Search results for: comprehensive benefit
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4681

Search results for: comprehensive benefit

3601 TechWhiz: Empowering Deaf Students through Inclusive Education

Authors: Paula Escudeiro, Nuno Escudeiro, Márcia Campos, Francisca Escudeiro

Abstract:

In today's world, technical and scientific knowledge plays a vital role in education, research, and employment. Deaf students face unique challenges in educational settings, particularly when it comes to understanding technical and scientific terminology. The reliance on written and spoken languages can create barriers for deaf individuals who primarily communicate using sign language. This lack of accessibility can hinder their learning experience and compromise equity in education. To address this issue, the TechWhiz project has been developed as a comprehensive glossary of scientific and technical concepts explained in sign language. By providing deaf students with access to education in their first language, TechWhiz aims to enhance their learning achievements and promote inclusivity while also fostering equity in education for all students.

Keywords: deaf students, technical and scientific knowledge, automatic sign language, inclusive education

Procedia PDF Downloads 68
3600 Strengthening Legal Protection of Personal Data through Technical Protection Regulation in Line with Human Rights

Authors: Tomy Prihananto, Damar Apri Sudarmadi

Abstract:

Indonesia recognizes the right to privacy as a human right. Indonesia provides legal protection against data management activities because the protection of personal data is a part of human rights. This paper aims to describe the arrangement of data management and data management in Indonesia. This paper is a descriptive research with qualitative approach and collecting data from literature study. Results of this paper are comprehensive arrangement of data that have been set up as a technical requirement of data protection by encryption methods. Arrangements on encryption and protection of personal data are mutually reinforcing arrangements in the protection of personal data. Indonesia has two important and immediately enacted laws that provide protection for the privacy of information that is part of human rights.

Keywords: Indonesia, protection, personal data, privacy, human rights, encryption

Procedia PDF Downloads 182
3599 A Pragmatic Reading of the Verb "Kana" and Its Meanings

Authors: Manal M. H. Said Najjar

Abstract:

Arab Grammarians stood at variance with regard to the definition of kana (which might equal was, were, the past form of “be” in English). Kana was considered as a verb, a particle, or a quasi-verb by different scholars; others saw it as an auxiliary verb; while some other scholars categorized kana as one of the incomplete verbs or (Afa’al naqisa) based on two different claims: first, a considerable group of grammarians saw kana as fie’l naqis or an incomplete verb since it indicates time, but not the event or action itself. Second, kana requires a predicate (xabar) to complete the meaning, i.e., it does not suffice itself with a noun in the nominal sentence. This study argues that categorizing the verb kana as fie’l naqis or an incomplete verb is inaccurate and confusing since the term “incomplete” does not agree with its characteristics, meanings, and temporal indications. Moreover, interpreting kana as a past verb is also inaccurate. kana كان (derived from the absolute action of being كون) is considered unique and the most comprehensive verb, encompassing all tenses of the past, present, and future within the dimensions of continuity and eternity of all possible actions under “being”.

Keywords: pragmatics, kana, context, Arab grammarians, meaning, fie’l naqis

Procedia PDF Downloads 94
3598 Analysis of Risk Factors Affecting the Motor Insurance Pricing with Generalized Linear Models

Authors: Puttharapong Sakulwaropas, Uraiwan Jaroengeratikun

Abstract:

Casualty insurance business, the optimal premium pricing and adequate cost for an insurance company are important in risk management. Normally, the insurance pure premium can be determined by multiplying the claim frequency with the claim cost. The aim of this research was to study in the application of generalized linear models to select the risk factor for model of claim frequency and claim cost for estimating a pure premium. In this study, the data set was the claim of comprehensive motor insurance, which was provided by one of the insurance company in Thailand. The results of this study found that the risk factors significantly related to pure premium at the 0.05 level consisted of no claim bonus (NCB) and used of the car (Car code).

Keywords: generalized linear models, risk factor, pure premium, regression model

Procedia PDF Downloads 466
3597 Economic Forecasting Analysis for Solar Photovoltaic Application

Authors: Enas R. Shouman

Abstract:

Economic development with population growth is leading to a continuous increase in energy demand. At the same time, growing global concern for the environment is driving to decrease the use of conventional energy sources and to increase the use of renewable energy sources. The objective of this study is to present the market trends of solar energy photovoltaic technology over the world and to represent economics methods for PV financial analyzes on the basis of expectations for the expansion of PV in many applications. In the course of this study, detailed information about the current PV market was gathered and analyzed to find factors influencing the penetration of PV energy. The paper methodology depended on five relevant economic financial analysis methods that are often used for investment decisions maker. These methods are payback analysis, net benefit analysis, saving-to-investment ratio, adjusted internal rate of return, and life-cycle cost. The results of this study may be considered as a marketing guide that helps diffusion of using PV Energy. The study showed that PV cost is economically reliable. The consumers will pay higher purchase prices for PV system installation but will get lower electricity bill.

