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1
Yakymchuk, N. M., and A. I. Toroshanko. "METHODS OF IDENTIFICATION AND COMPREHENSIVE DIAGNOSIS OF TELECOMMUNICATION SYSTEMS." Collection of scientific works of the Military Institute of Kyiv National Taras Shevchenko University, no. 69 (2020): 58–65. http://dx.doi.org/10.17721/2519-481x/2020/69-06.
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The article formulates the main tasks of management of information networks and telecommunications services in terms of ensuring their reliable operation. The telecommunication network is considered as a complex system consisting of many components, each of which has its own characteristics of operation during operation. The main functions of the telecommunication network control system are determined: fault detection and network status diagnostics, network device administration, forecasting and elimination of congestion and other possible deviations in network functioning, ensuring coordinated interaction between different types of control systems for providing telecommunication services with specified quality. Methods of analysis and management of networks are essentially a kind of identification methods, i.e. the current assessment of the parameters and condition of complex technical systems. There is a close relationship between identification and diagnostic tasks. The methods for solving these problems largely depend on the class to which the identification object can be assigned. Computer and telecommunication networks belong to the class of distributed systems with delays in signal and control information. Methods of retrospective identification are used to analyze the state of such systems. The influence of delays of signal and control information on the efficiency of search and determination of places of failures, overloads and emergency modes in communication networks is investigated. The results of computer simulation are given. The approach based on regular control of parameters and condition of network nodes taking into account delays of receipt of information on parameters and a condition of a concrete network node and delays of the control information necessary for adjustment of parameters of a network node as control object has found further development.
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Budzyński, Marcin, Jacek Szmagliński, Kazimierz Jamroz, Krystian Birr, Sławomir Grulkowski, and Joanna Wachnicka. "Assessing Tram Infrastructure Safety Using the Example of the City of Gdańsk." Journal of KONBiN 49, no. 3 (October 1, 2019): 293–322. http://dx.doi.org/10.2478/jok-2019-0060.
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Abstract Analysis of Gdańsk tram network statistics shows that incidents are quite frequent (about 650 within five years) and mostly involve collisions and crashes. As well as reducing the tram systems’ efficiency and reliability, incidents have a negative effect on road safety. As Polish cities extend their tram networks, they must also ensure that their existing networks are safe. This is to be achieved by conducting safety assessments. The article presents different assessment methods, at different stages of tram infrastructure lifecycle, providing a basis for a comprehensive diagnosis and recommendations for improvement. The objective of the study was to conduct a comprehensive safety assessment and analysis of the existing and planned tram network across Gdańsk, using different study methods and tools.
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Zhao, Qing Jian, and Zuo Min Wen. "Complex Social-Ecological Systems Network：New Perspective on the Sustainability." Advanced Materials Research 361-363 (October 2011): 1467–71. http://dx.doi.org/10.4028/www.scientific.net/amr.361-363.1467.
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The complex social-ecological systems network is an integrative platform of ecology, economy, management and complex networks which providing a new perspective on the comprehensive management of ecological and socio economical processes. Through research of the structures, functions and processes, one four-dimensional conceptual model of the complex social-ecological system for sustainable development was set up. The complex social-ecological systems comprise of natural subsystem, social subsystem, economic subsystem and integrative decision subsystem. The complex social-ecological systems network was defined as one six-element tuple which denotes the comprehensive spatial structure with different kinds of nodes of ecosystem, social system and economic system. The complex social-ecological systems network has some important characteristics including hierarchies, power-low, vulnerabilities, resilience, dynamics, co-evolution of flow and structure, et al. At last, based on the Multimedia Environment Pollutant Assessment System (MEPAS) of US EPA, the relationship between POPs (Persistent Organic Pollutants) exposure and lifetime fatal cancer risk was studied, and comprehensive risk network of the Taihu basin water pollution and human body health was established.
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Estakhr, Javad, Mohsen Simab, and Taher Niknam. "Security Analysis of Hybrid Multi-Carrier Energy Systems." Sustainability 13, no. 6 (March 12, 2021): 3102. http://dx.doi.org/10.3390/su13063102.
