Search results for: virtual domain
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2876

Search results for: virtual domain

716 Privacy Concerns and Law Enforcement Data Collection to Tackle Domestic and Sexual Violence

Authors: Francesca Radice

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Domestic and sexual violence provokes, on average in Australia, one female death per week due to intimate violence behaviours. 83% of couples meet online, and intercepting domestic and sexual violence at this level would be beneficial. It has been observed that violent or coercive behaviour has been apparent from initial conversations on dating apps like Tinder. Child pornography, stalking, and coercive control are some criminal offences from dating apps, including women murdered after finding partners through Tinder. Police databases and predictive policing are novel approaches taken to prevent crime before harm is done. This research will investigate how police databases can be used in a privacy-preserving way to characterise users in terms of their potential for violent crime. Using the COPS database of NSW Police, we will explore how the past criminal record can be interpreted to yield a category of potential danger for each dating app user. It is up to the judgement of each subscriber on what degree of the potential danger they are prepared to enter into. Sentiment analysis is an area where research into natural language processing has made great progress over the last decade. This research will investigate how sentiment analysis can be used to interpret interchanges between dating app users to detect manipulative or coercive sentiments. These can be used to alert law enforcement if continued for a defined number of communications. One of the potential problems of this approach is the potential prejudice a categorisation can cause. Another drawback is the possibility of misinterpreting communications and involving law enforcement without reason. The approach will be thoroughly tested with cross-checks by human readers who verify both the level of danger predicted by the interpretation of the criminal record and the sentiment detected from personal messages. Even if only a few violent crimes can be prevented, the approach will have a tangible value for real people.

Keywords: sentiment analysis, data mining, predictive policing, virtual manipulation

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715 Generating a Functional Grammar for Architectural Design from Structural Hierarchy in Combination of Square and Equal Triangle

Authors: Sanaz Ahmadzadeh Siyahrood, Arghavan Ebrahimi, Mohammadjavad Mahdavinejad

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Islamic culture was accountable for a plethora of development in astronomy and science in the medieval term, and in geometry likewise. Geometric patterns are reputable in a considerable number of cultures, but in the Islamic culture the patterns have specific features that connect the Islamic faith to mathematics. In Islamic art, three fundamental shapes are generated from the circle shape: triangle, square and hexagon. Originating from their quiddity, each of these geometric shapes has its own specific structure. Even though the geometric patterns were generated from such simple forms as the circle and the square, they can be combined, duplicated, interlaced, and arranged in intricate combinations. So in order to explain geometrical interaction principles between square and equal triangle, in the first definition step, all types of their linear forces individually and in the second step, between them, would be illustrated. In this analysis, some angles will be created from intersection of their directions. All angles are categorized to some groups and the mathematical expressions among them are analyzed. Since the most geometric patterns in Islamic art and architecture are based on the repetition of a single motif, the evaluation results which are obtained from a small portion, is attributable to a large-scale domain while the development of infinitely repeating patterns can represent the unchanging laws. Geometric ornamentation in Islamic art offers the possibility of infinite growth and can accommodate the incorporation of other types of architectural layout as well, so the logic and mathematical relationships which have been obtained from this analysis are applicable in designing some architecture layers and developing the plan design.

Keywords: angle, equal triangle, square, structural hierarchy

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714 Improving Fault Tolerance and Load Balancing in Heterogeneous Grid Computing Using Fractal Transform

Authors: Saad M. Darwish, Adel A. El-Zoghabi, Moustafa F. Ashry

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The popularity of the Internet and the availability of powerful computers and high-speed networks as low-cost commodity components are changing the way we use computers today. These technical opportunities have led to the possibility of using geographically distributed and multi-owner resources to solve large-scale problems in science, engineering, and commerce. Recent research on these topics has led to the emergence of a new paradigm known as Grid computing. To achieve the promising potentials of tremendous distributed resources, effective and efficient load balancing algorithms are fundamentally important. Unfortunately, load balancing algorithms in traditional parallel and distributed systems, which usually run on homogeneous and dedicated resources, cannot work well in the new circumstances. In this paper, the concept of a fast fractal transform in heterogeneous grid computing based on R-tree and the domain-range entropy is proposed to improve fault tolerance and load balancing algorithm by improve connectivity, communication delay, network bandwidth, resource availability, and resource unpredictability. A novel two-dimension figure of merit is suggested to describe the network effects on load balance and fault tolerance estimation. Fault tolerance is enhanced by adaptively decrease replication time and message cost while load balance is enhanced by adaptively decrease mean job response time. Experimental results show that the proposed method yields superior performance over other methods.

Keywords: Grid computing, load balancing, fault tolerance, R-tree, heterogeneous systems

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713 Women's Menstrual Experience in India: A Psycho-Social Approach

Authors: Bhavna Rajagopal, Mrinmoyi Kulkarni

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Today women experience more menstrual cycles than their ancestors did a hundred years ago, owing to early puberty, fewer pregnancies and dietary changes. Much of the research in menstruation is located in the medical domain with a focus on physical symptoms. The research in psychology is largely concerned with premenstrual syndrome (PMS), whereas the focus in sociology is on social and cultural practices relating to menstruation. Research that simultaneously studies the physical, psychological, social and cultural aspects is lacking. Therefore, in this study, an attempt has been made to identify socio-cultural, psychological and physical factors that interact to influence a woman’s experience of menstruation in the urban setting. The study included seven unmarried women in the age group of 24-30 and data was obtained through a focus group discussion. The transcript of the focus group discussion was thematically analysed. Two major themes relating to the self and social experience of menstruation emerged. Themes relating to the self included menarcheal experiences, self-perception, mood and management of menstrual hygiene and symptoms while themes relating to social experience included the construction of menstruation by family and peers, and cultural factors. Attitudes towards the menstrual cycle appeared to be primarily influenced by severity of symptoms and the resulting disruption to daily life. Outcomes of this study have indicated that future research needs to study menstruation and its impact on women’s wellbeing by adopting a socio-ecological approach and by collecting data using the whole cycle approach across a woman’s reproductive years.

