Search results for: eye vision assessment

Authors: E. Akpinar, A. Erol, M.F. Cakir

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Precast reinforced concrete (RC) structures are excellent alternatives for construction world all over the globe, thanks to their rapid erection phase, ease mounting process, better quality and reasonable prices. Such structures are rather popular for industrial buildings. For the sake of economic importance of such industrial buildings as well as significance of safety, like every other type of structures, performance assessment and structural risk analysis are important. Fragility curves are powerful tools for damage projection and assessment for any sort of building as well as precast structures. In this study, a comparative review of current knowledge on fragility analysis of industrial precast RC structures were presented and findings in previous studies were compiled. Effects of different structural variables, parameters and building geometries as well as soil conditions on fragility analysis of precast structures are reviewed. It was aimed to briefly present the information in the literature about the procedure of damage probability prediction including fragility curves for such industrial facilities. It is found that determination of the aforementioned structural parameters as well as selecting analysis procedure are critically important for damage prediction of industrial precast RC structures using fragility curves.

Keywords: damage prediction, fragility curve, industrial buildings, precast reinforced concrete structures

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Authors: Prodipta Bhowmik, Poulami Saha, Preety Mehra, Yogesh Soni, Triloki Nath Jha

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In India, the smart city concept is growing day by day. So, for smart city development, a better traffic management and monitoring system is a very important requirement. Nowadays, road accidents increase due to more vehicles on the road. Reckless driving is mainly responsible for a huge number of accidents. So, an efficient traffic management system is required for all kinds of roads to control the traffic speed. The speed limit varies from road to road basis. Previously, there was a radar system but due to high cost and less precision, the radar system is unable to become favorable in a traffic management system. Traffic management system faces different types of problems every day and it has become a researchable topic on how to solve this problem. This paper proposed a computer vision and machine learning-based automated system for multiple vehicle detection, tracking, and speed estimation of vehicles using image processing. Detection of vehicles and estimating their speed from a real-time video is tough work to do. The objective of this paper is to detect vehicles and estimate their speed as accurately as possible. So for this, a real-time video is first captured, then the frames are extracted from that video, then from that frames, the vehicles are detected, and thereafter, the tracking of vehicles starts, and finally, the speed of the moving vehicles is estimated. The goal of this method is to develop a cost-friendly system that can able to detect multiple types of vehicles at the same time.

Keywords: OpenCV, Haar Cascade classifier, DLIB, YOLOV3, centroid tracker, vehicle detection, vehicle tracking, vehicle speed estimation, computer vision

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Authors: Abeer K. Jameel, Harry Evdorides

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The Assessment of the road safety performance is a challengeable issue. This is not only because of the ineffective and unreliability of road and traffic crash data system but also because of its systematic character. Recent strategic plans and interventions implemented in some of the developed countries where a significant decline in the rate of traffic and road crashes considers that the road safety is a system. This system consists of four main elements which are: road user, road infrastructure, vehicles and speed in addition to other supporting elements such as the institutional framework and post-crash care system. To assess the performance of a system, it is required to assess all its elements. To present an understandable results of the assessment, it is required to present a unique term representing the performance of the overall system. This paper aims to develop an overall performance indicator which may be used to assess the road safety system. The variables of this indicators are the main elements of the road safety system. The data regarding these variables will be collected from the World Health Organization report. Multi-criteria analysis method is used to aggregate the four sub-indicators for the four variables. Two weighting methods will be assumed, equal weights and different weights. For the different weights method, the factor analysis method is used. The weights then will be converting to scores. The total score will be the overall indicator for the road safety performance in a national scale. This indicator will be used to compare and rank countries according to their road safety performance indicator. The country with the higher score is the country which provides most sustainable and effective interventions for successful road safety system. These indicator will be tested by comparing them with the aggregate real crash rate for each country.

Keywords: factor analysis, Multi-criteria analysis, road safety assessment, safe system indicator

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Authors: Pawel Kiper, Alfonc Baba, Mahmoud Alhelou, Giorgia Pregnolato, Michela Agostini, Andrea Turolla

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Impairment of cervical spine mobility is often related to pain triggered by musculoskeletal disorders or direct traumatic injuries of the spine. To date, these disorders are assessed with goniometers and inclinometers, which are the most popular devices used in clinical settings. Nevertheless, these technologies usually allow measurement of no more than two-dimensional range of motion (ROM) quotes in static conditions. Conversely, the wide use of motion tracking systems able to measure 3 to 6 degrees of freedom dynamically, while performing standard ROM assessment, are limited due to technical complexities in preparing the setup and high costs. Thus, motion tracking systems are primarily used in research. These systems are an integral part of virtual reality (VR) technologies, which can be used for measuring spine mobility. To our knowledge, the accuracy of VR measure has not yet been studied within virtual environments. Thus, the aim of this study was to test the reliability of a protocol for the assessment of sensorimotor function of the cervical spine in a population of healthy subjects and to compare whether using immersive or non-immersive VR for visualization affects the performance. Both VR assessments consisted of the same five exercises and random sequence determined which of the environments (i.e. immersive or non-immersive) was used as first assessment. Subjects were asked to perform head rotation (right and left), flexion, extension and lateral flexion (right and left side bending). Each movement was executed five times. Moreover, the participants were invited to perform head reaching movements i.e. head movements toward 8 targets placed along a circular perimeter each 45°, visualized one-by-one in random order. Finally, head repositioning movement was obtained by head movement toward the same 8 targets as for reaching and following reposition to the start point. Thus, each participant performed 46 tasks during assessment. Main measures were: ROM of rotation, flexion, extension, lateral flexion and complete kinematics of the cervical spine (i.e. number of completed targets, time of execution (seconds), spatial length (cm), angle distance (°), jerk). Thirty-five healthy participants (i.e. 14 males and 21 females, mean age 28.4±6.47) were recruited for the cervical spine assessment with immersive and non-immersive VR environments. Comparison analysis demonstrated that: head right rotation (p=0.027), extension (p=0.047), flexion (p=0.000), time (p=0.001), spatial length (p=0.004), jerk target (p=0.032), trajectory repositioning (p=0.003), and jerk target repositioning (p=0.007) were significantly better in immersive than non-immersive VR. A regression model showed that assessment in immersive VR was influenced by height, trajectory repositioning (p<0.05), and handedness (p<0.05), whereas in non-immersive VR performance was influenced by height, jerk target (p=0.002), head extension, jerk target repositioning (p=0.002), and by age, head flex/ext, trajectory repositioning, and weight (p=0.040). The results of this study showed higher accuracy of cervical spine assessment when executed in immersive VR. The assessment of ROM and kinematics of the cervical spine can be affected by independent and dependent variables in both immersive and non-immersive VR settings.