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Multi-carrier energy systems (MCESs) provide collaboration between various kinds of energy carriers to supply the electricity, heating, and cooling demands. With the widespread use of MCESs in recent years, the security assessment of energy systems has attracted the attention of many contemporary researchers. However, the complexity of an MCES, including electrical, natural gas, and district heating networks, and different uncertainties imposes vast challenges to keep a safe operation energy supply. In this paper, a systematic methodology for the security analysis of MCESs is presented. For this purpose, considering electrical, natural gas, and district heating networks, an integrated model of energy systems is introduced. The security analysis of this framework is evaluated using some indices. In this approach, two well-known performance indices, including power performance index (PIP) and voltage performance index (PIV), are used to analyze the electrical networks’ security. Besides, the concept of Energy not supplied (ENS) is used for natural gas and district heating networks. In this regard, security analysis of a typical MCES including the IEEE 14-bus electrical network, the IEEE 30-bus electrical network, 20-node Belgian natural gas network, and 14-node district heating network is examined. The applicability of the proposed technique will be proven using comprehensive simulation analysis.
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Zhou, Liang Sheng, Zhen Dong Tan, and Wei Guo Wu. "Study on Quality Management of Logistics Equipment Systems." Advanced Materials Research 662 (February 2013): 993–98. http://dx.doi.org/10.4028/www.scientific.net/amr.662.993.
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The research and manufacture of the military logistics equipment systems always brings problems in quality management for its complexity and particularity. To solve these problems, a analysis on equipment quality management is conducted. A comprehensive study on reliability, fault diagnosis, and risk analysis models are also performed. The reliability analysis of the system is fulfilled using a method of combined fuzzy inference and network analysis. This method solves the limitations of the traditional network analysis method, of which the result is defined for every failure mode. The abnormality of parameters corresponds to faults in the system, which can be used to establish a knowledge database and a fault diagnosis expert system. A quantitative risk assessment model is set up using a fuzzy comprehensive evaluation method and an incident loss comprehensive evaluation theory. Finally, the above method and model are examined for new trailer mounted equipment. The results validate the proposed method
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Meteleva, M. A. "DESIGN OF ENTREPRENEURIAL NETWORKS: EVALUATION OF THE NETWORK POTENTIAL IN RUSSIAN ARCTIC." Север и рынок: формирование экономического порядка 69, no. 3/2020 (November 27, 2020): 56–71. http://dx.doi.org/10.37614/2220-802x.2.2020.69.004.
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The article establishes the relationship between the function of sustainable economic growth in the informational productivity paradigm, which is the basis of the knowledge economy, and the modern interpretation of the economic content of entrepreneurship, which made it possible to draw a conclusion about the system-forming role of entrepreneurship in the formation of new socio-economic relations.In this regard, a refined definition of entrepreneurship based on the distinctive characteristics of its economic content is given. It is concluded that the new properties of informational socio-economic relations, the complication of their configuration and giving entrepreneurship a system-forming role in the knowledge economy, actualize the need for the development of network forms of organizing entrepreneurial activity.Methodological approaches to assessing the usefulness of one or another partner in the process of forming an inter-organizational alliance have been determined. It is proposed in the process of designing entrepreneurial networks to select potential actors using the methodology for assessing the network entrepreneurial potential of socio-economic systems of various levels. The definition of the network entrepreneurial potential of the territory is given.A method for a comprehensive assessment of the network entrepreneurial potential of a territory on the basis of a model that integrates the network entrepreneurial potential of business, the network entrepreneurial potential of civil society, and the network entrepreneurial potential of public administration, has been developed. The article presents a comprehensive assessment of the network entrepreneurial potential of the complex socio-economic system of the territory of the Russian Arctic, carried out using the proposed method. The territories of the Russian Arctic, the most attractive for the formation of entrepreneurial networks, have been identified based on the results of a comprehensive assessment of entrepreneurial potential and entrepreneurial potential of business, civil society and government.
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Zhang, Shengzhi, Xiaoqi Jia, Peng Liu, and Jiwu Jing. "PEDA: Comprehensive Damage Assessment for Production Environment Server Systems." IEEE Transactions on Information Forensics and Security 6, no. 4 (December 2011): 1323–34. http://dx.doi.org/10.1109/tifs.2011.2162062.
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Zisiadis, Dimitris, George Thanos, Spyros Kopsidas, and George Leventakis. "STAR-TRANS Modeling Language." International Journal of Information Systems for Crisis Response and Management 5, no. 2 (April 2013): 45–59. http://dx.doi.org/10.4018/jiscrm.2013040104.
