Search results for: network hierarchy

Authors: Liu Jiaxin

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This paper seeks to do an in-depth investigation on the phenomenon of Early Modern era (1500-1700s) Livonian werewolves. Noting their uniqueness in comparison to contemporaneous werewolves hailing from other geographic areas, the paper suggests that the Livonian werewolf is a metaphor for Livonian society at that time, one which was characterized by social turmoil and strict class hierarchy. This metaphor was utilized by different classes to establish their own interests in society, and thus the paper concludes that the werewolf is a mutable artifact whose value is contingent on its social context. This is demonstrated by the particular case of Old Thiess—a poor, elderly Livonian peasant who gave an unorthodox and anomalous testimony when accused of being a werewolf. In his court statement, it is shown how Thiess was, in fact, alluding to social tensions by lambasting the rich German elite and establishing the righteousness of the peasantry, of which he was a member. A close reading method was utilized on the trial transcript of Old Thiess with heavy reference to Carlo Ginzburg and Bruce Lincoln’s collaborative work Old Thiess, a Livonian werewolf: a classic case in comparative perspective. Through a contextual reading of Livonia’s social atmosphere, the paper draws connections between the content of the trial to wider societal disturbances happening at the time. The thesis—that the werewolf is a flexible metaphor for the social milieu—is further buttressed by numerous contemporaneous sources that had similar messages as Thiess’ transcript, which are discussed as well.

Keywords: early-modern baltic, Livonia, Old Thiess, social history, werewolves

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Authors: Ophir Nave

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In our research, we present the concept of singularly perturbed vector field (SPVF) method, and its application to thermal explosion of diesel spray combustion. Given a system of governing equations, which consist of hidden Multi-scale variables, the SPVF method transfer and decompose such system to fast and slow singularly perturbed subsystems (SPS). The SPVF method enables us to understand the complex system, and simplify the calculations. Later powerful analytical, numerical and asymptotic methods (e.g method of integral (invariant) manifold (MIM), the homotopy analysis method (HAM) etc.) can be applied to each subsystem. We compare the results obtained by the methods of integral invariant manifold and SPVF apply to spray droplets combustion model. The research deals with the development of an innovative method for extracting fast and slow variables in physical mathematical models. The method that we developed called singular perturbed vector field. This method based on a numerical algorithm applied to global quasi linearization applied to given physical model. The SPVF method applied successfully to combustion processes. Our results were compared to experimentally results. The SPVF is a general numerical and asymptotical method that reveals the hierarchy (multi-scale system) of a given system.

Keywords: polydisperse spray, model reduction, asymptotic analysis, multi-scale systems

Procedia PDF Downloads 220

Authors: Anukriti Kumar, Tanmay Singh, Dinesh Kumar Vishwakarma

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Traffic control has been one of the most common and irritating problems since the time automobiles have hit the roads. Problems like traffic congestion have led to a significant time burden around the world and one significant solution to these problems can be the proper implementation of the Intelligent Transport System (ITS). It involves the integration of various tools like smart sensors, artificial intelligence, position technologies and mobile data services to manage traffic flow, reduce congestion and enhance driver's ability to avoid accidents during adverse weather. Road and traffic signs’ recognition is an emerging field of research in ITS. Classification problem of traffic signs needs to be solved as it is a major step in our journey towards building semi-autonomous/autonomous driving systems. The purpose of this work focuses on implementing an approach to solve the problem of traffic sign classification by developing a Convolutional Neural Network (CNN) classifier using the GTSRB (German Traffic Sign Recognition Benchmark) dataset. Rather than using hand-crafted features, our model addresses the concern of exploding huge parameters and data method augmentations. Our model achieved an accuracy of around 97.6% which is comparable to various state-of-the-art architectures.

Keywords: multiclass classification, convolution neural network, OpenCV

Procedia PDF Downloads 176

Authors: Fei Gao, Xinyang Dong, Yisu Ge, Shufang Lu, Libo Weng

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Vehicle color recognition plays an important role in traffic accident investigation. However, due to the influence of illumination, weather, and noise, vehicle color recognition still faces challenges. In this paper, a vehicle color classification network based on spatial cluster loss and channel attention mechanism (SCNet) is proposed for vehicle color recognition. A channel attention module is applied to extract the features of vehicle color representative regions and reduce the weight of nonrepresentative color regions in the channel. The proposed loss function, called spatial clustering loss (SC-loss), consists of two channel-specific components, such as a concentration component and a diversity component. The concentration component forces all feature channels belonging to the same class to be concentrated through the channel cluster. The diversity components impose additional constraints on the channels through the mean distance coefficient, making them mutually exclusive in spatial dimensions. In the comparison experiments, the proposed method can achieve state-of-the-art performance on the public datasets, VCD, and VeRi, which are 96.1% and 96.2%, respectively. In addition, the ablation experiment further proves that SC-loss can effectively improve the accuracy of vehicle color recognition.

Keywords: feature extraction, convolutional neural networks, intelligent transportation, vehicle color recognition

Procedia PDF Downloads 183

Authors: Pui Shan Wong, Kosuke Tashiro, Satoru Kuhara, Sachiyo Aburatani

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Functional genomics and gene regulation inference has readily expanded our knowledge and understanding of gene interactions with regards to expression regulation. With the advancement of transcriptome sequencing in time-series comes the ability to study the sequential changes of the transcriptome. This method presented here works to augment existing regulation networks accumulated in literature with transcriptome data gathered from time-series experiments to construct a sequential representation of transcription factor activity. This method is applied on a time-series RNA-Seq data set from Escherichia coli as it transitions from growth to stationary phase over five hours. Investigations are conducted on the various metabolic activities in gene regulation processes by taking advantage of the correlation between regulatory gene pairs to examine their activity on a dynamic network. Especially, the changes in metabolic activity during phase transition are analyzed with focus on the pagP gene as well as other associated transcription factors. The visualization of the sequential transcriptional activity is used to describe the change in metabolic pathway activity originating from the pagP transcription factor, phoP. The results show a shift from amino acid and nucleic acid metabolism, to energy metabolism during the transition to stationary phase in E. coli.