Keywords: India, menstrual cycle, psychosocial approach, wellbeing

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712 Housing First, Not Housing Only: The Life Skills Project

Authors: Sara Cumming, Julianne DiSanto, Leah Burton

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Homelessness in Canada is a persistent problem. It has been widely argued that the best tactic for eradicating homelessness is to approach social issues from a Housing First perspective—an approach that centers on quickly moving people into permanent and independent housing and then providing them additional support and services as needed. It is recognized that life skills training is both necessary and an effective way to reduce cyclical homelessness; however, there is a scarcity of research on effective ways to teach life skills; this problem was exacerbated in a pandemic context, where in-person delivery was severely restricted or no longer possible. Very little attention has been paid to the diverse cultural needs of clients in a multicultural context and the need to foster cultural knowledge/awareness in individuals to successfully contribute to the cultural safety of communities. This research attempts to fill these gaps in the literature and in practice by employing a community-engaged research (CER) approach. Academic, government, funders, front-line staff, and clients at 15 not-for-profits from across the Greater Toronto Area in Ontario, Canada, collaborated to co-create a virtual, client-centric, equity, diversity, and inclusion (EDI) informed life skill learning management system. We employed a triangulation methodology for this research. An environmental scan was conducted for best practices. Two separate Creative Problem Solving Sessions were held with over 100 front-line workers, managers, and executive directors who work with homeless populations. Quantitative and open-ended surveys were completed by over 200 individuals with experience with homelessness. All sections of this research aimed to discover the areas of skills that individuals need to maintain housing and to ascertain what a more client-driven EDI approach to life skills training should include. This research will showcase which life skills are deemed essential for homeless and precariously housed individuals.

Keywords: homelessness, Housing First, life skills, community engaged research

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711 Critical Role of Lipid Rafts in Influenza a Virus Binding to Host Cell

Authors: Dileep Kumar Verma, Sunil Kumar Lal

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Influenza still remains one of the most challenging diseases posing significant threat to public health causing seasonal epidemics and pandemics. Influenza A Virus (IAV) surface protein hemagglutinin is known to play an important role in viral attachment to the host sialic acid receptors and concentrate in lipid rafts for efficient viral fusion. Selective nature of Influenza A virus to utilize rafts micro-domain for efficient virus assembly and budding has been explored in depth. However, the detailed mechanism of IAV binding to host cell membrane and entry into the host remains elusive. In the present study we investigated the role of lipid rafts in early life cycle events of IAV. Role of host lipid rafts was studied using raft disruption method by extraction of cholesterol by Methyl-β-Cyclodextrin. Using GM1, a well-known lipid raft marker, we were able to observe co-localization of IAV on lipid rafts on the host cell membrane. This experiment suggests a direct involvement of lipid rafts in the initiation of the IAV life cycle. Upon disruption of lipid rafts by Methyl-b-cyclodextrin, we observed a significant reduction in IAV binding on the host cell surface indicating a significant decrease in virus attachment to coherent membrane rafts. Our results provide proof that host lipid rafts and their constituents play an important role in the adsorption of IAV. This study opens a new avenues in IAV virus-host interactions to combat infection at a very early steps of the viral lifecycle.

Keywords: lipid raft, adsorption, cholesterol, methyl-β-cyclodextrin, GM1

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710 Modeling and Numerical Simulation of Heat Transfer and Internal Loads at Insulating Glass Units

Authors: Nina Penkova, Kalin Krumov, Liliana Zashcova, Ivan Kassabov

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The insulating glass units (IGU) are widely used in the advanced and renovated buildings in order to reduce the energy for heating and cooling. Rules for the choice of IGU to ensure energy efficiency and thermal comfort in the indoor space are well known. The existing of internal loads - gage or vacuum pressure in the hermetized gas space, requires additional attention at the design of the facades. The internal loads appear at variations of the altitude, meteorological pressure and gas temperature according to the same at the process of sealing. The gas temperature depends on the presence of coatings, coating position in the transparent multi-layer system, IGU geometry and space orientation, its fixing on the facades and varies with the climate conditions. An algorithm for modeling and numerical simulation of thermal fields and internal pressure in the gas cavity at insulating glass units as function of the meteorological conditions is developed. It includes models of the radiation heat transfer in solar and infrared wave length, indoor and outdoor convection heat transfer and free convection in the hermetized gas space, assuming the gas as compressible. The algorithm allows prediction of temperature and pressure stratification in the gas domain of the IGU at different fixing system. The models are validated by comparison of the numerical results with experimental data obtained by Hot-box testing. Numerical calculations and estimation of 3D temperature, fluid flow fields, thermal performances and internal loads at IGU in window system are implemented.

Keywords: insulating glass units, thermal loads, internal pressure, CFD analysis

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709 A Corporate Social Responsibility View on Bribery Control in Business Relationships

Authors: Irfan Ameer

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Bribery control in developing countries is the biggest challenge for multinational enterprises (MNEs). Bribery practices are socially embedded and institutionalized, and therefore may achieve collective legitimacy in the society. MNEs often have better and strict norms, codes and standards about such corrupt practices. Bribery in B2B sales relationships has been researched but studies focusing on the role of firm in controlling bribery are scarce. The main objective of this paper is to explore MNEs strategies to control bribery in an environment where bribery is institutionalized. This qualitative study uses narrative approach and focuses on key events, actors and their role in controlling bribery in B2B sales relationships. The context of this study is pharmaceutical industry of Pakistan and data is collected through 23 episodic interviews supported by secondary data. The Corporate social responsibility (CSR) literature e.g. CSR three domain model and CSR pyramid is used to make sense of MNEs strategies to control bribery in developing countries. Results show that MNEs’ bribery control strategies are rather emerging based on the role of some key stakeholders and events which shape bribery strategies. Five key bribery control strategies were found through which MNEs can control both demand and supply side of bribery: bribery related codes development; bribery related codes implementation; focusing on competitive advantage; find mutually beneficial ethical solution; and collaboration with ethical stakeholders. The results also highlight the problems associated with each strategy. Study is unique in a sense that it focuses on stakeholders having unethical interests and provides guidelines to MNEs in controlling bribery practices in B2B sales relationships.