Keywords: photovoltaic, financial methods, solar energy, economics, PV panel

Procedia PDF Downloads 109
3596 Addressing the Gap in Health and Wellbeing Evidence for Urban Real Estate Brownfield Asset Management Social Needs and Impact Analysis Using Systems Mapping Approach

Authors: Kathy Pain, Nalumino Akakandelwa

Abstract:

The study explores the potential to fill a gap in health and wellbeing evidence for purposeful urban real estate asset management to make investment a powerful force for societal good. Part of a five-year programme investigating the root causes of unhealthy urban development funded by the United Kingdom Prevention Research Partnership (UKPRP), the study pilots the use of a systems mapping approach to identify drivers and barriers to the incorporation of health and wellbeing evidence in urban brownfield asset management decision-making. Urban real estate not only provides space for economic production but also contributes to the quality of life in the local community. Yet market approaches to urban land use have, until recently, insisted that neo-classical technology-driven efficient allocation of economic resources should inform acquisition, operational, and disposal decisions. Buildings in locations with declining economic performance have thus been abandoned, leading to urban decay. Property investors are recognising the inextricable connection between sustainable urban production and quality of life in local communities. The redevelopment and operation of brownfield assets recycle existing buildings, minimising embodied carbon emissions. It also retains established urban spaces with which local communities identify and regenerate places to create a sense of security, economic opportunity, social interaction, and quality of life. Social implications of urban real estate on health and wellbeing and increased adoption of benign sustainability guidance in urban production are driving the need to consider how they affect brownfield real estate asset management decisions. Interviews with real estate upstream decision-makers in the study, find that local social needs and impact analysis is becoming a commercial priority for large-scale urban real estate development projects. Evidence of the social value-added of proposed developments is increasingly considered essential to secure local community support and planning permissions, and to attract sustained inward long-term investment capital flows for urban projects. However, little is known about the contribution of population health and wellbeing to socially sustainable urban projects and the monetary value of the opportunity this presents to improve the urban environment for local communities. We report early findings from collaborations with two leading property companies managing major investments in brownfield urban assets in the UK to consider how the inclusion of health and wellbeing evidence in social valuation can inform perceptions of brownfield development social benefit for asset managers, local communities, public authorities and investors for the benefit of all parties. Using holistic case studies and systems mapping approaches, we explore complex relationships between public health considerations and asset management decisions in urban production. Findings indicate a strong real estate investment industry appetite and potential to include health as a vital component of sustainable real estate social value creation in asset management strategies.

Keywords: brownfield urban assets, health and wellbeing, social needs and impact, social valuation, sustainable real estate, systems mapping

Procedia PDF Downloads 69
3595 From Protector to Violator: Assessing State's Role in Protecting Freedom of Religion in Indonesia

Authors: Manotar Tampubolon

Abstract:

Indonesia is a country that upholds the law, human rights and religious freedom. The freedom that implied in various laws and constitution (Undang-undang 1945) is not necessarily applicable in practice of religious life. In one side, the state has a duty as protector and guarantor of freedom, on the other side, however, it turns into one of the actors of freedom violations of religion minority. State action that interferes freedom of religion is done in various ways both intentionally or negligently or not to perform its obligations in the enforcement of human rights (human rights due diligence). Besides the state, non-state actors such as religious organizations, individuals also become violators of the rights of religious freedom. This article will discuss two fundamental issues that interfere freedom of religion in Indonesia after democratic era. In addition, this article also discusses a comprehensive state policy that discriminates minority religions to manifest their faith.

Keywords: religious freedom, constitution, minority faith, state actor

Procedia PDF Downloads 403
3594 The Impact of Social Support on Anxiety and Depression under the Context of COVID-19 Pandemic: A Scoping Review and Meta-Analysis

Authors: Meng Wu, Atif Rahman, Eng Gee, Lim, Jeong Jin Yu, Rong Yan

Abstract:

