD=13.3)completed an online semi-structured questionnaire consisting two sections: In the first section, participants were asked to report background information. In the second section, they were asked to answer 8 open-ended questions about their experience, perception, and coping with the covid-19 lockdown. Participation was voluntary, and anonymity was assured, they were not offered compensation of any kind. The data were subjected to qualitative content analysis that seeks to classify the participants` answers into an effective number of categories that represent similar meanings. Our content analysis of participants’ answers extended far beyond simple word counts; our objective was to try to identify recurrent categories that characterized participants’ responses to each question. We sought to ensure that the categories regarding the different questions are as mutually exclusive and exhaustive as possible. To ensure robust analysis, the data were initially analyzed by the first author, and a second opinion was then sought from research colleagues. Contribution: The present research expands our knowledge of individuals' experiences, perceptions, and coping mechanisms with continuous traumatic events. Reducing the use of maladaptive coping strategies has important implications for mental health outcomes.

Keywords: Covid-19, emotional distress, coping, continuous traumatic event

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Authors: Supunmali Ahangama, Danny Chiang Choon Poo

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Health analytics (HA) is used in healthcare systems for effective decision-making, management, and planning of healthcare and related activities. However, user resistance, the unique position of medical data content, and structure (including heterogeneous and unstructured data) and impromptu HA projects have held up the progress in HA applications. Notably, the accuracy of outcomes depends on the skills and the domain knowledge of the data analyst working on the healthcare data. The success of HA depends on having a sound process model, effective project management and availability of supporting tools. Thus, to overcome these challenges through an effective process model, we propose an HA process model with features from the rational unified process (RUP) model and agile methodology.

Keywords: agile methodology, health analytics, unified process model, UML

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Authors: Soumiya Bhattacharjee, P. K. Champati Ray, Shovan L. Chattoraj, Mrinmoy Dhara

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The entire Himalayan range is globally renowned for rainfall-induced landslides. The prime focus of the study is to determine rainfall based threshold for initiation of landslides that can be used as an important component of an early warning system for alerting stake holders. This research deals with temporal dimension of slope failures due to extreme rainfall events along the National Highway-58 from Karanprayag to Badrinath in the Garhwal Himalaya, India. Post processed 3-hourly rainfall intensity data and its corresponding duration from daily rainfall data available from Tropical Rainfall Measuring Mission (TRMM) were used as the prime source of rainfall data. Landslide event records from Border Road Organization (BRO) and some ancillary landslide inventory data for 2013 and 2014 have been used to determine Intensity Duration (ID) based rainfall threshold. The derived governing threshold equation, I= 4.738D^-0.025, has been considered for prediction of landslides of the study region. This equation was validated with an accuracy of 70% landslides during August and September 2014. The derived equation was considered for further prediction of landslides of the study region. From the obtained results and validation, it can be inferred that this equation can be used for initiation of landslides in the study area to work as a part of an early warning system. Results can significantly improve with ground based rainfall estimates and better database on landslide records. Thus, the study has demonstrated a very low cost method to get first-hand information on possibility of impending landslide in any region, thereby providing alert and better preparedness for landslide disaster mitigation.

Keywords: landslide, intensity-duration, rainfall threshold, TRMM, slope, inventory, early warning system

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Authors: Belkacem Laimouche

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With the field of artificial intelligence (AI) experiencing exponential growth, fueled by technological advancements that pave the way for increasingly innovative and promising applications, there is an escalating need to develop rigorous methods for assessing their performance in pursuit of transparency and equity. This article proposes a metrology-inspired statistical framework for evaluating bias and explainability in AI systems. Drawing from the principles of metrology, we propose a pioneering approach, using a concrete example, to evaluate the accuracy and precision of AI models, as well as to quantify the sources of measurement uncertainty that can lead to bias in their predictions. Furthermore, we explore a statistical approach for evaluating the explainability of AI systems based on their ability to provide interpretable and transparent explanations of their predictions.