Keywords: virtual reality, cervical spine, motion analysis, range of motion, measurement validity

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Authors: Jigg L. Pelayo, Ricardo G. Villar, Einstine M. Opiso

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The advances of aerial laser scanning in the Philippines has open-up entire fields of research in remote sensing and machine vision aspire to provide accurate timely information for the government and the public. Rapid mapping of polygonal roads and roof boundaries is one of its utilization offering application to disaster risk reduction, mitigation and development. The study uses low density LiDAR data and high resolution aerial imagery through object-oriented approach considering the theoretical concept of data analysis subjected to machine learning algorithm in minimizing the constraints of feature extraction. Since separating one class from another in distinct regions of a multi-dimensional feature-space, non-trivial computing for fitting distribution were implemented to formulate the learned ideal hyperplane. Generating customized hybrid feature which were then used in improving the classifier findings. Supplemental algorithms for filtering and reshaping object features are develop in the rule set for enhancing the final product. Several advantages in terms of simplicity, applicability, and process transferability is noticeable in the methodology. The algorithm was tested in the different random locations of Misamis Oriental province in the Philippines demonstrating robust performance in the overall accuracy with greater than 89% and potential to semi-automation. The extracted results will become a vital requirement for decision makers, urban planners and even the commercial sector in various assessment processes.

Keywords: feature extraction, machine learning, OBIA, remote sensing

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Authors: Agnese Natali, Francesco Morelli, Walter Salvatore

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Automated Rack Supported Warehouses (ARSWs) are structures currently designed as steel racks. Even if there are common characteristics, there are differences that don’t allow to adopt the same design approach. Aiming to highlight the factors influencing the design and the behavior of ARSWs, a set of 5 structures designed by 5 European companies specialized in this field is used to perform both a critical analysis of the design approaches and the assessment of the seismic performance, which is used to point out the criticalities and the necessity of new design philosophy.

Keywords: steel racks, automated rack supported warehouse, thin walled cold-formed elements, seismic assessment

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Authors: Rachelle McFarlane

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The Second Decade of Action Road Safety has begun with increased focus on countries who are disproportionately affected by road fatalities. Researchers highlight the low effectiveness of road safety campaigns in Latin America and the Caribbean (LAC) still reporting approximately 130,000 deaths and six million injuries annually. The regional fatality rate 19.2 per 100,000 with heightened concern for persons 15 to 44 years. In 2021, 483 Jamaicans died in 435 crashes, with 33% of these fatalities occurring during Covid-19 curfew hours. The study objective is to conduct a systemic safety review of Jamaican road crashes and provide a framework for its use in complementing traditional methods. The methodology involves the use of the FHWA Systemic Safety Project Selection Tool for analysis. This tool reviews systemwide data in order to identify risk factors across the network associated with severe and fatal crashes, rather that only hotspots. A total of 10,379 crashes with 745 fatalities and serious injuries were reviewed. Of the focus crash types listed, 50% of ‘Pedestrian Accidents’ resulted in fatalities and serious injuries, followed by 32% ‘Bicycle’, 24% ‘Single’ and 12% of ‘Head-on’. This study seeks to understand the associated risk factors with these priority crash types across the network and recommend cost-effective countermeasures across common sites. As we press towards Vision Zero, the inclusion of the systemic safety review method, complementing traditional methods, may create a wider impact in reducing road fatalities and serious injury by targeting issues across network with similarities; focus crash types and contributing factors.

Keywords: systemic safety review, risk factors, road crashes, crash types

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Authors: Kwok Tak Kit

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The construction industry plays an important role in environmental and carbon emissions as it consumes a huge amount of natural resources and energy. Sustainable engineering involves the process of planning, design, procurement, construction and delivery in which the whole building and construction process resulting from building and construction can be effectively and sustainability managed to achieve the use of natural resources. Implementation of sustainable technology development and innovation, adoption of the advanced construction process and facilitate the facilities management to implement the energy and waste control more accurately and effectively. Study and research in the relationship of BIM and environment assessment tools lack a clear discussion. In this paper, we will focus on the synergy of BIM technology and sustainable engineering in the AEC industry and outline the key factors which enhance the use of advanced innovation, technology and method and define the role of stakeholders to achieve zero-carbon emission toward the Paris Agreement to limit global warming to well below 2ᵒC above pre-industrial levels. A case study of the adoption of Building Information Modeling (BIM) and environmental assessment tools in Hong Kong will be discussed in this paper.