Keywords: bribery, developing countries, CSR, narrative research, B2B sales, MNEs

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708 Scientific Development as Diffusion on a Social Network: An Empirical Case Study

Authors: Anna Keuchenius

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Broadly speaking, scientific development is studied in either a qualitative manner with a focus on the behavior and interpretations of academics, such as the sociology of science and science studies or in a quantitative manner with a focus on the analysis of publications, such as scientometrics and bibliometrics. Both come with a different set of methodologies and few cross-references. This paper contributes to the bridging of this divide, by on the on hand approaching the process of scientific progress from a qualitative sociological angle and using on the other hand quantitative and computational techniques. As a case study, we analyze the diffusion of Granovetter's hypothesis from his 1973 paper 'On The Strength of Weak Ties.' A network is constructed of all scientists that have referenced this particular paper, with directed edges to all other researchers that are concurrently referenced with Granovetter's 1973 paper. Studying the structure and growth of this network over time, it is found that Granovetter's hypothesis is used by distinct communities of scientists, each with their own key-narrative into which the hypothesis is fit. The diffusion within the communities shares similarities with the diffusion of an innovation in which innovators, early adopters, and an early-late majority can clearly be distinguished. Furthermore, the network structure shows that each community is clustered around one or few hub scientists that are disproportionately often referenced and seem largely responsible for carrying the hypothesis into their scientific subfield. The larger implication of this case study is that the diffusion of scientific hypotheses and ideas are not the spreading of well-defined objects over a network. Rather, the diffusion is a process in which the object itself dynamically changes in concurrence with its spread. Therefore it is argued that the methodology presented in this paper has potential beyond the scientific domain, in the study of diffusion of other not well-defined objects, such as opinions, behavior, and ideas.

Keywords: diffusion of innovations, network analysis, scientific development, sociology of science

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707 Numerical Simulations of Fire in Typical Air Conditioned Railway Coach

Authors: Manoj Sarda, Abhishek Agarwal, Juhi Kaushik, Vatsal Sanjay, Arup Kumar Das

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Railways in India remain primary mode of transport having one of the largest networks in the world and catering to billions of transits yearly. Catastrophic economic damage and loss to life is encountered over the past few decades due to fire to locomotives. Study of fire dynamics and fire propagation plays an important role in evacuation planning and reducing losses. Simulation based study of propagation of fire and soot inside an air conditioned coach of Indian locomotive is done in this paper. Finite difference based solver, Fire Dynamic Simulator (FDS) version 6 has been used for analysis. A single air conditioned 3 tier coupe closed to ambient surroundings by glass windows having occupancy for 8 people is the basic unit of the domain. A system of three such coupes combined is taken to be fundamental unit for the entire study to resemble effect to an entire coach. Analysis of flame and soot contours and concentrations is done corresponding to variations in heat release rate per unit volume (HRRPUA) of fire source, variations in conditioned air velocity being circulated inside coupes by vents and an alternate fire initiation and propagation mechanism via ducts. Quantitative results of fractional area in top and front view of the three coupes under fire and smoke are obtained using MATLAB (IMT). Present simulations and its findings will be useful for organizations like Commission of Railway Safety and others in designing and implementing safety and evacuation measures.

Keywords: air conditioned coaches, fire propagation, flame contour, soot flow, train fire

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706 Identification of Vehicle Dynamic Parameters by Using Optimized Exciting Trajectory on 3- DOF Parallel Manipulator

Authors: Di Yao, Gunther Prokop, Kay Buttner

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Dynamic parameters, including the center of gravity, mass and inertia moments of vehicle, play an essential role in vehicle simulation, collision test and real-time control of vehicle active systems. To identify the important vehicle dynamic parameters, a systematic parameter identification procedure is studied in this work. In the first step of the procedure, a conceptual parallel manipulator (virtual test rig), which possesses three rotational degrees-of-freedom, is firstly proposed. To realize kinematic characteristics of the conceptual parallel manipulator, the kinematic analysis consists of inverse kinematic and singularity architecture is carried out. Based on the Euler's rotation equations for rigid body dynamics, the dynamic model of parallel manipulator and derivation of measurement matrix for parameter identification are presented subsequently. In order to reduce the sensitivity of parameter identification to measurement noise and other unexpected disturbances, a parameter optimization process of searching for optimal exciting trajectory of parallel manipulator is conducted in the following section. For this purpose, the 321-Euler-angles defined by parameterized finite-Fourier-series are primarily used to describe the general exciting trajectory of parallel manipulator. To minimize the condition number of measurement matrix for achieving better parameter identification accuracy, the unknown coefficients of parameterized finite-Fourier-series are estimated by employing an iterative algorithm based on MATLAB®. Meanwhile, the iterative algorithm will ensure the parallel manipulator still keeps in an achievable working status during the execution of optimal exciting trajectory. It is showed that the proposed procedure and methods in this work can effectively identify the vehicle dynamic parameters and could be an important application of parallel manipulator in the fields of parameter identification and test rig development.