Keywords: Escherichia coli, gene regulation, network, time-series

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Authors: Tarek Dandashi

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WSNs may provide a fast and reliable solution for the early detection of environment events like forest fires. This is crucial for alerting and calling for fire brigade intervention. Sensor nodes communicate sensor data to a host station, which enables a global analysis and the generation of a reliable decision on a potential fire and its location. A WSN with TinyOS and nesC for the capturing and transmission of a variety of sensor information with controlled source, data rates, duration, and the records/displaying activity traces is presented. We propose a similarity distance (SD) between the distribution of currently sensed data and that of a reference. At any given time, a fire causes diverging opinions in the reported data, which alters the usual data distribution. Basically, SD consists of a metric on the Cumulative Distribution Function (CDF). SD is designed to be invariant versus day-to-day changes of temperature, changes due to the surrounding environment, and normal changes in weather, which preserve the data locality. Evaluation shows that SD sensitivity is quadratic versus an increase in sensor node temperature for a group of sensors of different sizes and neighborhood. Simulation of fire spreading when ignition is placed at random locations with some wind speed shows that SD takes a few minutes to reliably detect fires and locate them. We also discuss the case of false negative and false positive and their impact on the decision reliability.

Keywords: forest fire, WSN, wireless sensor network, algortihm

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Authors: Ghodhbani Salah, Jemili Farah

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With the growth of cyber attacks, information safety has become an important issue all over the world. Many firms rely on security technologies such as intrusion detection systems (IDSs) to manage information technology security risks. IDSs are considered to be the last line of defense to secure a network and play a very important role in detecting large number of attacks. However the main problem with today’s most popular commercial IDSs is generating high volume of alerts and huge number of false positives. This drawback has become the main motivation for many research papers in IDS area. Hence, in this paper we present a data mining technique to assist network administrators to analyze and reduce false positive alarms that are produced by an IDS and increase detection accuracy. Our data mining technique is unsupervised clustering method based on hybrid ANT algorithm. This algorithm discovers clusters of intruders’ behavior without prior knowledge of a possible number of classes, then we apply K-means algorithm to improve the convergence of the ANT clustering. Experimental results on real dataset show that our proposed approach is efficient with high detection rate and low false alarm rate.

Keywords: intrusion detection system, alarm filtering, ANT class, ant clustering, intruders’ behaviors, false alarms

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Authors: Ganesh B. Shinde, Vijaya B. Musande

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Cotton crop identification based on the timely information has significant advantage to the different implications of food, economic and environment. Due to the significant advantages, the accurate detection of cotton crop regions using supervised learning procedure is challenging problem in remote sensing. Here, classifiers on the direct image are played a major role but the results are not much satisfactorily. In order to further improve the effectiveness, variety of vegetation indices are proposed in the literature. But, recently, the major challenge is to find the better vegetation indices for the cotton crop identification through the proposed methodology. Accordingly, fuzzy c-means clustering is combined with neural network algorithm, trained by Levenberg-Marquardt for cotton crop classification. To experiment the proposed method, five LISS-III satellite images was taken and the experimentation was done with six vegetation indices such as Simple Ratio, Normalized Difference Vegetation Index, Enhanced Vegetation Index, Green Atmospherically Resistant Vegetation Index, Wide-Dynamic Range Vegetation Index, Green Chlorophyll Index. Along with these indices, Green Leaf Area Index is also considered for investigation. From the research outcome, Green Atmospherically Resistant Vegetation Index outperformed with all other indices by reaching the average accuracy value of 95.21%.

Keywords: Fuzzy C-Means clustering (FCM), neural network, Levenberg-Marquardt (LM) algorithm, vegetation indices

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Authors: Mohammad Reza Esmaili

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One of the most important parts of the restoration process of a power network is the synchronizing of its subsystems. In this situation, the biggest concern of the system operators will be the reduction of the standing phase angle (SPA) between the endpoints of the two islands. In this regard, the system operators perform various actions and maneuvers so that the synchronization operation of the subsystems is successfully carried out and the system finally reaches acceptable stability. The most common of these actions include load control, generation control and, in some cases, changing the network topology. Although these maneuvers are simple and common, due to the weak network and extreme load changes, the restoration will be associated with low speed. One of the best ways to control the SPA is to use FACTS devices. By applying a soft control signal, these tools can reduce the SPA between two subsystems with more speed and accuracy, and the synchronization process can be done in less time. Meanwhile, the unified power controller (UPFC), a series-parallel compensator device with the change of transmission line power and proper adjustment of the phase angle, will be the proposed option in order to realize the subject of this research. Therefore, with the optimal placement of UPFC in a power system, in addition to improving the normal conditions of the system, it is expected to be effective in reducing the SPA during power system restoration. Therefore, the presented paper provides an optimal structure to coordinate the three problems of improving the division of subsystems, reducing the SPA and optimal power flow with the aim of determining the optimal location of UPFC and optimal subsystems. The proposed objective functions in this paper include maximizing the quality of the subsystems, reducing the SPA at the endpoints of the subsystems, and reducing the losses of the power system. Since there will be a possibility of creating contradictions in the simultaneous optimization of the proposed objective functions, the structure of the proposed optimization problem is introduced as a non-linear multi-objective problem, and the Pareto optimization method is used to solve it. The innovative technique proposed to implement the optimization process of the mentioned problem is an optimization algorithm called the water cycle (WCA). To evaluate the proposed method, the IEEE 39 bus power system will be used.

