Search results for: rolling stock reliability
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2847

Search results for: rolling stock reliability

297 Development of a Data-Driven Method for Diagnosing the State of Health of Battery Cells, Based on the Use of an Electrochemical Aging Model, with a View to Their Use in Second Life

Authors: Desplanches Maxime

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Accurate estimation of the remaining useful life of lithium-ion batteries for electronic devices is crucial. Data-driven methodologies encounter challenges related to data volume and acquisition protocols, particularly in capturing a comprehensive range of aging indicators. To address these limitations, we propose a hybrid approach that integrates an electrochemical model with state-of-the-art data analysis techniques, yielding a comprehensive database. Our methodology involves infusing an aging phenomenon into a Newman model, leading to the creation of an extensive database capturing various aging states based on non-destructive parameters. This database serves as a robust foundation for subsequent analysis. Leveraging advanced data analysis techniques, notably principal component analysis and t-Distributed Stochastic Neighbor Embedding, we extract pivotal information from the data. This information is harnessed to construct a regression function using either random forest or support vector machine algorithms. The resulting predictor demonstrates a 5% error margin in estimating remaining battery life, providing actionable insights for optimizing usage. Furthermore, the database was built from the Newman model calibrated for aging and performance using data from a European project called Teesmat. The model was then initialized numerous times with different aging values, for instance, with varying thicknesses of SEI (Solid Electrolyte Interphase). This comprehensive approach ensures a thorough exploration of battery aging dynamics, enhancing the accuracy and reliability of our predictive model. Of particular importance is our reliance on the database generated through the integration of the electrochemical model. This database serves as a crucial asset in advancing our understanding of aging states. Beyond its capability for precise remaining life predictions, this database-driven approach offers valuable insights for optimizing battery usage and adapting the predictor to various scenarios. This underscores the practical significance of our method in facilitating better decision-making regarding lithium-ion battery management.

Keywords: Li-ion battery, aging, diagnostics, data analysis, prediction, machine learning, electrochemical model, regression

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296 Results of Three-Year Operation of 220kV Pilot Superconducting Fault Current Limiter in Moscow Power Grid

Authors: M. Moyzykh, I. Klichuk, L. Sabirov, D. Kolomentseva, E. Magommedov

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Modern city electrical grids are forced to increase their density due to the increasing number of customers and requirements for reliability and resiliency. However, progress in this direction is often limited by the capabilities of existing network equipment. New energy sources or grid connections increase the level of short-circuit currents in the adjacent network, which can exceed the maximum rating of equipment–breaking capacity of circuit breakers, thermal and dynamic current withstand qualities of disconnectors, cables, and transformers. Superconducting fault current limiter (SFCL) is a modern solution designed to deal with the increasing fault current levels in power grids. The key feature of this device is its instant (less than 2 ms) limitation of the current level due to the nature of the superconductor. In 2019 Moscow utilities installed SuperOx SFCL in the city power grid to test the capabilities of this novel technology. The SFCL became the first SFCL in the Russian energy system and is currently the most powerful SFCL in the world. Modern SFCL uses second-generation high-temperature superconductor (2G HTS). Despite its name, HTS still requires low temperatures of liquid nitrogen for operation. As a result, Moscow SFCL is built with a cryogenic system to provide cooling to the superconductor. The cryogenic system consists of three cryostats that contain a superconductor part and are filled with liquid nitrogen (three phases), three cryocoolers, one water chiller, three cryopumps, and pressure builders. All these components are controlled by an automatic control system. SFCL has been continuously operating on the city grid for over three years. During that period of operation, numerous faults occurred, including cryocooler failure, chiller failure, pump failure, and others (like a cryogenic system power outage). All these faults were eliminated without an SFCL shut down due to the specially designed cryogenic system backups and quick responses of grid operator utilities and the SuperOx crew. The paper will describe in detail the results of SFCL operation and cryogenic system maintenance and what measures were taken to solve and prevent similar faults in the future.

Keywords: superconductivity, current limiter, SFCL, HTS, utilities, cryogenics

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295 Geographic Mapping of Tourism in Rural Areas: A Case Study of Cumbria, United Kingdom

Authors: Emma Pope, Demos Parapanos

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Rural tourism has become more obvious and prevalent, with tourists’ increasingly seeking authentic experiences. This movement accelerated post-Covid, putting destinations in danger of reaching levels of saturation called ‘overtourism’. Whereas the phenomenon of overtourism has been frequently discussed in the urban context by academics and practitioners over recent years, it has hardly been referred to in the context of rural tourism, where perhaps it is even more difficult to manage. Rural tourism was historically considered small-scale, marked by its traditional character and by having little impact on nature and rural society. The increasing number of rural areas experiencing overtourism, however, demonstrates the need for new approaches, especially as the impacts and enablers of overtourism are context specific. Cumbria, with approximately 47 million visitors each year, and 23,000 operational enterprises, is one of these rural areas experiencing overtourism in the UK. Using the county of Cumbria as an example, this paper aims to explore better planning and management in rural destinations by clustering the area into rural and ‘urban-rural’ tourism zones. To achieve the aim, this study uses secondary data from a variety of sources to identify variables relating to visitor economy development and demand. These data include census data relating to population and employment, tourism industry-specific data including tourism revenue, visitor activities, and accommodation stock, and big data sources such as Trip Advisor and All Trails. The combination of these data sources provides a breadth of tourism-related variables. The subsequent analysis of this data draws upon various validated models. For example, tourism and hospitality employment density, territorial tourism pressure, and accommodation density. In addition to these statistical calculations, other data are utilized to further understand the context of these zones, for example, tourist services, attractions, and activities. The data was imported into ARCGIS where the density of the different variables is visualized on maps. This study aims to provide an understanding of the geographical context of visitor economy development and tourist behavior in rural areas. The findings contribute to an understanding of the spatial dynamics of tourism within the region of Cumbria through the creation of thematized maps. Different zones of tourism industry clusters are identified, which include elements relating to attractions, enterprises, infrastructure, tourism employment and economic impact. These maps visualize hot and cold spots relating to a variety of tourism contexts. It is believed that the strategy used to provide a visual overview of tourism development and demand in Cumbria could provide a strategic tool for rural areas to better plan marketing opportunities and avoid overtourism. These findings can inform future sustainability policy and destination management strategies within the areas through an understanding of the processes behind the emergence of both hot and cold spots. It may mean that attract and disperse needs to be reviewed in terms of a strategic option. In other words, to use sector or zonal policies for the individual hot or cold areas with transitional zones dependent upon local economic, social and environmental factors.

Keywords: overtourism, rural tourism, sustainable tourism, tourism planning, tourism zones

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294 Evaluation of Commercial Back-analysis Package in Condition Assessment of Railways

Authors: Shadi Fathi, Moura Mehravar, Mujib Rahman

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Over the years,increased demands on railways, the emergence of high-speed trains and heavy axle loads, ageing, and deterioration of the existing tracks, is imposing costly maintenance actions on the railway sector. The need for developing a fast andcost-efficient non-destructive assessment method for the structural evaluation of railway tracksis therefore critically important. The layer modulus is the main parameter used in the structural design and evaluation of the railway track substructure (foundation). Among many recently developed NDTs, Falling Weight Deflectometer (FWD) test, widely used in pavement evaluation, has shown promising results for railway track substructure monitoring. The surface deflection data collected by FWD are used to estimate the modulus of substructure layers through the back-analysis technique. Although there are different commerciallyavailableback-analysis programs are used for pavement applications, there are onlya limited number of research-based techniques have been so far developed for railway track evaluation. In this paper, the suitability, accuracy, and reliability of the BAKFAAsoftware are investigated. The main rationale for selecting BAKFAA as it has a relatively straightforward user interfacethat is freely available and widely used in highway and airport pavement evaluation. As part of the study, a finite element (FE) model of a railway track section near Leominsterstation, Herefordshire, UK subjected to the FWD test, was developed and validated against available field data. Then, a virtual experimental database (including 218 sets of FWD testing data) was generated using theFE model and employed as the measured database for the BAKFAA software. This database was generated considering various layers’ moduli for each layer of track substructure over a predefined range. The BAKFAA predictions were compared against the cone penetration test (CPT) data (available from literature; conducted near to Leominster station same section as the FWD was performed). The results reveal that BAKFAA overestimatesthe layers’ moduli of each substructure layer. To adjust the BAKFA with the CPT data, this study introduces a correlation model to make the BAKFAA applicable in railway applications.