Context: The COVID-19 pandemic has had a profound impact on mental health, with increased rates of anxiety and depression observed. Social support, a critical factor in mental well-being, has also undergone significant changes during the pandemic. This study aims to explore the relationship between social support, anxiety, and depression during COVID-19, taking into account various demographic and contextual factors. Research Aim: The main objective of this study is to conduct a comprehensive systematic review and meta-analysis to examine the impact of social support on anxiety and depression during the COVID-19 pandemic. The study aims to determine the consistency of these relationships across different age groups, occupations, regions, and research paradigms. Methodology: A scoping review and meta-analytic approach were employed in this study. A search was conducted across six databases from 2020 to 2022 to identify relevant studies. The selected studies were then subjected to random effects models, with pooled correlations (r and ρ) estimated. Homogeneity was assessed using Q and I² tests. Subgroup analyses were conducted to explore variations across different demographic and contextual factors. Findings: The meta-analysis of both cross-sectional and longitudinal studies revealed significant correlations between social support, anxiety, and depression during COVID-19. The pooled correlations (ρ) indicated a negative relationship between social support and anxiety (ρ = -0.30, 95% CI = [-0.333, -0.255]) as well as depression (ρ = -0.27, 95% CI = [-0.370, -0.281]). However, further investigation is required to validate these results across different age groups, occupations, and regions. Theoretical Importance: This study emphasizes the multifaceted role of social support in mental health during the COVID-19 pandemic. It highlights the need to reevaluate and expand our understanding of social support's impact on anxiety and depression. The findings contribute to the existing literature by shedding light on the associations and complexities involved in these relationships. Data Collection and Analysis Procedures: The data collection involved an extensive search across six databases to identify relevant studies. The selected studies were then subjected to rigorous analysis using random effects models and subgroup analyses. Pooled correlations were estimated, and homogeneity was assessed using Q and I² tests. Question Addressed: This study aimed to address the question of the impact of social support on anxiety and depression during the COVID-19 pandemic. It sought to determine the consistency of these relationships across different demographic and contextual factors. Conclusion: The findings of this study highlight the significant association between social support, anxiety, and depression during the COVID-19 pandemic. However, further research is needed to validate these findings across different age groups, occupations, and regions. The study emphasizes the need for a comprehensive understanding of social support's multifaceted role in mental health and the importance of considering various contextual and demographic factors in future investigations.

Keywords: social support, anxiety, depression, COVID-19, meta-analysis

Procedia PDF Downloads 62
3593 Rural-Urban Education Gap and Left-Behind Children Education in China

Authors: Jiawei Liang

Abstract:

Against the backdrop of China's burgeoning migration from rural to urban areas, a demographic group has emerged in China, which is called left-behind children. Due to many reasons, including the issue of the rural-urban education gap, the education of left-behind children has been below the national education average. In this situation, the issue has attracted the attention of researchers and policymakers. In order to gain a comprehensive understanding of this issue, this paper adopts an analytical approach to studying the rural-urban education gap and left-behind children in rural China. The paper first introduces the current situation of migration, the education gap, and left-behind children within China. Then, it further explores the causes of these two questions and barriers as well as the consequences for left-behind children. Finally, the study offers some suggestions to alleviate the urban-rural gap and the current situation of education for left-behind children in rural areas, which will hopefully shed light on the issue of left-behind children in China and the urban-rural education gap.

Keywords: left-behind children, rural China, education improvement, Hukou policy, rural-urban education gap

Procedia PDF Downloads 104
3592 Investigating Causes of Pavement Deterioration in Khartoum State, Sudan

Authors: Magdi Mohamed Eltayeb Zumrawi

Abstract:

It is quite essential to investigate the causes of pavement deterioration in order to select the proper maintenance technique. The objective of this study was to identify factors cause deterioration of recently constructed roads in Khartoum state. A comprehensive literature concerning the factors of road deterioration, common road defects and their causes were reviewed. Three major road projects with different deterioration reasons were selected for this study. The investigation involved field survey and laboratory testing on those projects to examine the existing pavement conditions. The results revealed that the roads investigated experienced severe failures in the forms of cracks, potholes and rutting in the wheel path. The causes of those failures were found mainly linked to poor drainage, traffic overloading, expansive subgrade soils and the use of low quality materials in construction. Based on the results, recommendations were provided to help highway engineers in selecting the most effective repair techniques for specific kinds of distresses.

Keywords: pavement, deterioration, causes, failures

Procedia PDF Downloads 354
3591 Nanotechnology: A New Revolution to Increase Agricultural Production

Authors: Reshu Chaudhary, R. S. Sengar

Abstract:

To increase the agricultural production Indian farmer needs to aware of the latest technology i.e. precision farming to maximize the crop yield and minimize the input (fertilizer, pesticide etc.) through monitoring the environmental factors. Biotechnology and information technology have provided lots of opportunities for the development of agriculture. But, still we have to do much more for increasing our agricultural production in order to achieve the target growth of agriculture to secure food, to eliminate poverty and improve living style, to enhance agricultural exports and national income and to improve quality of agricultural products. Nanotechnology can be a great element to satisfy these requirements and to boost the multi-dimensional development of agriculture in order to fulfill the dream of Indian farmers. Nanotechnology is the most rapidly growing area of science and technology with its application in physical science, chemical science, life science, material science and earth science. Nanotechnology is a part of any nation’s future. Research in nanotechnology has extremely high potential to benefit society through application in agricultural sciences. Nanotechnology has greater potential to bring revolution in the agricultural sector.