Keywords: artificial intelligence, metrology, measurement uncertainty, prediction error, bias, machine learning algorithms, probabilistic models, interlaboratory comparison, data analysis, data reliability, measurement of bias impact on predictions, improvement of model accuracy and reliability

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Authors: Surita Maini, Sanjay Dhanka

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Machine learning (ML) involves developing algorithms and statistical models that enable computers to learn and make predictions or decisions based on data without being explicitly programmed. Because of its unlimited abilities ML is gaining popularity in medical sectors; Medical Imaging, Electronic Health Records, Genomic Data Analysis, Wearable Devices, Disease Outbreak Prediction, Disease Diagnosis, etc. In the last few decades, many researchers have tried to diagnose Breast Cancer (BC) using ML, because early detection of any disease can save millions of lives. Working in this direction, the authors have proposed a hybrid ML technique RBF SVM, to predict the BC in earlier the stage. The proposed method is implemented on the Breast Cancer UCI ML dataset with 569 instances and 32 attributes. The authors recorded performance metrics of the proposed model i.e., Accuracy 98.24%, Sensitivity 98.67%, Specificity 97.43%, F1 Score 98.67%, Precision 98.67%, and run time 0.044769 seconds. The proposed method is validated by K-Fold cross-validation.

Keywords: breast cancer, support vector classifier, machine learning, hyper parameter tunning

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Authors: Osarobo Omorogieva Ighodaro, Josephus Otejere

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This paper contains the modelling and simulation of GT13E2 combined cycle gas turbine with the aid of the software EBSILON PROFESSIONAL. The design mode was modeled using guaranteed performance data from the power plant, in the off design, temperature variation of ambient air and fogging (spray water at inlet to compressor) was simulated. The fogging was simulated under two different modes; constant fuel consumption and constant turbine exhaust temperature .The model results were validated using actual operating data by applying error percentage analysis. The validation results obtained ranged from -0.0038% to 0% in design condition while the results varied from -0.9202% to 10.24% The model shows that fogging decreases compressor inlet temperature which in turn decreases the power required to drive the compressor hence improving the simple cycle efficiency and hence increasing power generated.

Keywords: inlet fogging, off design, combined cycle, modelling

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Authors: S. Pullteap, M. Pathomsuriyaporn

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In this article, a study of employee’s opinion to the factors that affect to the flood preventive and the corrective action plan in an electronic industry at the Sharp Manufacturing (Thailand) Co., Ltd. has been investigated. The surveys data of 175 workers and supervisors have, however, been selected for data analysis. The results is shown that the employees emphasize about the needs in a subsidy at the time of disaster at high levels of 77.8%, as the plan focusing on flood prevention of the rehabilitation equipment is valued at the intermediate level, which is 79.8%. Demonstration of the hypothesis has found that the different education levels has thus been affected to the needs factor at the flood disaster time. Moreover, most respondents give priority to flood disaster risk management factor. Consequently, we found that the flood prevention plan is valued at high level, especially on information monitoring, which is 93.4% for the supervisor item. The respondents largely assume that the flood will have impacts on the industry, up to 80%, thus to focus on flood management plans is enormous.

Keywords: flood prevention plan, flood event, electronic industrial plant, disaster, risk management

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Authors: Krzysztof Rafał, Weronika Radziszewska, Hubert Biedka, Oskar Grabowski, Krzysztof Mik

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We present a method to choose energy storage technologies and their parameters for the economic operation of a microgrid. A grid-connected system with local loads and PV generation is assumed, where an energy storage system (ESS) is attached to minimize energy cost by providing energy balancing and arbitrage functionalities. The ESS operates in a hybrid configuration and consists of two unique technologies operated in a coordinated way. Based on given energy profiles and economical data a model calculates financial flow for ESS investment, including energy cost and ESS depreciation resulting from degradation. The optimization strategy proposes a hybrid set of two technologies with their respective power and energy ratings to minimize overall system cost in a given timeframe. Results are validated through microgrid simulations using real-life input profiles.

Keywords: energy storage, hybrid energy storage, cost-benefit analysis, microgrid, battery sizing

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Authors: Khaleel Bader Bataineh

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Past studies have maintained that the Arab learners' beliefs about language learning hold vital effects on their performance. Thus, this study was carried out to investigate the language learning beliefs of Irbid National University students. It aimed at identifying the language learning beliefs according to gender. This study is a descriptive design that employed survey questionnaire of Language Learning Beliefs Inventory (BALLI). The data were elicited from 83 English major students during the class sessions. The data were analyzed using an SPSS program in which frequency analysis and t-test were performed to examine the students’ responses. Thus, the major findings of this research indicated that there is a variation in responses with regards to the subjects’ beliefs about English learning. Also, the findings show significant differences in four questionnaire items according to gender. It is hoped that the findings provide valuable insights to educators about the learners’ beliefs which assist them to develop the teaching and learning English language process in Jordan universities.

