Search results for: network security management

Authors: R. Rezaeipour, A. R. Mehrabi

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Recent increase of the DGs and microgrids in distribution systems, disturbs the tradition structure of the system. Coordination between protection devices in such a system becomes the concern of the network operators. This paper presents a new method for fault location detection in the active distribution networks, independent of the fault type or its resistance. The method uses synchronized voltage and current measurements at the interconnection of DG units and is able to adapt to changes in the topology of the system. The method has been tested on a 38-bus distribution system, with very encouraging results.

Keywords: fault location detection, active distribution system, micro grids, network operators

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Authors: Piyangkun Kukutapan, Siridech Boonsang

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The article proposes maximum power point tracking without mechanical sensor using Multilayer Perceptron Neural Network (MLPNN). The aim of article is to reduce the cost and complexity but still retain efficiency. The experimental is that duty cycle is generated maximum power, if it has suitable qualification. The measured data from DC generator, voltage (V), current (I), power (P), turnover rate of power (dP), and turnover rate of voltage (dV) are used as input for MLPNN model. The output of this model is duty cycle for driving the converter. The experiment implemented using Arduino Uno board. This diagram is compared to MPPT using MLPNN and P&O control (Perturbation and Observation control). The experimental results show that the proposed MLPNN based approach is more efficiency than P&O algorithm for this application.

Keywords: maximum power point tracking, multilayer perceptron netural network, optimal duty cycle, DC generator

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Authors: El Mahdi Barrah, Said Safi, Abdessamad Malaoui

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In this paper, we present an algorithm for reconstruction from incomplete 2D scans for tifinagh characters. This algorithm is based on using correlation between the lost block and its neighbors. This system proposed contains three main parts: pre-processing, features extraction and recognition. In the first step, we construct a database of tifinagh characters. In the second step, we will apply “shape analysis algorithm”. In classification part, we will use Neural Network. The simulation results demonstrate that the proposed method give good results.

Keywords: Tifinagh character recognition, neural networks, local cost computation, ANN

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Authors: Anusha M., V. Srikanth

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Maximizing spectrum usage and numerous applications of the wireless communication networks have forced to a high interest of available spectrum. Cognitive Radio control its receiver and transmitter features exactly so that they can utilize the vacant approved spectrum without impacting the functionality of the principal licensed users. The Use of various channels assists to address interferences thereby improves the whole network efficiency. The MAC protocol in cognitive radio network explains the spectrum usage by interacting with multiple channels among the users. In this paper we studied about the architecture of cognitive wireless mesh network and traditional TDMA dependent MAC method to allocate channels dynamically. The majority of the MAC protocols suggested in the research are operated on Common-Control-Channel (CCC) to handle the services between Cognitive Radio secondary users. In this paper, an extensive study of Multi-Channel Multi-Radios or frequency range channel allotment and continually synchronized TDMA scheduling are shown in summarized way.

Keywords: TDMA, MAC, multi-channel, multi-radio, WMN’S, cognitive radios

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Authors: D. López-Mancilla, J. M. Roblero-Villa

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Since 1990, the research on chaotic dynamics has received considerable attention, particularly in light of potential applications of this phenomenon in secure communications. Data encryption using chaotic systems was reported in the 90's as a new approach for signal encoding that differs from the conventional methods that use numerical algorithms as the encryption key. The algorithms for image encryption have received a lot of attention because of the need to find security on image transmission in real time over the internet and wireless networks. Known algorithms for image encryption, like the standard of data encryption (DES), have the drawback of low level of efficiency when the image is large. The encrypting based on chaos proposes a new and efficient way to get a fast and highly secure image encryption. In this work, a user interface for image encryption and a novel and easiest way to encrypt images using chaos are presented. The main idea is to reshape any image into a n-dimensional vector and combine it with vector extracted from a chaotic system, in such a way that the vector image can be hidden within the chaotic vector. Once this is done, an array is formed with the original dimensions of the image and turns again. An analysis of the security of encryption from the images using statistical analysis is made and is used a stage of optimization for image encryption security and, at the same time, the image can be accurately recovered. The user interface uses the algorithms designed for the encryption of images, allowing you to read an image from the hard drive or another external device. The user interface, encrypt the image allowing three modes of encryption. These modes are given by three different chaotic systems that the user can choose. Once encrypted image, is possible to observe the safety analysis and save it on the hard disk. The main results of this study show that this simple method of encryption, using the optimization stage, allows an encryption security, competitive with complicated encryption methods used in other works. In addition, the user interface allows encrypting image with chaos, and to submit it through any public communication channel, including internet.