Keywords: UPFC, SPA, water cycle algorithm, multi-objective problem, pareto

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Authors: Mohamed Rasslan, Doaa Abdelrahman, Mahmoud M. Nasreldin, Ghada Farouk, Heba K. Aslan

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Blockchain is a distributed database that endorses transparency while bitcoin is a decentralized cryptocurrency (electronic cash) that endorses anonymity and is powered by blockchain technology. Smart contracts are programs that are stored on a blockchain. Smart contracts are executed when predetermined conditions are fulfilled. Smart contracts automate the agreement execution in order to make sure that all participants immediate-synchronism of the outcome-certainty, without any intermediary's involvement or time loss. Currently, the Bitcoin market worth billions of dollars. Bitcoin could be transferred from one purchaser to another without the need for an intermediary bank. Network nodes through cryptography verify bitcoin transactions, which are registered in a public-book called “blockchain”. Bitcoin could be replaced by other coins, merchandise, and services. Rapid growing of the bitcoin market-value, encourages its counterparts to make use of its weaknesses and exploit vulnerabilities for profit. Moreover, it motivates scientists to define known vulnerabilities, offer countermeasures, and predict future threats. In his paper, we study blockchain technology and bitcoin from the attacker’s point of view. Furthermore, mitigations for the attacks are suggested, and contemporary security solutions are discussed. Finally, research methods that achieve strict security and privacy protocol are elaborated.

Keywords: Cryptocurrencies, Blockchain, Bitcoin, Smart Contracts, Peer-to-Peer Network, Security Issues, Privacy Techniques

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Authors: Yun-na Wu, Zhen Wang

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Due to the economic downturn and the deterioration of the living environment, the development of residential buildings as high energy consuming building is gradually changing from “extensive” to green building in China. So, the evaluation system of green building is continuously improved, but the current evaluation work has the following problems: (1) There are differences in the cost of the actual investment and the purchasing power of residents, also construction target of green residential building is single and lacks multi-objective performance development. (2) Green building evaluation lacks regional characteristics and cannot reflect the different regional residents demand. (3) In the process of determining the criteria weight, the experts’ judgment matrix is difficult to meet the requirement of consistency. Therefore, to solve those problems, questionnaires which are about the green residential building for Ningxia area are distributed, and the results of questionnaires can feedback the purchasing power of residents and the acceptance of the green building cost. Secondly, combined with the geographical features of Ningxia minority areas, the evaluation criteria system of green residential building is constructed. Finally, using the improved group AHP method and the grey clustering method, the criteria weight is determined, and a real case is evaluated, which is located in Xing Qing district, Ningxia. A conclusion can be obtained that the professional evaluation for this project and good social recognition is basically the same.

Keywords: evaluation, green residential building, grey clustering method, group AHP

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Authors: Zbigniew Olczykowski

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The paper presents the impact of work on the electric arc furnace power grid. The arc furnace operating will be modeled at different power conditions of steelworks. The paper will describe how to determine the increase in voltage fluctuations caused by working in parallel arc furnaces. The analysis of indicators characterizing the quality of electricity recorded during several cycles of measurement made at the same time at three points grid, with different power and different short-circuit rated voltage, will be carried out. The measurements analysis presented in this paper were conducted in the mains of one of the Polish steel. The indicators characterizing the quality of electricity was recorded during several cycles of measurement while making measurements at three points of different power network short-circuit power and various voltage ratings. Measurements of power quality indices included the one-week measurement cycles in accordance with the EN-50160. Data analysis will include the results obtained during the simultaneous measurement of three-point grid. This will determine the actual propagation of interference generated by the device. Based on the model studies and measurements of quality indices of electricity we will establish the effect of a specific arc on the mains. The short-circuit power network’s minimum value will also be estimated, this is necessary to limit the voltage fluctuations generated by arc furnaces.

Keywords: arc furnaces, long-term flicker, measurement and modeling of power quality, voltage fluctuations

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Authors: Maharani Yulisti, Amin Mugera, James Fogarty

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Food safety standards have received significant attention in the fisheries global market due to health issues, free trade agreements, and increasing aquaculture production. Vertical coordination throughout the supply chain of fish producing and exporting countries is needed to meet food safety demands imposed by importing countries. However, the complexities of the supply chain governance structures and difficulties in standard implementation can generate safety uncertainty and high transaction costs. Using a Transaction Cost Economics framework, this paper examines the alignment between food safety standards and the governance structures in the shrimp supply chain in Indonesia. We find the supply chain is organized closer to the hierarchy-like governance structure where private standard (organic standard) are implemented and more towards a market-like governance structure where public standard (IndoGAP certification) are more prevalent. To verify the statements, two cases are examined from Sidoarjo district as a centre of shrimp production in Indonesia. The results show that public baseline FSS (Food Safety Standards) need additional mechanism to achieve a coordinated chain-wide response because uncertainty, asset specificity, and performance measurement problems are high in this chain. Organic standard as private chain-wide FSS is more efficient because it has been achieved by hierarchical-like type of governance structure.

