Search results for: accident database
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1996

Search results for: accident database

1156 Wireless Sensor Anomaly Detection Using Soft Computing

Authors: Mouhammd Alkasassbeh, Alaa Lasasmeh

Abstract:

We live in an era of rapid development as a result of significant scientific growth. Like other technologies, wireless sensor networks (WSNs) are playing one of the main roles. Based on WSNs, ZigBee adds many features to devices, such as minimum cost and power consumption, and increasing the range and connect ability of sensor nodes. ZigBee technology has come to be used in various fields, including science, engineering, and networks, and even in medicinal aspects of intelligence building. In this work, we generated two main datasets, the first being based on tree topology and the second on star topology. The datasets were evaluated by three machine learning (ML) algorithms: J48, meta.j48 and multilayer perceptron (MLP). Each topology was classified into normal and abnormal (attack) network traffic. The dataset used in our work contained simulated data from network simulation 2 (NS2). In each database, the Bayesian network meta.j48 classifier achieved the highest accuracy level among other classifiers, of 99.7% and 99.2% respectively.

Keywords: IDS, Machine learning, WSN, ZigBee technology

Procedia PDF Downloads 542
1155 Microstructure and High Temperature Deformation Behavior of Cast 310S Alloy

Authors: Jung-Ho Moon, Myung-Gon Yoon, Tae Kwon Ha

Abstract:

High temperature deformation behavior of cast 310S stainless steel has been investigated in this study by performing tensile and compression tests at temperatures from 900 to 1200°C. Rectangular ingots of which the dimensions were 350×350×100 in millimeter were cast using vacuum induction melting. Phase equilibrium was calculated using the FactSage®, thermodynamic software and database. Thermal expansion coefficient was also measured on the ingot in the temperature range from room temperature to 1200°C. Tensile strength of cast 310S stainless steel was 9 MPa at 1200°C, which is a little higher than that of a wrought 310S. With temperature decreased, tensile strength increased rapidly and reached up to 72 MPa at 900°C. Elongation also increased with temperature decreased. Microstructure observation revealed that σ phase was precipitated along the grain boundary and within the matrix over 1200°C, which is detrimental to high temperature elongation.

Keywords: stainless steel, STS 310S, high temperature deformation, microstructure, mechanical properties

Procedia PDF Downloads 393
1154 Assessing Knowledge and Compliance of Motor Riders on Road Safety Regulations in Hohoe Municipality of Ghana: A Cross-Sectional Quantitative Study

Authors: Matthew Venunye Fianu, Jerry Fiave, Ebenezer Kye-Mensah, Dacosta Aboagye, Felix Osei-Sarpong

Abstract:

Introduction: Road traffic accidents involving motorbikes are a priority public health concern in Ghana. While there are local initiatives to address this public health challenge, little is known about motor riders’ knowledge and compliance with road safety regulations (RSR) and their association with RTAs. The aim of this study was, therefore, to assess motorbike riders’ knowledge and compliance with RSRs. Methodology: Motorbike riders in Hohoe Municipality were randomly sampled in a cross-sectional study in June 2022. Data were collected from 237 riders using a questionnaire designed in Kobocollect and administered by ten research assistants. A score of 70% or less is considered low for knowledge and compliance. The data were exported into Excel and imported into STATA 17 for analysis. A chi-square test was performed to generate descriptive and inferential statistics to establish the association between independent and dependent variables. Results: All 237 respondents were male, and each of them completed the questionnaire representing a 100% response rate. Participants who had knowledge about speed limit at different segments of the road were 59(24.9%), the use of helmet were 124 (52.3%), and alcohol use were 152 (64.1%). Participants who complied with regulations on speed limits, helmet use, and alcohol use were 108 (45.6%), 179(75.5%), and 168(70.8%), respectively. Riders who had at least junior high school education were 2.43 times more likely to adhere to RSR [cOR =2.43(95%CI= 1.15-6.33) p= 0.023] than those who had less education. Similarly, riders who had high knowledge about RSR were 2.07 times more likely to comply with RSR than those who had less knowledge [AOR= -2.07 (95% CI= 0.34-0.97), p=0.038]. Conclusion: Motor riders in the Hohoe Municipality had low knowledge as well as low compliance with road safety regulations. This could be a contributor to road traffic accidents. It is therefore recommended that road safety regulatory authorities and relevant stakeholders enhance the enforcement of RSR. There should also be country-specific efforts to increase awareness among all motor riders, especially those with less than junior high school education.

Keywords: compliance, motor riders, road safety regulations, road traffic accident

Procedia PDF Downloads 84
1153 How to Perform Proper Indexing?