Keywords: agriculture, biotechnology, crop yield, nanotechnology

Procedia PDF Downloads 361
3590 Biodistribution Studies of 177Lu-DOTATOC in Mouse Tumor Model: Possible Utilization in Adenocarcinoma Breast Cancer Treatment

Authors: M. Mousavi-Daramoroudi, H. Yousefnia, F. Abbasi-Davani, S. Zolghadri, S. Kakaei

Abstract:

Despite the appropriate characteristics of 177Lu and DOTATOC, to our best knowledge, the therapeutic benefit of 177Lu-DOTATOC complex in breast cancer has not been reported until now. In this study, biodistribution of 177Lu-DOTA-TOC in mouse tumor model for evaluation of possible utilization of this complex in breast cancer treatment was investigated.177Lu was prepared with the specific activity of 2.6-3 GBq.mg-1 and radionuclidic purity higher than 99%. The radiolabeled complex was prepared in the optimized conditions with the radiochemical purity higher than 99%. The final solution was injected to the BALB/c mice with adenocarcinoma breast cancer. The biodistribution results showed major accumulation in the kidneys as the major excretion route and the somatostatin receptor-positive tissues such as pancreas compared with the other tissues. Also, significant uptake was observed in tumor even in longer time after injection. According to the results obtained in this research study, somatostatin receptors expressed in breast cancers can be targeted with DOTATOC analogues especially with 177Lu-DOTATOC as an ideal therapeutic agent.

Keywords: ¹⁷⁷Lu, adenocarcinoma breast cancer, DOTATOC, BALB/c mice

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3589 Evaluation of Sensor Pattern Noise Estimators for Source Camera Identification

Authors: Benjamin Anderson-Sackaney, Amr Abdel-Dayem

Abstract:

This paper presents a comprehensive survey of recent source camera identification (SCI) systems. Then, the performance of various sensor pattern noise (SPN) estimators was experimentally assessed, under common photo response non-uniformity (PRNU) frameworks. The experiments used 1350 natural and 900 flat-field images, captured by 18 individual cameras. 12 different experiments, grouped into three sets, were conducted. The results were analyzed using the receiver operator characteristic (ROC) curves. The experimental results demonstrated that combining the basic SPN estimator with a wavelet-based filtering scheme provides promising results. However, the phase SPN estimator fits better with both patch-based (BM3D) and anisotropic diffusion (AD) filtering schemes.

Keywords: sensor pattern noise, source camera identification, photo response non-uniformity, anisotropic diffusion, peak to correlation energy ratio

Procedia PDF Downloads 441
3588 Elevating Environmental Impact Assessment through Remote Sensing in Engineering

Authors: Spoorthi Srupad

Abstract:

Environmental Impact Assessment (EIA) stands as a critical engineering application facilitated by Earth Resources and Environmental Remote Sensing. Employing advanced technologies, this process enables a systematic evaluation of potential environmental impacts arising from engineering projects. Remote sensing techniques, including satellite imagery and geographic information systems (GIS), play a pivotal role in providing comprehensive data for assessing changes in land cover, vegetation, water bodies, and air quality. This abstract delves into the significance of EIA in engineering, emphasizing its role in ensuring sustainable and environmentally responsible practices. The integration of remote sensing technologies enhances the accuracy and efficiency of impact assessments, contributing to informed decision-making and the mitigation of adverse environmental consequences associated with engineering endeavors.

Keywords: environmental impact assessment, engineering applications, sustainability, environmental monitoring, remote sensing, geographic information systems, environmental management

Procedia PDF Downloads 92
3587 Small Farm Diversification Opportunities in Viticulture-Winemaking Sector of Georgia

Authors: E. Kharaishvili

Abstract:

The paper analyses the role of small farms in socio-economic development of agriculture in Georgia and evaluates modern concepts regarding the development of the farms of this size. The scale of farms in Georgia is studied and the major problems are revealed. Opportunities and directions of diversification are discussed from the point of increasing the share of Georgian grapes and wine both on domestic and international markets. It’s shown that the size of vineyard areas is directly reflected on the grape and wine production potential. Accordingly, vineyard area and grape production dynamics is discussed. Comparative analysis of small farms in Georgia and Italy is made and the major differences are identified. Diversification is evaluated based on cost-benefit analysis on the one hand and on the other hand, from the point of promoting economic activities, protecting nature and rural area development. The paper provides proofs for the outcomes of diversification. The key hindering factors for the development of small farms are identified and corresponding conclusions are made, based on which recommendations for diversification of the farms of this size are developed.

Keywords: small farms, scale of farms, diversification, Georgia

Procedia PDF Downloads 391
3586 Study on Empowering Youth and Adults to Overcome Mental Health Hardships Using a Web Application

Authors: Jennis Delina Giles, Nimesha Liyanage, Damindi Senadheera, Dilan Randima, Kushnara Suriyawansa

Abstract:

Mental health is essential during childhood, adolescence, and adulthood. Mental health issues can influence one's thoughts, disposition, and conduct. A record number of mental health problems are caused by a global pandemic. Prevention of mental disease is vital for both children and adults. We desired to develop a web application for those with mental health difficulties. This web application will provide group chat, discussion, a community feed, and counseling services. The community feed function provides information regarding scheduled conversation space meetings, and the counselor uploads uplifting thoughts and tales of patients who received proper care and overcame mental health issues. Community feed can filter content based on user preferences. The mental health system for adults and adolescents will be updated. The community feed delivers relevant and instructive postings, links, and images so that service recipients can benefit from other platform features and receive encouraging words to assist them in overcoming mental health difficulties.