Keywords: image encryption, chaos, secure communications, user interface

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Authors: Jordan Georgiev Deliversky

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Human trafficking and smuggling of migrants are criminal activities, which are on the rise over recent years. The number of legal migrants arrived in Europe from outside the European Union are far less than those who want to come and settle in Europe. The objective of this paper is to present the impact on economic and social life of significant measures influencing the smuggling of migrants. The analysis is focused on various complex factors which have multiple origins and are highly influential as regard to the process of migration and the smuggling of migrants. The smuggling of migrants is a criminal activity, directly related to migration. The main results show that often the routes chosen for smuggling of migrants are circuitous, as smugglers carefully avoid strictly controlled roads, checkpoints, and countries or jurisdictions where there is efficiency of justice, with particular emphasis on the law on trafficking of persons and smuggling of migrants.

Keywords: corruption, migration, security, smuggling

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Authors: Ganesh Nandakumaran, Mehmet Karaata

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A wave is a distributed execution, often made up of a broadcast phase followed by a feedback phase, requiring the participation of all the system processes before a particular event called decision is taken. Wave algorithms with one initiator such as the 1-wave algorithm have been shown to be very efficient for broadcasting messages in tree networks. Extensions of this algorithm broadcasting a sequence of waves using a single initiator have been implemented in algorithms such as the m-wave algorithm. However as the network size increases, having a single initiator adversely affects the message delivery times to nodes further away from the initiator. As a remedy, broadcast waves can be allowed to be initiated by multiple initiator nodes distributed across the network to reduce the completion time of broadcasts. These waves initiated by one or more initiator processes form a collection of waves covering the entire network. Solutions to global-snapshots, distributed broadcast and various synchronization problems can be solved efficiently using waves with multiple concurrent initiators. In this paper, we propose the first stabilizing multi-wave sequence algorithm implementing waves started by multiple initiator processes such that every process in the network receives at least one sequence of broadcasts. Due to being stabilizing, the proposed algorithm can withstand transient faults and do not require initialization. We view a fault as a transient fault if it perturbs the configuration of the system but not its program.

Keywords: distributed computing, multi-node broadcast, propagation of information with feedback and cleaning (PFC), stabilization, wave algorithms

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Authors: Busra Gulnihan Dascıoglu, Ozalp Vayvay, Zeynep Tugce Kalender

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Humanitarian supply chain management has gain popularity in recent years in research fields. The aim of this paper is to review the literature on humanitarian operations and crisis/disaster management from 2010 to latest researches in order to identify the current research and to provide direction for future research in this growing field. Researches are classified considering the research publication year, research fields. Articles from humanitarian supply chain management were reviewed, keywords were identified within a disaster management lifecycle framework. Research gaps are identified for future research areas.

Keywords: crisis, disaster, humanitarian supply chain management, relief operations

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Authors: Luvisa Kusuma, Panji Yudha Prakasa

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Cloud storage, as a subservice of infrastructure as a service (IaaS) in Cloud Computing, is the model of nerworked storage where data can be stored in server. In this paper, we propose a secure cloud storage system consisting of two main components; client as a user who uses the cloud storage service and server who provides the cloud storage service. In this system, we propose the protocol schemes to guarantee against security attacks in the data transmission. The protocols are login protocol, upload data protocol, download protocol, and push data protocol, which implement hybrid cryptographic mechanism based on data encryption before it is sent to the cloud, so cloud storage provider does not know the user's data and cannot analysis user’s data, because there is no correspondence between data and user.