Keywords: foreign language, students’ beliefs, language learning, Arab students

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Authors: Fantu Lombamo Untiso, Sylvia Murphy, Emily Pieracci

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Background: Rabies is a highly fatal viral disease of all warm-blooded animals including human globally. However, effective rabies control program still remains to be a reality and needs to be strengthened. Objective: Reviewing of recorded data and analyzing it to generate information on the status of rabies in Addis Ababa in the year 2012/13. Methods: A retrospective data were used from the Ethiopian Public Health Institute rabies case record book registered in the year 2012/13. Results: Among 1357 suspected rabid animals clinically examined; only 8.84% were positive for rabies. Out of 216 animal brains investigated in the laboratory with Fluorescent Antibody Technique, 55.5% were confirmed rabies positive. Among the laboratory confirmed positive rabies cases, high percentage of the animals came from Yeka (20%) and lower number from Kirkos subcity (3.3%). Out of 1149 humans who came to the institute seeking anti-rabies post-exposure prophylaxis, 85.65% and 7.87% of them were exposed to suspected dogs and cats respectively. 3 human deaths due to rabies were reported in the year after exposure to dog bite of unknown vaccination status. Conclusion: The principal vector of rabies in Addis Ababa is dog. Effective rabies management and control based on confirmed cases and mass-immunization and control of stray dog populations is recommended.

Keywords: Addis Ababa, exposure, rabies, surveillance

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Authors: Ke He, Wumaier Parezhati, Haruka Yamashita

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Recently, online marketplaces in the e-commerce industry, such as Rakuten and Alibaba, have become some of the most popular online marketplaces in Asia. In these shopping websites, consumers can select purchase products from a large number of stores. Additionally, consumers of the e-commerce site have to register their name, age, gender, and other information in advance, to access their registered account. Therefore, establishing a method for analyzing consumer preferences from both the store and the product side is required. This study uses the Doc2Vec method, which has been studied in the field of natural language processing. Doc2Vec has been used in many cases to analyze the extraction of semantic relationships between documents (represented as consumers) and words (represented as products) in the field of document classification. This concept is applicable to represent the relationship between users and items; however, the problem is that one more factor (i.e., shops) needs to be considered in Doc2Vec. More precisely, a method for analyzing the relationship between consumers, stores, and products is required. The purpose of our study is to combine the analysis of the Doc2vec model for users and shops, and for users and items in the same feature space. This method enables the calculation of similar shops and items for each user. In this study, we derive the real data analysis accumulated in the online marketplace and demonstrate the efficiency of the proposal.

Keywords: Doc2Vec, online marketplace, marketing, recommendation systems

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Authors: A. Delimitsou, C. Gouedard, E. Konstanta, A. Koletis, S. Patera, E. Manou, K. Spaho, S. Murray

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Background: There remains a lack of International Standard Control Reference materials for Next Generation Sequencing-based approaches or device calibration. We have designed and validated dsDNA biomimetic reference materials for targeted such approaches incorporating proprietary motifs (patent pending) for device/test calibration. They enable internal single-sample calibration, alleviating sample comparisons to pooled historical population-based data assembly or statistical modelling approaches. We have validated such an approach for BRCA Copy Number Variation analytics using iQRS™-CNVSUITE versus Mixed Ligation-dependent Probe Amplification. Methods: Standard BRCA Copy Number Variation analysis was compared between mixed ligation-dependent probe amplification and next generation sequencing using a cohort of 198 breast/ovarian cancer patients. Next generation sequencing based copy number variation analysis of samples spiked with iQRS™ dsDNA biomimetics were analysed using proprietary CNVSUITE software. Mixed ligation-dependent probe amplification analyses were performed on an ABI-3130 Sequencer and analysed with Coffalyser software. Results: Concordance of BRCA – copy number variation events for mixed ligation-dependent probe amplification and CNVSUITE indicated an overall sensitivity of 99.88% and specificity of 100% for iQRS™-CNVSUITE. The negative predictive value of iQRS-CNVSUITE™ for BRCA was 100%, allowing for accurate exclusion of any event. The positive predictive value was 99.88%, with no discrepancy between mixed ligation-dependent probe amplification and iQRS™-CNVSUITE. For device calibration purposes, precision was 100%, spiking of patient DNA demonstrated linearity to 1% (±2.5%) and range from 100 copies. Traditional training was supplemented by predefining the calibrator to sample cut-off (lock-down) for amplicon gain or loss based upon a relative ratio threshold, following training of iQRS™-CNVSUITE using spiked iQRS™ calibrator and control mocks. BRCA copy number variation analysis using iQRS™-CNVSUITE™ was successfully validated and ISO15189 accredited and now enters CE-IVD performance evaluation. Conclusions: The inclusion of a reference control competitor (iQRS™ dsDNA mimetic) to next generation sequencing-based sequencing offers a more robust sample-independent approach for the assessment of copy number variation events compared to mixed ligation-dependent probe amplification. The approach simplifies data analyses, improves independent sample data analyses, and allows for direct comparison to an internal reference control for sample-specific quantification. Our iQRS™ biomimetic reference materials allow for single sample copy number variation analytics and further decentralisation of diagnostics to single patient sample assessment.