Keywords: parameter identification, parallel manipulator, singularity architecture, dynamic modelling, exciting trajectory

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705 Numerical Investigation of Pressure Drop in Core Annular Horizontal Pipe Flow

Authors: John Abish, Bibin John

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Liquid-liquid flow in horizontal pipe is investigated in order to reveal the flow patterns arising from the co-existed flow of oil and water. The main focus of the study is to identify the feasibility of reducing the pumping power requirements of petroleum transportation lines by having an annular flow of water around the thick oil core. This idea makes oil transportation cheaper and easier. The present study uses computational fluid dynamics techniques to model oil-water flows with liquids of similar density and varying viscosity. The simulation of the flow is conducted using commercial package Ansys Fluent. Flow domain modeling and grid generation accomplished through ICEM CFD. The horizontal pipe is modeled with two different inlets and meshed with O-Grid mesh. The standard k-ε turbulence scheme along with the volume of fluid (VOF) multiphase modeling method is used to simulate the oil-water flow. Transient flow simulations carried out for a total period of 30s showed significant reduction in pressure drop while employing core annular flow concept. This study also reveals the effect of viscosity ratio, mass flow rates of individual fluids and ration of superficial velocities on the pressure drop across the pipe length. Contours of velocity and volume fractions are employed along with pressure predictions to assess the effectiveness of this proposed concept quantitatively as well as qualitatively. The outcome of the present study is found to be very relevant for the petrochemical industries.

Keywords: computational fluid dynamics, core-annular flows, frictional flow resistance, oil transportation, pressure drop

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704 A U-Net Based Architecture for Fast and Accurate Diagram Extraction

Authors: Revoti Prasad Bora, Saurabh Yadav, Nikita Katyal

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In the context of educational data mining, the use case of extracting information from images containing both text and diagrams is of high importance. Hence, document analysis requires the extraction of diagrams from such images and processes the text and diagrams separately. To the author’s best knowledge, none among plenty of approaches for extracting tables, figures, etc., suffice the need for real-time processing with high accuracy as needed in multiple applications. In the education domain, diagrams can be of varied characteristics viz. line-based i.e. geometric diagrams, chemical bonds, mathematical formulas, etc. There are two broad categories of approaches that try to solve similar problems viz. traditional computer vision based approaches and deep learning approaches. The traditional computer vision based approaches mainly leverage connected components and distance transform based processing and hence perform well in very limited scenarios. The existing deep learning approaches either leverage YOLO or faster-RCNN architectures. These approaches suffer from a performance-accuracy tradeoff. This paper proposes a U-Net based architecture that formulates the diagram extraction as a segmentation problem. The proposed method provides similar accuracy with a much faster extraction time as compared to the mentioned state-of-the-art approaches. Further, the segmentation mask in this approach allows the extraction of diagrams of irregular shapes.

Keywords: computer vision, deep-learning, educational data mining, faster-RCNN, figure extraction, image segmentation, real-time document analysis, text extraction, U-Net, YOLO

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703 Artificial Intelligence in Bioscience: The Next Frontier

Authors: Parthiban Srinivasan

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With recent advances in computational power and access to enough data in biosciences, artificial intelligence methods are increasingly being used in drug discovery research. These methods are essentially a series of advanced statistics based exercises that review the past to indicate the likely future. Our goal is to develop a model that accurately predicts biological activity and toxicity parameters for novel compounds. We have compiled a robust library of over 150,000 chemical compounds with different pharmacological properties from literature and public domain databases. The compounds are stored in simplified molecular-input line-entry system (SMILES), a commonly used text encoding for organic molecules. We utilize an automated process to generate an array of numerical descriptors (features) for each molecule. Redundant and irrelevant descriptors are eliminated iteratively. Our prediction engine is based on a portfolio of machine learning algorithms. We found Random Forest algorithm to be a better choice for this analysis. We captured non-linear relationship in the data and formed a prediction model with reasonable accuracy by averaging across a large number of randomized decision trees. Our next step is to apply deep neural network (DNN) algorithm to predict the biological activity and toxicity properties. We expect the DNN algorithm to give better results and improve the accuracy of the prediction. This presentation will review all these prominent machine learning and deep learning methods, our implementation protocols and discuss these techniques for their usefulness in biomedical and health informatics.

Keywords: deep learning, drug discovery, health informatics, machine learning, toxicity prediction

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702 Academic Education and Internship towards Architecture Professional Practice

Authors: Sawsan Saridar masri, Hisham Arnaouty

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Architecture both defines and is defined by social, cultural, political and financial constraints: this is where the discipline and the profession of architecture meet. This mutual sway evolves wherever interferences in the built environment are thought-out and can be strengthened or weakened by the many ways in which the practice of architecture can be undertaken. The more familiar we are about the concerns and factors that control what can be made, the greater the opportunities to propose and make appropriate architectures. Apparently, the criteria in any qualification policy should permit flexibility of approach and will – for reasons including cultural choice, political issues, and son on – vary significantly from country to country. However the weighting of the various criteria have to ensure adequate standards both in educational system as in the professional training. This paper develops, deepens and questions about the regulatory entry routes to the professional practice of architecture in the Arab world. It is also intended to provide an informed basis about strategies for conventional and unconventional models of practice in preparation for the next stages of architect’s work experience and professional experience. With the objective of promoting the implementation of adequate built environment in the practice of architecture, a comprehensive analysis of various pathways of access to the profession are selected as case studies, encompassing examples from across the world. The review of such case studies allows the creation of a comprehensive picture in relation to the conditions for qualification of practitioners of the built environment at the level of the Middle Eastern countries and the Arab World. Such investigation considers the following aspects: professional title and domain of practice, accreditation of courses, internship and professional training, professional examination and continuing professional development.