Keywords: cloud storage, security, cryptographic protocol, artificial intelligence

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Authors: Bagus Hanindhito, Fariz Azmi Pratama, Ulfah Nadiya

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Nowadays, digital system including, but not limited to, computer and internet have penetrated the education system widely. Critical information such as students’ academic records is stored in a server off- or on-campus. Although several countermeasures have been taken to protect the vital resources from outsider attack, the defense from insiders threat is not getting serious attention. At the end of 2017, a security incident that involved academic information system in one of the most respected universities in Indonesia affected not only the reputation of the institution and its academia but also academic integrity in Indonesia. In this paper, we will explain our efforts in investigating this security incident where we have implemented a novel rapid evidence remote acquisition method in high-availability server and storage system thus our data collection efforts do not disrupt the academic information system and can be conducted remotely minutes after incident report has been received. The acquired evidence is analyzed during digital forensic by constructing the model of the system in an isolated environment which allows multiple investigators to work together. In the end, the suspect is identified as a student (insider), and the investigation result is used by prosecutors to charge the suspect as an academic crime.

Keywords: academic information system, academic crime, digital forensic, high-availability server and storage, rapid evidence remote acquisition, security incident

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Authors: Muhammad Tanveer Altaf, Mehmet Bedir, Waqas Liaqat, Gönül Cömertpay, Volkan Çatalkaya, Celaluddin Barutçular, Nergiz Çoban, Ibrahim Cerit, Muhammad Azhar Nadeem, Tolga Karaköy, Faheem Shehzad Baloch

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Food production needs to be almost double by 2050 in order to feed around 9 billion people around the Globe. Plant production mostly relies on fertilizers, which also have one of the main roles in environmental pollution. In addition to this, climatic conditions are unpredictable, and the earth is expected to face severe drought conditions in the future. Therefore, water and fertilizers, especially nitrogen are considered as main constraints for future food security. To face these challenges, developing integrative approaches for germplasm characterization and selecting the resilient genotypes performing under limiting conditions is very crucial for effective breeding to meet the food requirement under climatic change scenarios. This study is part of the European Research Area Network (ERANET) project for the characterization of the diversity panel of 172 sorghum accessions and six hybrids as control cultivars under limiting (+N/-H2O, -N/+H2O) and non-limiting conditions (+N+H2O). This study was planned to characterize the sorghum diversity in relation to resource Use Efficiency (RUE), with special attention on harnessing the interaction between genotype and environment (GxE) from a physiological and agronomic perspective. Experiments were conducted at Adana, a Mediterranean climate, with augmented design, and data on various agronomic and physiological parameters were recorded. Plentiful diversity was observed in the sorghum diversity panel and significant variations were seen among the limiting water and nitrogen conditions in comparison with the control experiment. Potential genotypes with the best performance are identified under limiting conditions. Whole genome resequencing was performed for whole germplasm under investigation for diversity analysis. GWAS analysis will be performed using genotypic and phenotypic data and linked markers will be identified. The results of this study will show the adaptation and improvement of sorghum under climate change conditions for future food security.

Keywords: germplasm, sorghum, drought, nitrogen, resources use efficiency, sequencing

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Authors: Taimur Khan, Zakirullah, Muhammad Shahab

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The SARS-CoV-2 variant BA.2.86 (Omicron) has emerged with unique mutations that may increase its transmission and infectivity. This study investigates how these mutations alter the Omicron receptor-binding domain's interaction network and dynamic properties (RBD) compared to the wild-type virus, focusing on its binding affinity to the human ACE2 (hACE2) receptor. Protein-protein docking and all-atom molecular dynamics simulations were used to analyze structural and dynamic differences. Despite the structural similarity to the wild-type virus, the Omicron variant exhibits a distinct interaction network involving new residues that enhance its binding capacity. The dynamic analysis reveals increased flexibility in the RBD, particularly in loop regions crucial for hACE2 interaction. Mutations significantly alter the secondary structure, leading to greater flexibility and conformational adaptability compared to the wild type. Binding free energy calculations confirm that the Omicron RBD has a higher binding affinity (-70.47 kcal/mol) to hACE2 than the wild-type RBD (-61.38 kcal/mol). These results suggest that the altered interaction network and enhanced dynamics of the Omicron variant contribute to its increased infectivity, providing insights for the development of targeted therapeutics and vaccines.