Keywords: validation, diagnostics, oncology, copy number variation, reference material, calibration

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Authors: Hecson Christian, Joel Macwan

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Landfill site selection in an urban area is a critical issue in the planning process. With the growth of the urbanization, it has a mammoth impact on the economy, ecology, and environmental health of the region. Outsized amount of wastes are produced and the problem gets soared every day. Hence, selection of ideal site for sanitary landfill is a challenge for urban planners and solid waste managers. Disposal site is a function of many parameters. Among all, Geotechnical parameters are very vital as the same is related to surrounding open land. Moreover, the accessible safe and acceptable land is also scarce. Therefore, in this paper geotechnical parameters are used to develop a GIS model to identify an ideal location for landfill purpose. Metropolitan city of Surat is highly populated and fastest growing urban area in India. The research objectives are to conduct field experiments to collect data and to transfer the facts in GIS platform to evolve a model, to find ideal location. Planners’ preferences were obtained to use analytical hierarchical process (AHP) to find weights of each parameter. Integration of GIS and Multi-Criteria Decision Analysis (MCDA) techniques are applied to improve decision-making. It augments an environment for transformation and combination of geographical data and planners’ preferences. GIS performs deterministic overlay and buffer operations. MCDA methods evaluate alternatives based on the decision makers’ subjective values and priorities. Research results have shown many alternative locations. Economic analysis of selected site from actual operations point of view is not included in this research.

Keywords: GIS, AHP, MCDA, Geo-technical

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Authors: Samiah Alammari, Nassim Ammour

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When providing a massive number of tasks successively to a deep learning process, a good performance of the model requires preserving the previous tasks data to retrain the model for each upcoming classification. Otherwise, the model performs poorly due to the catastrophic forgetting phenomenon. To overcome this shortcoming, we developed a successful continual learning deep model for remote sensing hyperspectral image regions classification. The proposed neural network architecture encapsulates two trainable subnetworks. The first module adapts its weights by minimizing the discrimination error between the land-cover classes during the new task learning, and the second module tries to learn how to replicate the data of the previous tasks by discovering the latent data structure of the new task dataset. We conduct experiments on HSI dataset Indian Pines. The results confirm the capability of the proposed method.

Keywords: continual learning, data reconstruction, remote sensing, hyperspectral image segmentation

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Authors: Pilly Joseph Kagosi

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The study aims at assessing challenges observed during implementation of participatory irrigation management (PIM) approach for food security in semi-arid areas of Tanzania. Data were collected through questionnaire, PRA tools, key informants discussion, Focus Group Discussion (FGD), participant observation and literature review. Data collected from questionnaire was analyzed using SPSS while PRA data was analyzed with the help of local communities during PRA exercise. Data from other methods were analyzed using content analysis. The study revealed that PIM approach has contribution in improved food security at household level due to involvement of communities in water management activities and decision making which enhanced availability of water for irrigation and increased crop production. However there were challenges observed during implementation of the approach including; minimum participation of beneficiaries in decision making during planning and designing stages, meaning inadequate devolution of power among scheme owners; Inadequate and lack of transparency on income expenditure in Water Utilization Associations’ (WUAs), water conflict among WUAs members, conflict between farmers and livestock keepers and conflict between WUAs leaders and village government regarding training opportunities and status; WUAs rules and regulation are not legally recognized by the National court and few farmers involved in planting trees around water sources. However it was realized that some of the mentioned challenges were rectified by farmers themselves facilitated by government officials. The study recommends that, the identified challenges need to be rectified for farmers to realize impotence of PIM approach as it was realized by other Asian countries.

