Search results for: vision transformers

Authors: Olena Kovalchuk

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How to define the understanding of social responsibility issues by Ukrainian companies is a contravention question. Thus, one of the practical uses of social responsibility is a diagnostic tool development for educational, business or scientific purposes. So the purpose of this research is to develop a tool for measurement of social responsibility in organization. Methodology: A 21-item questionnaire “Organization Social Responsibility Scale” was developed. This tool was adapted for the Ukrainian sample and based on the questionnaire “Perceived Role of Ethics and Social Responsibility” which connects ethical and socially responsible behavior to different aspects of the organizational effectiveness. After surveying the respondents, the factor analysis was made by the method of main compounds with orthogonal rotation VARIMAX. On the basis of the obtained results the 21-item questionnaire was developed (Cronbach’s alpha – 0,768; Inter-Item Correlations – 0,34). Participants: 121 managers at all levels of Ukrainian organizations (57 males; 65 females) took part in the research. Results: Factor analysis showed five ethical dilemmas concerning the social responsibility and profit compatibility in Ukrainian organizations. Below we made an attempt to interpret them: — Social responsibility vs profit. Corporate social responsibility can be a way to reduce operational costs. A firm’s first priority is employees’ morale. Being ethical and socially responsible is the priority of the organization. The most loaded question is "Corporate social responsibility can reduce operational costs". Significant effect of this factor is 0.768. — Profit vs social responsibility. Efficiency is much more important to a firm than ethics or social responsibility. Making the profit is the most important concern for a firm. The dominant question is "Efficiency is much more important to a firm than whether or not the firm is seen as ethical or socially responsible". Significant effect of this factor is 0.793. — A balanced combination of social responsibility and profit. Organization with social responsibility policy is more attractive for its stakeholders. The most loaded question is "Social responsibility and profitability can be compatible". Significant effect of this factor is 0.802. — Role of Social Responsibility in the successful organizational performance. Understanding the value of social responsibility and business ethics. Well-being and welfare of the society. The dominant question is "Good ethics is often good business". Significant effect of this factor is 0.727. — Global vision of social responsibility. Issues related to global social responsibility and sustainability. Innovative approaches to poverty reduction. Awareness of climate change problems. Global vision for successful business. The dominant question is "The overall effectiveness of a business can be determined to a great extent by the degree to which it is ethical and socially responsible". Significant effect of this factor is 0.842. The theoretical contribution. The perspective of the study is to develop a tool for measurement social responsibility in organizations and to test questionnaire’s adequacy for social and cultural context. Practical implications. The research results can be applied for designing a training programme for business school students to form their global vision for successful business as well as the ability to solve ethical dilemmas in managerial practice. Researchers interested in social responsibility issues are welcome to join the project.

Keywords: corporate social responsibility, Cronbach’s alpha, ethical behaviour, psychodiagnostic tool

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Authors: R. Pääkkönen, L. Korpinen

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This study aimed to evaluate parameters influencing well-being and how to maintain well-being as long as possible after retirement. There is contradictory information on the health changes after retirement in Finland. This work is based on interviews, statistics, and literature evaluation of Finland. Most often, balance, multitasking reaction time, and adaptation of vision in dim and darks areas are worsened. Slowing is one characteristic that is difficult to measure properly. The most important is try to determine ways to manage daily activities and symptoms of disease after retirement. Medicine is advancing, problems are often also on the economic side. Information of technical aids is important. It is worth planning a retirement age.

Keywords: retirement, working, aging, wellness

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Authors: Aderonke Oluseun Akinwumi, Olusola A. Komolaf

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This paper gives information about the wide array of challenges facing both the electric utilities and consumers in the distribution system in developing countries, using Obafemi Awolowo University, Ile-Ife Nigeria as a case study. It also proffers cost-effective solution through remote monitoring, diagnostic and operation of distribution networks without compromising the system reliability. As utilities move from manned and unintelligent networks to completely unmanned smart grids, switching activities at substations and feeders will be managed and controlled remotely by dedicated systems hence this design. The Substation Remote Diagnostic and Operation Solution (sRDOs) would remotely monitor the load on Medium Voltage (MV) and Low Voltage (LV) feeders as well as distribution transformers and allow the utility disconnect non-paying customers with absolutely no extra resource deployment and without interrupting supply to paying customers. The aftermath of the implementation of this design improved the lifetime of key distribution infrastructure by automatically isolating feeders during overload conditions and more importantly erring consumers. This increased the ratio of revenue generated on electricity bills to total network load.

Keywords: electric utility, consumers, remote monitoring, diagnostic, system reliability, manned and unintelligent networks, unmanned smart grids, switching activities, medium voltage, low voltage, distribution transformer

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Authors: Mehrzad Soltani, Pegah Rezaei

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In response to the escalating challenges posed by resource scarcity, urban congestion, and the dearth of green spaces, contemporary urban areas have undergone a remarkable transformation into smart cities. This evolution necessitates a strategic and forward-thinking approach to urban development, with the primary objective of diminishing and eventually eradicating dependence on non-renewable energy sources. This steadfast commitment to sustainable development is geared toward the continual enhancement of our global urban milieu, ensuring a healthier and more prosperous environment for forthcoming generations. This transformative vision has been meticulously shaped by an extensive research framework, incorporating in-depth field studies and investigations conducted at both neighborhood and city levels. Our holistic strategy extends its purview to encompass major cities and states, advocating for the realization of exceptional development firmly rooted in the principles of sustainable intelligence. At its core, this approach places a paramount emphasis on stringent pollution control measures, concurrently safeguarding ecological equilibrium and regional cohesion. Central to the realization of this vision is the widespread adoption of environmentally friendly materials and components, championing the cultivation of plant life and harmonious green spaces, and the seamless integration of intelligent lighting and irrigation systems. These systems, including solar panels and solar energy utilization, are deployed wherever feasible, effectively meeting the essential lighting and irrigation needs of these dynamic urban ecosystems. Overall, the transformation of urban areas into smart cities necessitates a holistic and innovative approach to urban development. By actively embracing sustainable intelligence and adhering to strict environmental standards, these cities pave the way for a brighter and more sustainable future, one that is marked by resilient, thriving, and eco-conscious urban communities.