Keywords: architecture, internship, mobility, professional practice

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701 Visual Simulation for the Relationship of Urban Fabric

Authors: Ting-Yu Lin, Han-Liang Lin

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This article is about the urban form of visualization by Cityengine. City is composed of different domains, and each domain has its own fabric because of arrangement. For example, a neighborhood unit contains fabrics such as schools, street networks, residential and commercial spaces. Therefore, studying urban morphology can help us understand the urban form in planning process. Streets, plots, and buildings seem as urban fabrics, and they configure urban form. Traditionally, urban morphology usually discussed single parameter, which is building type, ignoring other parameters such as streets and plots. However, urban space is three-dimensional, instead of two-dimensional. People perceive urban space by their visualization. Therefore, using visualization can fill the gap between two dimensions and three dimensions. Hence, the study of urban morphology will strengthen the understanding of whole appearance of a city. Cityengine is a software which can edit, analyze and monitor the data and visualize the result for GIS, a common tool to analyze data and display the map for urban plan and urban design. Cityengine can parameterize the data of streets, plots and building types and visualize the result in three-dimensional way. The research will reappear the real urban form by visualizing. We can know whether the urban form can be parameterized and the parameterized result can match the real urban form. Then, visualizing the result by software in three dimension to analyze the rule of urban form. There will be three stages of the research. It will start with a field survey of Tainan East District in Taiwan to conclude the relationships between urban fabrics of street networks, plots and building types. Second, to visualize the relationship, it will turn the relationship into codes which Cityengine can read. Last, Cityengine will automatically display the result by visualizing.

Keywords: Cityengine, urban fabric, urban morphology, visual simulation

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700 Effectiveness of Gamified Virtual Physiotherapy Patients with Shoulder Problems

Authors: A. Barratt, M. H. Granat, S. Buttress, B. Roy

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Introduction: Physiotherapy is an essential part of the treatment of patients with shoulder problems. The focus of treatment is usually centred on addressing specific physiotherapy goals, ultimately resulting in the improvement in pain and function. This study investigates if computerised physiotherapy using gamification principles are as effective as standard physiotherapy. Methods: Physiotherapy exergames were created using a combination of commercially available hardware, the Microsoft Kinect, and bespoke software. The exergames used were validated by mapping physiotherapy goals of physiotherapy which included; strength, range of movement, control, speed, and activation of the kinetic chain. A multicenter, randomised prospective controlled trial investigated the use of exergames on patients with Shoulder Impingement Syndrome who had undergone Arthroscopic Subacromial Decompression surgery. The intervention group was provided with the automated sensor-based technology, allowing them to perform exergames and track their rehabilitation progress. The control group was treated with standard physiotherapy protocols. Outcomes from different domains were used to compare the groups. An important metric was the assessment of shoulder range of movement pre- and post-operatively. The range of movement data included abduction, forward flexion and external rotation which were measured by the software, pre-operatively, 6 weeks and 12 weeks post-operatively. Results: Both groups show significant improvement from pre-operative to 12 weeks in elevation in forward flexion and abduction planes. Results for abduction showed an improvement for the interventional group (p < 0.015) as well as the test group (p < 0.003). Forward flexion improvement was interventional group (p < 0.0201) with the control group (p < 0.004). There was however no significant difference between the groups at 12 weeks for abduction (p < 0.118067) , forward flexion (p < 0.189755) or external rotation (p < 0.346967). Conclusion: Exergames may be used as an alternative to standard physiotherapy regimes; however, further analysis is required focusing on patient engagement.

Keywords: shoulder, physiotherapy, exergames, gamification

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699 Online Information Seeking: A Review of the Literature in the Health Domain

Authors: Sharifah Sumayyah Engku Alwi, Masrah Azrifah Azmi Murad

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The development of the information technology and Internet has been transforming the healthcare industry. The internet is continuously accessed to seek for health information and there are variety of sources, including search engines, health websites, and social networking sites. Providing more and better information on health may empower individuals, however, ensuring a high quality and trusted health information could pose a challenge. Moreover, there is an ever-increasing amount of information available, but they are not necessarily accurate and up to date. Thus, this paper aims to provide an insight of the models and frameworks related to online health information seeking of consumers. It begins by exploring the definition of information behavior and information seeking to provide a better understanding of the concept of information seeking. In this study, critical factors such as performance expectancy, effort expectancy, and social influence will be studied in relation to the value of seeking health information. It also aims to analyze the effect of age, gender, and health status as the moderator on the factors that influence online health information seeking, i.e. trust and information quality. A preliminary survey will be carried out among the health professionals to clarify the research problems which exist in the real world, at the same time producing a conceptual framework. A final survey will be distributed to five states of Malaysia, to solicit the feedback on the framework. Data will be analyzed using SPSS and SmartPLS 3.0 analysis tools. It is hoped that at the end of this study, a novel framework that can improve online health information seeking is developed. Finally, this paper concludes with some suggestions on the models and frameworks that could improve online health information seeking.

Keywords: information behavior, information seeking, online health information, technology acceptance model, the theory of planned behavior, UTAUT

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698 Real-Time Hybrid Simulation for a Tuned Liquid Column Damper Implementation

Authors: Carlos Riascos, Peter Thomson

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Real-time hybrid simulation (RTHS) is a modern cyber-physical technique used for the experimental evaluation of complex systems, that treats the system components with predictable behavior as a numerical substructure and the components that are difficult to model as an experimental substructure. Therefore it is an attractive method for evaluation of the response of civil structures under earthquake, wind and anthropic loads. Another practical application of RTHS is the evaluation of control systems, as these devices are often nonlinear and their characterization is an important step in the design of controllers with the desired performance. In this paper, the response of three-story shear frame controlled by a tuned liquid column damper (TLCD) and subject to base excitation is considered. Both passive and semi-active control strategies were implemented and are compared. While the passive TLCD achieved a reduction of 50% in the acceleration response of the main structure in comparison with the structure without control, the semi-active TLCD achieved a reduction of 70%, and was robust to variations in the dynamic properties of the main structure. In addition, a RTHS was implemented with the main structure modeled as a linear, time-invariant (LTI) system through a state space representation and the TLCD, with both control strategies, was evaluated on a shake table that reproduced the displacement of the virtual structure. Current assessment measures for RTHS were used to quantify the performance with parameters such as generalized amplitude, equivalent time delay between the target and measured displacement of the shake table, and energy error using the measured force, and prove that the RTHS described in this paper is an accurate method for the experimental evaluation of structural control systems.