Keywords: bio medical, mental helath care, empower youths & adults, counselling

Procedia PDF Downloads 155
3585 Improved Performance in Content-Based Image Retrieval Using Machine Learning Approach

Authors: B. Ramesh Naik, T. Venugopal

Abstract:

This paper presents a novel approach which improves the high-level semantics of images based on machine learning approach. The contemporary approaches for image retrieval and object recognition includes Fourier transforms, Wavelets, SIFT and HoG. Though these descriptors helpful in a wide range of applications, they exploit zero order statistics, and this lacks high descriptiveness of image features. These descriptors usually take benefit of primitive visual features such as shape, color, texture and spatial locations to describe images. These features do not adequate to describe high-level semantics of the images. This leads to a gap in semantic content caused to unacceptable performance in image retrieval system. A novel method has been proposed referred as discriminative learning which is derived from machine learning approach that efficiently discriminates image features. The analysis and results of proposed approach were validated thoroughly on WANG and Caltech-101 Databases. The results proved that this approach is very competitive in content-based image retrieval.

Keywords: CBIR, discriminative learning, region weight learning, scale invariant feature transforms

Procedia PDF Downloads 181
3584 Impact of the Energy Transition on Security of Supply - A Case Study of Vietnam Power System in 2030

Authors: Phuong Nguyen, Trung Tran

Abstract:

Along with the global ongoing energy transition, Vietnam has indicated a strong commitment in the last COP events on the zero-carbon emission target. However, it is a real challenge for the nation to replace fossil-fired power plants by a significant amount of renewable energy sources (RES) while maintaining security of supply. The unpredictability and variability of RES would cause technical issues for supply-demand balancing, network congestions, system balancing, among others. It is crucial to take these into account while planning the future grid infrastructure. This study will address both generation and transmission adequacy and reveal a comprehensive analysis about the impact of ongoing energy transition on the development of Vietnam power system in 2030. This will provide insight for creating an secure, stable, and affordable pathway for the country in upcoming years.

Keywords: generation adequacy, transmission adequacy, security of supply, energy transition

Procedia PDF Downloads 86
3583 A Qualitative Study: Teaching Fractions with Augmented Reality for 5th Grade Students in Turkey

Authors: Duygu Özdemir, Bilal Özçakır

Abstract:

Usage of augmented reality in education helps students to make sense of the three-dimensional world of mathematics. In this study, it was aimed to develop activities about fractions for 5th-grade students by augmented reality and also aimed to assess these activities in terms of students’ understanding and views. Data obtained from 60 students in a private school in Marmaris, Turkey was obtained through classroom observations, students’ worksheets and semi-structured interviews during two weeks. Data analysis was conducted by using constant-comparative analysis which leads to meaningful categories of findings. Findings of this study indicated that usage of augmented reality is a facilitator to make concretize and provide real-life application for fractions. Moreover, students’ opinions about its usage were lead to categories as benefit for learning, enjoyment and creating awareness of usage of augmented reality in mathematics education. In general, this study could be a bridge to show the contributions of augmented reality applications to mathematics education and also highlights that augmented reality could be used with subjects like fractions rather than subjects only in geometry learning domain.

Keywords: augmented reality, mathematics, fractions, students

Procedia PDF Downloads 199
3582 Knowledge Spillovers from Patent Citations: Evidence from Swiss Manufacturing Industry

Authors: Racha Khairallah, Lamia Ben Hamida

Abstract:

Our paper attempts to examine how Swiss manufacturing firms manage to learn from patent citations to improve their innovation performance. We argue that the assessment of these effects needs a detailed analysis of spillovers according to the source of knowledge with respect to formal and informal patent citations made in European and internal search, the horizontal and vertical mechanisms by which knowledge spillovers take place, and the technological characteristics of innovative firms that able them to absorb external knowledge and integrate it in their existing innovation process. We use OECD data and find evidence that knowledge spillovers occur only from horizontal and backward linkages. The importance of these effects depends on the type of citation, in which the references to non-patent literature (informal citations made in European and international searches) have a greater impact. In addition, only firms with high technological capacities benefit from knowledge spillovers from formal and informal citations. Low-technology firms fail to catch up and efficiently learn external knowledge from patent citations.