Keywords: smart city, green urban, sustainability, urban management

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Authors: Niaz Gharavi, Hexin Zhang

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In the structural timber design, the shear modulus of the timber beam is an important factor that needs to be determined accurately. According to BS EN 408, shear modulus can be determined using torsion test or shear field test method. Although torsion test creates pure shear status in the beam, it does not represent the real-life situation when the beam is in the service. On the other hand, shear field test method creates similar loading situation as in reality. The latter method is based on shear distortion measurement of the beam at the zone with the constant transverse load in the standardized four-point bending test as indicated in BS EN 408. Current testing practice code advised using two metallic arms act as an instrument to measure the diagonal displacement of the constructing square. Timber is not a homogenous material, but a heterogeneous and this characteristic makes timber to undergo a non-uniform deformation. Therefore, the dimensions and the location of the constructing square in the area with the constant transverse force might alter the shear modulus determination. This study aimed to investigate the impact of the shape, size, and location of the square in the shear field test method. A binocular stereo vision system was developed to capture the 3D displacement of a grid of target points. This approach is an accurate and non-contact method to extract the 3D coordination of targeted object using two cameras. Two group of three glue laminated beams were produced and tested by the mean of four-point bending test according to BS EN 408. Group one constructed using two materials, laminated bamboo lumber and structurally graded C24 timber and group two consisted only structurally graded C24 timber. Analysis of Variance (ANOVA) was performed on the acquired data to evaluate the significance of size and location of the square in the determination of shear modulus of the beam. The results have shown that the size of the square is an affecting factor in shear modulus determination. However, the location of the square in the area with the constant shear force does not affect the shear modulus.

Keywords: shear field test method, BS EN 408, timber shear modulus, photogrammetry approach

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Authors: Nataša Stojić, Mira Pucarević, Nebojša Ralević, Vojislava Bursić, Gordan Stojić

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Surface soil (0 – 10 cm) samples from 52 sampling sites along the length of railway tracks on the territory of Srem (the western part of the Autonomous Province of Vojvodina, itself part of Serbia) were collected and analyzed for 7 polychlorinated biphenyls (PCBs) in order to see how the distance from the railroad on the one hand and dump on the other hand, affect the concentration of PCBs (CPCBs) in the soil. Samples were taken at a distance of 0.03 to 4.19 km from the railway and 0.43 to 3.35 km from the landfills. For the soil extraction the Soxhlet extraction (USEPA 3540S) was used. The extracts were purified on a silica-gel column (USEPA 3630C). The analysis of the extracts was performed by gas chromatography with tandem mass spectrometry. PCBs were not detected only at two locations. Mean total concentration of PCBs for all other sampling locations was 0,0043 ppm dry weight (dw) with a range of 0,0005 to 0,0227 ppm dw. On the part of the data that were interesting for this research with statistical methods (PCA) were isolated factors that affect the concentration of PCBs. Data were also analyzed using the Pearson's chi-squared test which showed that the hypothesis of independence of CPCBs and distance from the railway can be rejected. Hypothesis of independence between CPCB and the percentage of humus in the soil can also be rejected, in contrast to dependence of CPCB and the distance from the landfill where the hypothesis of independence cannot be rejected. Based on these results can be said that railway transport is a potential source of PCBs. The next step in this research is to establish the position of transformers which are located near sampling sites as another important factor that affects the concentration of PCBs in the soil.

Keywords: GC/MS, landfill, PCB, railway, soil

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Authors: Deepa S N, Srinivasan a D, Veeramanju K T

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The power transformer is a critical equipment in the transmission and distribution network that must be managed to ensure uninterrupted power service. The liquid insulation is essential for the proper functioning of the transformer, as it serves as both coolant and insulating medium, which influences the transformer’s durability. Further, the insulating state of a power transformer has a significant impact on its reliability. Mineral oil derived from petroleum crude oil has been employed as liquid dielectrics for decades due to its superior functional characteristics, however as a resource for the same are getting depleted over the years. Research is undertaken across the globe to identify a viable substitute for mineral oil. Further, alternate insulating oils are being investigated for better environmental impact, biodegradability and economics. Several combinations of vegetable oil derived natural esters are being inspected by researchers across the globe in these domains. In this work, mineral oil is blended with soyabean oil with various proportions and dielectric properties such as dielectric breakdown voltage, relative permittivity, dissipation factor, viscosity, flash and fire point have been investigated according to international standards. A quantitative comparison is made among various samples and is observed that the blended oil sample of equal proportion of mineral oil and soyabean oil, MO50+SO50 exhibits superior dielectric properties such as breakdown voltage of 65kV, dissipation factor of 0.0044, relative permittivity of 3.1680 that are closer to the range of values recommended for power transformer applications. Also, Breakdown voltage values of all the investigated oil samples obeyed the Weibull and Normal probability distribution.

Keywords: blended oil, dielectric breakdown, liquid insulation, power transformer

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Authors: Huailei Wen

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The Kramers vs. Kramers (1979) is a film that comprehensively examines the role and status of women under the traditional secular vision, where women have become subordinate to the patriarchal society and family. Through the construction of the protagonist Joanna's dissatisfaction with the social and ethical status quo, her struggle to subvert the existing status of women, and her return to her own self, the story comprehensively reflects the difficult journey of women, represented by Joanna, to subvert the stereotypes and return to their own selves in the specific historical context of the time, revealing the self-value of Joanna's phenomenon to modern women.