Keywords: sustainability, sustainable engineering, BIM, LEED

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Authors: Ian Marc G. Cabugsa, Kim Ryan Won, Kareem Mamac, Manuel Dee, Merlita Garcia

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An optimized cacao fermentation technique was developed for the cacao farmers of Davao City Philippines. Cacao samples with weights ranging from 150-250 kilograms were collected from various cacao farms in Davao City and Zamboanga City Philippines. Different fermentation techniques were used starting with design of the sweat box, prefermentation conditionings, number of days for fermentation and number of turns. As the beans are being fermented, its temperature was regularly monitored using a digital thermometer. The resultant cacao beans were assessed using physical and chemical means. For the physical assessment, the bean cut test, bean count tests, and sensory test were used. Quantification of theobromine, caffeine, and antioxidants in the form of equivalent quercetin was used for chemical assessment. Both the theobromine and caffeine were analyzed using HPLC method while the antioxidant was analyzed spectrometrically. To come up with the best fermentation procedure, the different assessment were given priority coefficients wherein the physical tests – taste test, cut, and bean count tests were given priority over the results of the chemical test. The result of the study was an optimized fermentation protocol that is readily adaptable and transferable to any cacao cooperatives or groups in Mindanao or even Philippines as a whole.

Keywords: cacao, fermentation, HPLC, optimization, Philippines

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Authors: Ingy Ibrahim El-Darwish, Neveen Youssef Azmy

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The endowment of a healthy environment can be implemented by endorsing sustainable fundamentals. Design of sustainable buildings through recycling of waste, can reduce health problems, provide good environments and contribute to the aesthetically pleasing entourage. Such environments can help in providing energy-saving alternatives to consolidate the principles of sustainability. The poor community awareness and the absence of laws and legislation in Egypt for waste management specifically in residential areas have led to an inability to provide an integrated system for waste management in urban and rural areas. Many problems and environmental challenges face the Egyptian urban environments. From these problems, is the lack of a cohesive vision for waste collection and recycling for energy-saving. The second problem is the lack public awareness of the short term and long term vision of waste management. Bad practices have adversely affected the efficiency of environmental management systems due to lack of urban legislations that codify collection and recycling of residential communities in Egyptian urban environments. Hence, this research tries to address residents on waste management matters to facilitate legislative process on waste collection and classification within residential units and outside them in a preparation phase for recycling in the Egyptian urban environments. In order to achieve this goal, one of the Egyptian communities has been addressed, analyzed and studied. Waste collection, classification, separation and access to recycling places in the urban city are proposed in preparation for a legislation ruling and regulating the process. Hence, sustainable principles are to be achieved.

Keywords: recycling, residential buildings, sustainability, waste

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Authors: K. Shimola, M. Krishnaveni

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This paper examines vulnerability assessment of water resources in a semi-arid basin using the 4-step approach. The vulnerability assessment framework is developed to study the water resources vulnerability which includes the creation of GIS-based vulnerability maps. These maps represent the spatial variability of the vulnerability index. This paper introduces the 4-step approach to assess vulnerability that incorporates a new set of indicators. The approach is demonstrated using a framework composed of a precipitation data for (1975–2010) period, temperature data for (1965–2010) period, hydrological model outputs and the water resources GIS data base. The vulnerability assessment is a function of three components such as exposure, sensitivity and adaptive capacity. The current water resources vulnerability is assessed using GIS based spatio-temporal information. Rainfall Coefficient of Variation, monsoon onset and end date, rainy days, seasonality indices, temperature are selected for the criterion ‘exposure’. Water yield, ground water recharge, evapotranspiration (ET) are selected for the criterion ‘sensitivity’. Type of irrigation and storage structures are selected for the criterion ‘Adaptive capacity’. These indicators were mapped and integrated in GIS environment using overlay analysis. The five sub-basins, namely Arjunanadhi, Kousiganadhi, Sindapalli-Uppodai and Vallampatti Odai, fall under medium vulnerability profile, which indicates that the basin is under moderate stress of water resources. The paper also explores prioritization of sub-basinwise adaptation strategies to climate change based on the vulnerability indices.

Keywords: adaptive capacity, exposure, overlay analysis, sensitivity, vulnerability

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Authors: Byron Joseph A. Hallar, Annjeannette Alain D. Galang, Maria Visitacion N. Gumabay

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One of the unique challenges provided by the twenty-first century to Philippine higher education is the utilization of Big Data. The higher education system in the Philippines is generating burgeoning amounts of data that contains relevant data that can be used to generate the information and knowledge needed for accurate data-driven decision making. This study examines the status, relevance and future of Big Data and Analytics in Philippine higher education. The insights gained from the study may be relevant to other developing nations similarly situated as the Philippines.

Keywords: big data, data analytics, higher education, republic of the philippines, assessment

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Authors: Yumei Han, Naiqing Song, Xiaoping Yang, Yuping Han

