Search results for: Bitcoin network

Authors: Sa'ad Ali

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This study explores wasta as an example of a social network and how it impacts business practice in the Arab Middle East, drawing links with social network impact in different regions of the world. In doing so, particular attention will be paid to the socio-economic and cultural influences on business practice. In exploring relationships in business, concepts such as social network analysis, social capital and group identity are used to explore the different forms of social networks and how they influence business decisions and practices in the regions and countries where they prevail. The use of social networks to achieve objectives is known as guanxi in China, wasta in the Arab Middle East and blat in ex-Soviet countries. Wasta can be defined as favouritism based on tribal and family affiliation and is a widespread practice that has a substantial impact on political, social and business interactions in the Arab Middle East. Within the business context, it is used in several ways, such as to secure a job or promotion or to cut through bureaucracy in government interactions. The little research available is fragmented, and most studies reveal a negative attitude towards its usage in business. Paradoxically, while wasta is widely practised, people from the Arab Middle East often deny its influence. Moreover, despite the regular exhibition of a negative opinion on the practice of wasta, it can also be a source of great pride. This paper addresses this paradox by conducting a positional literature review, exploring the current literature on wasta and identifying how the identified paradox can be explained. The findings highlight how wasta, to a large extent, has been treated as an umbrella concept, whilst it is a highly complex practice which has evolved from intermediary wasta to intercessory wasta and therefore from bonding social capital relationships to more bridging social capital relationships. In addition, the research found that Islam, as the predominant religion in the region and the main source of ethical guidance for the majority of people from the region, plays a substantial role in this paradox. Specifically, it is submitted that wasta can be viewed positively in Islam when it is practised to aid others without breaking Islamic ethical guidelines, whilst it can be viewed negatively when it is used in contradiction with the teachings of Islam. As such, the unique contribution to knowledge of this study is that it ties together the fragmented literature on wasta, highlighting and helping us understand its complexity. In addition, it sheds light on the role of Islam in wasta practices, aiding our understanding of the paradoxical nature of the practice.

Keywords: Islamic ethics, social capital, social networks, Wasta

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Authors: T. Botelho de Sousa, F. Raphael Cabral Furtado, O. Eduardo da Silva Ferri, A. Batista, W. Augusto Varella, C. Eduardo Pinto, J. Mimar Santa Cruz Yabarrena, S. Gibran Ruwer, F. Müller Guerrini, L. Adalberto Philippsen Júnior

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Lean Supply Chain Management (LSCM) is an emerging research field in Operations Management (OM). As a strategic model that focuses on reduced cost and waste with fulfilling the needs of customers, LSCM attracts great interest among researchers and practitioners. The purpose of this paper is to present an overview of Lean Supply Chains literature, based on bibliometric analysis through 57 papers published in indexed journals by SCOPUS and/or Web of Science databases. The results indicate that the last three years (2015, 2016, and 2017) were the most productive on LSCM discussion, especially in Supply Chain Management and International Journal of Lean Six Sigma journals. India, USA, and UK are the most productive countries; nevertheless, cross-country studies by collaboration among researchers were detected, by social network analysis, as a research practice, appearing to play a more important role on LSCM studies. Despite existing limitation, such as limited indexed journal database, bibliometric analysis helps to enlighten ongoing efforts on LSCM researches, including most used technical procedures and collaboration network, showing important research gaps, especially, for development countries researchers.

Keywords: Lean Supply Chains, Bibliometric Study, SCOPUS, Web of Science

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Authors: Paweł Konieczka, Lech Raczyński, Wojciech Wiślicki, Oleksandr Fedoruk, Konrad Klimaszewski, Przemysław Kopka, Wojciech Krzemień, Roman Shopa, Jakub Baran, Aurélien Coussat, Neha Chug, Catalina Curceanu, Eryk Czerwiński, Meysam Dadgar, Kamil Dulski, Aleksander Gajos, Beatrix C. Hiesmayr, Krzysztof Kacprzak, łukasz Kapłon, Grzegorz Korcyl, Tomasz Kozik, Deepak Kumar, Szymon Niedźwiecki, Dominik Panek, Szymon Parzych, Elena Pérez Del Río, Sushil Sharma, Shivani Shivani, Magdalena Skurzok, Ewa łucja Stępień, Faranak Tayefi, Paweł Moskal

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This paper develops the transformation of non-image data into 2-dimensional matrices, as a preparation stage for classification based on convolutional neural networks (CNNs). In positron emission tomography (PET) studies, CNN may be applied directly to the reconstructed distribution of radioactive tracers injected into the patient's body, as a pattern recognition tool. Nonetheless, much PET data still exists in non-image format and this fact opens a question on whether they can be used for training CNN. In this contribution, the main focus of this paper is the problem of processing vectors with a small number of features in comparison to the number of pixels in the output images. The proposed methodology was applied to the classification of PET coincidence events.

Keywords: convolutional neural network, kernel principal component analysis, medical imaging, positron emission tomography

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Authors: Sang Ho Lee, Yountaik Leem

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This paper reviews Korean cases of smart cities through the analysis framework of strategic foci, characteristics and effects. Firstly, national strategies including c(cyber), e(electronic), u(ubiquitous) and s(smart) Korea strategies were considered from strategic angles. Secondly, the characteristics of smart cities in Korea were looked through the smart cities examples such as Seoul, Busan, Songdo and Sejong cities etc. from the views on the by STIM (Service, Technology, Infrastructure and Management) analysis. Finally, the effects of smart cities on socio-economies were investigated from industrial perspective using the input-output model and structural path analysis. Korean smart city strategies revealed that there were different kinds of strategic foci. c-Korea strategy focused on information and communications network building and user IT literacy. e-Korea strategy encouraged e-government and e-business through utilizing high-speed information and communications network. u-Korea strategy made ubiquitous service as well as integrated information and communication operations center. s-Korea strategy is propelling 4th industrial platform. Smart cities in Korea showed their own features and trends such as eco-intelligence, high efficiency and low cost oriented IoT, citizen sensored city, big data city. Smart city progress made new production chains fostering ICTs (Information Communication Technologies) and knowledge intermediate inputs to industries.