Keywords: potentials of implementing participatory approach, challenges of participatory approach, irrigation management, Tanzania

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Authors: Almutazballlah Qablan, Jihan M. Muhaidat, Bana Abu Rajab

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Background: Acne vulgaris is the most common skin condition that general practitioners and dermatologists encounter. It represents a chronic inflammatory disease affecting the pilosebaceous unit. Although acne vulgaris is not a life-threatening condition, it has a considerable psychological impact on the affected person. Acne patients have poor body image, low self-esteem, social isolation, and restricted activities. As part of the emotional impact, increased levels of anxiety, anger, depression, and frustration have also been observed in acne patients. (1) In this study, we want to assess the association between two modifiable risk factors; BMI and smoking, regarding acne vulgaris. Methods: A case-control study was conducted at King Abdullah University Hospital in Irbid, north Jordan in 2019/2020. A total number of 163 Acne cases were collected and interviewed by the author; on the other hand, there were 162 control cases. Anthropometric measures for Acne patients and control individuals were taken, and BMI was calculated. Both groups were asked about smoking habits. Data on subjects between 14 and 33 years of age were extracted. The characteristics of people who reported acne were compared with those with no acne using univariate and multivariate analysis. The Statistical Package for Social Sciences (SPSS) was relied on to analyze the collected data. The crosstabs methods (chi-square) and odd ratios were relied on to test the study hypothesis. Results: Cigarette smoking was highly associated with no-acne, with an odds ratio of 0.4 (95% CI: 0.2–0.9), P-value = 0.018. BMI and waterpipe smoking were not significantly associated with acne in the multivariate analysis. Conclusion: Cigarette smoking was found to be protective from Acne. No significant relation between BMI nor waterpipe smoking and the development of Acne Vulgaris.

Keywords: acne, BMI, smoking, case-control

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Authors: Veniamin Boiarkin, Bruno Bogaz Zarpelão, Muttukrishnan Rajarajan

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The manufacturing sector is a vital component of most economies, which leads to a large number of cyberattacks on organisations, whereas disruption in operation may lead to significant economic consequences. Adversaries aim to disrupt the production processes of manufacturing companies, gain financial advantages, and steal intellectual property by getting unauthorised access to sensitive data. Access to sensitive data helps organisations to enhance the production and management processes. However, the majority of the existing data-sharing mechanisms are either susceptible to different cyber attacks or heavy in terms of computation overhead. In this paper, a privacy-preserving data-sharing scheme for smart utilities is proposed. First, a customer’s privacy adjustment mechanism is proposed to make sure that end-users have control over their privacy, which is required by the latest government regulations, such as the General Data Protection Regulation. Secondly, a local differential privacy-based mechanism is proposed to ensure the privacy of the end-users by hiding real data based on the end-user preferences. The proposed scheme may be applied to different industrial control systems, whereas in this study, it is validated for energy utility use cases consisting of smart, intelligent devices. The results show that the proposed scheme may guarantee the required level of privacy with an expected relative error in utility.

Keywords: data-sharing, local differential privacy, manufacturing, privacy-preserving mechanism, smart utility

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Authors: Chander Shekhar, Jeetendra Yadav, Shaziya Allarakha

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Hypertension has been described as an 'iceberg disease' as those who suffered are ignored and hence usually seek healthcare services at a very late stage. It is estimated that more than 2 million Indians are suffering from hypertensive heart disease that contributed to above 0.13 million deaths in 2016. The paper study aims to know the prevalence of Hypertension in India and its variation by socioeconomic backgrounds and to find out risk factors discriminating hypertension with special emphasis on consumption of tobacco and alcohol among men aged 15-54 years in India. The paper uses NFHS (2015-16) data. The paper used binary logistic regression and discriminant analysis to find significant predictors and discriminants of interest. The prevalence of hypertension was 16.5% in the study population. The results suggest that consumption of alcohol and tobacco are significant discriminant characteristics in carrying hypertension irrespective of what socioeconomic background characteristic he possesses.