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Transportation networks are open and accessible, by design, and thus vulnerable to malicious attacks. Transportation networks are integral parts of larger systems, where individual transportation networks form a network-of-networks within a defined geographical region. A security incident on an asset can propagate to new security incidents in interconnected assets of the same or different networks, resulting in cascading failures in the overall network-of-networks. The present work introduces the STAR-TRANS Modeling Language (STML) and provides a reference implementation case. STML is a feature-rich, domain specific, high-level modeling language, capable of expressing the concepts and processes of the Strategic Risk Assessment and Contingency Planning in Interconnected Transportation Networks (STAR- TRANS) framework. STAR-TRANS is a comprehensive transportation security risk assessment framework for assessing related risks that provides cohered contingency management procedures for interconnected, interdependent and heterogeneous transport networks. STML has been used to produce the STAR-TRANS Impact Assessment Tool.
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Zhiming, Cai, Li Daming, and Deng Lianbing. "Risk evaluation of urban rainwater system waterlogging based on neural network and dynamic hydraulic model." Journal of Intelligent & Fuzzy Systems 39, no. 4 (October 21, 2020): 5661–71. http://dx.doi.org/10.3233/jifs-189045.
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With the rapid development of urban construction and the further improvement of the degree of urbanization, despite the intensification of the drainage system construction, the problem of urban waterlogging is still showing an increasingly significant trend. In this paper, the authors analyze the risk evaluation of urban rainwater system waterlogging based on neural network and dynamic hydraulic model. This article introduces the concept of risk into the study of urban waterlogging problems, combines advanced computer simulation methods to simulate different conditions of rainwater systems, and conducts urban waterlogging risk assessment. Because the phenomenon of urban waterlogging is vague, it is affected by a variety of factors and requires comprehensive evaluation. Therefore, the fuzzy comprehensive evaluation method is very suitable for solving the risk evaluation problem of urban waterlogging. In order to improve the scientificity of drainage and waterlogging prevention planning, sponge cities should gradually establish rainwater impact assessment and waterlogging risk evaluation systems, comprehensively evaluate the current capacity of urban drainage and waterlogging prevention facilities and waterlogging risks, draw a map of urban rainwater and waterlogging risks, and determine the risk level. At the same time, delineate drainage and waterlogging prevention zones and risk management zones to provide effective technical support for the formulation of drainage and storm waterlogging prevention plans and emergency management.
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Guo, Wei-Feng, Xiangtian Yu, Qian-Qian Shi, Jing Liang, Shao-Wu Zhang, and Tao Zeng. "Performance assessment of sample-specific network control methods for bulk and single-cell biological data analysis." PLOS Computational Biology 17, no. 5 (May 6, 2021): e1008962. http://dx.doi.org/10.1371/journal.pcbi.1008962.
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In the past few years, a wealth of sample-specific network construction methods and structural network control methods has been proposed to identify sample-specific driver nodes for supporting the Sample-Specific network Control (SSC) analysis of biological networked systems. However, there is no comprehensive evaluation for these state-of-the-art methods. Here, we conducted a performance assessment for 16 SSC analysis workflows by using the combination of 4 sample-specific network reconstruction methods and 4 representative structural control methods. This study includes simulation evaluation of representative biological networks, personalized driver genes prioritization on multiple cancer bulk expression datasets with matched patient samples from TCGA, and cell marker genes and key time point identification related to cell differentiation on single-cell RNA-seq datasets. By widely comparing analysis of existing SSC analysis workflows, we provided the following recommendations and banchmarking workflows. (i) The performance of a network control method is strongly dependent on the up-stream sample-specific network method, and Cell-Specific Network construction (CSN) method and Single-Sample Network (SSN) method are the preferred sample-specific network construction methods. (ii) After constructing the sample-specific networks, the undirected network-based control methods are more effective than the directed network-based control methods. In addition, these data and evaluation pipeline are freely available on https://github.com/WilfongGuo/Benchmark_control.
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Medini, Khaled, Sophie Peillon, Martha Orellano, Stefan Wiesner, and Ang Liu. "System Modelling and Analysis to Support Economic Assessment of Product-Service Systems." Systems 9, no. 1 (January 21, 2021): 6. http://dx.doi.org/10.3390/systems9010006.