Keywords: Korean smart cities, Korean smart city strategies, STIM, smart service, infrastructure, technologies, management, effect of smart city

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Authors: Jameela Ali, Hamid A. Jalab, Loay E. George, Abdul Rahim Ahmad, Azizah Suliman, Karim Al-Jashamy

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Red blood cells (RBC) are the most common types of blood cells and are the most intensively studied in cell biology. The lack of RBCs is a condition in which the amount of hemoglobin level is lower than normal and is referred to as “anemia”. Abnormalities in RBCs will affect the exchange of oxygen. This paper presents a comparative study for various techniques for classifyig the red blood cells as normal, or abnormal (anemic) using WEKA. WEKA is an open source consists of different machine learning algorithms for data mining applications. The algorithm tested are Radial Basis Function neural network, Support vector machine, and K-Nearest Neighbors algorithm. Two sets of combined features were utilized for classification of blood cells images. The first set, exclusively consist of geometrical features, was used to identify whether the tested blood cell has a spherical shape or non-spherical cells. While the second set, consist mainly of textural features was used to recognize the types of the spherical cells. We have provided an evaluation based on applying these classification methods to our RBCs image dataset which were obtained from Serdang Hospital-Malaysia, and measuring the accuracy of test results. The best achieved classification rates are 97%, 98%, and 79% for Support vector machines, Radial Basis Function neural network, and K-Nearest Neighbors algorithm respectively

Keywords: red blood cells, classification, radial basis function neural networks, suport vector machine, k-nearest neighbors algorithm

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Authors: M. Ibrahim Ali, M. El Dawi, M. A. Mohamed Ali

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In this study, the use of magnetic gradient survey, and the geoelectrical ground methods used together to explore archaeological features in Nuri’s pyramids area. Research methods used and the procedures and methodologies have taken full right during the study. The magnetic survey method was used to search for archaeological features using (Geoscan Fluxgate Gradiometer (FM36)). The study area was divided into a number of squares (networks) exactly equal (20 * 20 meters). These squares were collected at the end of the study to give a major network for each region. Networks also divided to take the sample using nets typically equal to (0.25 * 0.50 meter), in order to give a more specific archaeological features with some small bipolar anomalies that caused by buildings built from fired bricks. This definition is important to monitor many of the archaeological features such as rooms and others. This main network gives us an integrated map displayed for easy presentation, and it also allows for all the operations required using (Geoscan Geoplot software). The parallel traverse is the main way to take readings of the magnetic survey, to get out the high-quality data. The study area is very rich in old buildings that vary from small to very large. According to the proportion of the sand dunes and the loose soil, most of these buildings are not visible from the surface. Because of the proportion of the sandy dry soil, there is no connection between the ground surface and the electrodes. We tried to get electrical readings by adding salty water to the soil, but, unfortunately, we failed to confirm the magnetic readings with electrical readings as previously planned.

Keywords: archaeological features, independent grids, magnetic gradient, Nuri pyramid

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Authors: Ang Chia Hong, Julian Khoo Xubin, Burra Venkata Durga Kumar

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Distributed systems offer many benefits to the healthcare industry. From big data analysis to business intelligence, the increased computational power and efficiency from distributed systems serve as an invaluable resource in the healthcare sector to utilize. However, as the usage of these distributed systems increases, many issues arise. The main focus of this paper will be on security issues. Many security issues stem from distributed systems in the healthcare industry, particularly information security. The data of people is especially sensitive in the healthcare industry. If important information gets leaked (Eg. IC, credit card number, address, etc.), a person’s identity, financial status, and safety might get compromised. This results in the responsible organization losing a lot of money in compensating these people and even more resources expended trying to fix the fault. Therefore, a framework for a blockchain-based healthcare data management system for healthcare was proposed. In this framework, the usage of a blockchain network is explored to store the encryption key of the patient’s data. As for the actual data, it is encrypted and its encrypted data, called ciphertext, is stored in a cloud storage platform. Furthermore, there are some issues that have to be emphasized and tackled for future improvements, such as a multi-user scheme that could be proposed, authentication issues that have to be tackled or migrating the backend processes into the blockchain network. Due to the nature of blockchain technology, the data will be tamper-proof, and its read-only function can only be accessed by authorized users such as doctors and nurses. This guarantees the confidentiality and immutability of the patient’s data.

Keywords: distributed, healthcare, efficiency, security, blockchain, confidentiality and immutability

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Authors: Farhad Salek, Shahaboddin Resalati

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The production of electric vehicles (EVs) featuring lithium-ion battery technology has substantially escalated over the past decade, demonstrating a steady and persistent upward trajectory. The imminent retirement of electric vehicle (EV) batteries after approximately eight years underscores the critical need for their redirection towards recycling, a task complicated by the current inadequacy of recycling infrastructures globally. A potential solution for such concerns involves extending the operational lifespan of electric vehicle (EV) batteries through their utilization in stationary energy storage systems during secondary applications. Such adoptions, however, require addressing the safety concerns associated with batteries’ knee points and thermal runaways. This paper develops an accurate mathematical model representative of the second-life battery packs from a cell-to-pack scale using an equivalent circuit model (ECM) methodology. Neural network algorithms are employed to forecast the degradation parameters based on the EV batteries' aging history to develop a degradation model. The degradation model is integrated with the ECM to reflect the impacts of the cycle aging mechanism on battery parameters during operation. The developed model is tested under real-life load profiles to evaluate the life span of the batteries in various operating conditions. The methodology and the algorithms introduced in this paper can be considered the basis for Battery Management System (BMS) design and techno-economic analysis of such technologies.