Keywords: hypertention, alcohol, tobacco, discriminant

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Authors: Kohkan Shamsi

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Background: MRI and PET are now extensively utilized in Alzheimer's disease (AD) trials for patient eligibility, efficacy assessment, and safety evaluations but including imaging in AD trials impacts site selection process, patient recruitment, and patient retention. Methods: PET/MRI are performed at baseline and at multiple follow-up timepoints. This requires prospective site imaging qualification, evaluation of phantom data, training and continuous monitoring of machines for acquisition of standardized and consistent data. This also requires prospective patient/caregiver training as patients must go to multiple facilities for imaging examinations. We will share our experience form one of the largest AD programs. Lesson learned: Many neurological diseases have a similar presentation as AD or could confound the assessment of drug therapy. The inclusion of wrong patients has ethical and legal issues, and data could be excluded from the analysis. Centralized eligibility evaluation read process will be discussed. Amyloid related imaging abnormalities (ARIA) were observed in amyloid-β trials. FDA recommended regular monitoring of ARIA. Our experience in ARIA evaluations in large phase III study at > 350 sites will be presented. Efficacy evaluation: MRI is utilized to evaluate various volumes of the brain. FDG PET or amyloid PET agents has been used in AD trials. We will share our experience about site and central independent reads. Imaging logistic issues that need to be handled in the planning phase will also be discussed as it can impact patient compliance thereby increasing missing data and affecting study results. Conclusion: imaging must be prospectively planned to include standardizing imaging methodologies, site selection process and selecting assessment criteria. Training should be transparently conducted and documented. Prospective patient/caregiver awareness of imaging requirement is essential for patient compliance and reduction in missing imaging data.

Keywords: Alzheimer's disease, ARIA, MRI, PET, patient recruitment, retention

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Authors: Xiaohong Li, Wenfan Yan

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Background: While it is widely considered that the university library plays a critical role in fulfilling the institution's mission and providing students’ learning experience beyond the classrooms, how the technology-enhanced library reform changed college students’ learning experience hasn’t been thoroughly investigated. The purpose of this study is to explore how technology-enhanced library reform affects students’ learning experience and career readiness and further identify the factors and effective conditions that enable the quality learning outcome of Chinese college students. Methodologies: This study selected the qualitative comparative analysis (QCA) method to explore the effects of technology-enhanced university library reform on college students’ learning experience and career readiness. QCA is unique in explaining the complex relationship between multiple factors from a holistic perspective. Compared with the traditional quantitative and qualitative analysis, QCA not only adds some quantitative logic but also inherits the characteristics of qualitative research focusing on the heterogeneity and complexity of samples. Shenyang Normal University (SNU) selected a sample of the typical comprehensive university in China that focuses on students’ learning and application of professional knowledge and trains professionals to different levels of expertise. A total of 22 current university students and 30 graduates who joined the Library Readers Association of SNU from 2011 to 2019 were selected for semi-structured interviews. Based on the data collected from these participating students, qualitative comparative analysis (QCA), including univariate necessity analysis and the multi-configuration analysis, was conducted. Findings and Discussion: QCA analysis results indicated that the influence of technology-enhanced university library restructures and reorganization on student learning experience and career readiness is the result of multiple factors. Technology-enhanced library equipment and other hardware restructured to meet the college students learning needs and have played an important role in improving the student learning experience and learning persistence. More importantly, the soft characteristics of technology-enhanced library reform, such as library service innovation space and culture space, have a positive impact on student’s career readiness and development. Technology-enhanced university library reform is not only the change in the building's appearance and facilities but also in library service quality and capability. The study also provides suggestions for policy, practice, and future research.

Keywords: career readiness, college student learning experience, qualitative comparative analysis (QCA), technology-enhanced library reform

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Authors: Jonahid Chakder, Mahfuzul Haque