Keywords: governance structure, shrimp value chain, food safety standards, transaction costs economics

Procedia PDF Downloads 379

Authors: Darshani Premaratne, Afshin Kandampath Puthiyadath

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The Government of Qatar is taking active steps in improving quality of health care industry in the state of Qatar. In this initiative development and market introduction of Clinical Information System and Electronic Health Record (EHR) system are proved to be a highly challenging process. Along with an organization specialized on EHR system development and with the blessing of Health Ministry of Qatar the process of introduction of EHR system in Qatar healthcare industry was undertaken. Initially a market survey was carried out to understand the requirements. Secondly, the available government regulations, needs and possible upcoming regulations were carefully studied before deployment of resources for software development. Sufficient flexibility was allowed to cater for both the changes in the market and the regulations. As the first initiative a system that enables integration of referral network where referral clinic and laboratory system for all single doctor (and small scale) clinics was developed. Setting of isolated single doctor clinics all over the state to bring in to an integrated referral network along with a referral hospital need a coherent steering force and a solid top down framework. This paper discusses about the lessons learned in developing, in obtaining approval of the health ministry and in introduction to the industry of the single doctor referral network along with an EHR system. It was concluded that development of this nature required continues balance between the market requirements and upcoming regulations. Further accelerating the development based on the emerging needs, implementation based on the end user needs while tallying with the regulations, diffusion, and uptake of demand-driven and evidence-based products, tools, strategies, and proper utilization of findings were equally found paramount in successful development of end product. Development of full scale Clinical Information System and EHR system are underway based on the lessons learned. The Government of Qatar is taking active steps in improving quality of health care industry in the state of Qatar. In this initiative development and market introduction of Clinical Information System and Electronic Health Record (EHR) system are proved to be a highly challenging process. Along with an organization specialized on EHR system development and with the blessing of Health Ministry of Qatar the process of introduction of EHR system in Qatar healthcare industry was undertaken. Initially a market survey was carried out to understand the requirements. Secondly the available government regulations, needs and possible upcoming regulations were carefully studied before deployment of resources for software development. Sufficient flexibility was allowed to cater for both the changes in the market and the regulations. As the first initiative a system that enables integration of referral network where referral clinic and laboratory system for all single doctor (and small scale) clinics was developed. Setting of isolated single doctor clinics all over the state to bring in to an integrated referral network along with a referral hospital need a coherent steering force and a solid top down framework. This paper discusses about the lessons learned in developing, in obtaining approval of the health ministry and in introduction to the industry of the single doctor referral network along with an EHR system. It was concluded that development of this nature required continues balance between the market requirements and upcoming regulations. Further accelerating the development based on the emerging needs, implementation based on the end user needs while tallying with the regulations, diffusion, and uptake of demand-driven and evidence-based products, tools, strategies, and proper utilization of findings were equally found paramount in successful development of end product. Development of full scale Clinical Information System and EHR system are underway based on the lessons learned.

Keywords: clinical information system, electronic health record, state regulations, integrated referral network of clinics

Procedia PDF Downloads 362

Authors: Osama Abdallah Mohammed Enan, Amin Babiker A/Nabi Mustafa

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The aim of this study is to evaluate and analyze different parameters of WCDMA (wideband code division multiplication). Moreover, this study also incorporates brief yet throughout analysis of WCDMA’s components as well as its internal architecture. This study also examines different power controls. These power controls may include open loop power control, closed or inner group loop power control and outer loop power control. Different handover techniques or methods of WCDMA are also illustrated in this study. These handovers may include hard handover, inter system handover and soft and softer handover. Different duplexing techniques are also described in the paper. This study has also presented an idea about different parameters of WCDMA that leads the system towards QoS issues. This may help the operator in designing and developing adequate network configuration. In addition to this, the study has also investigated various parameters including Bit Energy per Noise Spectral Density (Eb/No), Noise rise, and Bit Error Rate (BER). After simulating these parameters, using MATLAB environment, it was investigated that, for a given Eb/No value the system capacity increase by increasing the reuse factor. Besides that, it was also analyzed that, noise rise is decreasing for lower data rates and for lower interference levels. Finally, it was examined that, BER increase by using one type of modulation technique than using other type of modulation technique.

Keywords: duplexing, handover, loop power control, WCDMA

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Authors: Mimi Roy, Sriroop Chaudhuri

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Sustainable water supply is among the basic needs for human development, especially in the rural areas of the developing nations where safe water supply and basic sanitation infrastructure is direly needed. In light of the above, we propose a simple methodology to develop a composite water sustainability index (WSI) to assess the collective performance of the existing rural water supply services (RWSS) in India over time. The WSI will be computed by summarizing the details of all the different varieties of water supply schemes presently available in India comprising of 40 liters per capita per day (lpcd), 55 lpcd, and piped water supply (PWS) per household. The WSI will be computed annually, between 2010 and 2016, to elucidate changes in holistic RWSS performances. Results will be integrated within a robust geospatial framework to identify the ‘hotspots’ (states/districts) which have persistent issues over adequate RWSS coverage and warrant spatially-optimized policy reforms in future to address sustainable human development. Dataset will be obtained from the National Rural Drinking Water Program (NRDWP), operating under the aegis of the Ministry of Drinking Water and Sanitation (MoDWS), at state/district/block levels to offer the authorities a cross-sectional view of RWSS at different levels of administrative hierarchy. Due to simplistic design, complemented by spatio-temporal cartograms, similar approaches can also be adopted in other parts of the world where RWSS need a thorough appraisal.

Keywords: rural water supply services, piped water supply, sustainability, composite index, spatial, drinking water

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Authors: Zane Bulderberga

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Spatial dimension in development planning is becoming more topical in 21st century as a result of changes in population structure. Sustainable spatial development focuses on identifying and using territorial advantages to foster the harmonized development of the entire country, reducing negative effects of population concentration, increasing availability and mobility. EU and national development planning documents state polycentrism as main tool for balance spatial development, including investment concentration in growth centres. If mutual cooperation of growth centres as well as urban-rural cooperation is not fostered, then territorial differences can deepen and create unbalanced development. The aim of research: to evaluate the urban-rural interaction, elaborating spatial development scenarios in framework of Latvian regional policy. To perform the research monographic, comparison, abstract-logical method, synthesis and analysis will be used when studying the theoretical aspects of research aiming at collecting the ideas of scientists from different countries, concepts, regulations as well as to create meaningful scientific discussion. Hierarchy analysis process (AHP) will be used to state further scenarios of spatial development in Latvia. Experts from various institutions recognized urban-rural interaction and co-operation as an essential tool for the development. The most important factors for balanced spatial development in Latvia are availability of public transportation and improvement of service availability. Evaluating the three alternative scenarios, it was concluded that the urban-rural partnership will ensure a balanced development in Latvian regions.