Keywords: second life battery, electric vehicles, degradation, neural network

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Authors: Kaito Sugane, Mitsuhiro Shibata

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Self-healing polymers have attracted attention because their physical damage and cracks can be effectively repaired, thereby extending the lifetime of the materials. Self-healing polymers using host-guest interaction have the advantage that they are quickly repaired under mild temperature conditions when compared with self-healing polymer using dynamic covalent bonds such as Diels-Alder (DA)/retro-DA and disulfide metathesis reactions. Especially, it is known that hydrogels utilizing the host-guest interaction between cyclodextrin and various guest molecules are repeatedly self-repaired at room temperature. However, most of the works deal with hydrogels, and little attention has been paid for thermosetting resins as polyurethane, epoxy and unsaturated polyester resins. In this study, polyetherurethane networks (PUN-CD-Ads) incorporating cyclodextrin and adamantane moieties were prepared by the crosslinking reactions of β-cyclodextrin (CD), 1-adamantanol (AdOH), glycerol ethoxylate (GCE) and hexamethylene diisocyanate (HDI), and thermal, mechanical and self-healing properties of the polymer network films were investigated. Our attention was focused on the influences of molar ratio of CD/AdOH, GCE/CD and OH/NCO on the properties. The FT-IR, and gel fraction analysis revealed that the urethanization reaction smoothly progress to form polyurethane networks. When two cut pieces of the films were contacted at the cross-section at room temperature for 30 seconds, the two pieces adhered to produce a self-healed film. Especially, the PUN-CD-Ad prepared at GCE/CD = 5/1, CD/AdOH = 1/1, and OH/NCO = 1/1 film exhibited the highest healing efficiency for tensile strength. Most of the PUN-CD-Ads were successfully self-healed at room temperature.

Keywords: host-guest interaction, network polymer, polyurethane, self-healing

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Authors: Gertrude I Hewapathirana, Mohamed M. Moustafa, Michel G. Zaitouni

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The purposes of this research are: (a) to provide an epistemological and ontological understanding of the WLB theory, practice, and research to illuminate how the WLB evolved between 2000 to 2020 and (b) to analyze peer-reviewed research to identify the gaps, hotspots, underlying dynamics, theoretical and thematic trends, influential authors, research collaborations, geographic networks, and the multidisciplinary nature of the WLB theory to guide future researchers. The research used four-step bibliometric network analysis to explore five research questions. Using keywords such as WLB and associated variants, 1190 peer-reviewed articles were extracted from the Scopus database and transformed to a plain text format for filtering. The analysis was conducted using the R version 4.1 software (R Development Core Team, 2021) and several libraries such as bibliometrics, word cloud, and ggplot2. We used the VOSviewer software (van Eck & Waltman, 2019) for network visualization. The WLB theory has grown into a multifaceted, multidisciplinary field of research. There is a paucity of research between 2000 to 2005 and an exponential growth from 2006 to 2015. The rapid increase of WLB research in the USA, UK, and Australia reflects the increasing workplace stresses due to hyper competitive workplaces, inflexible work systems, and increasing diversity and the emergence of WLB support mechanisms, legal and constitutional mandates to enhance employee and family wellbeing at multilevel social systems. A severe knowledge gap exists due to inadequate publications disseminating the "core" WLB research. "Locally-centralized-globally-discrete" collaboration among researchers indicates a "North-South" divide between developed and developing nations. A shortage in WLB research in developing nations and a lack of research collaboration hinder a global understanding of the WLB as a universal phenomenon. Policymakers and practitioners can use the findings to initiate supporting policies, and innovative work systems. The boundary expansion of the WLB concepts, categories, relations, and properties would facilitate researchers/theoreticians to test a variety of new dimensions. This is the most comprehensive WLB landscape analysis that reveals emerging trends, concepts, networks, underlying dynamics, gaps, and growing theoretical and disciplinary boundaries. It portrays the WLB as a universal theory.

Keywords: work-life balance, co-citation networks; keyword co-occurrence network, bibliometric analysis

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Authors: Lizhi Ma, Dan Liu

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Pipeline parallelism has been widely used to accelerate distributed deep learning to alleviate GPU memory bottlenecks and to ensure that models can be trained and deployed smoothly under limited graphics memory conditions. However, in highly heterogeneous distributed clusters, traditional model partitioning methods are not able to achieve load balancing. The overlap of communication and computation is also a big challenge. In this paper, HePipe is proposed, an efficient pipeline parallel training method for highly heterogeneous clusters. According to the characteristics of the neural network model pipeline training task, oriented to the 2-level heterogeneous cluster computing topology, a training method based on the 2-level stage division of neural network modeling and partitioning is designed to improve the parallelism. Additionally, a multi-forward 1F1B scheduling strategy is designed to accelerate the training time of each stage by executing the computation units in advance to maximize the overlap between the forward propagation communication and backward propagation computation. Finally, a dynamic recomputation strategy based on task memory requirement prediction is proposed to improve the fitness ratio of task and memory, which improves the throughput of the cluster and solves the memory shortfall problem caused by memory differences in heterogeneous clusters. The empirical results show that HePipe improves the training speed by 1.6×−2.2× over the existing asynchronous pipeline baselines.

Keywords: pipeline parallelism, heterogeneous cluster, model training, 2-level stage partitioning

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Authors: Mojtaba Mahmoodian, Joshua Phelan, Mehdi Shahparvari

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With a large percentage of countries’ total infrastructure expenditure attributed to water network maintenance, it is essential to optimise maintenance strategies to rehabilitate or replace underground pipes before failure occurs. The aim of this paper is to provide water utility managers with a maintenance management approach for underground water pipes, subject to external loading and material corrosion, to give the lowest life cycle cost over a predetermined time period. This reliability-based maintenance management methodology details the optimal years for intervention, the ideal number of maintenance activities to perform before replacement and specifies feasible renewal options and intervention prioritisation to minimise the life cycle cost. The study was then extended to include feasible renewal methods by determining the structural condition index and potential for soil loss, then obtaining the failure impact rating to assist in prioritising pipe replacement. A case study on optimisation of maintenance plans for the Melbourne water pipe network is considered in this paper to evaluate the practicality of the proposed methodology. The results confirm that the suggested methodology can provide water utility managers with a reliable systematic approach to determining optimum maintenance plans for pipe networks.