Authors: Watheq Mansour, Waleed Bin Owais, Mohammad Basheer Kotit, Khaled Khan

Abstract:

Efficient query processing is one of the utmost requisites in any business environment to satisfy consumer needs. This paper investigates the various types of indexing models, viz. primary, secondary, and multi-level. The investigation is done under the ambit of various types of queries to which each indexing model performs with efficacy. This study also discusses the inherent advantages and disadvantages of each indexing model and how indexing models can be chosen based on a particular environment. This paper also draws parallels between various indexing models and provides recommendations that would help a Database administrator to zero-in on a particular indexing model attributed to the needs and requirements of the production environment. In addition, to satisfy industry and consumer needs attributed to the colossal data generation nowadays, this study has proposed two novel indexing techniques that can be used to index highly unstructured and structured Big Data with efficacy. The study also briefly discusses some best practices that the industry should follow in order to choose an indexing model that is apposite to their prerequisites and requirements.

Keywords: indexing, hashing, latent semantic indexing, B-tree

Procedia PDF Downloads 153
1152 PRISM: An Analytical Tool for Forest Plan Development

Authors: Dung Nguyen, Yu Wei, Eric Henderson

Abstract:

Analytical tools have been used for decades to assist in the development of forest plans. In 2016, a new decision support system, PRISM, was jointly developed by United States Forest Service (USFS) Northern Region and Colorado State University to support the forest planning process. Prism has a friendly user interface with functionality for database management, model development, data visualization, and sensitivity analysis. The software is tailored for USFS planning, but it is flexible enough to support planning efforts by other forestland owners and managers. Here, the core capability of PRISM and its applications in developing plans for several United States national forests are presented. The strengths of PRISM are also discussed to show its potential of being a preferable tool for managers and experts in the domain of forest management and planning.

Keywords: decision support, forest management, forest plan, graphical user interface, software

Procedia PDF Downloads 107
1151 Modeling of Global Solar Radiation on a Horizontal Surface Using Artificial Neural Network: A Case Study

Authors: Laidi Maamar, Hanini Salah

Abstract:

The present work investigates the potential of artificial neural network (ANN) model to predict the horizontal global solar radiation (HGSR). The ANN is developed and optimized using three years meteorological database from 2011 to 2013 available at the meteorological station of Blida (Blida 1 university, Algeria, Latitude 36.5°, Longitude 2.81° and 163 m above mean sea level). Optimal configuration of the ANN model has been determined by minimizing the Root Means Square Error (RMSE) and maximizing the correlation coefficient (R2) between observed and predicted data with the ANN model. To select the best ANN architecture, we have conducted several tests by using different combinations of parameters. A two-layer ANN model with six hidden neurons has been found as an optimal topology with (RMSE=4.036 W/m²) and (R²=0.999). A graphical user interface (GUI), was designed based on the best network structure and training algorithm, to enhance the users’ friendliness application of the model.

Keywords: artificial neural network, global solar radiation, solar energy, prediction, Algeria

Procedia PDF Downloads 493
1150 Coupling Large Language Models with Disaster Knowledge Graphs for Intelligent Construction

Authors: Zhengrong Wu, Haibo Yang

Abstract:

In the context of escalating global climate change and environmental degradation, the complexity and frequency of natural disasters are continually increasing. Confronted with an abundance of information regarding natural disasters, traditional knowledge graph construction methods, which heavily rely on grammatical rules and prior knowledge, demonstrate suboptimal performance in processing complex, multi-source disaster information. This study, drawing upon past natural disaster reports, disaster-related literature in both English and Chinese, and data from various disaster monitoring stations, constructs question-answer templates based on large language models. Utilizing the P-Tune method, the ChatGLM2-6B model is fine-tuned, leading to the development of a disaster knowledge graph based on large language models. This serves as a knowledge database support for disaster emergency response.

Keywords: large language model, knowledge graph, disaster, deep learning

Procedia PDF Downloads 46
1149 Reallocation of Bed Capacity in a Hospital Combining Discrete Event Simulation and Integer Linear Programming

Authors: Muhammed Ordu, Eren Demir, Chris Tofallis

Abstract:

The number of inpatient admissions in the UK has been significantly increasing over the past decade. These increases cause bed occupancy rates to exceed the target level (85%) set by the Department of Health in England. Therefore, hospital service managers are struggling to better manage key resource such as beds. On the other hand, this severe demand pressure might lead to confusion in wards. For example, patients can be admitted to the ward of another inpatient specialty due to lack of resources (i.e., bed). This study aims to develop a simulation-optimization model to reallocate the available number of beds in a mid-sized hospital in the UK. A hospital simulation model was developed to capture the stochastic behaviours of the hospital by taking into account the accident and emergency department, all outpatient and inpatient services, and the interactions between each other. A couple of outputs of the simulation model (e.g., average length of stay and revenue) were generated as inputs to be used in the optimization model. An integer linear programming was developed under a number of constraints (financial, demand, target level of bed occupancy rate and staffing level) with the aims of maximizing number of admitted patients. In addition, a sensitivity analysis was carried out by taking into account unexpected increases on inpatient demand over the next 12 months. As a result, the major findings of the approach proposed in this study optimally reallocate the available number of beds for each inpatient speciality and reveal that 74 beds are idle. In addition, the findings of the study indicate that the hospital wards will be able to cope with 14% demand increase at most in the projected year. In conclusion, this paper sheds a new light on how best to reallocate beds in order to cope with current and future demand for healthcare services.