Keywords: SARS-CoV-2, molecular dynamic simulation, receptor binding domain, vaccine

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Authors: M. Okeke, A. Blyth

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Industrial Control Systems (ICS) such as Supervisory Control And Data Acquisition (SCADA) can be seen in many different critical infrastructures, from nuclear management to utility, medical equipment, power, waste and engine management on ships and planes. The role SCADA plays in critical infrastructure has resulted in a call to secure them. Many lives depend on it for daily activities and the attack vectors are becoming more sophisticated. Hence, the security of ICS is vital as malfunction of it might result in huge risk. This paper describes how the application of Prey Predator (PP) approach in flocks of birds could enhance the detection of malicious activities on ICS. The PP approach explains how these animals in groups or flocks detect predators by following some simple rules. They are not necessarily very intelligent animals but their approach in solving complex issues such as detection through corporation, coordination and communication worth emulating. This paper will emulate flocking behavior seen in birds in detecting predators. The PP approach will adopt six nearest bird approach in detecting any predator. Their local and global bests are based on the individual detection as well as group detection. The PP algorithm was designed following MapReduce methodology that follows a Split Detection Convergence (SDC) approach.

Keywords: artificial life, industrial control system (ICS), IDS, prey predator (PP), SCADA, SDC

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Authors: Kartik Mahajan

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DevOps methodologies streamline software development and operations, promoting collaboration and automation. Traditional server management often relies on manual, repetitive tasks, leading to inefficiencies, potential errors, and increased operational costs. Ansible, as a configuration management tool, presents a compelling solution for automating infrastructure management processes. This review paper explores the implementation and testing of Ansible for server management, specifically focusing on automated user account configuration. By replacing manual procedures with Ansible playbooks, we aim to optimize server management, reduce human error, and potentially mitigate operational expenses. This study offers insights into Ansible’s efficacy within a DevOps context, highlighting its potential to transform server administration practices.

Keywords: cloud, Devops, automation, ansible

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Authors: Irbulat Utepbergenov, Lyazzat Issabekova, Shara Toybayeva

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This article discusses quality management using the bread baking process as an example. The baking process must be strictly controlled and repeatable. Automation and monitoring of quality management systems can help. After baking bread, quality control of the finished product should be carried out. This may include an evaluation of appearance, weight, texture, and flavor. It is important to continuously work to improve processes and products based on data and feedback from the quality management system. A method and model of automated quality management and an intelligent automated management system based on intelligent technologies are proposed, which allow to automate the processes of QMS implementation and support and improve the validity, efficiency, and effectiveness of management decisions by automating a number of functions of decision makers and staff. This project is supported by the grant of the Ministry of Education and Science of the Republic of Kazakhstan (Zhas Galym project No. AR 13268939 Research and development of digital technologies to ensure consistency of the carriers of normative documents of the quality management system).

Keywords: automated control system, quality management, efficiency evaluation, bakery oven, intelligent system

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Authors: Mehrnoosh Askarizadeh

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People, process and IT are the most important assets of any organization. Optimal utilization of these resources has been the question of research in business for many decades. The business world have responded by inventing various methodologies that can be used for addressing problems of quality improvement, efficiency of processes, continuous improvement, reduction of waste, automation, strategy alignments etc. Some of these methodologies can be commonly called as Business Process Quality Management methodologies (BPQM). In essence, the first references to the process management can be traced back to Frederick Taylor and scientific management. Time and motion study was addressed to improvement of manufacturing process efficiency. The ideas of scientific management were in use for quite a long period until more advanced quality management techniques were developed in Japan and USA. One of the first prominent methods had been Total Quality Management (TQM) which evolved during 1980’s. About the same time, Six Sigma (SS) originated at Motorola as a separate method. SS spread and evolved; and later joined with ideas of Lean manufacturing to form Lean Six Sigma. In 1990’s due to emerging IT technologies, beginning of globalization, and strengthening of competition, companies recognized the need for better process and quality management. Business Process Management (BPM) emerged as a novel methodology that has taken all this into account and helped to align IT technologies with business processes and quality management. In this article we will study various aspects of above mentioned methods and identified their relations.