Keywords: water pipe networks, maintenance management, reliability analysis, optimum maintenance plan

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Authors: Juliana C. Alencar, Monica Ferreira do Amaral Porto

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The blue-green infrastructure in recent years has been pointed out as a possibility to increase the environmental quality of watersheds. The regulation ecosystem services brought by these areas are many, such as the improvement of the air quality of the air, water, soil, microclimate, besides helping to control the peak flows and to promote the quality of life of the population. This study proposes a blue-green infrastructure scenario for the Jaguaré watershed, located in the western zone of the São Paulo city in Brazil. Based on the proposed scenario, it was verified the impact of the adoption of the blue and green infrastructure in the control of the peak flow of the basin, the benefits for the avifauna that are also reflected in the flora and finally, the quantification of the regulation ecosystem services brought by the adoption of the scenario proposed. A survey of existing green areas and potential areas for expansion and connection of these areas to form a network in the watershed was carried out. Based on this proposed new network of green areas, the peak flow for the proposed scenario was calculated with the help of software, ABC6. Finally, a survey of the ecosystem services contemplated in the proposed scenario was made. It was possible to conclude that the blue and green infrastructure would provide several regulation ecosystem services for the watershed, such as the control of the peak flow, the connection frame between the forest fragments that promoted the environmental enrichment of these fragments, improvement of the microclimate and the provision of leisure areas for the population.

Keywords: green and blue infrastructure, sustainable drainage, urban waters, ecosystem services

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Authors: Iva Zdrilić, Petra Došenović Bonča, Darija Aleksić

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Since the boundaryless career, with its emphasis on cross-employer movements, was introduced as a new paradigm of career development, inter-organizational employee mobility has been increasing. Although this phenomenon may have positive implications for individual careers and destination organizations, the consequences for the source organizations losing workers are less clear. The aim of this paper is thus to develop a comprehensive typology of possible inter-organizational employee mobility determinants. Since the most common classification differentiates between mobility determinants at different levels (i.e., economic, organizational, and individual), this paper focuses on building a comprehensive multi-level typology of inter-organizational mobility determinants across diverse sectors and industries. By using a structured literature review approach and bibliometric analysis, the paper reveals both intricate relationships between different mobility determinants and the complexity of inter-organizational networks and social ties. The latter appears as both a mobility determinant (at the organizational and individual level) and a mobility effect. Indeed, inter-organizational employee mobility leads to the formation of networks between source and destination organizations. These networks are practically based on the social ties between mobile employees and their colleagues and, in this way, they close the "inter-organizational employee mobility - inter-organizational network/ties" circle. The paper contributes to the career development literature by uncovering hitherto underexplored diverse determinants of intra- and inter-sectoral mobility as well as the conflicting results of the existing studies on some factors (e.g., inter-organizational networks and/or social ties) that appear both as a mobility determinant and a mobility effect.

Keywords: inter-organizational mobility, social ties, inter-organizational network, knowledge transfer

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Authors: Mehrdad Abkenari, Mehmet Kunt, Mahdi Nourollahi

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Evaluating the environmental risk factors is a combination of analysis of transportation effects. Various definitions for risk can be found in different scientific sources. Each definition depends on a specific and particular perspective or dimension. The effects of potential risks present along the new proposed routes and existing infrastructures of large transportation projects like railways should be studied under comprehensive engineering frameworks. Despite various definitions provided for ‘risk’, all include a uniform concept. Two obvious aspects, loss and unreliability, have always been pointed in all definitions of this term. But, selection as the third aspect is usually implied and means how one notices it. Currently, conducting engineering studies on the environmental effects of railway projects have become obligatory according to the Environmental Assessment Act in developing countries. Considering the longitudinal nature of these projects and probable passage of railways through various ecosystems, scientific research on the environmental risk of these projects have become of great interest. Although many areas of expertise such as road construction in developing countries have not seriously committed to these studies yet, attention to these subjects in establishment or implementation of different systems have become an inseparable part of this wave of research. The present study used environmental risks identified and existing in previous studies and stations to use in next step. The second step proposes a new hybrid approach of analytical network process (ANP) and DEMATEL in fuzzy conditions for assessment of determined risks. Since evaluation of identified risks was not an easy touch, mesh structure was an appropriate approach for analyzing complex systems which were accordingly employed for problem description and modeling. Researchers faced the shortage of real space data and also due to the ambiguity of experts’ opinions and judgments, they were declared in language variables instead of numerical ones. Since fuzzy logic is appropriate for ambiguity and uncertainty, formulation of experts’ opinions in the form of fuzzy numbers seemed an appropriate approach. Fuzzy DEMATEL method was used to extract the relations between major and minor risk factors. Considering the internal relations of risk major factors and its sub-factors in the analysis of fuzzy network, the weight of risk’s main factors and sub-factors were determined. In general, findings of the present study, in which effective railway environmental risk indicators were theoretically identified and rated through the first usage of combined model of DEMATEL and fuzzy network analysis, indicate that environmental risks can be evaluated more accurately and also employed in railway projects.

Keywords: DEMATEL, ANP, fuzzy, risk

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Authors: Shramana Mondal

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As a city is growing in population, sprawl, and complexity, use of public spaces increases variably and thus ensuring safety for the people becomes an utmost priority. While active monitoring measures may be necessary in some places, urban design can play a major role in devising self-policing and encourage active public life. This paper aims to explore the various spatial and psychological reasons for the occurrence of crime and the role of ‘urban design’ to address this issue. In this research, the principles of urban design are examined, as well as projected on actual site by addressing the issue with urban design principles. In this review the sociological, psychological, typological and morphological factors are addressed which affect the safety of a space and the possible framing guidelines, controls and urban design strategies are explored to address a safe neighborhood. On the basis of statistical survey, the residential and street network of Malviya Nagar in Delhi is chosen as the area of demonstration. The programs inhibit a safe neighborhood and a movement network that are addressed based on the four principles of natural surveillance, territoriality, community building, and connectivity. The paper concludes with a discussion of the urban design as an effective tool by creating an intense active zone with mixed use feature to ensure throughout activity and also ensuring safe pedestrian zone by introducing sense of community feeling and territoriality thus achieving active, useful and public friendly space.