Keywords: innovation performance, patent citation, absorptive capacity, knowledge spillover mechanisms

Procedia PDF Downloads 109
3581 Early Predictive Signs for Kasai Procedure Success

Authors: Medan Isaeva, Anna Degtyareva

Abstract:

Context: Biliary atresia is a common reason for liver transplants in children, and the Kasai procedure can potentially be successful in avoiding the need for transplantation. However, it is important to identify factors that influence surgical outcomes in order to optimize treatment and improve patient outcomes. Research aim: The aim of this study was to develop prognostic models to assess the outcomes of the Kasai procedure in children with biliary atresia. Methodology: This retrospective study analyzed data from 166 children with biliary atresia who underwent the Kasai procedure between 2002 and 2021. The effectiveness of the operation was assessed based on specific criteria, including post-operative stool color, jaundice reduction, and bilirubin levels. The study involved a comparative analysis of various parameters, such as gestational age, birth weight, age at operation, physical development, liver and spleen sizes, and laboratory values including bilirubin, ALT, AST, and others, measured pre- and post-operation. Ultrasonographic evaluations were also conducted pre-operation, assessing the hepatobiliary system and related quantitative parameters. The study was carried out by two experienced specialists in pediatric hepatology. Comparative analysis and multifactorial logistic regression were used as the primary statistical methods. Findings: The study identified several statistically significant predictors of a successful Kasai procedure, including the presence of the gallbladder and levels of cholesterol and direct bilirubin post-operation. A detectable gallbladder was associated with a higher probability of surgical success, while elevated post-operative cholesterol and direct bilirubin levels were indicative of a reduced chance of positive outcomes. Theoretical importance: The findings of this study contribute to the optimization of treatment strategies for children with biliary atresia undergoing the Kasai procedure. By identifying early predictive signs of success, clinicians can modify treatment plans and manage patient care more effectively and proactively. Data collection and analysis procedures: Data for this analysis were obtained from the health records of patients who received the Kasai procedure. Comparative analysis and multifactorial logistic regression were employed to analyze the data and identify significant predictors. Question addressed: The study addressed the question of identifying predictive factors for the success of the Kasai procedure in children with biliary atresia. Conclusion: The developed prognostic models serve as valuable tools for early detection of patients who are less likely to benefit from the Kasai procedure. This enables clinicians to modify treatment plans and manage patient care more effectively and proactively. Potential limitations of the study: The study has several limitations. Its retrospective nature may introduce biases and inconsistencies in data collection. Being single centered, the results might not be generalizable to wider populations due to variations in surgical and postoperative practices. Also, other potential influencing factors beyond the clinical, laboratory, and ultrasonographic parameters considered in this study were not explored, which could affect the outcomes of the Kasai operation. Future studies could benefit from including a broader range of factors.

Keywords: biliary atresia, kasai operation, prognostic model, native liver survival

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3580 Molecular Timeline Analysis of Acropora: Review of Coral Development, Growth and Environmental Resilience

Authors: Ariadna Jalife Gómez, Claudia Rangel Escareño

Abstract:

The Acropora coral genus has experienced impactful consequences of climate change, especially in terms of population reduction related to limited thermal tolerance, however, comprehensive resources for genetic responses of these corals to phenomena are lacking. Thus, this study aims to identify key genes expressed across different developmental stages and conditions of Acropora spp. highlighted in published studies given the shared tissue and polyp-level characteristics among the species comprising the genus, as it is hypothesized that common reproductive, developmental, and stress response mechanisms are conserved. The presented resources, aiming to streamline the genus’ biology, elucidate several signaling pathways of development and stress response that contribute to the understanding of researchers of overall biological responses, while providing a genetic framework for potential further studies that might contribute to reef preservation strategies.

Keywords: acropora, development, genes, transcriptomics

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3579 Gamification of a Business Intelligence Tool

Authors: Stephen Miller

Abstract:

The act of applying game mechanics and dynamics (which have been traditionally used in video games) into business applications is being widely trialed in an effort to make conventional business software a bit more participative, fun and engaging. This new trend, named ‘gamification’ has its believers and of course, its critics who still need convincing that the concept is an effective and beneficial business tool worthy of investment. The literature reveals that user engagement of business intelligence (BI) tools is much lower than expected and investors are failing to get a good return on their investment (ROI). So, a software prototype will be designed and developed to add gamification to a BI tool to determine its effect upon the user engagement levels of test participants. The experimental study will be evaluated using the comprehensive User Engagement Scale (UES) to see if there are improvements in areas such as; aesthetics, perceived usability, endurability, novelty, felt involvement and focused attention. The results of this unique study should demonstrate whether or not ‘gamifying’ a BI tool has the potential to increase an individual’s motivation to use BI software more often.