Keywords: structural control, hybrid simulation, tuned liquid column damper, semi-active sontrol strategy

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697 The Importance of Visual Communication in Artificial Intelligence

Authors: Manjitsingh Rajput

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Visual communication plays an important role in artificial intelligence (AI) because it enables machines to understand and interpret visual information, similar to how humans do. This abstract explores the importance of visual communication in AI and emphasizes the importance of various applications such as computer vision, object emphasis recognition, image classification and autonomous systems. In going deeper, with deep learning techniques and neural networks that modify visual understanding, In addition to AI programming, the abstract discusses challenges facing visual interfaces for AI, such as data scarcity, domain optimization, and interpretability. Visual communication and other approaches, such as natural language processing and speech recognition, have also been explored. Overall, this abstract highlights the critical role that visual communication plays in advancing AI capabilities and enabling machines to perceive and understand the world around them. The abstract also explores the integration of visual communication with other modalities like natural language processing and speech recognition, emphasizing the critical role of visual communication in AI capabilities. This methodology explores the importance of visual communication in AI development and implementation, highlighting its potential to enhance the effectiveness and accessibility of AI systems. It provides a comprehensive approach to integrating visual elements into AI systems, making them more user-friendly and efficient. In conclusion, Visual communication is crucial in AI systems for object recognition, facial analysis, and augmented reality, but challenges like data quality, interpretability, and ethics must be addressed. Visual communication enhances user experience, decision-making, accessibility, and collaboration. Developers can integrate visual elements for efficient and accessible AI systems.

Keywords: visual communication AI, computer vision, visual aid in communication, essence of visual communication.

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696 Leading with Skill Development: A Collaborative and Community Based Approach to Ending Open Defecation in Rural India via Computerized Technical Vocational Education and Training

Authors: Srividya Sheshadri, Christopher Coley, Roa. R. Bhavani

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India currently accounts for 60 percent of the open defecation that is practiced globally. While research in the domain of sanitation development makes it apparent that girls and women living in rural India are disproportionately affected, interventions to address this dilemma are lacking. An important but relatively unexplored connection with poor sanitation is that women living in rural India are not only the largest marginalized group without access to adequate sanitation facilities, they also represent a majority of India’s unskilled workers. By training women to build their own toilets, through an approach that has demonstrated success in empowering marginalized communities through technical and vocational education and training (TVET), a collaborative dynamic emerges that can engage entire communities in the movement towards total sanitation. Designed and implemented by Amrita University, this technology-enhanced, community-based approach to skill development, known as Amrita computerized Vocational Education and Training (or Amrita cVET), has begun to show promise in addressing the struggle to end open defecation, and raise sanitation awareness, as well as strengthen personal and community development among women living in rural India. While Amrita cVET project, known as Women Empowerment: Sanitation, is currently in implementation in seven states throughout India, this paper will discuss early stages of the intervention in rural villages within the Indian states of: Karnataka and Goa, where previous sanitation efforts have failed to take hold.

Keywords: community based development, empowerment studies, sanitation in India, computerized vocational training

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695 Simulation and Fabrication of Plasmonic Lens for Bacteria Detection

Authors: Sangwoo Oh, Jaewoo Kim, Dongmin Seo, Jaewon Park, Yongha Hwang, Sungkyu Seo

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Plasmonics has been regarded one of the most powerful bio-sensing modalities to evaluate bio-molecular interactions in real-time. However, most of the plasmonic sensing methods are based on labeling metallic nanoparticles, e.g. gold or silver, as optical modulation markers, which are non-recyclable and expensive. This plasmonic modulation can be usually achieved through various nano structures, e.g., nano-hole arrays. Among those structures, plasmonic lens has been regarded as a unique plasmonic structure due to its light focusing characteristics. In this study, we introduce a custom designed plasmonic lens array for bio-sensing, which was simulated by finite-difference-time-domain (FDTD) approach and fabricated by top-down approach. In our work, we performed the FDTD simulations of various plasmonic lens designs for bacteria sensor, i.e., Samonella and Hominis. We optimized the design parameters, i.e., radius, shape, and material, of the plasmonic lens. The simulation results showed the change in the peak intensity value with the introduction of each bacteria and antigen i.e., peak intensity 1.8711 a.u. with the introduction of antibody layer of thickness of 15nm. For Salmonella, the peak intensity changed from 1.8711 a.u. to 2.3654 a.u. and for Hominis, the peak intensity changed from 1.8711 a.u. to 3.2355 a.u. This significant shift in the intensity due to the interaction between bacteria and antigen showed a promising sensing capability of the plasmonic lens. With the batch processing and bulk production of this nano scale design, the cost of biological sensing can be significantly reduced, holding great promise in the fields of clinical diagnostics and bio-defense.

Keywords: plasmonic lens, FDTD, fabrication, bacteria sensor, salmonella, hominis

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694 Key Success Factors and Enterprise Resource Planning Implementation in Higher Education Institutions: Multiple Case Studies of Jordanian Universities

Authors: Abdallah Abu Madi, Dongmei Cao, Alexeis Garcia-Perez, Qile He

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The failure of Enterprise Resource Planning (ERP) implementation in higher education institutions (HEIs) worldwide is much higher in comparison to other sectors, such as banking or manufacturing, to our knowledge limited research has been conducted on this issue. To date, prior literature has identified some key success factors (KSFs) mostly either in the domain of information and system (IS) or in the industrial context. However, evidence of ERP implementation in the higher education sector has had little attention in the extant literature. Hence, this paper identifies and categories KSFs of ERP implementation in HEIs. Semi-structured face-to-face interviews were conducted with technicians and managers from three Jordanian HEIs. From these case studies, three new sector- and context-specific KSFs were identified and categorized according to two dimensions: organizational and technical. The first new KSF is the selection of the ERP system, which is an influential factor in the organizational dimension. Results show that an ERP solution that is suitable to one context may be disastrous in another. The second new KSF, which falls under the technical dimension, is the relationship between vendors and HEIs. This must be fair and impartial to enable successful decision-making and thus the achievement of pre-defined goals. Also within the technical dimension is the third factor: in-house maintenance. Once an appropriate system is selected and a strong relationship is established, the ERP system requires continuous maintenance for effective operation. HEIs should ensure that qualified IT support is in place and in-house to avoid excessive running expenses.