Keywords: e-process, quality, TQM, BPM, lean, six sigma, CPI, information technology, management

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Authors: Rajkumar Ghosh

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Climate change has led to decreased water availability in the Gomti Nagar area of Uttar Pradesh, India. Climate change has reduced the amount of precipitation and increased the rate of evaporation. The region is heavily reliant on surface water sources (Gomti river, Sharda Canal) and groundwater. Efficient management of groundwater resources is crucial for addressing water shortages. These may include: Exploring alternative water sources, such as wastewater recycling and desalination, can help augment water supply and reduce dependency on rainfall-dependent sources. Promoting the use of water-efficient technologies in industries, agriculture, and water-efficient infrastructure in urban areas can contribute to reducing water demand and optimizing water use. Incorporating climate change considerations into urban planning and infrastructure development can help ensure water security in the face of future climate uncertainties. Addressing water scarcity in the Gomti Nagar area requires a multi-pronged approach that combines sustainable groundwater management practices, climate change adaptation strategies, and integrated water resource management. By implementing these measures, the region can work towards ensuring a more sustainable and reliable water supply in the context of climate change. Water is the most important natural resource for the existence of living beings in the Earth's ecosystem. On Earth, 1.2 percent of the water is drinkable, but only 0.3 percent is usable by people. Water scarcity is a growing concern in India due to the impact of climate change and over-exploitation of water resources. Excess groundwater withdrawal causes regular declines in groundwater level. Due to city boundary expansion and growing urbanization, the recharge point for groundwater tables is decreasing. Rainwater infiltration into the subsoil is also reduced by unplanned, uneven settlements in urban change.

Keywords: climate change, water scarcity, groundwater, rainfall, water supply

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Authors: Kun Xu, Yuan Xu, Jia Qiao

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The document detection plays an important role in optical character recognition and text analysis. Because the traditional detection methods have weak generalization ability, and deep neural network has complex structure and large number of parameters, which cannot be well applied in mobile devices, this paper proposes a lightweight Document Corner Detection Network (DCDNet). DCDNet is a two-stage architecture. The first stage with Encoder-Decoder structure adopts depthwise separable convolution to greatly reduce the network parameters. After introducing the Feature Attention Union (FAU) module, the second stage enhances the feature information of spatial and channel dim and adaptively adjusts the size of receptive field to enhance the feature expression ability of the model. Aiming at solving the problem of the large difference in the number of pixel distribution between corner and non-corner, Weighted Binary Cross Entropy Loss (WBCE Loss) is proposed to define corner detection problem as a classification problem to make the training process more efficient. In order to make up for the lack of Dataset of document corner detection, a Dataset containing 6620 images named Document Corner Detection Dataset (DCDD) is made. Experimental results show that the proposed method can obtain fast, stable and accurate detection results on DCDD.

Keywords: document detection, corner detection, attention mechanism, lightweight

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Authors: Renata Kurpiewska-Korbut

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Making an assumption that the use and sharing of data generated in humanitarian action constitute a core function of humanitarian organizations, the paper analyzes the position of the largest Polish humanitarian non-governmental organizations in the humanitarian data ecosystem in Ukraine and their approach to non-personal and personal data management since February of 2022. Both expert interviews and document analysis of non-profit organizations providing a direct response in the Ukrainian crisis context, i.e., the Polish Humanitarian Action, Caritas, Polish Medical Mission, Polish Red Cross, and the Polish Center for International Aid and the applicability of theoretical perspective of contingency theory – with its central point that the context or specific set of conditions determining the way of behavior and the choice of methods of action – help to examine the significance of data complexity and adaptive approach to data management by relief organizations in the humanitarian supply chain network. The purpose of this study is to determine how the existence of well-established and accurate internal procedures and good practices of using and sharing data (including safeguards for sensitive data) by the surveyed organizations with comparable human and technological capabilities are implemented and adjusted to Ukrainian humanitarian settings and data infrastructure. The study also poses a fundamental question of whether this crisis experience will have a determining effect on their future performance. The obtained finding indicate that Polish humanitarian organizations in Ukraine, which have their own unique code of conduct and effective managerial data practices determined by contingencies, have limited influence on improving the situational awareness of other assistance providers in the data ecosystem despite their attempts to undertake interagency work in the area of data sharing.