Keywords: business intelligence, gamification, human computer interaction, user engagement

Procedia PDF Downloads 585
3578 Using Geographic Information Systems to Trace Conditions for Young Women's Experiences of Public Spaces in Disadvantaged Neighborhoods

Authors: Alazar G. Ejigu

Abstract:

Cities have traditionally been designed for and by men. Despite positive changes in this regard, contemporary cities appear to offer limited options and experiences to women in their everyday life. There are differences regarding the quality of space. Distressed or disadvantaged areas often have less access to urban qualities, such as services, parks, and public places, than more privileged ones. The most attractive meeting-places are located centrally, whereas many suburban areas lack these elements. By focusing on young women living in multi-ethnic working-class suburban areas in Stockholm - a group generally ignored and disadvantaged; the study aims to examine various forms of inequality or equality in three selected neighborhoods. Spatial data was collected through walk-along with the young girls, inventory of the places, and geodata made available by Statistics Sweden (SCB). The combined data was analyzed with the help of Geographic Information Systems (GIS). In line with Crenshaw - one of the forerunners of intersectional thinking – the project departs from the idea that if we address the needs of those who are disadvantaged and restructure urban space accordingly, then others will benefit too. Thus, working our way towards a more equal city.

Keywords: GIS, segregation, gender equality, urban planning

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3577 Revolutionizing Financial Forecasts: Enhancing Predictions with Graph Convolutional Networks (GCN) - Long Short-Term Memory (LSTM) Fusion

Authors: Ali Kazemi

Abstract:

Those within the volatile and interconnected international economic markets, appropriately predicting market trends, hold substantial fees for traders and financial establishments. Traditional device mastering strategies have made full-size strides in forecasting marketplace movements; however, monetary data's complicated and networked nature calls for extra sophisticated processes. This observation offers a groundbreaking method for monetary marketplace prediction that leverages the synergistic capability of Graph Convolutional Networks (GCNs) and Long Short-Term Memory (LSTM) networks. Our suggested algorithm is meticulously designed to forecast the traits of inventory market indices and cryptocurrency costs, utilizing a comprehensive dataset spanning from January 1, 2015, to December 31, 2023. This era, marked by sizable volatility and transformation in financial markets, affords a solid basis for schooling and checking out our predictive version. Our algorithm integrates diverse facts to construct a dynamic economic graph that correctly reflects market intricacies. We meticulously collect opening, closing, and high and low costs daily for key inventory marketplace indices (e.g., S&P 500, NASDAQ) and widespread cryptocurrencies (e.g., Bitcoin, Ethereum), ensuring a holistic view of marketplace traits. Daily trading volumes are also incorporated to seize marketplace pastime and liquidity, providing critical insights into the market's shopping for and selling dynamics. Furthermore, recognizing the profound influence of the monetary surroundings on financial markets, we integrate critical macroeconomic signs with hobby fees, inflation rates, GDP increase, and unemployment costs into our model. Our GCN algorithm is adept at learning the relational patterns amongst specific financial devices represented as nodes in a comprehensive market graph. Edges in this graph encapsulate the relationships based totally on co-movement styles and sentiment correlations, enabling our version to grasp the complicated community of influences governing marketplace moves. Complementing this, our LSTM algorithm is trained on sequences of the spatial-temporal illustration discovered through the GCN, enriched with historic fee and extent records. This lets the LSTM seize and expect temporal marketplace developments accurately. Inside the complete assessment of our GCN-LSTM algorithm across the inventory marketplace and cryptocurrency datasets, the version confirmed advanced predictive accuracy and profitability compared to conventional and opportunity machine learning to know benchmarks. Specifically, the model performed a Mean Absolute Error (MAE) of 0.85%, indicating high precision in predicting day-by-day charge movements. The RMSE was recorded at 1.2%, underscoring the model's effectiveness in minimizing tremendous prediction mistakes, which is vital in volatile markets. Furthermore, when assessing the model's predictive performance on directional market movements, it achieved an accuracy rate of 78%, significantly outperforming the benchmark models, averaging an accuracy of 65%. This high degree of accuracy is instrumental for techniques that predict the course of price moves. This study showcases the efficacy of mixing graph-based totally and sequential deep learning knowledge in economic marketplace prediction and highlights the fee of a comprehensive, records-pushed evaluation framework. Our findings promise to revolutionize investment techniques and hazard management practices, offering investors and economic analysts a powerful device to navigate the complexities of cutting-edge economic markets.

Keywords: financial market prediction, graph convolutional networks (GCNs), long short-term memory (LSTM), cryptocurrency forecasting

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3576 Investigating Real Ship Accidents with Descriptive Analysis in Turkey

Authors: İsmail Karaca, Ömer Söner

Abstract:

The use of advanced methods has been increasing day by day in the maritime sector, which is one of the sectors least affected by the COVID-19 pandemic. It is aimed to minimize accidents, especially by using advanced methods in the investigation of marine accidents. This research aimed to conduct an exploratory statistical analysis of particular ship accidents in the Transport Safety Investigation Center of Turkey database. 46 ship accidents, which occurred between 2010-2018, have been selected from the database. In addition to the availability of a reliable and comprehensive database, taking advantage of the robust statistical models for investigation is critical to improving the safety of ships. Thus, descriptive analysis has been used in the research to identify causes and conditional factors related to different types of ship accidents. The research outcomes underline the fact that environmental factors and day and night ratio have great influence on ship safety.