Keywords: star image, feminism, Kramers vs. Kramers, Hollywood

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Authors: I. Hakki Eraslan, Birol Ozturk, Istemi Comlekci

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This paper begins by defining what is meant by “globalization” in finance and by identifying the sources of value-added in the internationally-competitive financial services sector origination, trading and distribution of debt and equity capital market instruments and their derivatives, foreign exchange trading and securities brokerage, management of market risk and credit risk, loan syndication and structured bank financings, corporate finance and advisory services, and asset management. These activities are considered in terms of a “value-chain” one that ultimately gives rise to the real economic gains attributable to financial-center operations. The research presents available evidence as to where the relevant value-added activities usually take place. It then examines the “centrifugal” and “centripetal” forces that determine the concentration or dispersal of value-added activity in financial intermediation, both interregionally and internationally. Next, the research assesses the factors, which appear to underlie the locational pattern of international financial centers that has evolved. In preparing this paper, also it is examined the current position and the main opportunities and challenges facing world major financial services sector, and attempted to lay out a potential vision and strategies. It is conducted extensive research, including many internal research materials and publications. It is also engaged closely with the academia, industry practitioners and regulators, and consulted market experts from major world financial centers. More than 60 in‐depth consultative sessions were conducted in the past two years which provided insightful suggestions and innovative ideas on how to further financial industry’s position as an international financial centre. The paper concludes with the outlook for the future pattern of financial centers in the global competitive environment. The ideas and advice gathered are condensed into this paper that recommends to the strategic decision leaders a vision and a strategy for financial services sector to move forward amid a highly competitive environment.

Keywords: financial centers, competitiveness, financial services industry, economics

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Authors: Reza Nematirad, Anil Pahwa, Balasubramaniam Natarajan

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Time series data consist of successive data points collected over a period of time. Accurate prediction of future values is essential for informed decision-making in several real-world applications, including electricity load demand forecasting, lifetime estimation of industrial machinery, traffic planning, weather prediction, and the stock market. Due to their critical relevance and wide application, there has been considerable interest in time series forecasting in recent years. However, the proliferation of sensors and IoT devices, real-time monitoring systems, and high-frequency trading data introduce significant intricate temporal variations, rapid changes, noise, and non-linearities, making time series forecasting more challenging. Classical methods such as Autoregressive integrated moving average (ARIMA) and Exponential Smoothing aim to extract pre-defined temporal variations, such as trends and seasonality. While these methods are effective for capturing well-defined seasonal patterns and trends, they often struggle with more complex, non-linear patterns present in real-world time series data. In recent years, deep learning has made significant contributions to time series forecasting. Recurrent Neural Networks (RNNs) and their variants, such as Long short-term memory (LSTMs) and Gated Recurrent Units (GRUs), have been widely adopted for modeling sequential data. However, they often suffer from the locality, making it difficult to capture local trends and rapid fluctuations. Convolutional Neural Networks (CNNs), particularly Temporal Convolutional Networks (TCNs), leverage convolutional layers to capture temporal dependencies by applying convolutional filters along the temporal dimension. Despite their advantages, TCNs struggle with capturing relationships between distant time points due to the locality of one-dimensional convolution kernels. Transformers have revolutionized time series forecasting with their powerful attention mechanisms, effectively capturing long-term dependencies and relationships between distant time points. However, the attention mechanism may struggle to discern dependencies directly from scattered time points due to intricate temporal patterns. Lastly, Multi-Layer Perceptrons (MLPs) have also been employed, with models like N-BEATS and LightTS demonstrating success. Despite this, MLPs often face high volatility and computational complexity challenges in long-horizon forecasting. To address intricate temporal variations in time series data, this study introduces Times2D, a novel framework that parallelly integrates 2D spectrogram and derivative heatmap techniques. The spectrogram focuses on the frequency domain, capturing periodicity, while the derivative patterns emphasize the time domain, highlighting sharp fluctuations and turning points. This 2D transformation enables the utilization of powerful computer vision techniques to capture various intricate temporal variations. To evaluate the performance of Times2D, extensive experiments were conducted on standard time series datasets and compared with various state-of-the-art algorithms, including DLinear (2023), TimesNet (2023), Non-stationary Transformer (2022), PatchTST (2023), N-HiTS (2023), Crossformer (2023), MICN (2023), LightTS (2022), FEDformer (2022), FiLM (2022), SCINet (2022a), Autoformer (2021), and Informer (2021) under the same modeling conditions. The initial results demonstrated that Times2D achieves consistent state-of-the-art performance in both short-term and long-term forecasting tasks. Furthermore, the generality of the Times2D framework allows it to be applied to various tasks such as time series imputation, clustering, classification, and anomaly detection, offering potential benefits in any domain that involves sequential data analysis.

Keywords: derivative patterns, spectrogram, time series forecasting, times2D, 2D representation

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Authors: Eduardo Álvarez, Gerardo Quiroga, Jorge Orozco, Gabriel Chavira

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AmI proposes a new way of thinking about computers, which follows the ideas of the Ubiquitous Computing vision of Mark Weiser. In these, there is what is known as a Disappearing Computer Initiative, with users immersed in intelligent environments. Hence, technologies need to be adapted so that they are capable of replacing the traditional inputs to the system by embedding these in every-day artifacts. In this work, we present an approach, which uses Radiofrequency Identification (RFID) and Near Field Communication (NFC) technologies. In the latter, a new form of interaction appears by contact. We compare both technologies by analyzing their requirements and advantages. In addition, we propose using a combination of RFID and NFC.