Keywords: back-analysis, bakfaa, railway track substructure, falling weight deflectometer (FWD), cone penetration test (CPT)

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293 A Comparative Study on the Positive and Negative of Electronic Word-of-Mouth on the SERVQUAL Scale-Take A Certain Armed Forces General Hospital in Taiwan As An Example

Authors: Po-Chun Lee, Li-Lin Liang, Ching-Yuan Huang

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Purpose: Research on electronic word-of-mouth (eWOM)& online review has been widely used in service industry management research in recent years. The SERVQUAL scale is the most commonly used method to measure service quality. Therefore, the purpose of this research is to combine electronic word of mouth & online review with the SERVQUAL scale. To explore the comparative study of positive and negative electronic word-of-mouth reviews of a certain armed force general hospital in Taiwan. Data sources: This research obtained online word-of-mouth comment data on google maps from a military hospital in Taiwan in the past ten years through Internet data mining technology. Research methods: This study uses the semantic content analysis method to classify word-of-mouth reviews according to the revised PZB SERVQUAL scale. Then carry out statistical analysis. Results of data synthesis: The results of this study disclosed that the negative reviews of this military hospital in Taiwan have been increasing year by year. Under the COVID-19 epidemic, positive word-of-mouth has a downward trend. Among the five determiners of SERVQUAL of PZB, positive word-of-mouth reviews performed best in “Assurance,” with a positive review rate of 58.89%, Followed by 43.33% of “Responsiveness.” In negative word-of-mouth reviews, “Assurance” performed the worst, with a positive rate of 70.99%, followed by responsive 29.01%. Conclusions: The important conclusions of this study disclosed that the total number of electronic word-of-mouth reviews of the military hospital has revealed positive growth in recent years, and the positive word-of-mouth growth has revealed negative growth after the epidemic of COVID-19, while the negative word-of-mouth has grown substantially. Regardless of the positive and negative comments, what patients care most about is “Assurance” of the professional attitude and skills of the medical staff, which needs to be strengthened most urgently. In addition, good “Reliability” will help build positive word-of-mouth. However, poor “Responsiveness” can easily lead to the spread of negative word-of-mouth. This study suggests that the hospital should focus on these few service-oriented quality management and audits.

Keywords: quality of medical service, electronic word-of-mouth, armed forces general hospital

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292 An Evaluation and Guidance for mHealth Apps

Authors: Tareq Aljaber

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The number of mobile health apps is growing at a fast frequency as it's nearly doubled in a year between 2015 and 2016. Though, there is a lack of an effective evaluation framework to verify the usability and reliability of mobile phone health education applications which would help saving time and effort for the numerous user groups. This abstract describing a framework for evaluating mobile applications in specifically mobile health education applications, along with a guidance select tool to assist different users to select the most suitable mobile health education apps. The effective framework outcome is intended to meet the requirements and needs of the different stakeholder groups additionally to enhancing the development of mobile health education applications with software engineering approaches, by producing new and more effective techniques to evaluate such software. This abstract highlights the significance and consequences of mobile health education apps, before focusing the light on the required to create an effective evaluation framework for these apps. An explanation of the effective evaluation framework is going to be delivered in the abstract, beside with some specific evaluation metrics: an efficient hybrid of selected heuristic evaluation (HE) and usability evaluation (UE) metrics to enable the determination of the usefulness and usability of health education mobile apps. Moreover, an explanation of the qualitative and quantitative outcomes for the effective evaluation framework was accomplished using Epocrates mobile phone app in addition to some other mobile phone apps. This proposed framework-An Evaluation Framework for Mobile Health Education Apps-consists of a hybrid of 5 metrics designated from a larger set in usability evaluation and heuristic evaluation, illuminated grounded on 15 unstructured interviews from software developers (SD), health professionals (HP) and patients (P). These five metrics corresponding to explicit facets of usability recognised through a requirements analysis of typical stakeholders of mobile health apps. These five hybrid selected metrics were scattered across 24 specific questionnaire questions, which are available on request from first author. This questionnaire has been sent to 81 participants distributed in three sets of stakeholders from software developers (SD), health professionals (HP) and patients/general users (P/GU) on the purpose of ranking three sets of mobile health education applications. Finally, the outcomes from the questionnaire data helped us to approach our aims which are finding the profile for different stakeholders, finding the profile for different mobile health educations application packages, ranking different mobile health education application and guide us to build the select guidance too which is apart from the Evaluation Framework for Mobile Health Education Apps.

Keywords: evaluation framework, heuristic evaluation, usability evaluation, metrics

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291 Solar Photovoltaic Foundation Design

Authors: Daniel John Avutia

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Solar Photovoltaic (PV) development is reliant on the sunlight hours available in a particular region to generate electricity. A potential area is assessed through its inherent solar radiation intensity measured in watts per square meter. Solar energy development involves the feasibility, design, construction, operation and maintenance of the relevant infrastructure, but this paper will focus on the design and construction aspects. Africa and Australasia have the longest sunlight hours per day and the highest solar radiation per square meter, 7 sunlight hours/day and 5 kWh/day respectively. Solar PV support configurations consist of fixed-tilt support and tracker system structures, the differentiation being that the latter was introduced to improve the power generation efficiency of the former due to the sun tracking movement capabilities. The installation of Solar PV foundations involves rammed piles, drilling/grout piles and shallow raft reinforced concrete structures. This paper presents a case study of 2 solar PV projects in Africa and Australia, discussing the foundation design consideration and associated construction cost implications of the selected foundations systems. Solar PV foundations represent up to one fifth of the civil works costs in a project. Therefore, the selection of the most structurally sound and feasible foundation for the prevailing ground conditions is critical towards solar PV development. The design wind speed measured by anemometers govern the pile embedment depth for rammed and drill/grout foundation systems. The lateral pile deflection and vertical pull out resistance of piles increase proportionally with the embedment depth for uniform pile geometry and geology. The pile driving rate may also be used to anticipate the lateral resistance and skin friction restraining the pile. Rammed pile foundations are the most structurally suitable due to the pile skin friction and ease of installation in various geological conditions. The competitiveness of solar PV projects within the renewable energy mix is governed by lowering capital expenditure, improving power generation efficiency and power storage technological advances. The power generation reliability and efficiency are areas for further research within the renewable energy niche.

Keywords: design, foundations, piles, solar

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290 Accreditation and Quality Assurance of Nigerian Universities: The Management Imperative

Authors: F. O Anugom

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The general functions of the university amongst other things include teaching, research and community service. Universities are recognized as the apex of learning, accumulating and imparting knowledge and skills of all kinds to students to enable them to be productive, earn their living and to make optimum contributions to national development. This is equivalent to the production of human capital in the form of high level manpower needed to administer the educational society, be useful to the society and manage the economy. Quality has become a matter of major importance for university education in Nigeria. Accreditation is the systematic review of educational programs to ensure that acceptable standards of education, scholarship and infrastructure are being maintained. Accreditation ensures that institution maintain quality. The process is designed to determine whether or not an institution has met or exceeded the published standards for accreditation, and whether it is achieving its mission and stated purposes. Ensuring quality assurance in accreditation process falls in the hands of university management which justified the need for this study. This study examined accreditation and quality assurance: the management imperative. Three research questions and three hypotheses guided the study. The design was a correlation survey with a population of 2,893 university administrators out of which 578 Heads of department and Dean of faculties were sampled. The instrument for data collection was titled Programme Accreditation Exercise scale with high levels of reliability. The research questions were answered with Pearson ‘r’ statistics. T-test statistics was used to test the hypotheses. It was found among others that the quality of accredited programme depends on the level of funding of universities in Nigeria. It was also indicated that quality of programme accreditation and physical facilities of universities in Nigeria have high relationship. But it was also revealed that programme accreditation is positively related to staffing in Nigerian universities. Based on the findings of the study, the researcher recommend that academic administrators should be included in the team of those who ensure quality programs in the universities. Private sector partnership should be encouraged to fund programs to ensure quality of programme in the universities. Independent agencies should be engaged to monitor the activities of accreditation teams to avoid bias.