Keywords: bed occupancy rate, bed reallocation, discrete event simulation, inpatient admissions, integer linear programming, projected usage

Procedia PDF Downloads 139
1148 The Potential for Recycling Household Wastes Generated from the Residential Areas of Obafemi Awolowo University, Ile-Ife

Authors: Asaolu Olugbenga Stephen, Afolabi Olusegun Temitope

Abstract:

Lack of proper solid waste management is one of the main causes of environmental pollution and degradation in many cities, especially in developing countries. The aim of this study was to estimate the quantity of waste generated per capita per day, determine the composition and identify the potentials for recycling of waste generated. Characterization of wastes from selected households in the residential areas was done for over a 7 day period. The weight of each sorted category of waste was recorded in a structured database that calculated the proportion of each waste component. The results indicated that 85.4% of the sampled waste characterized was found to be recyclable; with an estimated average waste generated of 1.82kg/capita/day. The various solid waste fractions were organic (64.6%), plastics (15.6%), metals (9.2%), glass materials (1.6%) and unclassified (8.9%). It was concluded from this study that a large proportion of the waste generated from OAU campus residential area was recyclable and that there is a need to enact policy on waste recycling within the university campus.

Keywords: recycling, household wastes, residential, solid waste management

Procedia PDF Downloads 393
1147 Development of a Decision-Making Method by Using Machine Learning Algorithms in the Early Stage of School Building Design

Authors: Pegah Eshraghi, Zahra Sadat Zomorodian, Mohammad Tahsildoost

Abstract:

Over the past decade, energy consumption in educational buildings has steadily increased. The purpose of this research is to provide a method to quickly predict the energy consumption of buildings using separate evaluation of zones and decomposing the building to eliminate the complexity of geometry at the early design stage. To produce this framework, machine learning algorithms such as Support vector regression (SVR) and Artificial neural network (ANN) are used to predict energy consumption and thermal comfort metrics in a school as a case. The database consists of more than 55000 samples in three climates of Iran. Cross-validation evaluation and unseen data have been used for validation. In a specific label, cooling energy, it can be said the accuracy of prediction is at least 84% and 89% in SVR and ANN, respectively. The results show that the SVR performed much better than the ANN.

Keywords: early stage of design, energy, thermal comfort, validation, machine learning

Procedia PDF Downloads 86
1146 Relationship between Growth of Non-Performing Assets and Credit Risk Management Practices in Indian Banks

Authors: Sirus Sharifi, Arunima Haldar, S. V. D. Nageswara Rao

Abstract:

The study attempts to analyze the impact of credit risk management practices of Indian scheduled commercial banks on their non-performing assets (NPAs). The data on credit risk practices was collected by administering a questionnaire to risk managers/executives at different banks. The data on NPAs (from 2012 to 2016) is sourced from Prowess, a database compiled by the Centre for Monitoring Indian Economy (CMIE). The model was estimated using cross-sectional regression method. As expected, the findings suggest that there is a negative relationship between credit risk management and NPA growth in Indian banks. The study has implications for Indian banks given the high level of losses, and the implementation of Basel III norms by the central bank, i.e. Reserve Bank of India (RBI). Evidence on credit risk management in Indian banks, and their relationship with non-performing assets held by them.

Keywords: credit risk, identification, Indian Banks, NPAs, ownership

Procedia PDF Downloads 399
1145 iCCS: Development of a Mobile Web-Based Student Integrated Information System using Hill Climbing Algorithm

Authors: Maria Cecilia G. Cantos, Lorena W. Rabago, Bartolome T. Tanguilig III

Abstract:

This paper describes a conducive and structured information exchange environment for the students of the College of Computer Studies in Manuel S. Enverga University Foundation in. The system was developed to help the students to check their academic result, manage profile, make self-enlistment and assist the students to manage their academic status that can be viewed also in mobile phones. Developing class schedules in a traditional way is a long process that involves making many numbers of choices. With Hill Climbing Algorithm, however, the process of class scheduling, particularly with regards to courses to be taken by the student aligned with the curriculum, can perform these processes and end up with an optimum solution. The proponent used Rapid Application Development (RAD) for the system development method. The proponent also used the PHP as the programming language and MySQL as the database.