Keywords: humanitarian data ecosystem, humanitarian data management, polish NGOs, Ukraine

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Authors: Lamaa Sellami, Bechir Alaya

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Nowadays, video-on-demand (VoD) applications are becoming one of the tendencies driving vehicular network users. In this paper, considering the unpredictable vehicle density, the unexpected acceleration or deceleration of the different cars included in the vehicular traffic load, and the limited radio range of the employed communication scheme, we introduce the “Dynamic Vehicular Clustering” (DVC) algorithm as a new scheme for video streaming systems over VANET. The proposed algorithm takes advantage of the concept of small cells and the introduction of wireless backhauls, inspired by the different features and the performance of the Long Term Evolution (LTE)- Advanced network. The proposed clustering algorithm considers multiple characteristics such as the vehicle’s position and acceleration to reduce latency and packet loss. Therefore, each cluster is counted as a small cell containing vehicular nodes and an access point that is elected regarding some particular specifications.

Keywords: video-on-demand, vehicular ad-hoc network, mobility, vehicular traffic load, small cell, wireless backhaul, LTE-advanced, latency, packet loss

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Authors: Santosh Kumar Sharma

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In view of management education with special reference to India, it has been noted that students have deviations between their career anchors and domain of specialization. As a consequence, they face problems in their summer internships and placements in the corporate sector. Eventually, they either change their career track or leave the management profession, which is a serious concern from the perspective of human capital. However, there is no substantial literature in the given context. Therefore, the present study contributes to the global discourse of management education and its spillover effect on human resource management. The objective of the present study is to analyze the deviation between career anchors and domain specialization with reference to management education in India. The present study is exploratory in nature, wherein data has been collected from a significant number of post-graduate students who are pursuing management education from a premium business school in India, followed by descriptive analysis. The present research contributes to the professional development of management students from the perspective of human capital, which is eventually related to various factors of the Indian economy.

Keywords: India, management education, domain specialization, placements

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Authors: Reza Safdari, Goli Arji, Robab Abdolkhani Maryam zahmatkeshan

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Background and purpose: Cardiovascular diseases are among the most common diseases in all societies. The most important step in minimizing myocardial infarction and its complications is to minimize its risk factors. The amount of medical data is increasingly growing. Medical data mining has a great potential for transforming these data into information. Using data mining techniques to generate predictive models for identifying those at risk for reducing the effects of the disease is very helpful. The present study aimed to collect data related to risk factors of heart infarction from patients’ medical record and developed predicting models using data mining algorithm. Methods: The present work was an analytical study conducted on a database containing 350 records. Data were related to patients admitted to Shahid Rajaei specialized cardiovascular hospital, Iran, in 2011. Data were collected using a four-sectioned data collection form. Data analysis was performed using SPSS and Clementine version 12. Seven predictive algorithms and one algorithm-based model for predicting association rules were applied to the data. Accuracy, precision, sensitivity, specificity, as well as positive and negative predictive values were determined and the final model was obtained. Results: five parameters, including hypertension, DLP, tobacco smoking, diabetes, and A+ blood group, were the most critical risk factors of myocardial infarction. Among the models, the neural network model was found to have the highest sensitivity, indicating its ability to successfully diagnose the disease. Conclusion: Risk prediction models have great potentials in facilitating the management of a patient with a specific disease. Therefore, health interventions or change in their life style can be conducted based on these models for improving the health conditions of the individuals at risk.

Keywords: decision trees, neural network, myocardial infarction, Data Mining

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Authors: Tobias Milz, L. Macpherson, Varvara Vetrova