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The evolution towards more customer-centric operations within manufacturing and service industries gave rise to novel ways of value creation and delivery such as Product–Service Systems (PSS). PSS integrate tangible and intangible elements to create new values for both customers and providers. Therefore, a close collaboration is required among various actors in a value network to co-create values towards win–win gains. For companies to keep up with this pace, new decision support tools are needed to accompany PSS engineering and to adjust business models. This need is confronted with the scarcity of PSS-oriented economic assessment models and methods. This paper presents a comprehensive framework for the economic assessment of PSS. The framework relies on a novel combination of system modelling and analysis approaches to enable cost and revenue attribution to different actors in a value network. The applicability and relevance of the framework are demonstrated through a case study in the industrial cleaning sector.
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Alidina, Shehnaz, and Michele Jordan. "The Challenges of Evaluating Health Systems Networks: Lessons Learned from an Early Evaluation of the Child Health Network for the Greater Toronto Area." Healthcare Management Forum 20, no. 2 (July 2007): 22–27. http://dx.doi.org/10.1016/s0840-4704(10)60511-x.
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This article describes the first system-wide evaluation of the Child Health Network (CHN) for the Greater Toronto Area (GTA), a partnership of 29 community and hospital care providers. The CHN performance evaluation sought to identify the impact of the network on the delivery of maternal, newborn and child health services in the GTA. CHN members identified seven criteria to be evaluated (appropriate care, accessibility, effectiveness, satisfaction, integrated and coordinated care, accountability and affordability) and then collaborated in selecting measurable indicators for each criterion. Data were compiled from administrative data sets, or collected as needed. This undertaking succeeded in providing a comprehensive assessment of the network's performance, identification of strategies to improve outcomes and network sustainability, as well as practical information that will inform the important new field of network evaluation.
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Guo, Wei-Feng, Shao-Wu Zhang, Tao Zeng, Tatsuya Akutsu, and Luonan Chen. "Network control principles for identifying personalized driver genes in cancer." Briefings in Bioinformatics 21, no. 5 (November 10, 2019): 1641–62. http://dx.doi.org/10.1093/bib/bbz089.
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Abstract To understand tumor heterogeneity in cancer, personalized driver genes (PDGs) need to be identified for unraveling the genotype–phenotype associations corresponding to particular patients. However, most of the existing driver-focus methods mainly pay attention on the cohort information rather than on individual information. Recent developing computational approaches based on network control principles are opening a new way to discover driver genes in cancer, particularly at an individual level. To provide comprehensive perspectives of network control methods on this timely topic, we first considered the cancer progression as a network control problem, in which the expected PDGs are altered genes by oncogene activation signals that can change the individual molecular network from one health state to the other disease state. Then, we reviewed the network reconstruction methods on single samples and introduced novel network control methods on single-sample networks to identify PDGs in cancer. Particularly, we gave a performance assessment of the network structure control-based PDGs identification methods on multiple cancer datasets from TCGA, for which the data and evaluation package also are publicly available. Finally, we discussed future directions for the application of network control methods to identify PDGs in cancer and diverse biological processes.
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Ociepa, Ewa, Robert Molik, and Joanna Lach. "Assessment of water loss level on the example of selected distribution systems." E3S Web of Conferences 44 (2018): 00131. http://dx.doi.org/10.1051/e3sconf/20184400131.
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One of the major problems of waterworks is the excessive failure of distribution systems and associated water leaks. Water losses in water supply networks and systems are often a very high percentage of water supplied into the network. Therefore, a comprehensive analysis and assessment of water losses should be the basis for undertaking modernisation efforts to reduce the costs associated with water production and distribution. The article presents the analysis of water losses performed on the basis of data provided by the Water Supply and Sewerage Company in Radomsko. The data comprised the information on the water supply infrastructure and quantitative water balance for the period of 2010–2015. Based on the data, the following water loss indices were calculated: the percentage water loss (PWS) or non revenue water (NRW) index, real loss basic (RLB), non revenue water basic index (NRWB), unavoidable annual real losses (UARL) and infrastructure leakage index (ILI). The obtained results demonstrate that due to continuous actions in the recent years the Water Supply and Sewerage Company in Radomsko has reduced the water loss to the levels that correspond to the average water loss on national and international levels.