Keywords: rural-urban interaction, rural-urban cooperation, spatial development, AHP

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Authors: Sharon Q. Yang, Robert J. Congleton

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Information security is a broad concept that covers any issues and concerns about the proper access and use of information on the Internet, including measures and procedures to protect intellectual property and private data from illegal access and online theft; the act of hacking; and any defensive technologies that contest such cybercrimes. As more research and commercial activities are conducted online, cybercrimes have increased significantly, putting sensitive information at risk. Information security has become critically important for organizations and private citizens alike. Hackers scan for network vulnerabilities on the Internet and steal data whenever they can. Cybercrimes disrupt our daily life, cause financial losses, and instigate fear in the public. Since the start of the pandemic, most data related cybercrimes targets have been either financial or health information from companies and organizations. Libraries also should have a high interest in understanding and adopting information security methods to protect their patron data and copyrighted materials. But according to information security professionals, higher education and cultural organizations, including their libraries, are the least prepared entities for cyberattacks. One recent example is that of Steven’s Institute of Technology in New Jersey in the US, which had its network hacked in 2020, with the hackers demanding a ransom. As a result, the network of the college was down for two months, causing serious financial loss. There are other cases where libraries, colleges, and universities have been targeted for data breaches. In order to build an effective defense, we need to understand the most common types of cybercrimes, including phishing, whaling, social engineering, distributed denial of service (DDoS) attacks, malware and ransomware, and hacker profiles. Our research will focus on each hacking technique and related defense measures; and the social background and reasons/purpose of hacker and hacking. Our research shows that hacking techniques will continue to evolve as new applications, housing information, and data on the Internet continue to be developed. Some cybercrimes can be stopped with effective measures, while others present challenges. It is vital that people understand what they face and the consequences when not prepared.

Keywords: cybercrimes, hacking technologies, higher education, information security, libraries

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Authors: Yeliz Sarı Nayim, B. Niyami Nayim

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Biotopes such as forest areas rich in biodiversity, wetlands, hedgerows and woodlands play important ecological roles in agricultural landscapes. Of these semi-natural areas and features, hedgerows are the most common landscape elements. Their most significant features are that they serve as a barrier between the agricultural lands, serve as shelter, add aesthetical value to the landscape and contribute significantly to the wildlife and biodiversity. Hedgerows surrounding agricultural landscapes also provide an important habitat for pollinators which are important for agricultural production. This study looks into the identification of hedgerows in agricultural lands in the Mugada rural area within Bartın province, Turkey. From field data and-and satellite images, it is clear that in this area, especially around rural settlements, large forest areas have been cleared for settlement and agriculture. A network of hedgerows is also apparent, which might potentially play an important role in the otherwise open agricultural landscape. We found that these hedgerows serve as an ecological and biological corridor, linking forest ecosystems. Forest patches of different sizes and creating a habitat network across the landscape. Some examples of this will be presented. The overall conclusion from the study is that ecologically, biologically and aesthetically important hedge biotopes should be maintained in the long term in agricultural landscapes such as this. Some suggestions are given for how they could be managed sustainably into the future.

Keywords: agricultural biotopes, Hedgerows, landscape ecology, Turkey

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Authors: Thilini M. Yatanwala

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CCTV (Closed-Circuit-Television) Surveillance System is being used in public places over decades and a large variety of data is being produced every moment. However, most of the CCTV data is stored in isolation without having integrity. As a result, identification of the behavior of suspicious people along with their location has become strenuous. This research was conducted to acquire more accurate and reliable timely information from the CCTV video records. The implemented system can identify human objects in public places based on outfit colors. Inter-process communication technologies were used to implement the CCTV camera network to track people in the premises. The research was conducted in three stages and in the first stage human objects were filtered from other movable objects available in public places. In the second stage people were uniquely identified based on their outfit colors and in the third stage an individual was continuously tracked in the CCTV network. A face detection algorithm was implemented using cascade classifier based on the training model to detect human objects. HAAR feature based two-dimensional convolution operator was introduced to identify features of the human face such as region of eyes, region of nose and bridge of the nose based on darkness and lightness of facial area. In the second stage outfit colors of human objects were analyzed by dividing the area into upper left, upper right, lower left, lower right of the body. Mean color, mod color and standard deviation of each area were extracted as crucial factors to uniquely identify human object using histogram based approach. Color based measurements were written in to XML files and separate directories were maintained to store XML files related to each camera according to time stamp. As the third stage of the approach, inter-process communication techniques were used to implement an acknowledgement based CCTV camera network to continuously track individuals in a network of cameras. Real time analysis of XML files generated in each camera can determine the path of individual to monitor full activity sequence. Higher efficiency was achieved by sending and receiving acknowledgments only among adjacent cameras. Suspicious incidents such as a person staying in a sensitive area for a longer period or a person disappeared from the camera coverage can be detected in this approach. The system was tested for 150 people with the accuracy level of 82%. However, this approach was unable to produce expected results in the presence of group of people wearing similar type of outfits. This approach can be applied to any existing camera network without changing the physical arrangement of CCTV cameras. The study of human identification and suspicious incident detection using outfit color analysis can achieve higher level of accuracy and the project will be continued by integrating motion and gait feature analysis techniques to derive more information from CCTV videos.