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Flash flood is among the foremost disastrous characteristic hazards which cause hampering within the environment and social orders due to climate change across the world. In Northeastern region of Bangladesh faces severe flash floods regularly, Such, the Khowai river is a flash flood-prone river. But until now, there are no previous studies about the flash flood of this river. Farmlands Building resilience, protection of crops & fish enclosures of wetland in Habiganj Haor areas, regional roads, and business establishments were submerged due to flash floods. The flash floods of the Khowai River are frequent events, which happened in 1988, 1998, 2000, 2007, 2017, and 2019. Therefore, this study tries to analyze Khowai river morphology, Precipitation, Water level, Satellite image, and Catchment characteristics: a catchment scale analysis that helps to comprehend Khowai river flash flood characteristics and factors of influence. From precipitation analysis, the finding outcome disclosed the data about flash flood accurate zones at the Khowai district watershed. The morphological analysis workout from satellite image and find out the consequence of sinuosity and gradient of this river. The sinuosity indicates that the Khowai river is an antecedent and a meandering river and a meandering river can’t influence the flash flood of any region, but other factors respond here. It is understood that the Khowai river catchment elevation analysis from DEM is directly influenced. The left Baramura and Right Atharamura anticline of the Khowai basin watershed reflects a major impact on the stratigraphy as an impermeable clay layer and this consequence the water passes downward with the drainage pattern and Tributary. This drainage system, the gradient of tributary and their runoff, and the confluence of water in the pre-monsoon season rise the Khowai river water level which influences flash floods (within six hours of Precipitation).

Keywords: geology, gradient, tributary, drainage, watershed, flash flood

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Authors: Nicodemus M. J. Mbwambo, Yu-Shan Sun, Murali Sitaraman, Joan Krone

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This paper presents a generic data abstraction that captures a navigable tree position. The mathematical modeling of the abstraction encapsulates the current tree position, which can be used to navigate and modify the tree. The encapsulation of the tree position in the data abstraction specification avoids the use of explicit references and aliasing, thereby simplifying verification of (imperative) client code that uses the data abstraction. To ease the tasks of such specification and verification, a general tree theory, rich with mathematical notations and results, has been developed. The paper contains an example to illustrate automated verification ramifications. With sufficient tree theory development, automated proving seems plausible even in the absence of a special-purpose tree solver.

Keywords: automation, data abstraction, maps, specification, tree, verification

Procedia PDF Downloads 155

Authors: Basan Shrestha

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The relationship between the household size and the poverty is not well understood. Malthus followers advocate that the increasing population add pressure to the dwindling resource base due to increasing demand that would lead to poverty. Others claim that bigger households are richer due to availability of household labour for income generation activities. Facts from Nepal were analyzed to examine the relationship between the household size and poverty rate. The analysis of data from 3,968 Village Development Committee (VDC)/ municipality (MP) located in 75 districts of all five development regions revealed that the average household size had moderate positive correlation with the poverty rate (Karl Pearson's correlation coefficient=0.44). In a regression analysis, the household size determined 20% of the variation in the poverty rate. Higher positive correlation was observed in eastern Nepal (Karl Pearson's correlation coefficient=0.66). The regression analysis showed that the household size determined 43% of the variation in the poverty rate in east. The relation was poor in far-west. It could be because higher incidence of poverty was there irrespective of household size. Overall, the facts revealed that the bigger households were relatively poorer. With the increasing level of awareness and interventions for family planning, it is anticipated that the household size will decrease leading to the decreased poverty rate. In addition, the government needs to devise a mechanism to create employment opportunities for the household labour force to reduce poverty.

Keywords: household size, poverty rate, nepal, regional development

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Authors: Julian Wise

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Newcrest Mining is one of the world’s top five gold and rare earth mining organizations by production, reserves and market capitalization in the world. This paper elaborates on the data acquisition processes employed by Newcrest in collaboration with Fortune 500 listed organization, Insight Enterprises, to standardize machine learning solutions which process data from over a hundred thousand distributed Internet of Things (IoT) devices located at mine sites globally. Through the utilization of software architecture cloud technologies and edge computing, the technological developments enable for standardized processes of machine learning applications to influence the strategic optimization of mineral processing. Target objectives of the machine learning optimizations include time savings on mineral processing, production efficiencies, risk identification, and increased production throughput. The data acquired and utilized for predictive modelling is processed through edge computing by resources collectively stored within a data lake. Being involved in the digital transformation has necessitated the standardization software architecture to manage the machine learning models submitted by vendors, to ensure effective automation and continuous improvements to the mineral process models. Operating at scale, the system processes hundreds of gigabytes of data per day from distributed mine sites across the globe, for the purposes of increased improved worker safety, and production efficiency through big data applications.

Keywords: mineral technology, big data, machine learning operations, data lake

Procedia PDF Downloads 104