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This study explores the conceptualization of key competencies that children are expected to develop in three year preschools (age 3-6) and the assessment practices of such key competencies in China. Assessment of children development has been put into the central place of early childhood education quality evaluation system in China. In the context of students key competencies development centered education reform in China, defining and selecting key competencies of children in preschools are of great significance in that they would lay a solid foundation for children’s lifelong learning path, and they would lead to curriculum and instruction reform, teacher development reform as well as quality evaluation reform in the early childhood education area. Based on sense making theory and framework, this study adopted multiple stakeholders’ (early childhood educators, parents, evaluation administrators, scholars in the early childhood education field) perspectives and grass root voices to conceptualize and operationalize key competencies for children in preschools in Southwest China. On the ground of children development theories, Chinese and international literature related to children development and key competencies, and key competencies frameworks by UNESCO, OECD and other nations, the authors designed a two-phase sequential mixed method study to address three main questions: (a) How is early childhood key competency defined or labeled from literature and from different stakeholders’ views? (b) Based on the definitions explicated in the literature and the surveys on different stakeholders, what domains and components are regarded to constitute the key competency framework of children in three-year preschools in China? (c) How have early childhood key competencies been assessed and measured, and how such assessment and measurement contribute to enhancing early childhood development quality? On the first phase, a series of focus group surveys were conducted among different types of stakeholders around the research questions. Moreover, on the second phase, based on the coding of the participants’ answers, together with literature synthesis findings, a questionnaire survey was designed and conducted to select most commonly expected components of preschool children’s key competencies. Semi-structured open questions were also included in the questionnaire for the participants to add on competencies beyond the checklist. Rudimentary findings show agreeable concerns on the significance and necessity of conceptualization and assessment of key competencies for children in preschools, and a key competencies framework composed of 7 domains and 25 indicators was constructed. Meanwhile, the findings also show issues in the current assessment practices of children’s competencies, such as lack of effective assessment tools, lack of teacher capacity in applying the tools to evaluating children and advancing children development accordingly. Finally, the authors put forth suggestions and implications for China and international communities in terms of restructuring early childhood key competencies framework, and promoting child development centered reform in early childhood education quality evaluation and development.

Keywords: assessment, conceptualization, early childhood education quality in China, key competencies

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Authors: Rowane May A. Fesalbon, Greyland C. Agno, Jodel L. Cuasay, Dindo A. Malonzo, Ma. Rosario Concepcion O. Ang

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The Department of Energy of the Republic of the Philippines estimates that the country’s energy reserves for 2015 are dwindling– observed in the rotating power outages in several localities. To aid in the energy crisis, a national hydropower resource assessment scheme is developed. Hydropower is a resource that is derived from flowing water and difference in elevation. It is a renewable energy resource that is deemed abundant in the Philippines – being an archipelagic country that is rich in bodies of water and water resources. The objectives of this study is to develop a methodology for a national hydropower resource assessment using hydrologic modeling and geospatial techniques in order to generate resource maps for future reference and use of the government and other stakeholders. The methodology developed for this purpose is focused on two models – the implementation of the Soil and Water Assessment Tool (SWAT) for the river discharge and the use of geospatial techniques to analyze the topography and obtain the head, and generate the theoretical hydropower potential sites. The methodology is highly coupled with Geographic Information Systems to maximize the use of geodatabases and the spatial significance of the determined sites. The hydrologic model used in this workflow is SWAT integrated in the GIS software ArcGIS. The head is determined by a developed algorithm that utilizes a Synthetic Aperture Radar (SAR)-derived digital elevation model (DEM) which has a resolution of 10-meters. The initial results of the developed workflow indicate hydropower potential in the river reaches ranging from pico (less than 5 kW) to mini (1-3 MW) theoretical potential.

Keywords: ArcSWAT, renewable energy, hydrologic model, hydropower, GIS

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Authors: Ethan James

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Over one billion people worldwide suffer from some level of vision loss or blindness as a result of progressive retinal diseases. Many patients, particularly in developing areas, are incorrectly diagnosed or undiagnosed whatsoever due to unconventional diagnostic tools and screening methods. Artificial intelligence (AI) based on deep learning (DL) convolutional neural networks (CNN) have recently gained a high interest in ophthalmology for its computer-imaging diagnosis, disease prognosis, and risk assessment. Optical coherence tomography (OCT) is a popular imaging technique used to capture high-resolution cross-sections of retinas. In ophthalmology, DL has been applied to fundus photographs, optical coherence tomography, and visual fields, achieving robust classification performance in the detection of various retinal diseases including macular degeneration, diabetic retinopathy, and retinitis pigmentosa. However, there is no complete diagnostic model to analyze these retinal images that provide a diagnostic accuracy above 90%. Thus, the purpose of this project was to develop an AI model that utilizes machine learning techniques to automatically diagnose specific retinal diseases from OCT scans. The algorithm consists of neural network architecture that was trained from a dataset of over 20,000 real-world OCT images to train the robust model to utilize residual neural networks with cyclic pooling. This DL model can ultimately aid ophthalmologists in diagnosing patients with these retinal diseases more quickly and more accurately, therefore facilitating earlier treatment, which results in improved post-treatment outcomes.

Keywords: artificial intelligence, deep learning, imaging, medical devices, ophthalmic devices, ophthalmology, retina

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Authors: Lai Xuejiang, Huang Li, Yang Yi

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To study the potential hazards of the sudden emergency relief of flare stack, the thermal radiation and noise calculation of flare stack is carried out by using Flaresim program 2.0. Thermal radiation and noise analysis should be considered as the sudden emergency relief takes place. According to the Flaresim software simulation results, the thermal radiation and noise meet the requirement.