Keywords: CCTV surveillance, human detection and identification, image processing, inter-process communication, security, suspicious detection

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Authors: Ahmad Lutfi, Nikolas Dhega

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The Malala deposit in northwest Sulawesi is the only known porphyry molybdenum and the only source for rhenium, occurrence in Indonesia. The neural network method produces results that correspond very closely to those of the knowledge-based fuzzy logic method and weights of evidence method. This method required data of solid geology, regional faults, airborne magnetic, gamma-ray survey data and GIS data. This interpretation of the network output fits with the intuitive notion that a prospective area has characteristics that closely resemble areas known to contain mineral deposits. Contrasts with the weights of evidence and fuzzy logic methods, where, for a given grid location, each input-parameter value automatically results in an increase in the prospective estimated. Malala District indicated molybdenum anomalies in stream sediments from in excess of 15 km2 were obtained, including the Takudan Fault as most prominent structure with striking 40̊ to 60̊ over a distance of about 30 km and in most places weakly at anomaly B, developed over an area of 4 km2, with a ‘shell’ up to 50 m thick at the intrusive contact with minor mineralization occurring in the Tinombo Formation. Series of NW trending, steeply dipping fracture zones, named the East Zone has an estimated resource of 100 Mt at 0.14% MoS2 and minimum target of 150 Mt 0.25%. The Malala porphyries occur as stocks and dykes with predominantly granitic, with fluorine-poor class of molybdenum deposits and belongs to the plutonic sub-type. Unidirectional solidification textures consisting of subparallel, crenulated layers of quartz that area separated by layers of intrusive material textures. The deuteric nature of the molybdenum mineralization and the dominance of carbonate alteration.The nature of the Stage I with alteration barren quartz K‐feldspar; and Stage II with alteration quartz‐K‐feldspar‐apatite-molybdenite veins combined with the presence of disseminated molybdenite with primary biotite in the host intrusive.

Keywords: molybdenite, Malala, porphyries, anomaly B

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Authors: Nan Deng, Zhenqiu Liu

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Thousands of patients with metastatic tumors were diagnosed with cancers of unknown primary sites each year. The inability to identify the primary cancer site may lead to inappropriate treatment and unexpected prognosis. Nowadays, a large amount of genomics and transcriptomics cancer data has been generated by next-generation sequencing (NGS) technologies, and The Cancer Genome Atlas (TCGA) database has accrued thousands of human cancer tumors and healthy controls, which provides an abundance of resource to differentiate cancer types. Meanwhile, deep convolutional neural networks (CNNs) have shown high accuracy on classification among a large number of image object categories. Here, we utilize 25 cancer primary tumors and 3 normal tissues from TCGA and convert their RNA-Seq gene expression profiling to color images; train, validate and test a CNN classifier directly from these images. The performance result shows that our CNN classifier can archive >80% test accuracy on most of the tumors and normal tissues. Since the gene expression pattern of distant metastases is similar to their primary tumors, the CNN classifier may provide a potential computational strategy on identifying the unknown primary origin of metastatic cancer in order to plan appropriate treatment for patients.

Keywords: bioinformatics, cancer, convolutional neural network, deep leaning, gene expression pattern

Procedia PDF Downloads 299

Authors: A. Assad, T. Zayed

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Water networks (WNs) are responsible of providing adequate amounts of safe, high quality, water to the public. As other critical infrastructure systems, WNs are subjected to deterioration which increases the number of breaks and leaks and lower water quality. In Canada, 35% of water assets require critical attention and there is a significant gap between the needed and the implemented investments. Thus, the need for efficient rehabilitation programs is becoming more urgent given the paradigm of aging infrastructure and tight budget. The first step towards developing such programs is to formulate a Performance Index that reflects the current condition of water assets along with its criticality. While numerous studies in the literature have focused on various aspects of condition assessment and reliability, limited efforts have investigated the criticality of such components. Critical water mains are those whose failure cause significant economic, environmental or social impacts on a community. Inclusion of criticality in computing the performance index will serve as a prioritizing tool for the optimum allocating of the available resources and budget. In this study, several social, economic, and environmental factors that dictate the criticality of a water pipelines have been elicited from analyzing the literature. Expert opinions were sought to provide pairwise comparisons of the importance of such factors. Subsequently, Fuzzy Logic along with Analytical Network Process (ANP) was utilized to calculate the weights of several criteria factors. Multi Attribute Utility Theories (MAUT) was then employed to integrate the aforementioned weights with the attribute values of several pipelines in Montreal WN. The result is a criticality index, 0-1, that quantifies the severity of the consequence of failure of each pipeline. A novel contribution of this approach is that it accounts for both the interdependency between criteria factors as well as the inherited uncertainties in calculating the criticality. The practical value of the current study is represented by the automated tool, Excel-MATLAB, which can be used by the utility managers and decision makers in planning for future maintenance and rehabilitation activities where high-level efficiency in use of materials and time resources is required.