Keywords: touching interaction, ambient intelligence, ubiquitous computing, interaction, NFC and RFID

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Authors: Rob van den Dam

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Today’s Internet of Things (IoT) comprises more than a billion intelligent devices, connected via wired/wireless communications. The expected proliferation of hundreds of billions more places us at the threshold of a transformation sweeping across the communications industry. Yet, we found that the IoT architecture and solutions that currently work for billions of devices won’t necessarily scale to tomorrow’s hundreds of billions of devices because of high cost, lack of privacy, not future-proof, lack of functional value and broken business models. As the IoT scales exponentially, decentralized networks have the potential to reduce infrastructure and maintenance costs to manufacturers. Decentralization also promises increased robustness by removing single points of failure that could exist in traditional centralized networks. By shifting the power in the network from the center to the edges, devices gain greater autonomy and can become points of transactions and economic value creation for owners and users. To validate the underlying technology vision, IBM jointly developed with Samsung Electronics the autonomous decentralized peer-to- peer proof-of-concept (PoC). The primary objective of this PoC was to establish a foundation on which to demonstrate several capabilities that are fundamental to building a decentralized IoT. Though many commercial systems in the future will exist as hybrid centralized-decentralized models, the PoC demonstrated a fully distributed proof. The PoC (a) validated the future vision for decentralized systems to extensively augment today’s centralized solutions, (b) demonstrated foundational IoT tasks without the use of centralized control, (c) proved that empowered devices can engage autonomously in marketplace transactions. The PoC opens the door for the communications and electronics industry to further explore the challenges and opportunities of potential hybrid models that can address the complexity and variety of requirements posed by the internet that continues to scale. Contents: (a) The new approach for an IoT that will be secure and scalable, (b) The three foundational technologies that are key for the future IoT, (c) The related business models and user experiences, (d) How such an IoT will create an 'Economy of Things', (e) The role of users, devices, and industries in the IoT future, (f) The winners in the IoT economy.

Keywords: IoT, internet, wired, wireless

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Authors: Shanaka Gunasekara, Maleen Jayasuriya, Nalin Harischandra, Lilantha Samaranayake, Gamini Dissanayake

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One serious facet of the worsening Human-Elephant conflict (HEC) in nations such as Sri Lanka involves elephant-train collisions. Endangered Asian elephants are maimed or killed during such accidents, which also often result in orphaned or disabled elephants, contributing to the phenomenon of lone elephants. These lone elephants are found to be more likely to attack villages and showcase aggressive behaviour, which further exacerbates the overall HEC. Furthermore, Railway Services incur significant financial losses and disruptions to services annually due to such accidents. Most elephant-train collisions occur due to a lack of adequate reaction time. This is due to the significant stopping distance requirements of trains, as the full braking force needs to be avoided to minimise the risk of derailment. Thus, poor driver visibility at sharp turns, nighttime operation, and poor weather conditions are often contributing factors to this problem. Initial investigations also indicate that most collisions occur in localised “hotspots” where elephant pathways/corridors intersect with railway tracks that border grazing land and watering holes. Taking these factors into consideration, this work proposes the leveraging of recent developments in Convolutional Neural Network (CNN) technology to detect elephants using an RGB/infrared capable camera around known hotspots along the railway track. The CNN was trained using a curated dataset of elephants collected on field visits to elephant sanctuaries and wildlife parks in Sri Lanka. With this vision-based detection system at its core, a prototype unit of an early warning system was designed and tested. This weatherised and waterproofed unit consists of a Reolink security camera which provides a wide field of view and range, an Nvidia Jetson Xavier computing unit, a rechargeable battery, and a solar panel for self-sufficient functioning. The prototype unit was designed to be a low-cost, low-power and small footprint device that can be mounted on infrastructures such as poles or trees. If an elephant is detected, an early warning message is communicated to the train driver using the GSM network. A mobile app for this purpose was also designed to ensure that the warning is clearly communicated. A centralized control station manages and communicates all information through the train station network to ensure coordination among important stakeholders. Initial results indicate that detection accuracy is sufficient under varying lighting situations, provided comprehensive training datasets that represent a wide range of challenging conditions are available. The overall hardware prototype was shown to be robust and reliable. We envision a network of such units may help contribute to reducing the problem of elephant-train collisions and has the potential to act as an important surveillance mechanism in dealing with the broader issue of human-elephant conflicts.

Keywords: computer vision, deep learning, human-elephant conflict, wildlife early warning technology

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Authors: Eric Bonetto, Anthony Piermatteo, Fabien Girandola, Gregory Lo Monaco

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The present contribution focuses on the effect of the structure of social representations on group identification. A social representation (SR) is defined as an organized and structured set of cognitions, produced and shared by members of a same group about a same social object. Within this framework, the central core theory establishes a structural distinction between central cognitions – or 'core' – and peripheral ones: the former are theoretically considered as more connected than the later to group members’ social identity and may play a greater role in SRs’ ability to allow group identification by means of a common vision of the object of representation. Indeed, the central core provides a reference point for the in-group as it constitutes a consensual vision that gives meaning to a social object particularly important to individuals and to the group. However, while numerous contributions clearly refer to the underlying role of SRs in group identification, there are only few empirical evidences of this aspect. Thus, we hypothesize an effect of the structure of SRs on group identification. More precisely, central cognitions (vs. peripheral ones) will lead to a stronger group identification. In addition, we hypothesize that the refutation of a cognition will lead to a stronger group identification than its activation. The SR mobilized here is that of 'studying' among a population of first-year undergraduate psychology students. Thus, a pretest (N = 82), using an Attribute-Challenge Technique, was designed in order to identify the central and the peripheral cognitions to use in the primings of our main study. The results of this pretest are in line with previous studies. Then, the main study (online; N = 184), using a social priming methodology, was based on a 2 (Structural status of the cognitions belonging to the prime: central vs. peripheral) x 2 (Type of prime: activation vs. refutation) experimental design in order to test our hypotheses. Results revealed, as expected, the main effect of the structure of the SR on group identification. Indeed, central cognitions trigger a higher level of identification than the peripheral ones. However, we observe neither effect of the type of prime, nor interaction effect. These results experimentally demonstrate for the first time the effect of the structure of SRs on group identification and indicate that central cognitions are more connected than peripheral ones to group members’ social identity. These results will be discussed considering the importance of understanding identity as a function of SRs and on their ability to potentially solve the lack of consideration of the definition of the group in Social Representations Theory.