Keywords: hill climbing algorithm, integrated system, mobile web-based, student information system

Procedia PDF Downloads 383
1144 Settlement Prediction for Tehran Subway Line-3 via FLAC3D and ANFIS

Authors: S. A. Naeini, A. Khalili

Abstract:

Nowadays, tunnels with different applications are developed, and most of them are related to subway tunnels. The excavation of shallow tunnels that pass under municipal utilities is very important, and the surface settlement control is an important factor in the design. The study sought to analyze the settlement and also to find an appropriate model in order to predict the behavior of the tunnel in Tehran subway line-3. The displacement in these sections is also determined by using numerical analyses and numerical modeling. In addition, the Adaptive Neuro-Fuzzy Inference System (ANFIS) method is utilized by Hybrid training algorithm. The database pertinent to the optimum network was obtained from 46 subway tunnels in Iran and Turkey which have been constructed by the new Austrian tunneling method (NATM) with similar parameters based on type of their soil. The surface settlement was measured, and the acquired results were compared to the predicted values. The results disclosed that computing intelligence is a good substitute for numerical modeling.

Keywords: settlement, Subway Line, FLAC3D, ANFIS Method

Procedia PDF Downloads 225
1143 An Erudite Technique for Face Detection and Recognition Using Curvature Analysis

Authors: S. Jagadeesh Kumar

Abstract:

Face detection and recognition is an authoritative technology for image database management, video surveillance, and human computer interface (HCI). Face recognition is a rapidly nascent method, which has been extensively discarded in forensics such as felonious identification, tenable entree, and custodial security. This paper recommends an erudite technique using curvature analysis (CA) that has less false positives incidence, operative in different light environments and confiscates the artifacts that are introduced during image acquisition by ring correction in polar coordinate (RCP) method. This technique affronts mean and median filtering technique to remove the artifacts but it works in polar coordinate during image acquisition. Investigational fallouts for face detection and recognition confirms decent recitation even in diagonal orientation and stance variation.

Keywords: curvature analysis, ring correction in polar coordinate method, face detection, face recognition, human computer interaction

Procedia PDF Downloads 280
1142 Fire Smoke Removal over Cu-Mn-Ce Oxide Catalyst with CO₂ Sorbent Addition: Co Oxidation and in-situ CO₂ Sorption

Authors: Jin Lin, Shouxiang Lu, Kim Meow Liew

Abstract:

In a fire accident, fire smoke often poses a serious threat to human safety especially in the enclosed space such as submarine and space-crafts environment. Efficient removal of the hazardous gas products particularly a large amount of CO and CO₂ gases from these confined space is critical for the security of the staff and necessary for the post-fire environment recovery. In this work, Cu-Mn-Ce composite oxide catalysts coupled with CO₂ sorbents were prepared using wet impregnation method, solid-state impregnation method and wet/solid-state impregnation method. The as-prepared samples were tested dynamically and isothermally for CO oxidation and CO₂ sorption and further characterized by the X-ray diffraction (XRD), nitrogen adsorption and desorption, and field emission scanning electron microscopy (FE-SEM). The results showed that all the samples were able to catalyze CO into CO₂ and capture CO₂ in situ by chemisorption. Among all the samples, the sample synthesized by the wet/solid-state impregnation method showed the highest catalytic activity toward CO oxidation and the fine ability of CO₂ sorption. The sample prepared by the solid-state impregnation method showed the second CO oxidation performance, while the coupled sample using the wet impregnation method exhibited much poor CO oxidation activity. The various CO oxidation and CO₂ sorption properties of the samples might arise from the different dispersed states of the CO₂ sorbent in the CO catalyst, owing to the different preparation methods. XRD results confirmed the high-dispersed sorbent phase in the samples prepared by the wet and solid impregnation method, while that of the sample prepared by wet/solid-state impregnation method showed the larger bulk phase as indicated by the high-intensity diffraction peaks. Nitrogen adsorption and desorption results further revealed that the latter sample had a higher surface area and pore volume, which were beneficial for the CO oxidation over the catalyst. Hence, the Cu-Mn-Ce oxide catalyst coupled with CO₂ sorbent using wet/solid-state impregnation method could be a good choice for fire smoke removal in the enclosed space.