Keywords: accreditation, quality assurance, national universities commission , physical facilities, staffing

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289 Characterization of Agroforestry Systems in Burkina Faso Using an Earth Observation Data Cube

Authors: Dan Kanmegne

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Africa will become the most populated continent by the end of the century, with around 4 billion inhabitants. Food security and climate changes will become continental issues since agricultural practices depend on climate but also contribute to global emissions and land degradation. Agroforestry has been identified as a cost-efficient and reliable strategy to address these two issues. It is defined as the integrated management of trees and crops/animals in the same land unit. Agroforestry provides benefits in terms of goods (fruits, medicine, wood, etc.) and services (windbreaks, fertility, etc.), and is acknowledged to have a great potential for carbon sequestration; therefore it can be integrated into reduction mechanisms of carbon emissions. Particularly in sub-Saharan Africa, the constraint stands in the lack of information about both areas under agroforestry and the characterization (composition, structure, and management) of each agroforestry system at the country level. This study describes and quantifies “what is where?”, earliest to the quantification of carbon stock in different systems. Remote sensing (RS) is the most efficient approach to map such a dynamic technology as agroforestry since it gives relatively adequate and consistent information over a large area at nearly no cost. RS data fulfill the good practice guidelines of the Intergovernmental Panel On Climate Change (IPCC) that is to be used in carbon estimation. Satellite data are getting more and more accessible, and the archives are growing exponentially. To retrieve useful information to support decision-making out of this large amount of data, satellite data needs to be organized so to ensure fast processing, quick accessibility, and ease of use. A new solution is a data cube, which can be understood as a multi-dimensional stack (space, time, data type) of spatially aligned pixels and used for efficient access and analysis. A data cube for Burkina Faso has been set up from the cooperation project between the international service provider WASCAL and Germany, which provides an accessible exploitation architecture of multi-temporal satellite data. The aim of this study is to map and characterize agroforestry systems using the Burkina Faso earth observation data cube. The approach in its initial stage is based on an unsupervised image classification of a normalized difference vegetation index (NDVI) time series from 2010 to 2018, to stratify the country based on the vegetation. Fifteen strata were identified, and four samples per location were randomly assigned to define the sampling units. For safety reasons, the northern part will not be part of the fieldwork. A total of 52 locations will be visited by the end of the dry season in February-March 2020. The field campaigns will consist of identifying and describing different agroforestry systems and qualitative interviews. A multi-temporal supervised image classification will be done with a random forest algorithm, and the field data will be used for both training the algorithm and accuracy assessment. The expected outputs are (i) map(s) of agroforestry dynamics, (ii) characteristics of different systems (main species, management, area, etc.); (iii) assessment report of Burkina Faso data cube.

Keywords: agroforestry systems, Burkina Faso, earth observation data cube, multi-temporal image classification

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288 Web-Based Decision Support Systems and Intelligent Decision-Making: A Systematic Analysis

Authors: Serhat Tüzün, Tufan Demirel

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Decision Support Systems (DSS) have been investigated by researchers and technologists for more than 35 years. This paper analyses the developments in the architecture and software of these systems, provides a systematic analysis for different Web-based DSS approaches and Intelligent Decision-making Technologies (IDT), with the suggestion for future studies. Decision Support Systems literature begins with building model-oriented DSS in the late 1960s, theory developments in the 1970s, and the implementation of financial planning systems and Group DSS in the early and mid-80s. Then it documents the origins of Executive Information Systems, online analytic processing (OLAP) and Business Intelligence. The implementation of Web-based DSS occurred in the mid-1990s. With the beginning of the new millennia, intelligence is the main focus on DSS studies. Web-based technologies are having a major impact on design, development and implementation processes for all types of DSS. Web technologies are being utilized for the development of DSS tools by leading developers of decision support technologies. Major companies are encouraging its customers to port their DSS applications, such as data mining, customer relationship management (CRM) and OLAP systems, to a web-based environment. Similarly, real-time data fed from manufacturing plants are now helping floor managers make decisions regarding production adjustment to ensure that high-quality products are produced and delivered. Web-based DSS are being employed by organizations as decision aids for employees as well as customers. A common usage of Web-based DSS has been to assist customers configure product and service according to their needs. These systems allow individual customers to design their own products by choosing from a menu of attributes, components, prices and delivery options. The Intelligent Decision-making Technologies (IDT) domain is a fast growing area of research that integrates various aspects of computer science and information systems. This includes intelligent systems, intelligent technology, intelligent agents, artificial intelligence, fuzzy logic, neural networks, machine learning, knowledge discovery, computational intelligence, data science, big data analytics, inference engines, recommender systems or engines, and a variety of related disciplines. Innovative applications that emerge using IDT often have a significant impact on decision-making processes in government, industry, business, and academia in general. This is particularly pronounced in finance, accounting, healthcare, computer networks, real-time safety monitoring and crisis response systems. Similarly, IDT is commonly used in military decision-making systems, security, marketing, stock market prediction, and robotics. Even though lots of research studies have been conducted on Decision Support Systems, a systematic analysis on the subject is still missing. Because of this necessity, this paper has been prepared to search recent articles about the DSS. The literature has been deeply reviewed and by classifying previous studies according to their preferences, taxonomy for DSS has been prepared. With the aid of the taxonomic review and the recent developments over the subject, this study aims to analyze the future trends in decision support systems.

Keywords: decision support systems, intelligent decision-making, systematic analysis, taxonomic review

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287 Conservation Challenges of Fish and Fisheries in Lake Tana, Ethiopia

Authors: Shewit Kidane, Abebe Getahun, Wassie Anteneh, Admassu Demeke, Peter Goethals

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We have reviewed major findings of scientific studies on Lake Tana fish resources and their threats. The aim was to provide summarized information for all concerned bodies and international readers to get full and comprehensive picture about the lake’s fish resource and conservation problems. The Lake Tana watershed comprise 28 fish species, of which 21 are endemic. Moreover, Lake Tana is the one among the top 250 lake regions of global importance for biodiversity and it is world recognized migratory birds wintering site. Lake Tana together with its adjacent wetlands provide directly and indirectly a livelihood for more than 500,000 people. However, owing to anthropogenic activities, the lake ecosystem as well as fish and attributes of the fisheries sector are severely degraded. Fish species in Lake Tana are suffering due to illegal fishing, damming, habitat/breeding ground degradation, wastewater disposal, introduction of exotic species, and lack of implementing fisheries regulations. Currently, more than 98% of fishers in Lake Tana are using the most destructive monofilament. Indeed, dams, irrigation schemes and hydropower are constructed in response to the emerging development need only. Mitigation techniques such as construction of fish ladders for the migratory fishes are the most forgotten. In addition, water resource developers are likely unaware of both the importance of the fisheries and the impact of dam construction on fish. As a result, the biodiversity issue is often missed. Besides, Lake Tana wetlands, which play vital role to sustain biodiversity, are not wisely utilised in the sense of the Ramsar Convention’s definition. Wetlands are considered as unhealthy and hence wetland conversion for the purpose of recession agriculture is still seen as advanced mode of development. As a result, many wetlands in the lake watershed are shrinking drastically over time and Cyprus papyrus, one of the characteristic features of Lake Tana, has dramatically declined in its distribution with some local extinction. Furthermore, the recently introduced water hyacinth (Eichhornia crassipes) is creating immense problems on the lake ecosystem. Moreover, currently, 1.56 million tons of sediment have deposited into the lake each year and wastes from the industries and residents are directly discharged into the lake without treatment. Recently, sign of eutrophication is revealed in Lake Tana and most coarsely, the incidence of cyanobacteria genus Microcystis was reported from the Bahir Dar Gulf of Lake Tana. Thus, the direct dependency of the communities on the lake water for drinking as well as to wash their body and clothes and its fisheries make the problem worst. Indeed, since it is home to many endemic migratory fish, such kind of unregulated developmental activities could be detrimental to their stocks. This can be best illustrated by the drastic stock reduction (>75% in biomass) of the world unique Labeobarbus species. So, unless proper management is put in place, the anthropogenic impacts can jeopardize the aquatic ecosystems. Therefore, in order to sustainably use the aquatic resources and fulfil the needs of the local people, every developmental activity and resource utilization should be carried out adhering to the available policies.