Keywords: crime, public life, safety, urban design

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Authors: Raya Sulaiman

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Critical discourse analysis investigates how discourse is used to abuse power relationships. Political debates constitute discourses which mirror aspects of ideologies. The Arab world has been one of the most unsettled zones in the world and has dominated global politics due to the Arab revolutions which started in 2010. This study aimed at uncovering the ideological intentions in the formulation and circulation of hegemonic political ideology in the TV political debates of the 2011 to 2012 Yemen revolution, how ideology was used as a tool of hegemony. The study specifically examined the ideologies associated with the use of protesters as a social actor. Data of the study consisted of four debates (17350 words) from four live debate programs: The Opposite Direction, In Depth, Behind the News and the Revolution Talk that were staged at Al Jazeera TV channel between 2011 and 2012. Data was readily transcribed by Al Jazeera online. Al Jazeera was selected for the study because it is the most popular TV network in the Arab world and has a strong presence, especially during the Arab revolutions. Al Jazeera has also been accused of inciting protests across the Arab region. Two debate sites were identified in the data: government and anti-government. The government side represented the president Ali Abdullah Saleh and his regime while the anti-government side represented the gathering squares who demanded the president to ‘step down’. The study analysed verbal discourse aspects of the debates using critical discourse analysis: aspects from the Social Actor Network model of van Leeuwen. This framework provides a step-by-step analysis model, and analyses discourse from specific grammatical processes into broader semantic issues. It also provides representative findings since it considers discourse as representative and reconstructed in social practice. Study findings indicated that Al Jazeera and the anti-government had similarities in terms of the ideological intentions related to the protesters. Al Jazeera victimized and incited the protesters which were similar to the anti-government. Al Jazeera used assimilation, nominalization, and active role allocation as the linguistic aspects in order to reach its ideological intentions related to the protesters. Government speakers did not share the same ideological intentions with Al Jazeera. Study findings indicated that Al Jazeera had excluded the government from its debates causing a violation to its slogan, the opinion, and the other opinion. This study implies the powerful role of discourse in shaping ideological media intentions and influencing the media audience.

Keywords: Al Jazeera network, critical discourse analysis, ideology, Yemeni revolution

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Authors: Teresita Lopez Joy, Jose A. Acevedo Suarez, Martha I. Gomez Acosta, Ana Julia Acevedo Urquiaga

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Current trends in business competitiveness indicate the need to manage businesses as supply chains and not in isolation. The use of strategies aimed at maximum satisfaction of customers in a network and based on inter-company cooperation; contribute to obtaining successful joint results. In the Cuban economic context, the development of productive linkages to achieve integrated management of supply chains is considering a key aspect. In order to achieve this jump, it is necessary to develop acting capabilities in the entities that make up the chains through a systematic procedure that allows arriving at a management model in consonance with the environment. The objective of the research focuses on: designing a model and procedure for the development of integrated management of supply chains in economic entities. The results obtained are: the Model and the Procedure for the Development of the Supply Chains Integrated Management (MP-SCIM). The Model is based on the development of logistics in the network actors, the joint work between companies, collaborative planning and the monitoring of a main indicator according to the end customers. The application Procedure starts from the well-founded need for development in a supply chain and focuses on training entrepreneurs as doers. The characterization and diagnosis is done to later define the design of the network and the relationships between the companies. It takes into account the feedback as a method of updating the conditions and way to focus the objectives according to the final customers. The MP-SCIM is the result of systematic work with a supply chain approach in companies that have consolidated as coordinators of their network. The cases of the edible oil chain and explosives for construction sector reflect results of more remarkable advances since they have applied this approach for more than 5 years and maintain it as a general strategy of successful development. The edible oil trading company experienced a jump in sales. In 2006, the company started the analysis in order to define the supply chain, apply diagnosis techniques, define problems and implement solutions. The involvement of the management and the progressive formation of performance capacities in the personnel allowed the application of tools according to the context. The company that coordinates the explosives chain for construction sector shows adequate training with independence and opportunity in the face of different situations and variations of their business environment. The appropriation of tools and techniques for the analysis and implementation of proposals is a characteristic feature of this case. The coordinating entity applies integrated supply chain management to its decisions based on the timely training of the necessary action capabilities for each situation. Other cases of study and application that validate these tools are also detailed in this paper, and they highlight the results of generalization in the quantitative and qualitative improvement according to the final clients. These cases are: teaching literature in universities, agricultural products of local scope and medicine supply chains.

Keywords: integrated management, logistic system, supply chain management, tactical-operative planning

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Authors: Malinwo Estone Ayikpa

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With the rapid increase of grid-connected PV systems over the last decades, genuine challenges have arisen for engineers and professionals of energy field in the planning and operation of existing distribution networks with the integration of new generation sources. However, the conventional distribution network, in its design was not expected to receive other generation outside the main power supply. The tools generally used to analyze the networks become inefficient and cannot take into account all the constraints related to the operation of grid-connected PV systems. Some of these constraints are voltage control difficulty, reverse power flow, and especially voltage unbalance which could be due to the poor distribution of single-phase PV systems in the network. In order to analyze the impact of the connection of small and large number of PV systems to the distribution networks, this paper presents an efficient optimization tool that minimizes voltage unbalance in three-phase distribution networks with active and reactive power injections from the allocation of single-phase and three-phase PV plants. Reactive power can be generated or absorbed using the available capacity and the adjustable power factor of the inverter. Good reduction of voltage unbalance can be achieved by reactive power control of the PV systems. The presented tool is based on the three-phase current injection method and the PV systems are modeled via an equivalent circuit. The primal-dual interior point method is used to obtain the optimal operating points for the systems.