Keywords: water networks, criticality assessment, asset management, fuzzy analytical network process

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Authors: Hao Yan, Xiaobing Zhang

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The working mechanism of miniaturized solid rocket motors (SRMs) is not yet fully understood. It is imperative to explore its unique features. However, there are many disadvantages to using common multi-objective evolutionary algorithms (MOEAs) in predicting the parameters of the miniaturized SRM during its conceptual design phase. Initially, the design variables and objectives are constrained in a lumped parameter model (LPM) of this SRM, which leads to local optima in MOEAs. In addition, MOEAs require a large number of calculations due to their population strategy. Although the calculation time for simulating an LPM just once is usually less than that of a CFD simulation, the number of function evaluations (NFEs) is usually large in MOEAs, which makes the total time cost unacceptably long. Moreover, the accuracy of the LPM is relatively low compared to that of a CFD model due to its assumptions. CFD simulations or experiments are required for comparison and verification of the optimal results obtained by MOEAs with an LPM. The conceptual design phase based on MOEAs is a lengthy process, and its results are not precise enough due to the above shortcomings. An artificial neural network (ANN) based parameter prediction is proposed as a way to reduce time costs and improve prediction accuracy. In this method, an ANN is used to build a surrogate model that is trained with a 3D numerical simulation. In design, the original LPM is replaced by a surrogate model. Each case uses the same MOEAs, in which the calculation time of the two models is compared, and their optimization results are compared with 3D simulation results. Using the surrogate model for the parameter prediction process of the miniaturized SRMs results in a significant increase in computational efficiency and an improvement in prediction accuracy. Thus, the ANN-based surrogate model does provide faster and more accurate parameter prediction for an initial design scheme. Moreover, even when the MOEAs converge to local optima, the time cost of the ANN-based surrogate model is much lower than that of the simplified physical model LPM. This means that designers can save a lot of time during code debugging and parameter tuning in a complex design process. Designers can reduce repeated calculation costs and obtain accurate optimal solutions by combining an ANN-based surrogate model with MOEAs.

Keywords: artificial neural network, solid rocket motor, multi-objective evolutionary algorithm, surrogate model

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Authors: Jesus Carretero, Mario Vasile, Guillermo Izquierdo, Javier Garcia-Blas

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Currently, there is a so called ‘identity crisis’ in cybersecurity caused by the substantial security, privacy and usability shortcomings encountered in existing systems for identity management. Federated Identity Management (FIM) could be solution for this crisis, as it is a method that facilitates management of identity processes and policies among collaborating entities without enforcing a global consistency, that is difficult to achieve when there are ID legacy systems. To cope with this problem, the Connecting Europe Facility (CEF) initiative proposed in 2014 a federated solution in anticipation of the adoption of the Regulation (EU) N°910/2014, the so-called eIDAS Regulation. At present, a network of eIDAS Nodes is being deployed at European level to allow that every citizen recognized by a member state is to be recognized within the trust network at European level, enabling the consumption of services in other member states that, until now were not allowed, or whose concession was tedious. This is a very ambitious approach, since it tends to enable cross-border authentication of Member States citizens without the need to unify the authentication method (eID Scheme) of the member state in question. However, this federation is currently managed by member states and it is initially applied only to citizens and public organizations. The goal of this paper is to present the results of a European Project, named eID@Cloud, that focuses on the integration of eID in 5 cloud platforms belonging to authentication service providers of different EU Member States to act as Service Providers (SP) for private entities. We propose an initiative based on a private eID Scheme both for natural and legal persons. The methodology followed in the eID@Cloud project is that each Identity Provider (IdP) is subscribed to an eIDAS Node Connector, requesting for authentication, that is subscribed to an eIDAS Node Proxy Service, issuing authentication assertions. To cope with high loads, load balancing is supported in the eIDAS Node. The eID@Cloud project is still going on, but we already have some important outcomes. First, we have deployed the federation identity nodes and tested it from the security and performance point of view. The pilot prototype has shown the feasibility of deploying this kind of systems, ensuring good performance due to the replication of the eIDAS nodes and the load balance mechanism. Second, our solution avoids the propagation of identity data out of the native domain of the user or entity being identified, which avoids problems well known in cybersecurity due to network interception, man in the middle attack, etc. Last, but not least, this system allows to connect any country or collectivity easily, providing incremental development of the network and avoiding difficult political negotiations to agree on a single authentication format (which would be a major stopper).

Keywords: cybersecurity, identity federation, trust, user authentication

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Authors: Mohanad Alhabo, Li Zhang, Naveed Nawaz

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Small cell deployment in 5G networks is a promising technology to enhance capacity and coverage. However, unplanned deployment may cause high interference levels and high number of unnecessary handovers, which in turn will result in an increase in the signalling overhead. To guarantee service continuity, minimize unnecessary handovers, and reduce signalling overhead in heterogeneous networks, it is essential to properly model the handover decision problem. In this paper, we model the handover decision according to Multiple Attribute Decision Making (MADM) method, specifically Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS). In this paper, we propose a hybrid TOPSIS method to control the handover in heterogeneous network. The proposed method adopts a hybrid weighting, which is a combination of entropy and standard deviation. A hybrid weighting control parameter is introduced to balance the impact of the standard deviation and entropy weighting on the network selection process and the overall performance. Our proposed method shows better performance, in terms of the number of frequent handovers and the mean user throughput, compared to the existing methods.

Keywords: handover, HetNets, interference, MADM, small cells, TOPSIS, weight

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Authors: Mohamamd Shahjahan

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Background: Cybercrime is common phenomenon at present both developed and developing countries. Young generation, especially adolescents now engaged internet frequently and they commit cybercrime frequently in Bangladesh. Objective: In this regard, the present study on the pattern of cybercrime among youngers of Bangladesh has been conducted. Methods and tools: This study was a cross-sectional study, descriptive in nature. Non-probability accidental sampling technique has been applied to select the sample because of the nonfinite population and the sample size was 167. A printed semi-structured questionnaire was used to collect data. Results: The study shows that adolescents mainly do hacking (94.6%), pornography (88.6%), software piracy (85 %), cyber theft (82.6%), credit card fraud (81.4%), cyber defamation (75.6%), sweet heart swindling (social network) (65.9%) etc. as cybercrime. According to findings the major causes of cybercrime among the respondents in Bangladesh were- weak laws (88.0%), defective socialization (81.4%), peer group influence (80.2%), easy accessibility to internet (74.3%), corruption (62.9%), unemployment (58.7%), and poverty (24.6%) etc. It is evident from the study that 91.0% respondents used password cracker as the techniques of cyber criminality. About 76.6%, 72.5%, 71.9%, 68.3% and 60.5% respondents’ technique was key loggers, network sniffer, exploiting, vulnerability scanner and port scanner consecutively. Conclusion: The study concluded that pattern of cybercrimes is frequently changing and increasing dramatically. Finally, it is recommending that the private public partnership and execution of existing laws can be controlling this crime.