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The law is a fundamental pillar of human societies as it shapes, controls and governs how humans conduct business, behave and interact with each other. Recent advances in computer-assisted technologies such as NLP, data science and AI are creating opportunities to support the practice, research and study of this pervasive domain. It is therefore not surprising that there has been an increase in investments into supporting technologies for the legal industry (also known as “legal tech” or “law tech”) over the last decade. A sub-discipline of particular appeal is concerned with assisted legal research. Supporting law researchers and practitioners to retrieve information from the vast amount of ever-growing legal documentation is of natural interest to the legal research community. One tool that has been in use for this purpose since the early nineteenth century is legal citation indexing. Among other use cases, they provided an effective means to discover new precedent cases. Nowadays, computer-assisted network analysis tools can allow for new and more efficient ways to reveal the “hidden” information that is conveyed through citation behavior. Unfortunately, access to openly available legal data is still lacking in New Zealand and access to such networks is only commercially available via providers such as LexisNexis. Consequently, there is a need to create, analyze and provide a legal citation network with sufficient data to support legal research tasks. This paper describes the development and analysis of a legal citation Network for New Zealand containing over 300.000 decisions from 125 different courts of all areas of law and jurisdiction. Using python, the authors assembled web crawlers, scrapers and an OCR pipeline to collect and convert court decisions from openly available sources such as NZLII into uniform and machine-readable text. This facilitated the use of regular expressions to identify references to other court decisions from within the decision text. The data was then imported into a graph-based database (Neo4j) with the courts and their respective cases represented as nodes and the extracted citations as links. Furthermore, additional links between courts of connected cases were added to indicate an indirect citation between the courts. Neo4j, as a graph-based database, allows efficient querying and use of network algorithms such as PageRank to reveal the most influential/most cited courts and court decisions over time. This paper shows that the in-degree distribution of the New Zealand legal citation network resembles a power-law distribution, which indicates a possible scale-free behavior of the network. This is in line with findings of the respective citation networks of the U.S. Supreme Court, Austria and Germany. The authors of this paper provide the database as an openly available data source to support further legal research. The decision texts can be exported from the database to be used for NLP-related legal research, while the network can be used for in-depth analysis. For example, users of the database can specify the network algorithms and metrics to only include specific courts to filter the results to the area of law of interest.

Keywords: case citation network, citation analysis, network analysis, Neo4j

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Authors: Dalma Varga, Nora Hubayne H.

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Nowadays, among the measures taken to offset the consequences of climate change, water resources management is one of the key tools, which can include excess water management. As a result of climate change’s effects and as a result of the frequent inappropriate landuse, more and more areas are affected by the excess water inundation. Hungary is located in the deepest part of the Pannonian Basin, which is exposed to water damage – especially lowland areas that are endangered by floods or excess waters. The periodical presence of excess water creates specific habitats in a given area, which have ecological, functional, and aesthetic values. Excess water inundation affects approximately 74% of Hungary’s lowland areas, of which about 46% is also under nature protection (such as national parks, protected landscape areas, nature conservation areas, Natura 2000 sites, etc.). These data prove that areas exposed to excess water inundation – which are predominantly characterized by agricultural land uses – have an important ecological role. Other research works have confirmed the presence of numerous rare and endangered plant species in drainage canals, on grasslands exposed to excess water, and on special agricultural fields with mud vegetation. The goal of this research is to define and analyze ecosystem services of areas exposed to excess water inundation. In addition to this, it is also important to determine the quantified indicators of these areas’ natural and landscape values besides the presence of protected species and the naturalness of habitats, so all in all, to analyze the various nature protections related to excess water. As a result, a practice-orientated assessment method has been developed that provides the ecological water demand, assimilates to ecological and habitat aspects, contributes to adaptive excess water management, and last but not least, increases or maintains the share of the green infrastructure network. In this way, it also contributes to reduce and mitigate the negative effects of climate change.

Keywords: ecosystem services, landscape architecture, excess water management, green infrastructure planning

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Authors: Mahmoud Ahmed Farrag, Ali Zain Elabdeen Heikal, Mohamed Shawky Ahmed, Ahmed Osama Amer

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Crowd-sourced data refers to data that is collected and shared by a large number of individuals or organizations, often through the use of digital technologies such as mobile devices and social media. The shortage in crash data collection in developing countries makes it difficult to fully understand and address road safety issues in these regions. In developing countries, crowd-sourced data can be a valuable tool for improving road safety, particularly in urban areas where the majority of road crashes occur. This study is -to our best knowledge- the first to develop safety performance functions using crowd-sourced data by adopting a negative binomial structure model and the Full Bayes model to investigate traffic safety for urban road networks and provide insights into the impact of roadway characteristics. Furthermore, as a part of the safety management process, network screening has been undergone through applying two different methods to rank the most hazardous road segments: PCR method (adopted in the Highway Capacity Manual HCM) as well as a graphical method using GIS tools to compare and validate. Lastly, recommendations were suggested for policymakers to ensure safer roads.