Keywords: flare stack, thermal radiation, safety assessment, noise

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Authors: Alexandra Steed

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Alexandra Steed URBAN was commissioned to undertake the South Essex Green and Blue Infrastructure Study (SEGBI) on behalf of the Association of South Essex Local Authorities (ASELA): a partnership of seven neighboring councils within the Thames Estuary. Located on London’s doorstep, the 70,000-hectare region is under extraordinary pressure for regeneration, further development, and economic expansion, yet faces extreme challenges: sea-level rise and inadequate flood defenses, stormwater flooding and threatened infrastructure, loss of internationally important habitats, significant existing community deprivation, and lack of connectivity and access to green space. The brief was to embrace these challenges in the creation of a document that would form a key part of ASELA’s Joint Strategic Framework and feed into local plans and master plans. Thus, helping to tackle climate change, ecological collapse, and social inequity at a regional scale whilst creating a relationship and awareness between urban communities and the surrounding landscapes and nature. The SEGBI project applied a ‘land-based’ methodology, combined with a co-design approach involving numerous stakeholders, to explore how living infrastructure can address these significant issues, reshape future planning and development, and create thriving places for the whole community of life. It comprised three key stages, including Baseline Review; Green and Blue Infrastructure Assessment; and the final Green and Blue Infrastructure Report. The resulting proposals frame an ambitious vision for the delivery of a new regional South Essex Estuary (SEE) Park – 24,000 hectares of protected and connected landscapes. This unified parkland system will drive effective place-shaping and “leveling up” for the most deprived communities while providing large-scale nature recovery and biodiversity net gain. Comprehensive analysis and policy recommendations ensure best practices will be embedded within planning documents and decisions guiding future development. Furthermore, a Natural Capital Account was undertaken as part of the strategy showing the tremendous economic value of the natural assets. This strategy sets a pioneering precedent that demonstrates how the prioritisation of living infrastructure has the capacity to address climate change and ecological collapse, while also supporting sustainable housing, healthier communities, and resilient infrastructures. It was only achievable through a collaborative and cross-boundary approach to strategic planning and growth, with a shared vision of place, and a strong commitment to delivery. With joined-up thinking and a joined-up region, a more impactful plan for South Essex was developed that will lead to numerous environmental, social, and economic benefits across the region, and enhancing the landscape and natural environs on the periphery of one of the largest cities in the world.

Keywords: climate change, green and blue infrastructure, landscape architecture, master planning, regional planning, social equity

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Authors: Aliyu Bello Mohammed

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Vital registration or registration of vital events is one of the three major sources of demographic data in Nigeria. The other two are the population census and sample survey. The former is judged to be an indispensable source of demographic data because, it provide information on vital statistics and population trends between two census periods. Various literacy works however depict the vital registration in Nigeria as incapable of providing accurate data for the country. The study has both theoretical and practical significances. The trends and pattern of vital registration has not received adequate research interest in Sub-Saharan Africa in general and Nigeria in particular. This has created a gap in understanding the extent and consequence of the scourge in Africa sub-region. Practically, the study also captures the policy interventions of government and Non-Governmental Organizations (NGOs) that would help enlighten the public on the importance of vital registration in Nigeria. Furthermore, feasible policy strategies that will enhance trends and pattern vital registration in the society would emanate from the study. The study adopted a cross sectional survey design and applied multi stage sampling techniques to sample 230 respondents from the general public in the study area. The first stage involved the splitting of the local government into wards. The second stage involves selecting streets, while the third stage was the households. In all, 6 wards were sampled for the study. The study utilized both primary and secondary sources of data. The primary sources of data used were the questionnaire, focus group discussion (FGD) and in-depth interview (IDI) guides while the secondary sources of data were journals and books, newspapers and magazines. Twelve FGD sessions with 96 study participants and five IDI sessions with the heads of vital registration facilities were conducted. The quantitative data were analyzed using Statistical Package for Social Sciences (SPSS). Descriptive statistics like tables, frequencies and percentages were employed in presenting and interpreting the data. Information from the qualitative data was transcribed and ordered in themes to ensure that outstanding points of the responses are noted. The following conclusions were drawn from the study: the available vital registration facilities are not adequate and were not evenly distributed in the study area; lack of awareness and knowledge of the existence and the importance of vital registration by majority of the people in the local government; distance to vital registration centres from their residents; most births in the area were not registered, and even among the few births that were registered, majority of them were registered after the limited period for registration. And the study reveals that socio-economic index, educational level and distance of facilities to residents are determinants of access to vital registration facility. The study concludes by discussing the need for a reliable and accurate vital registration system if Nigeria’s vision of becoming one of the top 20 economies in the world in 2020 would be realized.

Keywords: trends, patterns, vital, registration and assessment

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Authors: Dana Page, Erica McClure, Kate Snider, Jenni Pollard, Tim Landrum, Jeff Valentine

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Extensive research has been conducted on students with emotional and behavioral disorders (EBD) and their rates of challenging behavior. In the past, however, less attention has been given to their academic achievement and outcomes. Recent research examining outcomes for students with EBD has indicated that these students receive lower grades, are less likely to pass classes, and experience higher rates of school dropout than students without disabilities and students with other high incidence disabilities. Given that between 2% and 20% of the school-age population is likely to have EBD (though many may not be identified as such), this is no small problem. Despite the need for increased examination of this population’s academic achievement, research on the actual performance of students with EBD has been minimal. This study reports the results of a meta-analysis of the limited research examining academic achievement of students with EBD, including effect sizes of assessment scores and discussion of moderators potentially impacting academic outcomes. Researchers conducted a thorough literature search to identify potentially relevant documents before screening studies for inclusion in the systematic review. Screening identified 35 studies that reported results of academic assessment scores for students with EBD. These studies were then coded to extract descriptive data across multiple domains, including placement of students, participant demographics, and academic assessment scores. Results indicated possible collinearity between EBD disability status and lower academic assessment scores, despite a lack of association between EBD eligibility and lower cognitive ability. Quantitative analysis of assessment results yielded effect sizes for academic achievement of student participants, indicating lower performance levels and potential moderators (e.g., race, socioeconomic status, and gender) impacting student academic performance. In addition to discussing results of the meta-analysis, implications and areas for future research, policy, and practice are discussed.