Keywords: anthropogenic impacts, dams, endemic fish, wetland degradation

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286 Psychological Wellbeing, Lifestyle, and Negative and Positive Effects among Adults

Authors: Rahat Zaman

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The present study was conducted to investigate psychological well-being and positive and negative affect among adults. The sample comprised 221 adults; the sample was collected from all over Pakistan. Psychological well-being was measured with the help of the psychological well-being scale developed by Ryff and Keyes (1995). Lifestyle was measured with the help of the Health Promoting Lifestyle Profile Scale developed by Walker et al. (1995). Positive and negative effects were measured by PANAS, developed by Watson, Clark, and Tellegen (1998). To check the properties of scale, the alpha reliability coefficient was calculated. To test the hypotheses of the research, correlation, independent sample t-rest, and ANOVA were computed. It was hypothesized that there would be a positive relationship between psychological well-being and lifestyles and positive affect. The results show that psychological well-being, lifestyle, and positive affect are positively related. This also supports our hypothesis. The research also searched for relationships in the study variables according to the demographics of the sample. The respondents varied according to their dominant affect levels with respect to their psychological well-being and lifestyles. The research found significant differences for the genders in life appreciation, nutrition, and negative affect. Single and married individuals differed significantly on autonomy, environmental mastery, life appreciation, nutrition, and stress management. Individuals showed significant differences with respect to their living situation, joint and nuclear family members showed significant differences in personal growth, autonomy, health responsibilities, social support, physical activities, and stress management. The sample showed significant differences in environmental mastery, personal growth, purpose in life, life appreciation, health responsibilities, physical activities, stress management, and negative affect when divided in socioeconomic status. Age-wise analysis showed significant differences in autonomy, personal growth, purpose in life, life appreciation, nutrition, and stress management. Provincially significant differences were found in life appreciation, nutrition, social support, physical activities, and stress management, and both positive and negative effects were experienced. Implications of the results are discussed.

Keywords: wellbeing, healthy lifestyle, self acceptance, positive

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285 Adversarial Attacks and Defenses on Deep Neural Networks

Authors: Jonathan Sohn

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Deep neural networks (DNNs) have shown state-of-the-art performance for many applications, including computer vision, natural language processing, and speech recognition. Recently, adversarial attacks have been studied in the context of deep neural networks, which aim to alter the results of deep neural networks by modifying the inputs slightly. For example, an adversarial attack on a DNN used for object detection can cause the DNN to miss certain objects. As a result, the reliability of DNNs is undermined by their lack of robustness against adversarial attacks, raising concerns about their use in safety-critical applications such as autonomous driving. In this paper, we focus on studying the adversarial attacks and defenses on DNNs for image classification. There are two types of adversarial attacks studied which are fast gradient sign method (FGSM) attack and projected gradient descent (PGD) attack. A DNN forms decision boundaries that separate the input images into different categories. The adversarial attack slightly alters the image to move over the decision boundary, causing the DNN to misclassify the image. FGSM attack obtains the gradient with respect to the image and updates the image once based on the gradients to cross the decision boundary. PGD attack, instead of taking one big step, repeatedly modifies the input image with multiple small steps. There is also another type of attack called the target attack. This adversarial attack is designed to make the machine classify an image to a class chosen by the attacker. We can defend against adversarial attacks by incorporating adversarial examples in training. Specifically, instead of training the neural network with clean examples, we can explicitly let the neural network learn from the adversarial examples. In our experiments, the digit recognition accuracy on the MNIST dataset drops from 97.81% to 39.50% and 34.01% when the DNN is attacked by FGSM and PGD attacks, respectively. If we utilize FGSM training as a defense method, the classification accuracy greatly improves from 39.50% to 92.31% for FGSM attacks and from 34.01% to 75.63% for PGD attacks. To further improve the classification accuracy under adversarial attacks, we can also use a stronger PGD training method. PGD training improves the accuracy by 2.7% under FGSM attacks and 18.4% under PGD attacks over FGSM training. It is worth mentioning that both FGSM and PGD training do not affect the accuracy of clean images. In summary, we find that PGD attacks can greatly degrade the performance of DNNs, and PGD training is a very effective way to defend against such attacks. PGD attacks and defence are overall significantly more effective than FGSM methods.

Keywords: deep neural network, adversarial attack, adversarial defense, adversarial machine learning

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284 Using Rainfall Simulators to Design and Assess the Post-Mining Erosional Stability

Authors: Ashraf M. Khalifa, Hwat Bing So, Greg Maddocks

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Changes to the mining environmental approvals process in Queensland have been rolled out under the MERFP Act (2018). This includes requirements for a Progressive Rehabilitation and Closure Plan (PRC Plan). Key considerations of the landform design report within the PRC Plan must include: (i) identification of materials available for landform rehabilitation, including their ability to achieve the required landform design outcomes, (ii) erosion assessments to determine landform heights, gradients, profiles, and material placement, (iii) slope profile design considering the interactions between soil erodibility, rainfall erosivity, landform height, gradient, and vegetation cover to identify acceptable erosion rates over a long-term average, (iv) an analysis of future stability based on the factors described above e.g., erosion and /or landform evolution modelling. ACARP funded an extensive and thorough erosion assessment program using rainfall simulators from 1998 to 2010. The ACARP program included laboratory assessment of 35 soil and spoil samples from 16 coal mines and samples from a gold mine in Queensland using 3 x 0.8 m laboratory rainfall simulator. The reliability of the laboratory rainfall simulator was verified through field measurements using larger flumes 20 x 5 meters and catchment scale measurements at three sites (3 different catchments, average area of 2.5 ha each). Soil cover systems are a primary component of a constructed mine landform. The primary functions of a soil cover system are to sustain vegetation and limit the infiltration of water and oxygen into underlying reactive mine waste. If the external surface of the landform erodes, the functions of the cover system cannot be maintained, and the cover system will most likely fail. Assessing a constructed landform’s potential ‘long-term’ erosion stability requires defensible erosion rate thresholds below which rehabilitation landform designs are considered acceptably erosion-resistant or ‘stable’. The process used to quantify erosion rates using rainfall simulators (flumes) to measure rill and inter-rill erosion on bulk samples under laboratory conditions or on in-situ material under field conditions will be explained.

Keywords: open-cut, mining, erosion, rainfall simulator

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283 Realistic Modeling of the Preclinical Small Animal Using Commercial Software

Authors: Su Chul Han, Seungwoo Park

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As the increasing incidence of cancer, the technology and modality of radiotherapy have advanced and the importance of preclinical model is increasing in the cancer research. Furthermore, the small animal dosimetry is an essential part of the evaluation of the relationship between the absorbed dose in preclinical small animal and biological effect in preclinical study. In this study, we carried out realistic modeling of the preclinical small animal phantom possible to verify irradiated dose using commercial software. The small animal phantom was modeling from 4D Digital Mouse whole body phantom. To manipulate Moby phantom in commercial software (Mimics, Materialise, Leuven, Belgium), we converted Moby phantom to DICOM image file of CT by Matlab and two- dimensional of CT images were converted to the three-dimensional image and it is possible to segment and crop CT image in Sagittal, Coronal and axial view). The CT images of small animals were modeling following process. Based on the profile line value, the thresholding was carried out to make a mask that was connection of all the regions of the equal threshold range. Using thresholding method, we segmented into three part (bone, body (tissue). lung), to separate neighboring pixels between lung and body (tissue), we used region growing function of Mimics software. We acquired 3D object by 3D calculation in the segmented images. The generated 3D object was smoothing by remeshing operation and smoothing operation factor was 0.4, iteration value was 5. The edge mode was selected to perform triangle reduction. The parameters were that tolerance (0.1mm), edge angle (15 degrees) and the number of iteration (5). The image processing 3D object file was converted to an STL file to output with 3D printer. We modified 3D small animal file using 3- Matic research (Materialise, Leuven, Belgium) to make space for radiation dosimetry chips. We acquired 3D object of realistic small animal phantom. The width of small animal phantom was 2.631 cm, thickness was 2.361 cm, and length was 10.817. Mimics software supported efficiency about 3D object generation and usability of conversion to STL file for user. The development of small preclinical animal phantom would increase reliability of verification of absorbed dose in small animal for preclinical study.