Keywords: Enterprise Resource Planning (ERP)implementation, key success factors, higher education institutions, Jordanian higher education

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693 Performance Assessment of Carrier Aggregation-Based Indoor Mobile Networks

Authors: Viktor R. Stoynov, Zlatka V. Valkova-Jarvis

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The intelligent management and optimisation of radio resource technologies will lead to a considerable improvement in the overall performance in Next Generation Networks (NGNs). Carrier Aggregation (CA) technology, also known as Spectrum Aggregation, enables more efficient use of the available spectrum by combining multiple Component Carriers (CCs) in a virtual wideband channel. LTE-A (Long Term Evolution–Advanced) CA technology can combine multiple adjacent or separate CCs in the same band or in different bands. In this way, increased data rates and dynamic load balancing can be achieved, resulting in a more reliable and efficient operation of mobile networks and the enabling of high bandwidth mobile services. In this paper, several distinct CA deployment strategies for the utilisation of spectrum bands are compared in indoor-outdoor scenarios, simulated via the recently-developed Realistic Indoor Environment Generator (RIEG). We analyse the performance of the User Equipment (UE) by integrating the average throughput, the level of fairness of radio resource allocation, and other parameters, into one summative assessment termed a Comparative Factor (CF). In addition, comparison of non-CA and CA indoor mobile networks is carried out under different load conditions: varying numbers and positions of UEs. The experimental results demonstrate that the CA technology can improve network performance, especially in the case of indoor scenarios. Additionally, we show that an increase of carrier frequency does not necessarily lead to improved CF values, due to high wall-penetration losses. The performance of users under bad-channel conditions, often located in the periphery of the cells, can be improved by intelligent CA location. Furthermore, a combination of such a deployment and effective radio resource allocation management with respect to user-fairness plays a crucial role in improving the performance of LTE-A networks.

Keywords: comparative factor, carrier aggregation, indoor mobile network, resource allocation

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692 Numerical Performance Evaluation of a Savonius Wind Turbines Using Resistive Torque Modeling

Authors: Guermache Ahmed Chafik, Khelfellah Ismail, Ait-Ali Takfarines

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The Savonius vertical axis wind turbine is characterized by sufficient starting torque at low wind speeds, simple design and does not require orientation to the wind direction; however, the developed power is lower than other types of wind turbines such as Darrieus. To increase these performances several studies and researches have been developed, such as optimizing blades shape, using passive controls and also minimizing power losses sources like the resisting torque due to friction. This work aims to estimate the performance of a Savonius wind turbine introducing a User Defined Function to the CFD model analyzing resisting torque. This User Defined Function is developed to simulate the action of the wind speed on the rotor; it receives the moment coefficient as an input to compute the rotational velocity that should be imposed on computational domain rotating regions. The rotational velocity depends on the aerodynamic moment applied on the turbine and the resisting torque, which is considered a linear function. Linking the implemented User Defined Function with the CFD solver allows simulating the real functioning of the Savonius turbine exposed to wind. It is noticed that the wind turbine takes a while to reach the stationary regime where the rotational velocity becomes invariable; at that moment, the tip speed ratio, the moment and power coefficients are computed. To validate this approach, the power coefficient versus tip speed ratio curve is compared with the experimental one. The obtained results are in agreement with the available experimental results.

Keywords: resistant torque modeling, Savonius wind turbine, user-defined function, vertical axis wind turbine performances

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691 Ontology-Driven Knowledge Discovery and Validation from Admission Databases: A Structural Causal Model Approach for Polytechnic Education in Nigeria

Authors: Bernard Igoche Igoche, Olumuyiwa Matthew, Peter Bednar, Alexander Gegov

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This study presents an ontology-driven approach for knowledge discovery and validation from admission databases in Nigerian polytechnic institutions. The research aims to address the challenges of extracting meaningful insights from vast amounts of admission data and utilizing them for decision-making and process improvement. The proposed methodology combines the knowledge discovery in databases (KDD) process with a structural causal model (SCM) ontological framework. The admission database of Benue State Polytechnic Ugbokolo (Benpoly) is used as a case study. The KDD process is employed to mine and distill knowledge from the database, while the SCM ontology is designed to identify and validate the important features of the admission process. The SCM validation is performed using the conditional independence test (CIT) criteria, and an algorithm is developed to implement the validation process. The identified features are then used for machine learning (ML) modeling and prediction of admission status. The results demonstrate the adequacy of the SCM ontological framework in representing the admission process and the high predictive accuracies achieved by the ML models, with k-nearest neighbors (KNN) and support vector machine (SVM) achieving 92% accuracy. The study concludes that the proposed ontology-driven approach contributes to the advancement of educational data mining and provides a foundation for future research in this domain.

Keywords: admission databases, educational data mining, machine learning, ontology-driven knowledge discovery, polytechnic education, structural causal model

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690 Adopting Structured Mini Writing Retreats as a Tool for Undergraduate Researchers