Keywords: group identification, social identity, social representations, structural approach

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Authors: Helena M. Wilhelm, Paulo O. Fernandes, Laís P. Dill, Kethlyn G. Moscon

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The use of vegetable oil (or natural ester) as an insulating fluid in electrical transformers is a trend that aims to contribute to environmental preservation since it is biodegradable and non-toxic. Besides, vegetable oil has high flash and combustion points, being considered a fire safety fluid. However, vegetable oil is usually less stable towards oxidation than mineral oil. Both insulating fluids, mineral and vegetable oils, need to be tested periodically according to specific standards. Oxidation stability can be determined by the induction period measured by conductivity method (Rancimat) by monitoring the effectivity of oil’s antioxidant additives, a methodology already developed for food application and biodiesel but still not standardized for insulating fluids. Besides adequate oxidation stability, fluids must be compatible with transformer's construction materials under normal operating conditions to ensure that damage to the oil and parts of the transformer does not occur. ASTM standard and Brazilian normative differ in parameters evaluated, which reveals the need to regulate tests for each oil type. The aim of this study was to assess oxidation stability and compatibility of vegetable oils to suggest the best way to assure a viable performance of vegetable oil as transformer insulating fluid. The determination of the induction period for several vegetable insulating oils from the local market by using Rancimat was carried out according to BS EN 14112 standard, at different temperatures (110, 120, and 130 °C). Also, the compatibility of vegetable oil was assessed according to ASTM and ABNT NBR standards. The main results showed that the best temperature for use in the Rancimat test is 130 °C, which allows a better observation of conductivity change. The compatibility test results presented differences between vegetable and mineral oil standards that should be taken into account in oil testing since materials compatibility and oxidation stability are essential for equipment reliability.

Keywords: compatibility, Rancimat, natural ester, vegetable oil

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Authors: Giovanna Borges Bottino, Luis Felipe Freitas do Nascimento Alves Teixeira

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This article aims to present a case study of the National Civil Aviation Agency (ANAC) in Brazil, ANAC-id. ANAC-id is the artificial intelligence algorithm developed for image analysis that recognizes standard images of unobstructed and uprighted face without sunglasses, allowing to identify potential inconsistencies. It combines YOLO architecture and 3 libraries in python - face recognition, face comparison, and deep face, providing robust analysis with high level of accuracy.

Keywords: artificial intelligence, deepface, face compare, face recognition, YOLO, computer vision

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Authors: Daniel Li

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We present a novel application of neural rendering methods to confocal microscopy. Neural rendering and implicit neural representations have developed at a remarkable pace, and are prevalent in modern 3D computer vision literature. However, they have not yet been applied to optical microscopy, an important imaging field where 3D volume information may be heavily sought after. In this paper, we employ neural rendering on confocal microscopy focus stack data and share the results. We highlight the benefits and potential of adding neural rendering to the toolkit of microscopy image processing techniques.

Keywords: neural rendering, implicit neural representations, confocal microscopy, medical image processing

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Authors: Tesfaye Mengistu

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Power cables play a crucial role in the transmission and distribution of electrical energy. As the electricity generation, transmission, distribution, and storage systems become smarter, there is a growing emphasis on incorporating intelligent approaches to ensure the reliability of power cables. Various types of electrical cables are employed for transmitting and distributing electrical energy, with cross-linked polyethylene (XLPE) cables being widely utilized due to their exceptional electrical and mechanical properties. However, insulation defects can occur in XLPE cables due to subpar manufacturing techniques during production and cable joint installation. To address this issue, experts have proposed different methods for monitoring XLPE cables. Some suggest the use of interdigital capacitive (IDC) technology for online monitoring, while others propose employing continuous wave (CW) terahertz (THz) imaging systems to detect internal defects in XLPE plates used for power cable insulation. In this study, we have developed models that employ a custom dataset collected locally to classify the physical safety status of individual power cables. Our models aim to replace physical inspections with computer vision and image processing techniques to classify defective power cables from non-defective ones. The implementation of our project utilized the Python programming language along with the TensorFlow package and a convolutional neural network (CNN). The CNN-based algorithm was specifically chosen for power cable defect classification. The results of our project demonstrate the effectiveness of CNNs in accurately classifying power cable defects. We recommend the utilization of similar or additional datasets to further enhance and refine our models. Additionally, we believe that our models could be used to develop methodologies for detecting power cable defects from live video feeds. We firmly believe that our work makes a significant contribution to the field of power cable inspection and maintenance. Our models offer a more efficient and cost-effective approach to detecting power cable defects, thereby improving the reliability and safety of power grids.

Keywords: artificial intelligence, computer vision, defect detection, convolutional neural net

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Authors: Gabriel A. Orozco

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The purpose of this article is to make an approach to the Security Studies, exposing their theories and concepts to understand the role that have had in the interpretation of the changes and continuities of the world order and their impact on policies or decision-making facing the problems of the 21st century. The aim is to build a bridge between the security studies as a subfield and the meaning that has been given to the world order. The idea of epistemic communities serves as a methodological proposal about the different programs of research in security studies, showing their influence in the realities of States, intergovernmental organizations and transnational forces, moving to implement, perpetuate and project a vision of the world order.

Keywords: security studies, epistemic communities, international, relations

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Authors: Marcos Valdez Alexander Junior, Igor Aguilar-Alonso

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Malnutrition is the root of different diseases that universally affect everyone, diseases such as obesity and malnutrition. The objective of this research is to predict the calories of the food to be eaten, developing a smart mobile application to show the user if a meal is balanced. Due to the large percentage of obesity and malnutrition in Peru, the present work is carried out. The development of the intelligent application is proposed with a three-layer architecture, and for the prediction of the nutritional value of the food, the use of pre-trained models based on convolutional neural networks is proposed.