Keywords: mimics, preclinical small animal, segmentation, 3D printer

Procedia PDF Downloads 343
282 Hidro-IA: An Artificial Intelligent Tool Applied to Optimize the Operation Planning of Hydrothermal Systems with Historical Streamflow

Authors: Thiago Ribeiro de Alencar, Jacyro Gramulia Junior, Patricia Teixeira Leite

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The area of the electricity sector that deals with energy needs by the hydroelectric in a coordinated manner is called Operation Planning of Hydrothermal Power Systems (OPHPS). The purpose of this is to find a political operative to provide electrical power to the system in a given period, with reliability and minimal cost. Therefore, it is necessary to determine an optimal schedule of generation for each hydroelectric, each range, so that the system meets the demand reliably, avoiding rationing in years of severe drought, and that minimizes the expected cost of operation during the planning, defining an appropriate strategy for thermal complementation. Several optimization algorithms specifically applied to this problem have been developed and are used. Although providing solutions to various problems encountered, these algorithms have some weaknesses, difficulties in convergence, simplification of the original formulation of the problem, or owing to the complexity of the objective function. An alternative to these challenges is the development of techniques for simulation optimization and more sophisticated and reliable, it can assist the planning of the operation. Thus, this paper presents the development of a computational tool, namely Hydro-IA for solving optimization problem identified and to provide the User an easy handling. Adopted as intelligent optimization technique is Genetic Algorithm (GA) and programming language is Java. First made the modeling of the chromosomes, then implemented the function assessment of the problem and the operators involved, and finally the drafting of the graphical interfaces for access to the User. The results with the Genetic Algorithms were compared with the optimization technique nonlinear programming (NLP). Tests were conducted with seven hydroelectric plants interconnected hydraulically with historical stream flow from 1953 to 1955. The results of comparison between the GA and NLP techniques shows that the cost of operating the GA becomes increasingly smaller than the NLP when the number of hydroelectric plants interconnected increases. The program has managed to relate a coherent performance in problem resolution without the need for simplification of the calculations together with the ease of manipulating the parameters of simulation and visualization of output results.

Keywords: energy, optimization, hydrothermal power systems, artificial intelligence and genetic algorithms

Procedia PDF Downloads 394
281 Effects of Group Cognitive Restructuring and Rational Emotive Behavioral Therapy on Psychological Distress of Awaiting-Trial Inmates in Correctional Centers in North-West, Nigeria

Authors: Muhammad Shafi’U Adamu

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This study examined the effects of two groups of Cognitive Behavioral Therapies (CBT) which, includes Cognitive Restructuring (CB) and Rational Emotive Behavioral Therapy (REBT), on the Psychological Distress of awaiting-trial Inmates in Correctional Centers in North-West Nigeria. The study had four specific objectives, four research questions, and four null hypotheses. The study used a quasi-experimental design that involved pre-test and post-test. The population comprised of all 7,962 awaiting-trial inmates in correctional centers in North-west Nigeria. 131 awaiting trial inmates from three intact Correctional Centers were randomly selected using the census technique. The respondents were sampled and randomly put into 3 groups (CR, REBT and Control). Kessler Psychological Distress Scale (K10) was adapted for data collection in the study. The instrument was validated by experts and subjected to a pilot study using Cronbach's Alpha with a reliability coefficient of 0.772. Each group received treatment for 8 consecutive weeks (60 minutes/week). Data collected from the field were subjected to descriptive statistics of mean, standard deviation and mean difference to answer the research questions. Inferential statistics of ANOVA and independent sample t-test were used to test the null hypotheses at P≤ 0.05 level of significance. Results in the study revealed that there was no significant difference among the pre-treatment mean scores of experimental and control groups. Statistical evidence also showed a significant difference among the mean scores of the three groups, and thus, results of the Post Hoc multiple-comparison test indicated the posttreatment reduction of psychological distress in the awaiting-trial inmates. Documented output also showed a significant difference between the post-treatment psychologically distressed mean scores of male and female awaiting-trial inmates, but there was no difference in those exposed to REBT. The research recommends that a standardized structured CBT counseling technique treatment should be designed for correctional centers across Nigeria, and CBT counseling techniques could be used in the treatment of PD in both correctional and clinical settings.

Keywords: awaiting-trial inmates, cognitive restructuring, correctional centers, rational emotive behavioral therapy

Procedia PDF Downloads 48
280 The Interactive Effects among Supervisor Support, Academic Emotion, and Positive Mental Health: An Evidence Based on Longitudinal Cross-Lagged Panel Data Analysis on Postgraduates in China

Authors: Jianzhou Ni, Hua Fan

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It has been determined that supervisor support has a major influence on postgraduate students' academic emotions and is considered a method of successfully anticipating postgraduates' good psychological well-being levels. As a result, by assessing the mediating influence upon academic emotions for contemporary postgraduates in China, this study investigated the tight reciprocal relationship between psychological empowerment and positive mental well-being among postgraduates. To that end, a help enables a theoretical analysis of role clarity, academic emotion, and positive psychological health was developed, and its validity and reliability were demonstrated for the first time using the normalized postgrad relationship with supervisor scale, academic emotion scale, and positive mental scale, as well as questionnaire data from Chinese postgraduate students. This study used the cross-lagged (ARCL) panel model data to longitudinally measure 798 valid data from two survey questions polls taken in 2019 (T1) and 2021 (T2) to investigate the link between supervisor support and positive graduate student mental well-being in a bidirectional relationship of influence. The study discovered that mentor assistance could have a considerable beneficial impact on graduate students' academic emotions and, as a result, indirectly help learners attain positive mental health development. This verifies the theoretical premise that academic emotions partially mediate the effect of mentor support on positive mental health development and argues for the coexistence of the two. The outcomes of this study can help researchers gain a better knowledge of the dynamic interplay among three different research variables: supervisor support, academic emotions, and positive mental health, as well as fill gaps in previous research. In this regard, the study indicated that mentor assistance directly stimulates students' academic drive and assists graduate students in developing good academic emotions, which contributes to the development of positive mental health. However, given the restricted measurement time in this study's cross-lagged panel data and the potential effect of moderating effects other than academic mood on graduate students' good mental health, the results of this study need to be more fully understood and validated.