Keywords: CO oxidation, CO₂ sorption, preparation methods, smoke removal

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1141 Blockchain Technology in Supply Chain Management: A Systematic Review And Meta-Analysis

Authors: Mohammad Yousuf Khan, Bhavya Alankar

Abstract:

Blockchain is a promising technology with its features such as immutability and decentralized database. It has applications in various fields such as pharmaceutical, finance, & the food industry. At the core of its heart lies its feature, traceability which is the most desired key in supply chains. However, supply chains have always been hit rock bottom by scandals and controversies. In this review paper, we have explored the advancement and research gaps of blockchain technology (BT) in supply chain management (SCM). We have used the Prisma framework for systematic literature review (SLR) and included a minuscule amount of grey literature to reduce publication bias. We found that supply chain traceability and transparency is the most researched objective in SCM. There was hardly any research in supply chain resilience. Further, we found that 40 % of the papers were application based. Most articles have focused on the advantages of BT, rather than analyzing it critically. This study will help identify gaps and suitable actions to be followed for an efficient implementation of BT in SCM.

Keywords: blockchain technology, supply chain management, supply chain transparency, supply chain resilience

Procedia PDF Downloads 155
1140 Scientometrics Analysis of Food Supply Chain Risk Assessment Literature: Based On Web of Science Record 1996-2014

Authors: Mohsen Shirani, Shadi Asadzandi, Micaela Demichela

Abstract:

This paper presents the results of a study to assess crucial aspects and the strength of the scientific basis of a typically interdisciplinary, applied field: food supply chain risk assessment research. Our approach is based on an advanced scientometrics analysis with novel elements to assess the influence and dissemination of research results and to measure interdisciplinary. This paper aims to describe the quantity and quality of the publication trends in food supply chain risk assessment. The population under study was composed of 266 articles from database web of science. The results were analyzed based on date of publication, type of document, language of the documents, source of publications, subject areas, authors and their affiliations, and the countries involved in developing the articles.

Keywords: food supply chain, risk assessment, scientometrics, web of science

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1139 Generating Real-Time Visual Summaries from Located Sensor-Based Data with Chorems

Authors: Z. Bouattou, R. Laurini, H. Belbachir

Abstract:

This paper describes a new approach for the automatic generation of the visual summaries dealing with cartographic visualization methods and sensors real time data modeling. Hence, the concept of chorems seems an interesting candidate to visualize real time geographic database summaries. Chorems have been defined by Roger Brunet (1980) as schematized visual representations of territories. However, the time information is not yet handled in existing chorematic map approaches, issue has been discussed in this paper. Our approach is based on spatial analysis by interpolating the values recorded at the same time, by sensors available, so we have a number of distributed observations on study areas and used spatial interpolation methods to find the concentration fields, from these fields and by using some spatial data mining procedures on the fly, it is possible to extract important patterns as geographic rules. Then, those patterns are visualized as chorems.

Keywords: geovisualization, spatial analytics, real-time, geographic data streams, sensors, chorems

Procedia PDF Downloads 398
1138 The Efficacy of Open Educational Resources in Students’ Performance and Engagement

Authors: Huda Al-Shuaily, E. M. Lacap

Abstract:

Higher Education is one of the most essential fundamentals for the advancement and progress of a country. It demands to be as accessible as possible and as comprehensive as it can be reached. In this paper, we succeeded to expand the accessibility and delivery of higher education using an Open Educational Resources (OER), a freely accessible, openly licensed documents, and media for teaching and learning. This study creates a comparative design of student’s academic performance on the course Introduction to Database and student engagement to the virtual learning environment (VLE). The study was done in two successive semesters - one without using the OER and the other is using OER. In the study, we established that there is a significant increase in student’s engagement in VLE in the latter semester compared to the former. By using the latter semester’s data, we manage to show that the student’s engagement has a positive impact on students’ academic performance. Moreso, after clustering their academic performance, the impact is seen higher for students who are low performing. The results show that these engagements can be used to potentially predict the learning styles of the student with a high degree of precision.

Keywords: EDM, learning analytics, moodle, OER, student-engagement

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1137 A Context-Sensitive Algorithm for Media Similarity Search

Authors: Guang-Ho Cha

Abstract:

This paper presents a context-sensitive media similarity search algorithm. One of the central problems regarding media search is the semantic gap between the low-level features computed automatically from media data and the human interpretation of them. This is because the notion of similarity is usually based on high-level abstraction but the low-level features do not sometimes reflect the human perception. Many media search algorithms have used the Minkowski metric to measure similarity between image pairs. However those functions cannot adequately capture the aspects of the characteristics of the human visual system as well as the nonlinear relationships in contextual information given by images in a collection. Our search algorithm tackles this problem by employing a similarity measure and a ranking strategy that reflect the nonlinearity of human perception and contextual information in a dataset. Similarity search in an image database based on this contextual information shows encouraging experimental results.