Keywords: Photovoltaic system, Primal-dual interior point method, Three-phase optimal power flow, Voltage unbalance

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Authors: Devadrita Dey Sarkar

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Regardless of the many technologic advances in the past decade, increased training and experience, and the obvious benefits of uniform standards, the false-negative rate in screening mammography remains unacceptably high .A computer aided neural network classification of regions of suspicion (ROS) on digitized mammograms is presented in this abstract which employs features extracted by a new technique based on independent component analysis. CAD is a concept established by taking into account equally the roles of physicians and computers, whereas automated computer diagnosis is a concept based on computer algorithms only. With CAD, the performance by computers does not have to be comparable to or better than that by physicians, but needs to be complementary to that by physicians. In fact, a large number of CAD systems have been employed for assisting physicians in the early detection of breast cancers on mammograms. A CAD scheme that makes use of lateral breast images has the potential to improve the overall performance in the detection of breast lumps. Because breast lumps can be detected reliably by computer on lateral breast mammographs, radiologists’ accuracy in the detection of breast lumps would be improved by the use of CAD, and thus early diagnosis of breast cancer would become possible. In the future, many CAD schemes could be assembled as packages and implemented as a part of PACS. For example, the package for breast CAD may include the computerized detection of breast nodules, as well as the computerized classification of benign and malignant nodules. In order to assist in the differential diagnosis, it would be possible to search for and retrieve images (or lesions) with these CAD systems, which would be reliable and useful method for quantifying the similarity of a pair of images for visual comparison by radiologists.

Keywords: CAD(computer-aided design), lesions, neural network, ROS(region of suspicion)

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Authors: Latif Yanar, Muharrem Kaçan

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In this study, an Analytic Hierarchy Process and Analytic Network Process Decision Support System (DSS) model for determination of a navy base place in another country is proposed together with a decision support software (DESTEC 1.0) developed using C Sharp programming language. The proposed software also has the ability of performing the fuzzy models (Fuzzy AHP and Fuzzy ANP) of the proposed DSS to cope with the ambiguous and linguistic nature of the model. The AHP and ANP model, for a decision support for selecting the best place among the alternatives, including the criteria and alternatives, is developed and solved by the experts from Turkish Navy and Turkish academicians related to international relations branches of the universities in Turkey. Also, the questionnaires used for weighting of the criteria and the alternatives are filled by these experts.Some of our alternatives are: economic and political stability of the third country, the effect of another super power in that country, historical relations, security in that country, social facilities in the city in which the base will be built, the transportation security and difficulty from a main city that have an airport to the city will have the base etc. Over 20 criteria like these are determined which are categorized in social, political, economic and military aspects. As a result all the criteria and three alternatives are evaluated by different people who have background and experience to weight the criteria and alternatives as it must be in AHP and ANP evaluation system. The alternatives got their degrees all between 0 – 1 and the total is 1. At the end the DSS advices one of the alternatives as the best one to the decision maker according to the developed model and the evaluations of the experts.

Keywords: analytic hierarchical process, analytic network process, fuzzy logic, naval base place selection, multiple criteria decision making

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Authors: D. Berdous, H. Ferfera-Harrar

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Superabsorbent polymers (SAPs) or hydrogels with three-dimensional hydrophilic network structure are high-performance water absorbent and retention materials. The in situ synthesis of metal nanoparticles within polymeric network as antibacterial agents for bio-applications is an approach that takes advantage of the existing free-space into networks, which not only acts as a template for nucleation of nanoparticles, but also provides long term stability and reduces their toxicity by delaying their oxidation and release. In this work, SAP/nanosilver nanocomposites were successfully developed by a unique green process at room temperature, which involves in situ formation of silver nanoparticles (AgNPs) within hydrogels as a template. The aim of this study is to investigate whether these AgNPs-loaded hydrogels are potential candidates for antimicrobial applications. Firstly, the superabsorbents were prepared through radical copolymerization via grafting and crosslinking of acrylamide (AAm) onto chitosan backbone (Cs) using potassium persulfate as initiator and N,N’-methylenebisacrylamide as the crosslinker. Then, they were hydrolyzed to achieve superabsorbents with ampholytic properties and uppermost swelling capacity. Lastly, the AgNPs were biosynthesized and entrapped into hydrogels through a simple, eco-friendly and cost-effective method using aqueous silver nitrate as a silver precursor and curcuma longa tuber-powder extracts as both reducing and stabilizing agent. The formed superabsorbents nanocomposites (Cs-g-PAAm)/AgNPs were characterized by X-ray Diffraction (XRD), UV-visible Spectroscopy, Attenuated Total reflectance Fourier Transform Infrared Spectroscopy (ATR-FTIR), Inductively Coupled Plasma (ICP), and Thermogravimetric Analysis (TGA). Microscopic surface structure analyzed by Transmission Electron Microscopy (TEM) has showed spherical shapes of AgNPs with size in the range of 3-15 nm. The extent of nanosilver loading was decreased by increasing Cs content into network. The silver-loaded hydrogel was thermally more stable than the unloaded dry hydrogel counterpart. The swelling equilibrium degree (Q) and centrifuge retention capacity (CRC) in deionized water were affected by both contents of Cs and the entrapped AgNPs. The nanosilver-embedded hydrogels exhibited antibacterial activity against Escherichia coli and Staphylococcus aureus bacteria. These comprehensive results suggest that the elaborated AgNPs-loaded nanomaterials could be used to produce valuable wound dressing.