Keywords: crowdsourced data, road crashes, safety performance functions, Full Bayes models, network screening

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Authors: José Luis Carrillo-Medina, Roberto Latorre

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Experimental evidence has revealed that different living neural systems can sign their output signals with some specific neural signature. Although experimental and modeling results suggest that neural signatures can have an important role in the activity of neural networks in order to identify the source of the information or to contextualize a message, the functional meaning of these neural fingerprints is still unclear. The existence of cellular mechanisms to identify the origin of individual neural signals can be a powerful information processing strategy for the nervous system. We have recently built different models to study the ability of a neural network to process information based on the emission and recognition of specific neural fingerprints. In this paper we further analyze the features that can influence on the information processing ability of this kind of networks. In particular, we focus on the role that the duration of a refractory period in each neuron after emitting a signed message can play in the network collective dynamics.

Keywords: neural signature, neural fingerprint, processing based on signal identification, self-organizing neural network

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Authors: Emin Gundogar, Aysegul Yilmaz

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Strategic performance control is a significant procedure in management. There are various methods to improve this procedure. This study introduces an information system that is developed to score performance for municipal management. The application of the system is clarified by exemplifying municipal processes.

Keywords: management information system, municipal management, performance control

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Authors: Ajish Sreedharan

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With the fast evolution of digital data exchange, security information becomes much important in data storage and transmission. Due to the increasing use of images in industrial process, it is essential to protect the confidential image data from unauthorized access. As encryption process is applied to the whole image in AES ,it is difficult to improve the efficiency. In this paper, wavelet decomposition is used to concentrate the main information of image to the low frequency part. Then, AES encryption is applied to the low frequency part. The high frequency parts are XORed with the encrypted low frequency part and a wavelet reconstruction is applied. Theoretical analysis and experimental results show that the proposed algorithm has high efficiency, and satisfied security suits for image data transmission.

Keywords: discrete wavelet transforms, AES, dynamic SBox

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Authors: K. Govender, M. Sinclair

Abstract:

This paper demonstrates a proof of concept whereby shorter trips and land use densification can be promoted through an alternative approach to planning and implementation of road infrastructure in the South African context. It briefly discusses how the development of the Compact City concept relies on a combination of promoting shorter trips and densification through a change in focus in road infrastructure provision. The methodology developed in this paper uses a traffic model to test the impact of synthesized deterrence functions on congestion locations in the road network through the assignment of traffic on the study network. The results from this study demonstrate that intelligent planning of road infrastructure can indeed promote reduced urban sprawl, increased residential density and mixed-use areas which are supported by an efficient public transport system; and reduced dependence on the freeway network with a fixed road infrastructure budget. The study has resonance for all cities where urban sprawl is seemingly unstoppable.

Keywords: compact cities, densification, road infrastructure planning, transportation modelling

Procedia PDF Downloads 178

Authors: Noel Paolo Domingo, James Paul Menina, Laurente Ferrer

Abstract:

Most people were forced to stay at home and limit their physical contact during the COVID-19 pandemic. Due to the situation, strict implementation of government policies and safety protocols encouraged consumers to utilize cashless or digital transactions through e-wallets. In this study, the researchers aim to investigate the efficiency of using e-wallets as a payment method during the COVID-19 pandemic in Marikina City. The study examined the efficiency of e-wallets in terms of Usefulness, Convenience, and Safety and Security based on respondents’ assessment. Questionnaires developed by the researchers were distributed to a total of 400 e-wallet users in Marikina City aged 15 years old and above to gather data by using a purposive sampling technique. The data collected was processed using SPSS version 26. Frequency, percentage, and mean were utilized to describe the profile of respondents and their assessment of e-wallets in terms of the three constructs. ANOVA and t-tests were also employed to test the significant differences in the respondent’s assessment when the demographic profile was considered. The study revealed that when it comes to usefulness, e-wallet is efficient while in terms of convenience, and safety and security, e-wallet has been proven to be very efficient. During the COVID-19 pandemic, utilizing e-wallets has been embraced by most consumers. By enhancing its features, more people will be satisfied with using e-wallets.

Keywords: efficiency of e-wallets, usefulness, convenience, safety and security

Procedia PDF Downloads 141