Keywords: supervisor support, academic emotions, positive mental health, interaction effects, longitudinal cross-lagged measurements

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279 Analysis of Constraints and Opportunities in Dairy Production in Botswana

Authors: Som Pal Baliyan

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Dairy enterprise has been a major source of employment and income generation in most of the economies worldwide. Botswana government has also identified dairy as one of the agricultural sectors towards diversification of the mineral dependent economy of the country. The huge gap between local demand and supply of milk and milk products indicated that there are not only constraints but also; opportunities exist in this sub sector of agriculture. Therefore, this study was an attempt to identify constraints and opportunities in dairy production industry in Botswana. The possible ways to mitigate the constraints were also identified. The findings should assist the stakeholders especially, policy makers in the formulation of effective policies for the growth of dairy sector in the country. This quantitative study adopted a survey research design. A final survey followed by a pilot survey was conducted for data collection. The purpose of the pilot survey was to collect basic information on the nature and extent of the constraints, opportunities and ways to mitigate the constraints in dairy production. Based on the information from pilot survey, a four point Likert’s scale type questionnaire was constructed, validated and tested for its reliability. The data for the final survey were collected from purposively selected twenty five dairy farms. The descriptive statistical tools were employed to analyze data. Among the twelve constraints identified; high feed costs, feed shortage and availability, lack of technical support, lack of skilled manpower, high prevalence of pests and diseases and, lack of dairy related technologies were the six major constraints in dairy production. Grain feed production, roughage feed production, manufacturing of dairy feed, establishment of milk processing industry and, development of transportation systems were the five major opportunities among the eight opportunities identified. Increasing production of animal feed locally, increasing roughage feed production locally, provision of subsidy on animal feed, easy access to sufficient financial support, training of the farmers and, effective control of pests and diseases were identified as the six major ways to mitigate the constraints. It was recommended that the identified constraints and opportunities as well as the ways to mitigate the constraints need to be carefully considered by the stakeholders especially, policy makers during the formulation and implementation of the policies for the development of dairy sector in Botswana.

Keywords: dairy enterprise, milk production, opportunities, production constraints

Procedia PDF Downloads 366
278 Process Modeling in an Aeronautics Context

Authors: Sophie Lemoussu, Jean-Charles Chaudemar, Robertus A. Vingerhoeds

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Many innovative projects exist in the field of aeronautics, each addressing specific areas so to reduce weight, increase autonomy, reduction of CO2, etc. In many cases, such innovative developments are being carried out by very small enterprises (VSE’s) or small and medium sized-enterprises (SME’s). A good example concerns airships that are being studied as a real alternative to passenger and cargo transportation. Today, no international regulations propose a precise and sufficiently detailed framework for the development and certification of airships. The absence of such a regulatory framework requires a very close contact with regulatory instances. However, VSE’s/SME’s do not always have sufficient resources and internal knowledge to handle this complexity and to discuss these issues. This poses an additional challenge for those VSE’s/SME’s, in particular those that have system integration responsibilities and that must provide all the necessary evidence to demonstrate their ability to design, produce, and operate airships with the expected level of safety and reliability. The main objective of this research is to provide a methodological framework enabling VSE’s/SME’s with limited resources to organize the development of airships while taking into account the constraints of safety, cost, time and performance. This paper proposes to provide a contribution to this problematic by proposing a Model-Based Systems Engineering approach. Through a comprehensive process modeling approach applied to the development processes, the regulatory constraints, existing best practices, etc., a good image can be obtained as to the process landscape that may influence the development of airships. To this effect, not only the necessary regulatory information is taken on board, also other international standards and norms on systems engineering and project management are being modeled and taken into account. In a next step, the model can be used for analysis of the specific situation for given developments, derive critical paths for the development, identify eventual conflicting aspects between the norms, standards, and regulatory expectations, or also identify those areas where not enough information is available. Once critical paths are known, optimization approaches can be used and decision support techniques can be applied so to better support VSE’s/SME’s in their innovative developments. This paper reports on the adopted modeling approach, the retained modeling languages, and how they all fit together.

Keywords: aeronautics, certification, process modeling, project management, regulation, SME, systems engineering, VSE

Procedia PDF Downloads 136
277 Effects of Mental Skill Training Programme on Direct Free Kick of Grassroot Footballers in Lagos, Nigeria

Authors: Mayowa Adeyeye, Kehinde Adeyemo

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The direct free kick is considered a great opportunity to score a goal but this is not always the case amidst Nigerian and other elite footballers. This study, therefore, examined the extent to which an 8 weeks mental skill training programme is effective for improving accuracy in direct free kick in football. Sixty (n-60) students of Pepsi Football Academy participated in the study. They were randomly distributed into two groups of positive self-talk group (intervention n-30) and control group (n-30). The instrument used in the collection of data include a standard football goal post while the research materials include a dummy soccer wall, a cord, an improvised vanishing spray, a clipboard, writing materials, a recording sheet, a self-talk log book, six standard 5 football, cones, an audiotape and a compact disc. The Weinberge and Gould (2011) mental skills training manual was used. The reliability coefficient of the apparatus following a pilot study stood at 0.72. Before the commencement of the mental skills training programme, the participants were asked to take six simulated direct free kick. At the end of each physical skills training session after the pre-test, the researcher spent at least 15 minutes with the groups exposing them to the intervention. The mental skills training programme alongside physical skills training took place in two different locations for the different groups under study, these included Agege Stadium Main bowl Football Pitch (Imagery Group), and Ogba Ijaye (Control Group). The mental skills training programme lasted for eight weeks. After the completion of the mental skills training programme, all the participants were asked to take another six simulated direct free kick attempts using the same field used for the pre-test to determine the efficacy of the treatments. The pre-test and post-test data were analysed using inferential statistics of t-test, while the alpha level was set at 0.05. The result revealed significant differences in t-test for positive self-talk and control group. Based on the findings, it is recommended that athletes should be exposed to positive self-talk alongside their normal physical skills training for quality delivery of accurate direct free kick during training and competition.

Keywords: accuracy, direct free kick, pepsi football academy, positive self-talk

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276 Multi-Scale Damage Modelling for Microstructure Dependent Short Fiber Reinforced Composite Structure Design

Authors: Joseph Fitoussi, Mohammadali Shirinbayan, Abbas Tcharkhtchi

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Due to material flow during processing, short fiber reinforced composites structures obtained by injection or compression molding generally present strong spatial microstructure variation. On the other hand, quasi-static, dynamic, and fatigue behavior of these materials are highly dependent on microstructure parameters such as fiber orientation distribution. Indeed, because of complex damage mechanisms, SFRC structures design is a key challenge for safety and reliability. In this paper, we propose a micromechanical model allowing prediction of damage behavior of real structures as a function of microstructure spatial distribution. To this aim, a statistical damage criterion including strain rate and fatigue effect at the local scale is introduced into a Mori and Tanaka model. A critical local damage state is identified, allowing fatigue life prediction. Moreover, the multi-scale model is coupled with an experimental intrinsic link between damage under monotonic loading and fatigue life in order to build an abacus giving Tsai-Wu failure criterion parameters as a function of microstructure and targeted fatigue life. On the other hand, the micromechanical damage model gives access to the evolution of the anisotropic stiffness tensor of SFRC submitted to complex thermomechanical loading, including quasi-static, dynamic, and cyclic loading with temperature and amplitude variations. Then, the latter is used to fill out microstructure dependent material cards in finite element analysis for design optimization in the case of complex loading history. The proposed methodology is illustrated in the case of a real automotive component made of sheet molding compound (PSA 3008 tailgate). The obtained results emphasize how the proposed micromechanical methodology opens a new path for the automotive industry to lighten vehicle bodies and thereby save energy and reduce gas emission.

Keywords: short fiber reinforced composite, structural design, damage, micromechanical modelling, fatigue, strain rate effect

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275 Shoulder Range of Motion Measurements using Computer Vision Compared to Hand-Held Goniometric Measurements

Authors: Lakshmi Sujeesh, Aaron Ramzeen, Ricky Ziming Guo, Abhishek Agrawal

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Introduction: Range of motion (ROM) is often measured by physiotherapists using hand-held goniometer as part of mobility assessment for diagnosis. Due to the nature of hand-held goniometer measurement procedure, readings often tend to have some variations depending on the physical therapist taking the measurements (Riddle et al.). This study aims to validate computer vision software readings against goniometric measurements for quick and consistent ROM measurements to be taken by clinicians. The use of this computer vision software hopes to improve the future of musculoskeletal space with more efficient diagnosis from recording of patient’s ROM with minimal human error across different physical therapists. Methods: Using the hand-held long arm goniometer measurements as the “gold-standard”, healthy study participants (n = 20) were made to perform 4 exercises: Front elevation, Abduction, Internal Rotation, and External Rotation, using both arms. Assessment of active ROM using computer vision software at different angles set by goniometer for each exercise was done. Interclass Correlation Coefficient (ICC) using 2-way random effects model, Box-Whisker plots, and Root Mean Square error (RMSE) were used to find the degree of correlation and absolute error measured between set and recorded angles across the repeated trials by the same rater. Results: ICC (2,1) values for all 4 exercises are above 0.9, indicating excellent reliability. Lowest overall RMSE was for external rotation (5.67°) and highest for front elevation (8.00°). Box-whisker plots showed have showed that there is a potential zero error in the measurements done by the computer vision software for abduction, where absolute error for measurements taken at 0 degree are shifted away from the ideal 0 line, with its lowest recorded error being 8°. Conclusion: Our results indicate that the use of computer vision software is valid and reliable to use in clinical settings by physiotherapists for measuring shoulder ROM. Overall, computer vision helps improve accessibility to quality care provided for individual patients, with the ability to assess ROM for their condition at home throughout a full cycle of musculoskeletal care (American Academy of Orthopaedic Surgeons) without the need for a trained therapist.