Keywords: volume estimation, calorie estimation, artificial vision, food nutrition

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Authors: Aberdam Edith, Sangari Linda, Petit Isabelle, Aberdam Daniel

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Background and Rationale: Transparent avascularised cornea is essential for normal vision and depends on limbal stem cells (LSC) that reside between the cornea and the conjunctiva. Ocular burns or injuries may destroy the limbus, causing limbal stem cell deficiency (LSCD). The cornea becomes vascularised by invaded conjunctival cells, the stroma is scarring, resulting in corneal opacity and loss of vision. Grafted autologous limbus or cultivated autologous LCS can restore the vision, unless the two eyes are affected. Alternative cellular sources have been tested in the last decades, including oral mucosa or hair follicle epithelial cells. However, only partial success has been achieved by the use of these cells since they were not able to uniformly commit into corneal epithelial cells. Human pluripotent stem cells (iPSC) display both unlimited growth capacity and ability to differentiate into any cell type. Our goal was to design a standardized and reproducible protocol to produce transplantable autologous LSC from patients through cell reprogramming technology. Methodology: First, keratinocyte primary culture was established from a small number of plucked hair follicles of healthy donors. The resulting epithelial cells were reprogrammed into induced pluripotent stem cells (iPSCs) and further differentiate into corneal epithelial cells (CEC), according to a robust protocol that recapitulates the main step of corneal embryonic development. qRT-PCR analysis and immunofluorescent staining during the course of differentiation confirm the expression of stage specific markers of corneal embryonic lineage. First appear ectodermal progenitor-specific cytokeratins K8/K18, followed at day 7 by limbal-specific PAX6, TP63 and cytokeratins K5/K14. At day 15, K3/K12+-corneal cells are present. To amplify the iPSC-derived LSC (named COiPSC), intact small epithelial colonies were detached and cultivated in limbal cell-specific medium. In that culture conditions, the COiPSC can be frozen and thaw at any passage, while retaining their corneal characteristics for at least eight passages. To evaluate the potential of COiPSC as an alternative ocular toxicity model, COiPSC were treated at passage P0 to P4 with increasing amounts of SDS and Benzalkonium. Cell proliferation and apoptosis of treated cells was compared to LSC and the SV40-immortalized human corneal epithelial cell line (HCE) routinely used by cosmetological industrials. Of note, HCE are more resistant to toxicity than LSC. At P0, COiPSC were systematically more resistant to chemical toxicity than LSC and even to HCE. Remarkably, this behavior changed with passage since COiPSC at P2 became identical to LSC and thus closer to physiology than HCE. Comparative transcriptome analysis confirmed that COiPSC from P2 are similar to a mixture of LSC and CEC. Finally, by organotypic reconstitution assay, we demonstrated the ability of COiPSC to produce a 3D corneal epithelium on a stromal equivalent made of keratocytes. Conclusion: COiPSC could become valuable for two main applications: (1) an alternative robust tool to perform, in a reproducible and physiological manner, toxicity assays for cosmetic products and pharmacological tests of drugs. (2). COiPSC could become an alternative autologous source for cornea transplantation for LSCD.

Keywords: Limbal stem cell deficiency, iPSC, cornea, limbal stem cells

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Authors: Kofi Quartey, Kola Ijasan

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Achieving densification around transit-oriented development projects has proven the most ideal way of facilitating urban sprawl whilst increasing the mobility of the majority of the urban populations, making parts of the city that were inaccessible, accessible. Johannesburg has undertaken TOD vision, which was initially called the corridors of freedom. The TOD, in line with the Sustainable Development Goal 11, seeks to establish inclusive, sustainable cities and, in line with the Joburg Growth Development Strategy, aims to create an equitable world-class African city. Equity and inclusivity should occur from the onset of planning and implementation of TOD projects through meaningful community participation. Stakeholder engagement literature from various disciplinary backgrounds has documented dissatisfaction of communities regarding the lack of meaningful participation in government-led development initiatives. The views of other project stakeholders such as project policy planners and project implementors and their challenges in undertaking community participation are, however, not taken into account in such instances, leaving room for a biased perspective. Document analysis was undertaken to determine what is expected of the Project stakeholders according to policy and whether they carried out their duties) seven interviews were also conducted with city entities and community representatives to determine their experiences and challenges with community participation in the various TOD projects attributed to the CoF vision. The findings of the study indicated that stakeholder engagement processes were best described as an ‘educative process’; where local communities were limited to being informed from the onset rather than having an active involvement in the planning processes. Most community members felt they were being informed and educated as to what was going to happen in spite of having their views and opinions collected – primarily due to project deadlines and budget constraints, as was confirmed by professional stakeholders. Some community members exhibited reluctance to change due to feelings of having projects being imposed on them, and the implications of the projects on their properties and lifestyles. It is recommended that community participation should remain a participatory and engaging process that creates an exchange of knowledge and understanding in the form of a dialogue between communities and project stakeholders until a consensus is reached.

Keywords: stakeholder engagement, transit oriented development, community participation, Johannesburg

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Authors: Victoria H. Hamilton

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Charles Bonnet Syndrome (CBS) is when a person experiences pseudohallucinations that fill in visual information from any type of sight loss. CBS arises from an epiphenomenal process, with the physical actions of sight resulting in the mental formations of images. These pseudohallucinations—referred to as visions by the CBS community—manifest in a wide range of forms, from complex scenes to simple geometric shapes. To share these unique visual experiences, a remote co-creation website was created where CBS participants communicated their lived experiences. This created a reflexive process, and we worked to produce true representations of these interesting and little-known phenomena. Digital reconstruction of the visions is utilised as it echoes the vivid, experiential movie-like nature of what is being perceived. This paper critically analyses co-creation as a method for making digital assets. The implications of the participants' vision impairments and the application of ethical safeguards are examined in this context. Important to note, this research is of a medical syndrome for a non-medical, practice-based design. CBS research to date is primarily conducted by the ophthalmic, neurological, and psychiatric fields and approached with the primary concerns of these specialties. This research contributes a distinct approach incorporating practice-based digital design, autoethnography, and phenomenology. Autoethnography and phenomenology combine as a foundation, with the first bringing understanding and insights, balanced by the second philosophical, bigger picture, and established approach. With further refining, it is anticipated that the research may be applied to other conditions. Conditions where articulating internal experiences proves challenging and the use of digital methods could aid communication. Both the research and CBS communities will benefit from the insights regarding the relationship between cognitive perceptions and the vision process. This research combines the digital visualising of visions with interest in the link between metaphor, embodied cognition, and image. The argument for a link between CBS visions and metaphor may appear evident due to the cross-category mapping of images that is necessary for comprehension. They both are— CBS visions and metaphors—the experience of picturing images, often with lateral connections and imaginative associations.