Keywords: context-sensitive search, image search, similarity ranking, similarity search

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1136 Simulation of Gamma Rays Attenuation Coefficient for Some common Shielding Materials Using Monte Carlo Program

Authors: Cherief Houria, Fouka Mourad

Abstract:

In this work, the simulation of the radiation attenuation is carried out in a photon detector consisting of different common shielding material using a Monte Carlo program called PTM. The aim of the study is to investigate the effect of atomic weight and the thickness of shielding materials on the gamma radiation attenuation ability. The linear attenuation coefficients of Aluminum (Al), Iron (Fe), and lead (Pb) elements were evaluated at photons energy of 661:7KeV that are considered to be emitted from a standard radioactive point source Cs 137. The experimental measurements have been performed for three materials to obtain these linear attenuation coefficients, using a Gamma NaI(Tl) scintillation detector. Our results have been compared with the simulation results of the linear attenuation coefficient using the XCOM database and Geant4 codes and reveal that they are well agreed with both simulation data.

Keywords: gamma photon, Monte Carlo program, radiation attenuation, shielding material, the linear attenuation coefficient

Procedia PDF Downloads 195
1135 Radiation Safety Factor of Education and Research Institution in Republic of Korea

Authors: Yeo Ryeong Jeon, Pyong Kon Cho, Eun Ok Han, Hyon Chul Jang, Yong Min Kim

Abstract:

This study surveyed on recognition related to radiation safety for radiation safety managers and workers those who have been worked in Republic of Korea education and research institution. At present, South Korea has no guideline and manual of radiation safety for education and research institution. Therefore, we tried to find an educational basis for development of radiation safety guideline and manual. To check the level of knowledge, attitude, and behavior about radiation safety, we used the questionnaire that consisted of 29 questions against knowledge, attitude and behavior, 4 questions against self-efficacy and expectation based on four factors (radiation source, human, organizational and physical environment) of the Haddon's matrix. Responses were collected between May 4 and June 30, 2015. We analyzed questionnaire by means of IBM SPSS/WIN 15 which well known as statistical package for social science. The data were compared with mean, standard deviation, Pearson's correlation, ANOVA (analysis of variance) and regression analysis. 180 copies of the questionnaire were returned from 60 workplaces. The overall mean results for behavior level was relatively lower than knowledge and attitude level. In particular, organizational environment factor on the radiation safety management indicated the lowest behavior level. Most of the factors were correlated in Pearson’s correlation analysis, especially between knowledge of human factors and behavior of human factors (Pearson’s correlation coefficient 0.809, P<.01). When analysis performed in line with the main radiation source type, institutions where have been used only opened RI (radioisotope) behavior level was the lowest among all subjects. Finally, knowledge of radiation source factor (β=0.556, P<.001) and human factor(β=0.376, P<.001) had the greatest impact in terms of behavior practice. Radiation safety managers and workers think positively about radiation safety management, but are poorly informed organizational environment of their institution. Thus, each institution need to efforts to settlement of radiation safety culture. Also, pedagogical interventions for improving knowledge on radiation safety needs in terms of safety accident prevention.

Keywords: radiation safety management, factor analysis, SPSS, republic of Korea

Procedia PDF Downloads 362
1134 Journals' Productivity in the Literature on Malaria in Africa

Authors: Yahya Ibrahim Harande

Abstract:

The purpose of this study was to identify the journals that published articles on malaria disease in Africa and to determine the core of productive journals from the identified journals. The data for the study were culled out from African Index Medicus (AIM) database. A total of 529 articles was gathered from 115 journal titles from 1979-2011. In order to obtain the core of productive journals, Bradford`s law was applied to the collected data. Five journal titles were identified and determined as core journals. The data used for the study was analyzed and that, the subject matter used, Malaria was in conformity with the Bradford`s law. On the aspect dispersion of the literature, English was found to be the dominant language of the journals. (80.9%) followed by French (16.5%). Followed by Portuguese (1.7%) and German (0.9%). Recommendation is hereby proposed for the medical libraries to acquire these five journals that constitute the core in malaria literature for the use of their clients. It could also help in streamlining their acquision and selection exercises. More researches in the subject area using Bibliometrics approaches are hereby recommended.

Keywords: productive journals, malaria disease literature, Bradford`s law, core journals, African scholars

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1133 Corporate Social Responsibility Practices and Financial Performance: The Case of French Unlisted SMEs

Authors: Zineb Abidi, Marc-Arthur Diaye

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There exists a large empirical literature concerning the relationship between corporate social responsibility (CSR) and corporate financial performance. This literature, however, applies mainly to large corporations and/or listed firms. To the best of our knowledge, the question of whether meeting CSR requirements impacts the financial performance of small and medium-sized unlisted SMEs has not so far been analyzed. This paper aims to analyze, for the first time, the effect of CSR on the financial performance of SMEs. Using an original database including 5,257 French SMEs, we show that adopting CSR practices has a positive but weak effect on a firm’s financial performance. To develop this further, we analyzed CSR practices interactions assessing the best combination of CSR components that positively influence SME financial performance. Our results show that French SMEs benefit more from their pro-social behavior when they choose a combination of CSR components best adapted to their individual characteristics.