Keywords: physiotherapy, frozen shoulder, joint range of motion, computer vision

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274 A Comparison of Inverse Simulation-Based Fault Detection in a Simple Robotic Rover with a Traditional Model-Based Method

Authors: Murray L. Ireland, Kevin J. Worrall, Rebecca Mackenzie, Thaleia Flessa, Euan McGookin, Douglas Thomson

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Robotic rovers which are designed to work in extra-terrestrial environments present a unique challenge in terms of the reliability and availability of systems throughout the mission. Should some fault occur, with the nearest human potentially millions of kilometres away, detection and identification of the fault must be performed solely by the robot and its subsystems. Faults in the system sensors are relatively straightforward to detect, through the residuals produced by comparison of the system output with that of a simple model. However, faults in the input, that is, the actuators of the system, are harder to detect. A step change in the input signal, caused potentially by the loss of an actuator, can propagate through the system, resulting in complex residuals in multiple outputs. These residuals can be difficult to isolate or distinguish from residuals caused by environmental disturbances. While a more complex fault detection method or additional sensors could be used to solve these issues, an alternative is presented here. Using inverse simulation (InvSim), the inputs and outputs of the mathematical model of the rover system are reversed. Thus, for a desired trajectory, the corresponding actuator inputs are obtained. A step fault near the input then manifests itself as a step change in the residual between the system inputs and the input trajectory obtained through inverse simulation. This approach avoids the need for additional hardware on a mass- and power-critical system such as the rover. The InvSim fault detection method is applied to a simple four-wheeled rover in simulation. Additive system faults and an external disturbance force and are applied to the vehicle in turn, such that the dynamic response and sensor output of the rover are impacted. Basic model-based fault detection is then employed to provide output residuals which may be analysed to provide information on the fault/disturbance. InvSim-based fault detection is then employed, similarly providing input residuals which provide further information on the fault/disturbance. The input residuals are shown to provide clearer information on the location and magnitude of an input fault than the output residuals. Additionally, they can allow faults to be more clearly discriminated from environmental disturbances.

Keywords: fault detection, ground robot, inverse simulation, rover

Procedia PDF Downloads 279
273 Forced-Choice Measurement Models of Behavioural, Social, and Emotional Skills: Theory, Research, and Development

Authors: Richard Roberts, Anna Kravtcova

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Introduction: The realisation that personality can change over the course of a lifetime has led to a new companion model to the Big Five, the behavioural, emotional, and social skills approach (BESSA). BESSA hypothesizes that this set of skills represents how the individual is thinking, feeling, and behaving when the situation calls for it, as opposed to traits, which represent how someone tends to think, feel, and behave averaged across situations. The five major skill domains share parallels with the Big Five Factor (BFF) model creativity and innovation (openness), self-management (conscientiousness), social engagement (extraversion), cooperation (agreeableness), and emotional resilience (emotional stability) skills. We point to noteworthy limitations in the current operationalisation of BESSA skills (i.e., via Likert-type items) and offer up a different measurement approach: forced choice. Method: In this forced-choice paradigm, individuals were given three skill items (e.g., managing my time) and asked to select one response they believed they were “worst at” and “best at”. The Thurstonian IRT models allow these to be placed on a normative scale. Two multivariate studies (N = 1178) were conducted with a 22-item forced-choice version of the BESSA, a published measure of the BFF, and various criteria. Findings: Confirmatory factor analysis of the forced-choice assessment showed acceptable model fit (RMSEA<0.06), while reliability estimates were reasonable (around 0.70 for each construct). Convergent validity evidence was as predicted (correlations between 0.40 and 0.60 for corresponding BFF and BESSA constructs). Notable was the extent the forced-choice BESSA assessment improved upon test-criterion relationships over and above the BFF. For example, typical regression models find BFF personality accounting for 25% of the variance in life satisfaction scores; both studies showed incremental gains over the BFF exceeding 6% (i.e., BFF and BESSA together accounted for over 31% of the variance in both studies). Discussion: Forced-choice measurement models offer up the promise of creating equated test forms that may unequivocally measure skill gains and are less prone to fakability and reference bias effects. Implications for practitioners are discussed, especially those interested in selection, succession planning, and training and development. We also discuss how the forced choice method can be applied to other constructs like emotional immunity, cross-cultural competence, and self-estimates of cognitive ability.

Keywords: Big Five, forced-choice method, BFF, methods of measurements

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272 Accurate Mass Segmentation Using U-Net Deep Learning Architecture for Improved Cancer Detection

Authors: Ali Hamza

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Accurate segmentation of breast ultrasound images is of paramount importance in enhancing the diagnostic capabilities of breast cancer detection. This study presents an approach utilizing the U-Net architecture for segmenting breast ultrasound images aimed at improving the accuracy and reliability of mass identification within the breast tissue. The proposed method encompasses a multi-stage process. Initially, preprocessing techniques are employed to refine image quality and diminish noise interference. Subsequently, the U-Net architecture, a deep learning convolutional neural network (CNN), is employed for pixel-wise segmentation of regions of interest corresponding to potential breast masses. The U-Net's distinctive architecture, characterized by a contracting and expansive pathway, enables accurate boundary delineation and detailed feature extraction. To evaluate the effectiveness of the proposed approach, an extensive dataset of breast ultrasound images is employed, encompassing diverse cases. Quantitative performance metrics such as the Dice coefficient, Jaccard index, sensitivity, specificity, and Hausdorff distance are employed to comprehensively assess the segmentation accuracy. Comparative analyses against traditional segmentation methods showcase the superiority of the U-Net architecture in capturing intricate details and accurately segmenting breast masses. The outcomes of this study emphasize the potential of the U-Net-based segmentation approach in bolstering breast ultrasound image analysis. The method's ability to reliably pinpoint mass boundaries holds promise for aiding radiologists in precise diagnosis and treatment planning. However, further validation and integration within clinical workflows are necessary to ascertain their practical clinical utility and facilitate seamless adoption by healthcare professionals. In conclusion, leveraging the U-Net architecture for breast ultrasound image segmentation showcases a robust framework that can significantly enhance diagnostic accuracy and advance the field of breast cancer detection. This approach represents a pivotal step towards empowering medical professionals with a more potent tool for early and accurate breast cancer diagnosis.