Keywords: Charles Bonnet Syndrome, digital design, visual hallucinations, visual perception

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Authors: Ersumo Tessema, Bogale Girmaye Tamrat, Mohammed Burka

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Background: Hyperthyroidism is a common thyroid disorder especially in women and characterized by increased thyroid hormone synthesis and secretion. The disorder manifests predominantly as Graves’ disease in iodine-sufficient areas and has increasing prevalence in iodine-deficient countries in patients with nodular thyroid disease and following iodine fortification. In Ethiopia, the magnitude of the disorder is unknown and, in Africa, due to scarcity of resources, its management remains suboptimal. Objective: The aim of this study was to analyze the pattern and management of patients with hyperthyroidism at the United Vision Medical Services Center, Addis Ababa between August 30, 2013, and February 1, 2018. Patients and methods: The study was a retrospective analysis of medical records of all patients with hyperthyroidism at the United Vision Private Medical Services Center, Addis Ababa. A questionnaire was filled out; the collected data entered into a computer and statistically analyzed using the SPSS package. The results were tabulated and discussed with literature review. Results: A total of 589 patients were included in this study. The median age was 40 years, and the male to female ratio was 1.0:7.9. Most patients (93%) presented with goiter and the associated features of toxic goiter except weight loss, sweating and tachycardia were uncommon. Majority of patients presented more than two years after the onset of their presenting symptoms. The most common physical finding (91%), as well as diagnosis, was toxic nodular goiter. The most frequent (83%) derangement in the thyroid function tests was a low thyroid-stimulating hormone, and the most commonly (94%) used antithyroid drug was a propylthiouracil. The most common (96%) surgical procedure in 213 patients was a near-total thyroidectomy with a postoperative course without incident in 92% of all the patients. Conclusion: The incidence and prevalence of hyperthyroidism are apparently on the increase in Addis Ababa, which may be related to the existing severe iodine-deficiency and or the salt iodation program (iodine-induced hyperthyroidism). Hyperthyroidism predominantly affects women and, in surgical services, toxic nodular goiter is more common than diffuse goiter, and the treatment of choice in experienced hands is a near-total thyroidectomy.

Keywords: Ethiopia, grave’s disease, hyperthyroidism, toxic nodular goiter

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Authors: R. Schurig, T. Désesquelles, A. Dumont, E. Lefranc, A. Lux

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A cost-efficient alternative is proposed to the use of a single drone carrying multiple cameras in order to take stereoscopic images and videos during its flight. Such drone has to be particularly large enough to take off with its equipment, and stable enough in order to make valid measurements. Corresponding performance for a single aircraft usually comes with a large cost. Proposed solution consists in using multiple smaller and cheaper aircrafts carrying one camera each instead of a single expensive one. To give a proof of concept, AR drones, quad-rotor UAVs from Parrot Inc., are experimentally used.

Keywords: drone squadron, flight control, rotorcraft, Unmanned Aerial Vehicle (UAV), AR drone, stereoscopic vision

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Authors: Vaidehi Murarka, Sneha Mehta, Dishant Upadhyay

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Our project topic is “Alphabet Recognition using pixel probability distribution”. The project uses techniques of Image Processing and Machine Learning in Computer Vision. Alphabet recognition is the mechanical or electronic translation of scanned images of handwritten, typewritten or printed text into machine-encoded text. It is widely used to convert books and documents into electronic files etc. Alphabet Recognition based OCR application is sometimes used in signature recognition which is used in bank and other high security buildings. One of the popular mobile applications includes reading a visiting card and directly storing it to the contacts. OCR's are known to be used in radar systems for reading speeders license plates and lots of other things. The implementation of our project has been done using Visual Studio and Open CV (Open Source Computer Vision). Our algorithm is based on Neural Networks (machine learning). The project was implemented in three modules: (1) Training: This module aims “Database Generation”. Database was generated using two methods: (a) Run-time generation included database generation at compilation time using inbuilt fonts of OpenCV library. Human intervention is not necessary for generating this database. (b) Contour–detection: ‘jpeg’ template containing different fonts of an alphabet is converted to the weighted matrix using specialized functions (contour detection and blob detection) of OpenCV. The main advantage of this type of database generation is that the algorithm becomes self-learning and the final database requires little memory to be stored (119kb precisely). (2) Preprocessing: Input image is pre-processed using image processing concepts such as adaptive thresholding, binarizing, dilating etc. and is made ready for segmentation. “Segmentation” includes extraction of lines, words, and letters from the processed text image. (3) Testing and prediction: The extracted letters are classified and predicted using the neural networks algorithm. The algorithm recognizes an alphabet based on certain mathematical parameters calculated using the database and weight matrix of the segmented image.