Keywords: students with emotional behavioral disorders, academic achievement, systematic review, meta-analysis

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Authors: Reetika Sharma, Lalit Tejwani, Himanshu Shekhar, Arun Singhvi

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Purpose: Advanced Glaucoma with Failed trab is not an uncommon sight in glaucoma clinic, and such cases usually tend to present with high intraocular pressure (IOP) and advanced cupping, or even glaucomatous atrophy stage. Re-surgery is needed for such cases, and wound modulation poses a major challenge in these cases. We share our experience in this case series with the use of Ologen (collagen matrix implant) along with MMC 0.04% used in surgery. The purpose of the study was to evaluate the efficacy and outcome of collagen matrix implant in re-trabeculectomy in advanced glaucoma cases. Methodology: Eleven eyes of 11 patients (one eye of one patient) underwent re-trabeculectomy surgery with MMC and Ologen. Ologen implant was used in sub scleral and subconjunctival space, as a spacer and wound modulator. In five cases, triple modulation with implant soaked in anti-VEGF was used. Results: All patients had cupping more than 0.9, and one case was GOA. All cases were on maximal medication at presentation and majority were on systemic anti-glaucoma therapy also. Post-surgery, follow-up ranged from 13 – 34 months, and all cases had a follow longer than the gap between previous surgery (which was failed) and re-trab. One case needed AC reformation and one needling was done. Phaco was done at same sitting in four cases. All cases had their IOP lowered post surgery, and vision was maintained in all, however one case was considered as failed re-surgery case. Topical medication was needed in seven cases post-surgery also. Conclusion: Ologen as adjuvant should be considered in all re-trab cases and all high risk and advanced cases, and triple modulation can be next step in these cases. Aggressive IOP control and non- reluctance to continue topical medications post second surgery should be considered in such cases, to give them best possible vision.

Keywords: failed trabeculectomy, ologen, trabeculectomy, advanced glaucoma

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Authors: Raja Al-Ghamdi

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This paper aims to systematically assess the translation of key cultural texts. The paper, therefore, proposes a modification of the discourse analysis model for translation quality assessment introduced by the linguist Juliane House (1977, 1997, 2015). The data for analysis has been chosen from a religious text that has never been investigated before. It is an overt translation of the biography of Prophet Mohammad. The book is written originally in Arabic and translated into English. A soft copy of the translation, entitled The Sealed Nectar, is posted on numerous websites including the Internet Archive library which offers a free access to everyone. The text abounds with linguistic and cultural phenomena relevant to Islamic and Arab lingua-cultural context which make its translation a challenge, as well as its assessment. Interesting findings show that (1) culturemes are rich points and both the translator’s subjectivity and intervention are apparent in mediating them, (2) given the nature of historical narration, the source text reflects the author’s positive shading, whereas the target text reflects the translator’s axiological orientation as neutrally shaded, and, (3) linguistic gaps, metaphorical expressions and intertextuality are major stimuli to compensation strategies.

Keywords: Arabic-English discourse analysis, key cultural texts, overt translation, quality assessment

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Authors: Hee-Young Song

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Background and objectives: In 2011, the Global Initiative for Chronic Obstructive Lung Disease (GOLD) recommendations proposed a multidimensional assessment of patients’ conditions that included both functional parameters and patient-reported outcomes, with the aim to provide a comprehensive assessment of the disease, thus meeting both the needs of the patient and the role of the physician. However, few studies have evaluated patient-reported outcomes as well as objective functional assessments among individuals with chronic obstructive pulmonary disease (COPD) in clinical practice in Korea. This study was undertaken to explore the relationship between functional status assessed by the 6-minute walking distance (MWD) test and subjective health status reported by stable patients with COPD residing in community. Methods: A cross-sectional descriptive study was conducted with 118 stable COPD patients aged 69.4 years old and selected by a convenient sampling from an outpatient department of pulmonology in a tertiaryhospitals. The 6-MWD test was conducted according to standardized instructions. Participants also completed a constructed questionnaire including general characteristics, smoking history, dyspnea by modified medical research council (mMRC) scale, and health status by COPD assessment test (CAT). Anthropometric measurements were performed for body mass index (BMI). Medical records were reviewed to obtain disease-related characteristics including duration of the disease and forced expiratory volume in 1 second (FEV1). Data were analyzed using PASW statistics 20.0. Results: Mean FEV1% of participants was 63.51% and mean 6-MWD and CAT scores were 297.54m and 17.7, respectively. The 6-MWD and CAT showed significant negative correlations (r= -.280, p=.002); FEV1 and CAT did as well correlations (r= -.347, p < .001). Conclusions: Findings suggest that the better functional status an individual with COPD has, the better subjective health status is, and provide the support for using patient-reported outcomes along with functional parameters to facilitate comprehensive assessment of COPD patients in real clinical practices.

Keywords: chronic obstructive pulmonary disease, COPD assessment test, functional status, patient-reported outcomes

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Authors: Euan Donley

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Emergency Departments (EDs) are heavily burdened as presentation rates continue to rise. To improve patient flow National Emergency Access Targets (NEAT) were introduced. NEAT implements timelines for ED presentations, such as discharging patients within four hours of arrival. Mental health patients use EDs more than the general population and are generally more complex in their presentations. The aim of this study is to examine the impact of NEAT on psychiatric risk assessment of mental health patients in the ED. Seventy-eight mental health clinicians from 7 Victoria, Australia, hospital EDs participated in a mixed method analysis via anonymous online survey. NEAT was considered helpful as mental health patients were seen quicker, were less likely to abscond, could improve teamwork amongst ED staff, and in some cases administrative processes were better streamlined. However, clinicians felt that NEAT was also responsible for less time with patients and relatives’, resulted in rushed assessments, placed undue pressure on mental health clinicians, was not conducive to training, and the emphasis on time was the wrong focus for patient treatment. The profile of a patient typically likely to be treated within NEAT timelines showed a perfect storm of luck and compliance. If a patient was sober, medically stable, referred early, did not require much collateral information and did not have distressed relatives, NEAT was more likely to be met. Organisationally participants reported no organisational change or training to meet NEAT. Poor mental health staffing, multiple ED presentations and a shortage of mental health beds also hamper meeting NEAT. Findings suggest participants were supportive of NEAT in principle, but a demanding workload and organisational barriers meant NEAT had an overall negative effect on psychiatric risk assessment of mental health patients in ED.