Keywords: mage segmentation, U-Net, deep learning, breast cancer detection, diagnostic accuracy, mass identification, convolutional neural network

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271 An Investigation of the Determinants of Discount Rate Manipulation in Swedish and Finnish Listed Companies

Authors: Fredrik Hartwig, Peter Lindberg

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In 2004, the International Accounting Standards Board (IASB) issued new accounting standards for impairment testing of goodwill. IFRS 3 Business Combinations and IAS 36 Impairment of Assets prohibited amortization of acquired goodwill and instead required companies to test goodwill for impairment annually or more often if necessary. The goodwill impairment test is based on management’s judgement and estimations, making the impairment-only-approach subjective and unreliable. Management can use the discretion opportunistically by managing goodwill impairments. The IASB’s remedy to the reliability problem has been to demand transparent financial reports. IAS 36 paragraph 134 requires detailed disclosures regarding the impairment test in order to make potentially unreasonable assumptions and estimations visible. The disclosure requirements should thus (in theory) make it more difficult for management to ‘choose’ assumptions and estimations that suit an agenda. Whether the requirement to disclose detailed disclosures regarding the impairment test leads to less opportunism is however an empirical question. This work analyses whether one of the required disclosures in IAS 36 paragraph 134, the reported discount rate, differs from an independently estimated risk-adjusted discount rate. Estimates of discount rates that are either lower or higher than the independently estimated discount rate are here defined as opportunism. In the former case - i.e. when the reported discount rate is lower - the objective may be to avoid profit reducing impairment charges. In the latter case - i.e. when the reported discount rate is higher - the objective may be to reduce profits or take ‘big baths’. This paper differs in one important respect from previous similar studies, the majority of which are based on purely descriptive statistics; we use multivariate regression analysis to analyze what factors affect deviations between disclosed discount rates and independently estimated discount rates. The sample consists of Swedish and Finnish listed companies. Swedish and Finnish listed companies are analysed since the accounting oversight bodies differ between the two countries. The results show that discount rate deviations in Swedish and Finnish listed companies are significantly related to accounting oversight, size and industry but not financial risk, business risk and goodwill intensity.

Keywords: discount rate, manipulation, goodwill impairment test, disclosures

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270 Safety Climate Assessment and Its Impact on the Productivity of Construction Enterprises

Authors: Krzysztof J. Czarnocki, F. Silveira, E. Czarnocka, K. Szaniawska

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Research background: Problems related to the occupational health and decreasing level of safety occur commonly in the construction industry. Important factor in the occupational safety in construction industry is scaffold use. All scaffolds used in construction, renovation, and demolition shall be erected, dismantled and maintained in accordance with safety procedure. Increasing demand for new construction projects unfortunately still is linked to high level of occupational accidents. Therefore, it is crucial to implement concrete actions while dealing with scaffolds and risk assessment in construction industry, the way on doing assessment and liability of assessment is critical for both construction workers and regulatory framework. Unfortunately, professionals, who tend to rely heavily on their own experience and knowledge when taking decisions regarding risk assessment, may show lack of reliability in checking the results of decisions taken. Purpose of the article: The aim was to indicate crucial parameters that could be modeling with Risk Assessment Model (RAM) use for improving both building enterprise productivity and/or developing potential and safety climate. The developed RAM could be a benefit for predicting high-risk construction activities and thus preventing accidents occurred based on a set of historical accident data. Methodology/Methods: A RAM has been developed for assessing risk levels as various construction process stages with various work trades impacting different spheres of enterprise activity. This project includes research carried out by teams of researchers on over 60 construction sites in Poland and Portugal, under which over 450 individual research cycles were carried out. The conducted research trials included variable conditions of employee exposure to harmful physical and chemical factors, variable levels of stress of employees and differences in behaviors and habits of staff. Genetic modeling tool has been used for developing the RAM. Findings and value added: Common types of trades, accidents, and accident causes have been explored, in addition to suitable risk assessment methods and criteria. We have found that the initial worker stress level is more direct predictor for developing the unsafe chain leading to the accident rather than the workload, or concentration of harmful factors at the workplace or even training frequency and management involvement.

Keywords: safety climate, occupational health, civil engineering, productivity

Procedia PDF Downloads 287
269 Modeling and Simulation of Primary Atomization and Its Effects on Internal Flow Dynamics in a High Torque Low Speed Diesel Engine

Authors: Muteeb Ulhaq, Rizwan Latif, Sayed Adnan Qasim, Imran Shafi

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Diesel engines are most efficient and reliable in terms of efficiency, reliability and adaptability. Most of the research and development up till now have been directed towards High-Speed Diesel Engine, for Commercial use. In these engines objective is to optimize maximum acceleration by reducing exhaust emission to meet international standards. In high torque low-speed engines the requirement is altogether different. These types of Engines are mostly used in Maritime Industry, Agriculture industry, Static Engines Compressors Engines etc. Unfortunately due to lack of research and development, these engines have low efficiency and high soot emissions and one of the most effective way to overcome these issues is by efficient combustion in an engine cylinder, the fuel spray atomization process plays a vital role in defining mixture formation, fuel consumption, combustion efficiency and soot emissions. Therefore, a comprehensive understanding of the fuel spray characteristics and atomization process is of a great importance. In this research, we will examine the effects of primary breakup modeling on the spray characteristics under diesel engine conditions. KH-ACT model is applied to cater the effect of aerodynamics in an engine cylinder and also cavitations and turbulence generated inside the injector. It is a modified form of most commonly used KH model, which considers only the aerodynamically induced breakup based on the Kelvin–Helmholtz instability. Our model is extensively evaluated by performing 3-D time-dependent simulations on Open FOAM, which is an open source flow solver. Spray characteristics like Spray Penetration, Liquid length, Spray cone angle and Souter mean diameter (SMD) were validated by comparing the results of Open Foam and Matlab. Including the effects of cavitation and turbulence enhances primary breakup, leading to smaller droplet sizes, decrease in liquid penetration, and increase in the radial dispersion of spray. All these properties favor early evaporation of fuel which enhances Engine efficiency.

Keywords: Kelvin–Helmholtz instability, open foam, primary breakup, souter mean diameter, turbulence

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268 Sustainable Crop Production: Greenhouse Gas Management in Farm Value Chain

Authors: Aswathaman Vijayan, Manish Jha, Ullas Theertha

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Climate change and Global warming have become an issue for both developed and developing countries and perhaps the biggest threat to the environment. We at ITC Limited believe that a company’s performance must be measured by its Triple Bottom Line contribution to building economic, social and environmental capital. This Triple Bottom Line strategy focuses on - Embedding sustainability in business practices, Investing in social development and Adopting a low carbon growth path with a cleaner environment approach. The Agri Business Division - ILTD operates in the tobacco crop growing regions of Andhra Pradesh and Karnataka province of India. The Agri value chain of the company comprises of two distinct phases: First phase is Agricultural operations undertaken by ITC trained farmers and the second phase is Industrial operations which include marketing and processing of the agricultural produce. This research work covers the Greenhouse Gas (GHG) management strategy of ITC in the Agricultural operations undertaken by the farmers. The agriculture sector adds considerably to global GHG emissions through the use of carbon-based energies, use of fertilizers and other farming operations such as ploughing. In order to minimize the impact of farming operations on the environment, ITC has a taken a big leap in implementing system and process in reducing the GHG impact in farm value chain by partnering with the farming community. The company has undertaken a unique three-pronged approach for GHG management at the farm value chain: 1) GHG inventory at farm value chain: Different sources of GHG emission in the farm value chain were identified and quantified for the baseline year, as per the IPCC guidelines for greenhouse gas inventories. The major sources of emission identified are - emission due to nitrogenous fertilizer application during seedling production and main-field; emission due to diesel usage for farm machinery; emission due to fuel consumption and due to burning of crop residues. 2) Identification and implementation of technologies to reduce GHG emission: Various methodologies and technologies were identified for each GHG emission source and implemented at farm level. The identified methodologies are – reducing the consumption of chemical fertilizer usage at the farm through site-specific nutrient recommendation; Usage of sharp shovel for land preparation to reduce diesel consumption; implementation of energy conservation technologies to reduce fuel requirement and avoiding burning of crop residue by incorporation in the main field. These identified methodologies were implemented at farm level, and the GHG emission was quantified to understand the reduction in GHG emission. 3) Social and farm forestry for CO2 sequestration: In addition, the company encouraged social and farm forestry in the waste lands to convert it into green cover. The plantations are carried out with fast growing trees viz., Eucalyptus, Casuarina, and Subabul at the rate of 10,000 Ha of land per year. The above approach minimized considerable amount of GHG emission at the farm value chain benefiting farmers, community, and environment at a whole. In addition, the CO₂ stock created by social and farm forestry program has made the farm value chain to become environment-friendly.

Keywords: CO₂ sequestration, farm value chain, greenhouse gas, ITC limited

Procedia PDF Downloads 273