Keywords: cybercrime, adolescents, pattern, internet

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Authors: Yana Snegireva

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Carbonate reservoirs are known for their heterogeneity, resulting from various geological processes such as diagenesis and fracturing. These complexities may cause great challenges in understanding fluid flow behavior and predicting the production performance of naturally fractured reservoirs. The investigation of carbonate reservoirs is crucial, as many petroleum reservoirs are naturally fractured, which can be difficult due to the complexity of their fracture networks. This can lead to geological uncertainties, which are important for global petroleum reserves. The problem outlines the key challenges in carbonate reservoir modeling, including the accurate representation of fractures and their connectivity, as well as capturing the impact of fractures on fluid flow and production. Traditional reservoir modeling techniques often oversimplify fracture networks, leading to inaccurate predictions. Therefore, there is a need for a modern approach that can capture the complexities of carbonate reservoirs and provide reliable predictions for effective reservoir management and production optimization. The modern approach to carbonate reservoir modeling involves the utilization of the hybrid fracture modeling approach, including the discrete fracture network (DFN) method and implicit fracture network, which offer enhanced accuracy and reliability in characterizing complex fracture systems within these reservoirs. This study focuses on the application of the hybrid method in the Nepsko-Botuobinskaya anticline of the Eastern Siberia field, aiming to prove the appropriateness of this method in these geological conditions. The DFN method is adopted to model the fracture network within the carbonate reservoir. This method considers fractures as discrete entities, capturing their geometry, orientation, and connectivity. But the method has significant disadvantages since the number of fractures in the field can be very high. Due to limitations in the amount of main memory, it is very difficult to represent these fractures explicitly. By integrating data from image logs (formation micro imager), core data, and fracture density logs, a discrete fracture network (DFN) model can be constructed to represent fracture characteristics for hydraulically relevant fractures. The results obtained from the DFN modeling approaches provide valuable insights into the East Siberia field's carbonate reservoir behavior. The DFN model accurately captures the fracture system, allowing for a better understanding of fluid flow pathways, connectivity, and potential production zones. The analysis of simulation results enables the identification of zones of increased fracturing and optimization opportunities for reservoir development with the potential application of enhanced oil recovery techniques, which were considered in further simulations on the dual porosity and dual permeability models. This approach considers fractures as separate, interconnected flow paths within the reservoir matrix, allowing for the characterization of dual-porosity media. The case study of the East Siberia field demonstrates the effectiveness of the hybrid model method in accurately representing fracture systems and predicting reservoir behavior. The findings from this study contribute to improved reservoir management and production optimization in carbonate reservoirs with the use of enhanced and improved oil recovery methods.

Keywords: carbonate reservoir, discrete fracture network, fracture modeling, dual porosity, enhanced oil recovery, implicit fracture model, hybrid fracture model

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Authors: Bhim Kumar Dahal

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Transportation network development in the developing country is in rapid pace. The majority of the network belongs to railway and expressway which passes through diverse topography, landform and geological conditions despite the avoidance principle during route selection. Construction of such networks demand many low to high embankment which required improvement in the foundation soil. This paper is mainly focused on the various advanced ground improvement techniques used to improve the soft soil, modelling approach and its predictability for embankments construction. The ground improvement techniques can be broadly classified in to three groups i.e. densification group, drainage and consolidation group and reinforcement group which are discussed with some case studies.  Various methods were used in modelling of the embankments from simple 1-dimensional to complex 3-dimensional model using variety of constitutive models. However, the reliability of the predictions is not found systematically improved with the level of sophistication.  And sometimes the predictions are deviated more than 60% to the monitored value besides using same level of erudition. This deviation is found mainly due to the selection of constitutive model, assumptions made during different stages, deviation in the selection of model parameters and simplification during physical modelling of the ground condition. This deviation can be reduced by using optimization process, optimization tools and sensitivity analysis of the model parameters which will guide to select the appropriate model parameters.

Keywords: cement, improvement, physical properties, strength

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Authors: Omar Boutkhoum, Mohamed Hanine, Abdessadek Bendarag

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Sustainable economic growth is nowadays driving firms to extend toward the adoption of many green supply chain management (GSCM) solutions. However, the evaluation and selection of these solutions is a matter of concern that needs very serious decisions, involving complexity owing to the presence of various associated factors. To resolve this problem, a comparative analysis approach based on multi-criteria decision-making methods is proposed for adequate evaluation of sustainable supply chain management solutions. In the present paper, we propose an integrated decision-making model based on FAHP (Fuzzy Analytic Hierarchy Process), TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) and PROMETHEE (Preference Ranking Organisation METHod for Enrichment Evaluations) to contribute to a better understanding and development of new sustainable strategies for industrial organizations. Due to the varied importance of the selected criteria, FAHP is used to identify the evaluation criteria and assign the importance weights for each criterion, while TOPSIS and PROMETHEE methods employ these weighted criteria as inputs to evaluate and rank the alternatives. The main objective is to provide a comparative analysis based on TOPSIS and PROMETHEE processes to help make sound and reasoned decisions related to the selection problem of GSCM solution.

Keywords: GSCM solutions, multi-criteria analysis, decision support system, TOPSIS, FAHP, PROMETHEE

Procedia PDF Downloads 163