Keywords: assessment, emergency, risk, psychiatric

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Authors: Ian Omung'a

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Breast cancer remains to be one of the deadliest cancers for women worldwide, with the risk of developing tumors being as high as 50 percent in Sub-Saharan African countries like Kenya. With as many as 42 percent of these cases set to be diagnosed late when cancer has metastasized and or the prognosis has become terminal, Full Field Digital [FFD] Mammography remains an effective screening technique that leads to early detection where in most cases, successful interventions can be made to control or eliminate the tumors altogether. FFD Mammograms have been proven to multiply more effective when used together with Computer-Aided Detection and Diagnosis [CADe] systems, relying on algorithmic implementations of Deep Learning techniques in Computer Vision to carry out deep pattern recognition that is comparable to the level of a human radiologist and decipher whether specific areas of interest in the mammogram scan image portray abnormalities if any and whether these abnormalities are indicative of a benign or malignant tumor. Within this paper, we review emergent Deep Learning techniques that will prove relevant to the development of State-of-The-Art FFD Mammogram CADe systems. These techniques will span self-supervised learning for context-encoded occlusion, self-supervised learning for pre-processing and labeling automation, as well as the creation of a standardized large-scale mammography dataset as a benchmark for CADe systems' evaluation. Finally, comparisons are drawn between existing practices that pre-date these techniques and how the development of CADe systems that incorporate them will be different.

Keywords: breast cancer diagnosis, computer aided detection and diagnosis, deep learning, whole mammogram classfication, ultrasound classification, computer vision

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Authors: Mohammed Ahmed Ahmed Odah

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DNA barcoding is a crucial method for assessing and monitoring species diversity amidst escalating threats to global biodiversity. The author explores DNA barcoding's potential as a robust and reliable tool for biodiversity assessment. It begins with a comprehensive review of existing literature, delving into the theoretical foundations, methodologies and applications of DNA barcoding. The suitability of various DNA regions, like the COI gene, as universal barcodes is extensively investigated. Additionally, the advantages and limitations of different DNA sequencing technologies and bioinformatics tools are evaluated within the context of DNA barcoding. To evaluate the efficacy of DNA barcoding, diverse ecosystems, including terrestrial, freshwater and marine habitats, are sampled. Extracted DNA from collected specimens undergoes amplification and sequencing of the target barcode region. Comparison of the obtained DNA sequences with reference databases allows for the identification and classification of the sampled organisms. Findings demonstrate that DNA barcoding accurately identifies species, even in cases where morphological identification proves challenging. Moreover, it sheds light on cryptic and endangered species, aiding conservation efforts. The author also investigates patterns of genetic diversity and evolutionary relationships among different taxa through the analysis of genetic data. This research contributes to the growing knowledge of DNA barcoding and its applicability for biodiversity assessment. The advantages of this approach, such as speed, accuracy and cost-effectiveness, are highlighted, along with areas for improvement. By unlocking the genetic code, DNA barcoding enhances our understanding of biodiversity, supports conservation initiatives and informs evidence-based decision-making for the sustainable management of ecosystems.

Keywords: DNA barcoding, biodiversity assessment, genetic code, species identification, taxonomic resolution, next-generation sequencing

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Authors: James Hilton Williams

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Recent tsunami events, including the 2011 Tohoku Tsunami, Japan, and the 2015 Illapel Tsunami, Chile, have highlighted the potential for tsunami impacts on the built environment. International research in the tsunami impacts domain has been largely focused toward impacts on buildings and casualty estimations, while only limited attention has been placed on the impacts on infrastructure which is critical for the recovery of impacted communities. New Zealand, with 75% of the population within 10 km of the coast, has a large amount of coastal infrastructure exposed to local, regional and distant tsunami sources. To effectively manage tsunami risk for New Zealand critical infrastructure, including energy, transportation, and communications, the vulnerability of infrastructure networks and components must first be determined. This research develops infrastructure asset vulnerability, functionality and repair- cost functions based on international post-event tsunami impact assessment data from technologically similar countries, including Japan and Chile, and adapts these to New Zealand. These functions are then utilized within a New Zealand based impact framework, allowing for cost benefit analyses, effective tsunami risk management strategies and mitigation options for exposed critical infrastructure to be determined, which can also be applied internationally.

Keywords: impact assessment, infrastructure, tsunami impacts, vulnerability functions

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Authors: Y. T. Chui, W. M. Au, L. Li

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Recently, wearable electronic textiles have been emerging in today’s market and were developed rapidly since, beside the needs for the clothing uses for leisure, fashion wear and personal protection, there also exist a high demand for the clothing to be capable for function in this electronic age, such as interactive interfaces, sensual being and tangible touch, social fabric, material witness and so on. With the requirements of wearable electronic textiles to be more comfortable, adorable, and easy caring, conductive yarn becomes one of the most important fundamental elements within the wearable electronic textile for interconnection between different functional units or creating a functional unit. The properties of conductive yarns from different companies can vary to a large extent. There are vitally important criteria for selecting the conductive yarns, which may directly affect its optimization, prospect, applicability and performance of the final garment. However, according to the literature review, few researches on conductive yarns on shelf focus on the assessment methods of conductive yarns for the scientific selection of material by a systematic way under different conditions. Therefore, in this study, direction of selecting high-quality conductive yarns is given. It is to test the stability and reliability of the conductive yarns according the problems industrialists would experience with the yarns during the every manufacturing process, in which, this assessment system can be classified into four stage. That is 1) Yarn stage, 2) Fabric stage, 3) Apparel stage and 4) End user stage. Several tests with clear experiment procedures and parameters are suggested to be carried out in each stage. This assessment method suggested that the optimal conducting yarns should be stable in property and resistant to various corrosions at every production stage or during using them. It is expected that this demonstration of assessment method can serve as a pilot study that assesses the stability of Ag/nylon yarns systematically at various conditions, i.e. during mass production with textile industry procedures, and from the consumer perspective. It aims to assist industrialists to understand the qualities and properties of conductive yarns and suggesting a few important parameters that they should be reminded of for the case of higher level of suitability, precision and controllability.