Keywords: corporate social responsibility, financial performance, unlisted firms, SMEs

Procedia PDF Downloads 167
1132 Geospatial Data Complexity in Electronic Airport Layout Plan

Authors: Shyam Parhi

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Airports GIS program collects Airports data, validate and verify it, and stores it in specific database. Airports GIS allows authorized users to submit changes to airport data. The verified data is used to develop several engineering applications. One of these applications is electronic Airport Layout Plan (eALP) whose primary aim is to move from paper to digital form of ALP. The first phase of development of eALP was completed recently and it was tested for a few pilot program airports across different regions. We conducted gap analysis and noticed that a lot of development work is needed to fine tune at least six mandatory sheets of eALP. It is important to note that significant amount of programming is needed to move from out-of-box ArcGIS to a much customized ArcGIS which will be discussed. The ArcGIS viewer capability to display essential features like runway or taxiway or the perpendicular distance between them will be discussed. An enterprise level workflow which incorporates coordination process among different lines of business will be highlighted.

Keywords: geospatial data, geology, geographic information systems, aviation

Procedia PDF Downloads 414
1131 Automatic Facial Skin Segmentation Using Possibilistic C-Means Algorithm for Evaluation of Facial Surgeries

Authors: Elham Alaee, Mousa Shamsi, Hossein Ahmadi, Soroosh Nazem, Mohammad Hossein Sedaaghi

Abstract:

Human face has a fundamental role in the appearance of individuals. So the importance of facial surgeries is undeniable. Thus, there is a need for the appropriate and accurate facial skin segmentation in order to extract different features. Since Fuzzy C-Means (FCM) clustering algorithm doesn’t work appropriately for noisy images and outliers, in this paper we exploit Possibilistic C-Means (PCM) algorithm in order to segment the facial skin. For this purpose, first, we convert facial images from RGB to YCbCr color space. To evaluate performance of the proposed algorithm, the database of Sahand University of Technology, Tabriz, Iran was used. In order to have a better understanding from the proposed algorithm; FCM and Expectation-Maximization (EM) algorithms are also used for facial skin segmentation. The proposed method shows better results than the other segmentation methods. Results include misclassification error (0.032) and the region’s area error (0.045) for the proposed algorithm.

Keywords: facial image, segmentation, PCM, FCM, skin error, facial surgery

Procedia PDF Downloads 582
1130 Associated Factors of Hypercholesterolemia, Hyperuricemia and Double Burden of Hypercuricémia-Hypercholesterolemia in Gout Patients: Hospital Based Study

Authors: Pierre Mintom, Armel Assiene Agamou, Leslie Toukem, William Dakam, Christine Fernande Nyangono Biyegue

Abstract:

Context: Hyperuricemia, the presence of high levels of uric acid in the blood, is a known precursor to the development of gout. Recent studies have suggested a strong association between hyperuricemia and disorders of lipoprotein metabolism, specifically hypercholesterolemia. Understanding the factors associated with these conditions in gout patients is essential for effective treatment and management. Research Aim: The objective of this study was to determine the prevalence of hyperuricemia, hypercholesterolemia, and the double burden of hyperuricemia-hypercholesterolemia in the gouty population. Additionally, the study aimed to identify the factors associated with these conditions. Methodology: The study utilized a database from a survey of 150 gouty patients recruited at the Laquintinie Hospital in Douala between August 2017 and February 2018. The database contained information on anthropometric parameters, biochemical markers, and the food and drugs consumed by the patients. Hyperuricemia and hypercholesterolemia were defined based on specific serum uric acid and total cholesterol thresholds, and the double burden was defined as the co-occurrence of hyperuricemia and hypercholesterolemia. Findings: The study found that the prevalence rates for hyperuricemia, hypercholesterolemia, and the double burden were 61.3%, 76%, and 50.7% respectively. Factors associated with these conditions included hypertriglyceridemia, atherogenicity index TC/HDL ratio, atherogenicity index LDL/HDL ratio, family history, and the consumption of specific foods and drinks. Theoretical Importance: The study highlights the strong association between hyperuricemia and dyslipidemia, providing important insights for guiding treatment strategies in gout patients. Additionally, it emphasizes the significance of nutritional education in managing these metabolic disorders, suggesting the need to address eating habits in gout patients. Data Collection and Analysis Procedures: Data was collected through surveys and medical records of gouty patients. Information on anthropometric parameters, biochemical markers, and dietary habits was recorded. Prevalence rates and associated factors were determined through statistical analysis, employing odds ratios to assess the risks. Question Addressed: The study aimed to address the prevalence rates and associated factors of hyperuricemia, hypercholesterolemia, and the double burden in gouty patients. It sought to understand the relationships between these conditions and determine their implications for treatment and nutritional education. Conclusion: Findings show that it’s exists an association between hyperuricemia and hypercholesterolemia in gout patients, thus creating a double burden. The findings underscore the importance of considering family history and eating habits in addressing the double burden of hyperuricemia-hypercholesterolemia. This study provides valuable insights for guiding treatment approaches and emphasizes the need for nutritional education in gout patients. This study specifically focussed on the sick population. A case–control study between gouty and non-gouty populations would be interesting to better compare and explain the results observed.