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Juračak, Josip, and Vesna Očić. "Assessment of Farm Accountancy Data Network System in Croatia." Poljoprivreda 27, no. 2 (December 22, 2021): 91–98. http://dx.doi.org/10.18047/poljo.27.2.12.
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Croatia is the newest member of the EU Farm Accountancy Data Network (FADN). So far, no comprehensive evaluation of the national FADN system has been conducted, and this study based on a survey of staff involved and a desktop analysis was conducted to fill this gap. The three main elements of the Croatian FADN system are the National FADN Committee, the Ministry of Agriculture as Liaison Agency (LA) and the Croatian Bureau for statistics. All FADN survey activities are carried out by LA and the main burden of data collection lies with the data collectors and the farms. The system operates in accordance with relevant EU legislation and currently its main objective appears to be the fulfilment of its obligations to the FADN network. Other benefits like analysis of CAP measures etc. are not yet exploited. The main challenges are further development of quality assurance systems, the motivation of staff and farms to participate, the increased use of FADN data, and the expected changes in transformation of the FADN into the sustainability data network (FSDN). Croatia will successfully meet these challenges if it strengthens its capacity for FADN research and data analysis and establishes an effective quality assurance system.
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Zhou, Zhi-Wu, Julián Alcalá, Moacir Kripka, and Víctor Yepes. "Life Cycle Assessment of Bridges Using Bayesian Networks and Fuzzy Mathematics." Applied Sciences 11, no. 11 (May 27, 2021): 4916. http://dx.doi.org/10.3390/app11114916.
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At present, reducing the impact of the construction industry on the environment is the key to achieving sustainable development. Countries all over the world are using software systems for bridge environmental impact assessment. However, due to the complexity and discreteness of environmental factors in the construction industry, they are difficult to update and determine quickly, and there is a phenomenon of data missing in the database. Most of the lost data are optimized by Monte Carlo simulation, which greatly reduces the reliability and accuracy of the research results. This paper uses Bayesian advanced fuzzy mathematics theory to solve this problem. In the research, a Bayesian fuzzy mathematics evaluation and a multi-level sensitivity priority discrimination model are established, and the weights and membership degrees of influencing factors were defined to achieve comprehensive coverage of influencing factors. With the support of theoretical modelling, software analysis and fuzzy mathematics theory are used to comprehensively evaluate all the influencing factors of the five influencing stages in the entire life cycle of the bridge structure. The results show that the material manufacturing, maintenance, and operation of the bridge still produce environmental pollution; the main source of the emissions exceeds 53% of the total emissions. The effective impact factor reaches 3.01. At the end of the article, a big data sensitivity model was established. Through big data innovation and optimization analysis, traffic pollution emissions were reduced by 330 tonnes. Modeling of the comprehensive research model; application; clearly confirms the effectiveness and practicality of the Bayesian network fuzzy number comprehensive evaluation model in dealing with uncertain factors in the evaluation of the sustainable development of the construction industry. The research results have made important contributions to the realization of the sustainable development goals of the construction industry.
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Su, Yi-Zhu, and Wei-Chang Yeh. "Binary-Addition Tree Algorithm-Based Resilience Assessment for Binary-State Network Problems." Electronics 9, no. 8 (July 27, 2020): 1207. http://dx.doi.org/10.3390/electronics9081207.
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Applications in real life are composed of different kinds of network systems; these networks may be interfered by uncontrollable or unpredictable disruptive events involving natural disasters, human errors, evil-intentioned attacks, or other disturbances. Any of these disruptive events will cause networks to malfunction and possibly result in large economic losses. As a result, it is important to assess network resilience which is a measure to describe how a network system recovers its performance and functionality to a satisfactory level from a disruptive event. Inspired by the measures of reliability evaluation used in binary-state networks, this paper proposes a binary-addition tree algorithm-based resilience assessment for binary-state networks and applies it on a wildfire network with wireless sensors. Considering the stochastic nature of disruptive events, the proposed binary-addition tree algorithm-based resilience assessment comprehensively enumerates all the possible disruptive events and all the corresponding recovery strategies, and then calculate the network resilience. Furthermore, recovery cost limit is concerned in this paper for decision makers who choose the recovery strategies with their recovery cost limit and resilience requirement.