Keywords: applicability, assessment method, conductive yarn, wearable electronics

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Authors: Qingsong Xiong, Cheng Yuan, Qingzhao Kong, Haibei Xiong

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Deep-learning-driven approaches based on vibration responses have attracted larger attention in rapid structural condition assessment while obtaining sufficient measured training data with corresponding labels is relevantly costly and even inaccessible in practical engineering. This study proposes an integrated label propagation network for structural condition assessment, which is able to diffuse the labels from continuously-generating measurements by intact structure to those of missing labels of damage scenarios. The integrated network is embedded with damage-sensitive features extraction by deep autoencoder and pseudo-labels propagation by optimized fuzzy clustering, the architecture and mechanism which are elaborated. With a sophisticated network design and specified strategies for improving performance, the present network achieves to extends the superiority of self-supervised representation learning, unsupervised fuzzy clustering and supervised classification algorithms into an integration aiming at assessing damage conditions. Both numerical simulations and full-scale laboratory shaking table tests of a two-story building structure were conducted to validate its capability of detecting post-earthquake damage. The identifying accuracy of a present network was 0.95 in numerical validations and an average 0.86 in laboratory case studies, respectively. It should be noted that the whole training procedure of all involved models in the network stringently doesn’t rely upon any labeled data of damage scenarios but only several samples of intact structure, which indicates a significant superiority in model adaptability and feasible applicability in practice.

Keywords: autoencoder, condition assessment, fuzzy clustering, label propagation

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Authors: Wafaa M. El- Kotb, Soheir Mohamed Weheida, Manal E. Fareed

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The aim of this study was to determine the effect of implementing a teaching module about diet and exercises on clinical outcomes of patients with gout. Subjects: A purposive sample of 60 adult gouty patients was selected and randomly and alternatively divided into two equal groups 30 patients in each. Setting: The study was conducted in orthopedic out patient's clinic of Menoufia University. Tools of the study: Three tools were utilized for data collection: Knowledge assessment structured interview questionnaire, Clinical manifestation assessment tools and Nutritional assessment sheet. Results: All patients of both groups (100 %) had poor total knowledge score pre teaching, while 90 % of the study group had good total knowledge score post teaching by three months compared to 3.3 % of the control group. Moreover the recovery outcomes were significantly improved among study group compared to control group post teaching. Conclusion: Teaching study group about diet and exercises significantly improved their clinical outcomes. Recommendation: Patient's education about diet and exercises should be ongoing process for patients with gout.

Keywords: clinical outcomes, diet, exercises, teaching module

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Authors: Yuta Nakano, Kozo Kajiwara, Atsushi Hori, Takeshi Fujita

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In association with the wave of electric vehicles (EV), low energy consumption systems have become more and more important. One of the key technologies to realize low energy consumption is a dynamic vision sensor (DVS), or we can call it an event sensor, neuromorphic vision sensor and so on. This sensor has several features, such as high temporal resolution, which can achieve 1 Mframe/s, and a high dynamic range (120 DB). However, the point that can contribute to low energy consumption the most is its sparsity; to be more specific, this sensor only captures the pixels that have intensity change. In other words, there is no signal in the area that does not have any intensity change. That is to say, this sensor is more energy efficient than conventional sensors such as RGB cameras because we can remove redundant data. On the other side of the advantages, it is difficult to handle the data because the data format is completely different from RGB image; for example, acquired signals are asynchronous and sparse, and each signal is composed of x-y coordinate, polarity (two values: +1 or -1) and time stamp, it does not include intensity such as RGB values. Therefore, as we cannot use existing algorithms straightforwardly, we have to design a new processing algorithm to cope with DVS data. In order to solve difficulties caused by data format differences, most of the prior arts make a frame data and feed it to deep learning such as Convolutional Neural Networks (CNN) for object detection and recognition purposes. However, even though we can feed the data, it is still difficult to achieve good performance due to a lack of intensity information. Although polarity is often used as intensity instead of RGB pixel value, it is apparent that polarity information is not rich enough. Considering this context, we proposed to use the timestamp information as a data representation that is fed to deep learning. Concretely, at first, we also make frame data divided by a certain time period, then give intensity value in response to the timestamp in each frame; for example, a high value is given on a recent signal. We expected that this data representation could capture the features, especially of moving objects, because timestamp represents the movement direction and speed. By using this proposal method, we made our own dataset by DVS fixed on a parked car to develop an application for a surveillance system that can detect persons around the car. We think DVS is one of the ideal sensors for surveillance purposes because this sensor can run for a long time with low energy consumption in a NOT dynamic situation. For comparison purposes, we reproduced state of the art method as a benchmark, which makes frames the same as us and feeds polarity information to CNN. Then, we measured the object detection performances of the benchmark and ours on the same dataset. As a result, our method achieved a maximum of 7 points greater than the benchmark in the F1 score.

Keywords: event camera, dynamic vision sensor, deep learning, data representation, object recognition, low energy consumption

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