Keywords: gout, hyperuricemia, hypercholesterolemia, double burden

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1129 The Tramway in French Cities: Complication of Public Spaces and Complexity of the Design Process

Authors: Elisa Maître

Abstract:

The redeployment of tram networks in French cities has considerably modified public spaces and the way citizens use them. Above and beyond the image that trams have of contributing to the sustainable urban development, the question of safety for users in these spaces has not been studied much. This study is based on an analysis of use of public spaces laid out for trams, from the standpoint of legibility and safety concerns. The study also examines to what extent the complexity of the design process, with many interactions between numerous and varied players in this process has a role in the genesis of these problems. This work is mainly based on the analysis of links between the uses of these re-designed public spaces (through observations, interviews of users and accident studies) and the analysis of the design conditions and processes of the projects studied (mainly based on interviews with the actors of these projects). Practical analyses were based three points of view: that of the planner, that of the user (based on observations and interviews) and that of the road safety expert. The cities of Montpellier, Marseille and Nice are the three fields of study on which the demonstration of this thesis is based. On part, the results of this study allow showing that the insertion of tram poses some problems complication of public areas of French cities. These complications related to the restructuring of public spaces for the tram, create difficulties of use and safety concerns. On the other hand, interviews depth analyses, fully transcribed, have led us to develop particular dysfunction scenarios in the design process. These elements lead to question the way the legibility and safety of these new forms of public spaces are taken into account. Then, an in-depth analysis of the design processes of public spaces with trams systems would also be a way of better understanding the choices made, the compromises accepted, and the conflicts and constraints at work, weighing on the layout of these spaces. The results presented concerning the impact that spaces laid out for trams have on the difficulty of use, suggest different possibilities for improving the way in which safety for all users is taken into account in designing public spaces.

Keywords: public spaces, road layout, users, design process of urban projects

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1128 A t-SNE and UMAP Based Neural Network Image Classification Algorithm

Authors: Shelby Simpson, William Stanley, Namir Naba, Xiaodi Wang

Abstract:

Both t-SNE and UMAP are brand new state of art tools to predominantly preserve the local structure that is to group neighboring data points together, which indeed provides a very informative visualization of heterogeneity in our data. In this research, we develop a t-SNE and UMAP base neural network image classification algorithm to embed the original dataset to a corresponding low dimensional dataset as a preprocessing step, then use this embedded database as input to our specially designed neural network classifier for image classification. We use the fashion MNIST data set, which is a labeled data set of images of clothing objects in our experiments. t-SNE and UMAP are used for dimensionality reduction of the data set and thus produce low dimensional embeddings. Furthermore, we use the embeddings from t-SNE and UMAP to feed into two neural networks. The accuracy of the models from the two neural networks is then compared to a dense neural network that does not use embedding as an input to show which model can classify the images of clothing objects more accurately.

Keywords: t-SNE, UMAP, fashion MNIST, neural networks

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1127 An E-Assessment Website to Implement Hierarchical Aggregate Assessment

Authors: M. Lesage, G. Raîche, M. Riopel, F. Fortin, D. Sebkhi

Abstract:

This paper describes a Web server implementation of the hierarchical aggregate assessment process in the field of education. This process describes itself as a field of teamwork assessment where teams can have multiple levels of hierarchy and supervision. This process is applied everywhere and is part of the management, education, assessment and computer science fields. The E-Assessment website named “Cluster” records in its database the students, the course material, the teams and the hierarchical relationships between the students. For the present research, the hierarchical relationships are team member, team leader and group administrator appointments. The group administrators have the responsibility to supervise team leaders. The experimentation of the application has been performed by high school students in geology courses and Canadian army cadets for navigation patrols in teams. This research extends the work of Nance that uses a hierarchical aggregation process similar as the one implemented in the “Cluster” application.

Keywords: e-learning, e-assessment, teamwork assessment, hierarchical aggregate assessment

Procedia PDF Downloads 367