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Cao, Kerang, Kwang-nam Choi, Hoekyung Jung, and Lini Duan. "Deep Learning for Facial Beauty Prediction." Information 11, no. 8 (August 10, 2020): 391. http://dx.doi.org/10.3390/info11080391.
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Facial beauty prediction (FBP) is a burgeoning issue for attractiveness evaluation, which aims to make assessment consistent with human opinion. Since FBP is a regression problem, to handle this issue, there are data-driven methods for finding the relations between facial features and beauty assessment. Recently, deep learning methods have shown its amazing capacity for feature representation and analysis. Convolutional neural networks (CNNs) have shown tremendous performance on facial recognition and comprehension, which are proved as an effective method for facial feature exploration. Lately, there are well-designed networks with efficient structures investigated for better representation performance. However, these designs concentrate on the effective block but do not build an efficient information transmission pathway, which led to a sub-optimal capacity for feature representation. Furthermore, these works cannot find the inherent correlations of feature maps, which also limits the performance. In this paper, an elaborate network design for FBP issue is proposed for better performance. A residual-in-residual (RIR) structure is introduced to the network for passing the gradient flow deeper, and building a better pathway for information transmission. By applying the RIR structure, a deeper network can be established for better feature representation. Besides the RIR network design, an attention mechanism is introduced to exploit the inner correlations among features. We investigate a joint spatial-wise and channel-wise attention (SCA) block to distribute the importance among features, which finds a better representation for facial information. Experimental results show our proposed network can predict facial beauty closer to a human’s assessment than state-of-the-arts.
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Xian, Shi. "Research on Comprehensive Evaluation of Economic Management Performance Based on Improved Fuzzy Clustering Algorithm." Security and Communication Networks 2022 (March 8, 2022): 1–9. http://dx.doi.org/10.1155/2022/8578138.
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In order to solve the problems of low recall rate and precision rate, high error rate, and long evaluation time in traditional evaluation methods, a comprehensive evaluation of economic management performance based on an improved fuzzy clustering algorithm is designed. The improved magnetic optimization algorithm was used to optimize the fuzzy C-mean algorithm, the improved fuzzy clustering algorithm was completed, and the improved fuzzy clustering algorithm was used to mine the economic management performance data. Using data mining findings and AHP’s weighting formula, a complete method for evaluating economic management effectiveness was developed. The BP neural network was improved using a genetic algorithm based on the index weight calculation findings, and the full-assessment model of economic management performance was constructed. Using this approach, it is possible to accurately and quickly assess the economic management performance of a company with a high rate of recall and accuracy; the error rate of a thorough assessment ranges between −3 percent and 4 percent; the average duration for an assessment is 0.81 seconds.
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Zhu, Jun, Haitao Hu, Zhengyou He, Xiaomin Guo, and Weiguo Pan. "A power-quality monitoring and assessment system for high-speed railways based on train-network-data center integration." Railway Engineering Science 29, no. 1 (March 2021): 30–41. http://dx.doi.org/10.1007/s40534-020-00229-4.
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AbstractIn recent years, with the rapid development of high-speed railways (HSRs), power interruptions or disturbances in traction power supply systems have become increasingly dangerous. However, it is often impossible to detect these faults immediately through single-point monitoring or collecting data after accidents. To coordinate the power quality data of both traction power supply systems (TPSSs) and high-speed trains (HSTs), a monitoring and assessing system is proposed to access the power quality issues on HSRs. By integrating train monitoring, traction substation monitoring and data center, this monitoring system not only realizes the real-time monitoring of operational behaviors for both TPSSs and HSTs, but also conducts a comprehensive assessment of operational quality for train-network systems. Based on a large number of monitoring data, the field measurements show that this real-time monitoring system is effective for monitoring and evaluating a traction-network system.
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Panigrahi, Ranjit, Samarjeet Borah, Akash Kumar Bhoi, Muhammad Fazal Ijaz, Moumita Pramanik, Rutvij H. Jhaveri, and Chiranji Lal Chowdhary. "Performance Assessment of Supervised Classifiers for Designing Intrusion Detection Systems: A Comprehensive Review and Recommendations for Future Research." Mathematics 9, no. 6 (March 23, 2021): 690. http://dx.doi.org/10.3390/math9060690.