Keywords: descriptive analysis, maritime industry, maritime safety, ship accident statistics

Procedia PDF Downloads 139
3575 Developing Rice Disease Analysis System on Mobile via iOS Operating System

Authors: Rujijan Vichivanives, Kittiya Poonsilp, Canasanan Wanavijit

Abstract:

This research aims to create mobile tools to analyze rice disease quickly and easily. The principle of object-oriented software engineering and objective-C language were used for software development methodology and the principle of decision tree technique was used for analysis method. Application users can select the features of rice disease or the color appears on the rice leaves for recognition analysis results on iOS mobile screen. After completing the software development, unit testing and integrating testing method were used to check for program validity. In addition, three plant experts and forty farmers have been assessed for usability and benefit of this system. The overall of users’ satisfaction was found in a good level, 57%. The plant experts give a comment on the addition of various disease symptoms in the database for more precise results of the analysis. For further research, it is suggested that image processing system should be developed as a tool that allows users search and analyze for rice diseases more convenient with great accuracy.

Keywords: rice disease, data analysis system, mobile application, iOS operating system

Procedia PDF Downloads 287
3574 Comprehensive Interpretation of Leadership from the Narratives in Literature

Authors: Nidhi Kaushal, Sanjit Mishra

Abstract:

Narrative writings in literature are ample source of knowledge and easily understandable. In every old tradition, we found that people learn ethics from oral tales. They had their leaders and lessons of leadership in their stories. In India, we have sufficient amount of stories of leaders. Whether the story is of an ordinary person or a corporate leader of large firm, it always has a unique message of motivation. The objective of this paper is to elaborate the story lines in literature and get the leadership lessons from them, so that we can set up a new concept of leadership based on scholarship of literature. This is our hypothesis that leadership lessons can be learned from the study of literary writings and it can also act an innovative way of learning the management skills through literature. The role of the leader can be familiarly communicated in the form of the tales. Describing a positive psychological narrative from the text is the best way to manifesting an idea into the minds of people. We accomplished this paper that leadership as an attribute can be learned from the folk psychological literary writings.

Keywords: leadership, literature, management, psychology

Procedia PDF Downloads 267
3573 A Framework for Review Spam Detection Research

Authors: Mohammadali Tavakoli, Atefeh Heydari, Zuriati Ismail, Naomie Salim

Abstract:

With the increasing number of people reviewing products online in recent years, opinion sharing websites has become the most important source of customers’ opinions. Unfortunately, spammers generate and post fake reviews in order to promote or demote brands and mislead potential customers. These are notably destructive not only for potential customers but also for business holders and manufacturers. However, research in this area is not adequate, and many critical problems related to spam detection have not been solved to date. To provide green researchers in the domain with a great aid, in this paper, we have attempted to create a high-quality framework to make a clear vision on review spam-detection methods. In addition, this report contains a comprehensive collection of detection metrics used in proposed spam-detection approaches. These metrics are extremely applicable for developing novel detection methods.

Keywords: fake reviews, feature collection, opinion spam, spam detection

Procedia PDF Downloads 413
3572 Impact of Sericin Treatment on Perfection Dyeing of Polyester Viscose Blend

Authors: Omaima G. Allam, O. A. Hakeim, K. Haggag, N. S. Elshemy

Abstract:

In the midst of the two decades the use of microwave dielectric warming in the field of science has transformed into a powerful methodology to redesign compound procedures. The potential benefit of the application of these modern methods of treatment emphasize so as to reach to optimum treatment conditions and the best results, especially hydrophobicity, moisture content and increase dyeing processing while maintaining the physical and chemical properties of each textile. Moreover, polyester fibres are sometimes spun together with natural fibres to produce a cloth with blended properties. So that at the present task, the polyester/viscose mix fabrics (60 /40) were pretreated with 4 g/l of KOH for 2 min in microwave irradiation with a liquor ratio 1:25. Subsequently fabrics were inundated with different concentrations of sericin (10, 30, 50 g/l). Treated fabrics were coloured with the commercial dyes samples: Reactive Red 84(Dye 1). C. I. Acid Blue 203(Dye 2) and C.I. Reactive violet 5 (Dye 3). Colour value was specified as well as fastness properties. Likewise, the physical properties of untreated and treated fabrics such as moisture content %, tensile strength, elongation % and were evaluated. The untreated and treated fabrics are described by infrared spectroscopy (FTIR) and scanning electron microscopy.

Keywords: polyester viscose blends fabric, sericin, dyes, colour value

Procedia PDF Downloads 238