Keywords: contour-detection, neural networks, pre-processing, recognition coefficient, runtime-template generation, segmentation, weight matrix

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Authors: Dor Oppenheim, Yael Edan, Guy Shani

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This paper presents an image analysis algorithm to detect and count yellow tomato flowers in a greenhouse with uneven illumination conditions, complex growth conditions and different flower sizes. The algorithm is designed to be employed on a drone that flies in greenhouses to accomplish several tasks such as pollination and yield estimation. Detecting the flowers can provide useful information for the farmer, such as the number of flowers in a row, and the number of flowers that were pollinated since the last visit to the row. The developed algorithm is designed to handle the real world difficulties in a greenhouse which include varying lighting conditions, shadowing, and occlusion, while considering the computational limitations of the simple processor in the drone. The algorithm identifies flowers using an adaptive global threshold, segmentation over the HSV color space, and morphological cues. The adaptive threshold divides the images into darker and lighter images. Then, segmentation on the hue, saturation and volume is performed accordingly, and classification is done according to size and location of the flowers. 1069 images of greenhouse tomato flowers were acquired in a commercial greenhouse in Israel, using two different RGB Cameras – an LG G4 smartphone and a Canon PowerShot A590. The images were acquired from multiple angles and distances and were sampled manually at various periods along the day to obtain varying lighting conditions. Ground truth was created by manually tagging approximately 25,000 individual flowers in the images. Sensitivity analyses on the acquisition angle of the images, periods throughout the day, different cameras and thresholding types were performed. Precision, recall and their derived F1 score were calculated. Results indicate better performance for the view angle facing the flowers than any other angle. Acquiring images in the afternoon resulted with the best precision and recall results. Applying a global adaptive threshold improved the median F1 score by 3%. Results showed no difference between the two cameras used. Using hue values of 0.12-0.18 in the segmentation process provided the best results in precision and recall, and the best F1 score. The precision and recall average for all the images when using these values was 74% and 75% respectively with an F1 score of 0.73. Further analysis showed a 5% increase in precision and recall when analyzing images acquired in the afternoon and from the front viewpoint.

Keywords: agricultural engineering, image processing, computer vision, flower detection

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Authors: Yang-Keun Ahn, Kwang-Soon Choi, Young-Choong Park, Kwang-Mo Jung

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Vision based user interfaces to control TVs and PCs have the advantage of being able to perform natural control without being limited to a specific device. Accordingly, various studies on hand gesture recognition using RGB cameras or depth cameras have been conducted. However, such cameras have the disadvantage of lacking in accuracy or the construction cost being large. The proposed method uses a low cost IR camera to accurately differentiate between the hand and the background. Also, complicated learning and template matching methodologies are not used, and the correlation between the fingertips extracted through curvatures is utilized to recognize Click and Move gestures.

Keywords: recognition, hand gestures, infrared camera, RGB cameras

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Authors: Yahoel Van Essen, Gordon Ho, Brett Russell, Hans-Georg Worms, Xiao Lin Long, Edward David Cooper, Avner Bachar

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Weeds reduce farm and forest productivity, invade crops, smother pastures and some can harm livestock. Farmers need to spend a significant amount of money to control weeds by means of biological, chemical, cultural, and physical methods. To solve the global agricultural labor shortage and remove poisonous chemicals, a fully autonomous, eco-friendly, and sustainable weeding technology is developed. This takes the form of a weeding robot, ‘Roboweeder’. Roboweeder includes a four-wheel-drive self-driving vehicle, a 4-DOF robotic arm which is mounted on top of the vehicle, an electromagnetic wave generator (magnetron) which is mounted on the “wrist” of the robotic arm, 48V battery packs, and a control/communication system. Cameras are mounted on the front and two sides of the vehicle. Using image processing and recognition, distinguish types of weeds are detected before being eliminated. The electromagnetic wave technology is applied to heat the individual weeds and clusters dielectrically causing them to wilt and die. The 4-DOF robotic arm was modeled mathematically based on its structure/mechanics, each joint’s load, brushless DC motor and worm gear’ characteristics, forward kinematics, and inverse kinematics. The Proportional-Integral-Differential control algorithm is used to control the robotic arm’s motion to ensure the waveguide aperture pointing to the detected weeds. GPS and machine vision are used to traverse the farm and avoid obstacles without the need of supervision. A Roboweeder prototype has been built. Multiple test trials show that Roboweeder is able to detect, point, and kill the pre-defined weeds successfully although further improvements are needed, such as reducing the “weeds killing” time and developing a new waveguide with a smaller waveguide aperture to avoid killing crops surrounded. This technology changes the tedious, time consuming and expensive weeding processes, and allows farmers to grow more, go organic, and eliminate operational headaches. A patent of this technology is pending.

Keywords: autonomous navigation, machine vision, precision heating, sustainable and eco-friendly

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Authors: K. N. Dinesh Babu

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In this paper, the protection of a complicated bus arrangement with a dual bus coupler and bus sectionalizer using low impedance differential protection applicable for very high voltages like 220kV and 400kV is discussed. In many power generation stations, several operational procedures are implemented to utilize the transfer bus as the main bus and to facilitate the maintenance of circuit breakers and current transformers (in each section) without shutting down the bay(s). Owing to this fact, the complications in operational philosophy have thrown challenges for the bus bar protection implementation. Many bus topologies allow any one of the main buses available in the station to be used as an auxiliary bus. In such a system, pre-defined precautions and procedures are made as guidelines, which are followed before assigning any bus as an auxiliary bus. The procedure involves shifting of links, changing rotary switches, insertion of test block, and so on, thereby causing unreliable operation. This kind of unreliable operation or inadvertent procedural lapse may result in the isolation of the bus bar from the grid due to the unpredictable operation of the bus bar protection relay, which is a commonly occurring phenomenon due to manual mistakes. With the sophisticated configuration and implementation of logic in modern intelligent electronic devices, the operator is free to select the transfer arrangement without sacrificing the protection required by a bus differential system for a reliable operation, and labor-intensive processes are completely eliminated. This paper deals with the procedure to test the security logic for such special scenarios using Megger make SMRT, bus bar protection relay to assure system stability and get rid of all the specific operational precautions/procedure.

Keywords: bus bar protection, by-pass isolator, blind spot, breaker failure, intelligent electronic device, end fault, bus unification, directional principle, zones of protection, breaker re-trip, under voltage security, smart megger relay tester

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