Authors: Clare Cunningham

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Whilst there is a strong global research base on the benefits of structured writing retreats and similar provisions, such as Shut Up and Write events, for academic staff and postgraduate researchers, very little has been published about the worth of such events for undergraduate students. This is despite the fact that, internationally, undergraduate student researchers experience similar pressures, distractions and feelings towards writing as those who are at more senior levels within the academy. This paper reports on a mixed-methods study with cohorts of third-year undergraduate students over the course of four academic years. This involved a range of research instruments adopted over the four years of the study. They include the administration of four questionnaires across three academic years, a collection of ethnographic recordings in the second year, and the collation of reflective journal entries and evaluations from all four years. The final two years of data collection took place during the period of Covid-19 restrictions when writing retreats moved to the virtual space which adds an additional dimension of interest to the analysis. The analysis involved the collation of quantitative questionnaire data to observe patterns in expressions of attitudes towards writing. Qualitative data were analysed thematically and used to corroborate and support the quantitative data when appropriate. The resulting data confirmed that one of the biggest challenges for undergraduate students mirrors those reported in the findings of studies focused on more experienced researchers. This is not surprising, especially given the number of undergraduate students who now work alongside their studies, as well as the increasing number who have caring responsibilities, but it has, as yet, been under-reported. The data showed that the groups of writing retreat participants all had very positive experiences, with accountability, a sense of community and procrastination avoidance some of the key aspects. The analysis revealed the sometimes transformative power of these events for a number of these students in terms of changing the way they viewed writing and themselves as writers. The data presented in this talk will support the proposal that retreats should much more widely be offered to undergraduate students across the world.

Keywords: academic writing, students, undergraduates, writing retreat

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689 Precoding-Assisted Frequency Division Multiple Access Transmission Scheme: A Cyclic Prefixes- Available Modulation-Based Filter Bank Multi-Carrier Technique

Authors: Ying Wang, Jianhong Xiang, Yu Zhong

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The offset Quadrature Amplitude Modulation-based Filter Bank Multi-Carrier (FBMC) system provides superior spectral properties over Orthogonal Frequency Division Multiplexing. However, seriously affected by imaginary interference, its performances are hampered in many areas. In this paper, we propose a Precoding-Assisted Frequency Division Multiple Access (PA-FDMA) modulation scheme. By spreading FBMC symbols into the frequency domain and transmitting them with a precoding matrix, the impact of imaginary interference can be eliminated. Specifically, we first generate the coding pre-solution matrix with a nonuniform Fast Fourier Transform and pick the best columns by introducing auxiliary factors. Secondly, according to the column indexes, we obtain the precoding matrix for one symbol and impose scaling factors to ensure that the power is approximately constant throughout the transmission time. Finally, we map the precoding matrix of one symbol to multiple symbols and transmit multiple data frames, thus achieving frequency-division multiple access. Additionally, observing the interference between adjacent frames, we mitigate them by adding frequency Cyclic Prefixes (CP) and evaluating them with a signal-to-interference ratio. Note that PA-FDMA can be considered a CP-available FBMC technique because the underlying strategy is FBMC. Simulation results show that the proposed scheme has better performance compared to Single Carrier Frequency Division Multiple Access (SC-FDMA), etc.

Keywords: PA-FDMA, SC-FDMA, FBMC, non-uniform fast fourier transform

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688 1-D Convolutional Neural Network Approach for Wheel Flat Detection for Freight Wagons

Authors: Dachuan Shi, M. Hecht, Y. Ye

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With the trend of digitalization in railway freight transport, a large number of freight wagons in Germany have been equipped with telematics devices, commonly placed on the wagon body. A telematics device contains a GPS module for tracking and a 3-axis accelerometer for shock detection. Besides these basic functions, it is desired to use the integrated accelerometer for condition monitoring without any additional sensors. Wheel flats as a common type of failure on wheel tread cause large impacts on wagons and infrastructure as well as impulsive noise. A large wheel flat may even cause safety issues such as derailments. In this sense, this paper proposes a machine learning approach for wheel flat detection by using car body accelerations. Due to suspension systems, impulsive signals caused by wheel flats are damped significantly and thus could be buried in signal noise and disturbances. Therefore, it is very challenging to detect wheel flats using car body accelerations. The proposed algorithm considers the envelope spectrum of car body accelerations to eliminate the effect of noise and disturbances. Subsequently, a 1-D convolutional neural network (CNN), which is well known as a deep learning method, is constructed to automatically extract features in the envelope-frequency domain and conduct classification. The constructed CNN is trained and tested on field test data, which are measured on the underframe of a tank wagon with a wheel flat of 20 mm length in the operational condition. The test results demonstrate the good performance of the proposed algorithm for real-time fault detection.

Keywords: fault detection, wheel flat, convolutional neural network, machine learning

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687 Cognitive Impairment in Chronic Renal Patients on Hemodialysis

Authors: Fabiana Souza Orlandi, Juliana Gomes Duarte, Gabriela Dutra Gesualdo

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Chronic renal disease (CKD), accompanied by hemodialysis, causes chronic renal failure in a number of situations that compromises not only physical, personal and environmental aspects, but also psychological, social and family aspects. Objective: To verify the level of cognitive impairment of chronic renal patients on hemodialysis. Methodology: This is a descriptive, cross-sectional study. The present study was performed in a Dialysis Center of a city in the interior of the State of São Paulo. The inclusion criteria were: being 18 years or older; have a medical diagnosis of CKD; being in hemodialysis treatment in this unit; and agree to participate in the research, with the signature of the Informed Consent (TCLE). A total of 115 participants were evaluated through the Participant Characterization Instrument and the Addenbrooke Cognitive Exam - Revised Version (ACE-R), being scored from 0 to 100, stipulating the cut-off note for the complete battery <78 and subdivided into five domains: attention and guidance; memory; fluency; language; (66.9%) and caucasian (54.7%), 53.7 (±14.8) years old. Most of the participants were retired (74.7%), with incomplete elementary schooling (36.5%) and the average time of treatment was 46 months. Most of the participants (61.3%) presented impairment in the area of attention and orientation, 80.4% in the spatial visual domain. Regarding the total ACE-R score, 75.7% of the participants presented scores below the established cut grade. Conclusion: There was a high percentage (75.7%) below the cut-off score established for ACE-R, suggesting that there may be some cognitive impairment among these participants, since the instrument only performs a screening on cognitive health. The results of the study are extremely important so that possible interventions can be traced in order to minimize impairment, thus improving the quality of life of chronic renal patients.

Keywords: cognition, chronic renal insufficiency, adult health, dialysis

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