Keywords: antibacterial activity, nanocomposites, silver nanoparticles, superabsorbent Hydrogel

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Authors: Maria Pavlova

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In our days, it is possible to put the camera on different vehicles like quadcopter, train, airplane and etc. The camera also can be the input sensor in many different systems. That means the object recognition like non separate part of monitoring control can be key part of the most intelligent systems. The aim of this paper is to focus of the object recognition process during vehicles movement. During the vehicle’s movement the camera takes pictures from the environment without storage in Data Base. In case the camera detects a special object (for example human or animal), the system saves the picture and sends it to the work station in real time. This functionality will be very useful in emergency or security situations where is necessary to find a specific object. In another application, the camera can be mounted on crossroad where do not have many people and if one or more persons come on the road, the traffic lights became the green and they can cross the road. In this papers is presented the system has solved the aforementioned problems. It is presented architecture of the object recognition system includes the camera, Raspberry platform, GPS system, neural network, software and Data Base. The camera in the system takes the pictures. The object recognition is done in real time using the OpenCV library and Raspberry microcontroller. An additional feature of this library is the ability to display the GPS coordinates of the captured objects position. The results from this processes will be sent to remote station. So, in this case, we can know the location of the specific object. By neural network, we can learn the module to solve the problems using incoming data and to be part in bigger intelligent system. The present paper focuses on the design and integration of the image recognition like a part of smart systems.

Keywords: camera, object recognition, OpenCV, Raspberry

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Authors: Hatem Abou-Senna

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Interstate 4 (I-4) is a primary east-west transportation corridor between Tampa and Daytona cities, serving commuters, commercial and recreational traffic. I-4 is known to have severe recurring congestion during peak hours. The congestion spans about 11 miles in the evening peak period in the central corridor area as it is considered the only non-tolled limited access facility connecting the Orlando Central Business District (CBD) and the tourist attractions area (Walt Disney World). Florida officials had been skeptical of tolling I-4 prior to the recent legislation, and the public through the media had been complaining about the excessive toll facilities in Central Florida. So, in search for plausible mitigation to the congestion on the I-4 corridor, this research is implemented to evaluate the effectiveness of different toll pricing alternatives that might divert traffic from I-4 to the toll facilities during the peak period. The network is composed of two main diverging limited access highways, freeway (I-4) and toll road (SR 417) in addition to two east-west parallel toll roads SR 408 and SR 528, intersecting the above-mentioned highways from both ends. I-4 and toll road SR 408 are the most frequently used route by commuters. SR-417 is a relatively uncongested toll road with 15 miles longer than I-4 and $5 tolls compared to no monetary cost on 1-4 for the same trip. The results of the calibrated Orlando PARAMICS network showed that percentages of route diversion vary from one route to another and depends primarily on the travel cost between specific origin-destination (O-D) pairs. Most drivers going from Disney (O1) or Lake Buena Vista (O2) to Lake Mary (D1) were found to have a high propensity towards using I-4, even when eliminating tolls and/or providing real-time information. However, a diversion from I-4 to SR 417 for these OD pairs occurred only in the cases of the incident and lane closure on I-4, due to the increase in delay and travel costs, and when information is provided to travelers. Furthermore, drivers that diverted from I-4 to SR 417 and SR 528 did not gain significant travel-time savings. This was attributed to the limited extra capacity of the alternative routes in the peak period and the longer traveling distance. When the remaining origin-destination pairs were analyzed, average travel time savings on I-4 ranged between 10 and 16% amounting to 10 minutes at the most with a 10% increase in the network average speed. High propensity of diversion on the network increased significantly when eliminating tolls on SR 417 and SR 528 while doubling the tolls on SR 408 along with the incident and lane closure scenarios on I-4 and with real-time information provided. The toll roads were found to be a viable alternative to I-4 for these specific OD pairs depending on the user perception of the toll cost which was reflected in their specific travel times. However, on the macroscopic level, it was concluded that route diversion through toll reduction or elimination on surrounding toll roads would only have a minimum impact on reducing I-4 congestion during the peak period.

Keywords: congestion pricing, dynamic feedback assignment, microsimulation, paramics, route diversion

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Authors: Vivian Isaac, A. T. Joteeshwaran, Craig McLachlan

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The University of New South Wales (UNSW) Rural Clinical School has a strategic collaborative focus on chronic disease and public health. Our objectives are to understand rural environmental and biological interactions in vulnerable community populations. The UNSW Rural Clinical School translational model is a spoke and hub network. This spoke and hub model connects rural data and biological specimens with city based collaborative public health research networks. Similar spoke and hub models are prevalent across research centers in India. The Australia-India Council grant was awarded so we could establish sustainable public health and community research collaborations. As part of the collaborative network we are developing strategies around data and biological sharing platforms between Indian Institute of Public Health, Public Health Foundation of India (PHFI), Hyderabad and Rural Clinical School UNSW. The key objective is to understand how research collaborations are conducted in India and also how data can shared and tracked with external collaborators such as ourselves. A framework to improve data sharing for research collaborations, including DNA was proposed as a project outcome. The complexities of sharing biological data has been investigated via a visit to India. A flagship sustainable project between Rural Clinical School UNSW and PHFI would illustrate a model of data sharing platforms.

Keywords: data sharing, collaboration, public health research, chronic disease

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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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Authors: M. Mutemwa

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A Cybersecurity Operation Centre (SOC) is a centralized hub for network event monitoring and incident response. SOCs are critical when determining an organization’s cybersecurity posture because they can be used to detect, analyze and report on various malicious activities. For most organizations, a SOC is not part of the initial design and implementation of the Information Technology (IT) environment but rather an afterthought. As a result, it is not natively a plug and play component; therefore, there are integration challenges when a SOC is introduced into an organization. A SOC is an independent hub that needs to be integrated with existing procedures, policies and IT systems of an organization such as the service desk, ticket logging system, reporting, etc. This paper discussed the challenges of integrating a newly developed SOC to an organization’s existing IT environment. Firstly, the paper begins by looking at what data sources should be incorporated into the Security Information and Event Management (SIEM) such as which host machines, servers, network end points, software, applications, web servers, etc. for security posture monitoring. That is which systems need to be monitored first and the order by which the rest of the systems follow. Secondly, the paper also describes how to integrate the organization’s ticket logging system with the SOC SIEM. That is how the cybersecurity related incidents should be logged by both analysts and non-technical employees of an organization. Also the priority matrix for incident types and notifications of incidents. Thirdly, the paper looks at how to communicate awareness campaigns from the SOC and also how to report on incidents that are found inside the SOC. Lastly, the paper looks at how to show value for the large investments that are poured into designing, building and running a SOC.

Keywords: cybersecurity operation centre, incident response, priority matrix, procedures and policies

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Authors: Beng Zhen Yeow

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In most work that involves children, the voice of the children is often not heard. This is ironic since a lot of discussions might involve their welfare and safety. It might seem natural that the professionals should hear from them about what they wish for instead of deciding what is best for them. However, this, unfortunately, might be more the exception than the norm in most case and hence in many instances, children are merely 'subjects' in conversations about safety instead of active participants in the construction or creation of safety in the family. There might be many reasons why it does not happen in our work. Firstly, professionals have learnt how to 'socialise' into their professional roles and hence in the process become 'un-childlike'. Secondly, there is also a lack of professional training with regards to how to talk with children. Finally, there might be also a lack of concrete tools and techniques that are developed to facilitate the process. In this paper, the case study method is used to show how the idea of safety could be concretised and discussed with children and their family members, and hence making them active participants and co-creators of their own safety. Specific skills and techniques are highlighted through the case study. In this case, there was improvement in outcomes like no repeated offence or abuse. In addition, children were also able to advocate for their own safety after six months of intervention and how the family members were able to explicitly say what they can do to improve safety. The professionals in the safety network reported significant improvements. On top of that, the abused child who was removed due to child protection concerns, had verbalized observations of change in mother’s parenting abilities, and has requested for home leave to begin due to ownership of safety planning and having confidence to co-create safety for her siblings and herself together with the professionals in the safety network. Children becoming active participants in the co-creation of safety not only serve the purpose in allowing them to own a 'voice' but at the same time, give them greater confidence to protect themselves at home and in other contexts outside of home.

Keywords: partnering for safety, collaborative social work, family and systemic psychotherapy, child protection

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Authors: Kaustav Mukherjee

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In this paper we propose a Neural Style Transfer solution whereby we have created a Lightweight Separable Convolution Kernel Based GAN Architecture (SC-GAN) which will very useful for designing filter for Mobile Phone Cameras and also Edge Devices which will convert any image to its 2D ANIMATED COMIC STYLE Movies like HEMAN, SUPERMAN, JUNGLE-BOOK. This will help the 2D animation artist by relieving to create new characters from real life person's images without having to go for endless hours of manual labour drawing each and every pose of a cartoon. It can even be used to create scenes from real life images.This will reduce a huge amount of turn around time to make 2D animated movies and decrease cost in terms of manpower and time. In addition to that being extreme light-weight it can be used as camera filters capable of taking Comic Style Shots using mobile phone camera or edge device cameras like Raspberry Pi 4,NVIDIA Jetson NANO etc. Existing Methods like CartoonGAN with the model size close to 170 MB is too heavy weight for mobile phones and edge devices due to their scarcity in resources. Compared to the current state of the art our proposed method which has a total model size of 31 MB which clearly makes it ideal and ultra-efficient for designing of camera filters on low resource devices like mobile phones, tablets and edge devices running OS or RTOS. .Owing to use of high resolution input and usage of bigger convolution kernel size it produces richer resolution Comic-Style Pictures implementation with 6 times lesser number of parameters and with just 25 extra epoch trained on a dataset of less than 1000 which breaks the myth that all GAN need mammoth amount of data. Our network reduces the density of the Gan architecture by using Depthwise Separable Convolution which does the convolution operation on each of the RGB channels separately then we use a Point-Wise Convolution to bring back the network into required channel number using 1 by 1 kernel.This reduces the number of parameters substantially and makes it extreme light-weight and suitable for mobile phones and edge devices. The architecture mentioned in the present paper make use of Parameterised Batch Normalization Goodfellow etc al. (Deep Learning OPTIMIZATION FOR TRAINING DEEP MODELS page 320) which makes the network to use the advantage of Batch Norm for easier training while maintaining the non-linear feature capture by inducing the learnable parameters

Keywords: comic stylisation from camera image using GAN, creating 2D animated movie style custom stickers from images, depth-wise separable convolutional neural network for light-weight GAN architecture for EDGE devices, GAN architecture for 2D animated cartoonizing neural style, neural style transfer for edge, model distilation, perceptual loss

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Authors: Somayeh Komeylian

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The direction of arrival (DoA) estimation is the crucial aspect of the radar technologies for detecting and dividing several signal sources. In this scenario, the antenna array output modeling involves numerous parameters including noise samples, signal waveform, signal directions, signal number, and signal to noise ratio (SNR), and thereby the methods of the DoA estimation rely heavily on the generalization characteristic for establishing a large number of the training data sets. Hence, we have analogously represented the two different optimization models of the DoA estimation; (1) the implementation of the decision directed acyclic graph (DDAG) for the multiclass least-squares support vector machine (LS-SVM), and (2) the optimization method of the deep neural network (DNN) radial basis function (RBF). We have rigorously verified that the LS-SVM DDAG algorithm is capable of accurately classifying DoAs for the three classes. However, the accuracy and robustness of the DoA estimation are still highly sensitive to technological imperfections of the antenna arrays such as non-ideal array design and manufacture, array implementation, mutual coupling effect, and background radiation and thereby the method may fail in representing high precision for the DoA estimation. Therefore, this work has a further contribution on developing the DNN-RBF model for the DoA estimation for overcoming the limitations of the non-parametric and data-driven methods in terms of array imperfection and generalization. The numerical results of implementing the DNN-RBF model have confirmed the better performance of the DoA estimation compared with the LS-SVM algorithm. Consequently, we have analogously evaluated the performance of utilizing the two aforementioned optimization methods for the DoA estimation using the concept of the mean squared error (MSE).

Keywords: DoA estimation, Adaptive antenna array, Deep Neural Network, LS-SVM optimization model, Radial basis function, and MSE

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