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Supervised learning and pattern recognition is a crucial area of research in information retrieval, knowledge engineering, image processing, medical imaging, and intrusion detection. Numerous algorithms have been designed to address such complex application domains. Despite an enormous array of supervised classifiers, researchers are yet to recognize a robust classification mechanism that accurately and quickly classifies the target dataset, especially in the field of intrusion detection systems (IDSs). Most of the existing literature considers the accuracy and false-positive rate for assessing the performance of classification algorithms. The absence of other performance measures, such as model build time, misclassification rate, and precision, should be considered the main limitation for classifier performance evaluation. This paper’s main contribution is to analyze the current literature status in the field of network intrusion detection, highlighting the number of classifiers used, dataset size, performance outputs, inferences, and research gaps. Therefore, fifty-four state-of-the-art classifiers of various different groups, i.e., Bayes, functions, lazy, rule-based, and decision tree, have been analyzed and explored in detail, considering the sixteen most popular performance measures. This research work aims to recognize a robust classifier, which is suitable for consideration as the base learner, while designing a host-based or network-based intrusion detection system. The NSLKDD, ISCXIDS2012, and CICIDS2017 datasets have been used for training and testing purposes. Furthermore, a widespread decision-making algorithm, referred to as Techniques for Order Preference by Similarity to the Ideal Solution (TOPSIS), allocated ranks to the classifiers based on observed performance reading on the concern datasets. The J48Consolidated provided the highest accuracy of 99.868%, a misclassification rate of 0.1319%, and a Kappa value of 0.998. Therefore, this classifier has been proposed as the ideal classifier for designing IDSs.
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Stennikov, V. A., and I. V. Postnikov. "Methods for Comprehensive Analysis of Heat Supply Reliability." International Journal of Energy Optimization and Engineering 2, no. 4 (October 2013): 120–42. http://dx.doi.org/10.4018/ijeoe.2013100107.
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The paper deals with the problem of comprehensive analysis of heat supply reliability for consumers. It implies a quantitative assessment of the impact of all stages of heat energy production and distribution on heat supply reliability for each consumer of the heat supply system. A short review of existing methods for the analysis of fuel and heat supply reliability is presented that substantiates the key approaches to solving the problem of comprehensive analysis of heat supply reliability. A methodological approach is suggested, in which mathematical models and methods for nodal evaluation of heat supply reliability for consumers are developed and the studies on the impact of different elements of fuel and heat supply systems on its level are described. Mathematical modeling is based on the Markov random processes, models of flow distribution in a heat network, deterministic dependences of thermal processes of heat energy consumption and some other models.
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Dolgova, Anna Vladimirovna, and Pavel Konstantinovich Shkodun. "The use of fuzzy logic apparatus in development of expert systems for diagnosing traction electric motors of rolling stock." Transport of the Urals, no. 2 (2020): 65–69. http://dx.doi.org/10.20291/1815-9400-2020-2-65-69.
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The paper discusses the development of an expert system for diagnosing electric traction motors of rolling stock. The diagnostic parameters of the electric traction motor commutator-and-brush assembly, being the input linguistic variables of the fuzzy model, were selected with the use of graphoanalytic model. A fuzzy mathematical model and a fuzzy neural network for comprehensive indicator of quality of mechanical machining implementing the Takagi — Sugeno fuzzy inference algorithm were developed. The authors confirmed the practicability and the adequacy of the previously proposed comprehensive indicator of quality of mechanical machining for assessing the technical condition of the electric traction motor commutator-and-brush assembly. The studies carried out allowed creating an element of intelligent expert diagnostics system that enables a comprehensive assessment of technical condition of electric traction motor.
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Viswanathan, Meera, Carol Mansfield, Lucia Rojas Smith, Carol Woodell, Niamh Darcy, Yvonne U. Ohadike, Julie Kennedy Lesch, and Floyd J. Malveaux. "Cross-Site Evaluation of a Comprehensive Pediatric Asthma Project." Health Promotion Practice 12, no. 6_suppl_1 (November 2011): 20S—33S. http://dx.doi.org/10.1177/1524839911412595.
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The Merck Childhood Asthma Network, Inc. (MCAN) initiative selected five sites that had high asthma burden and established asthma programs but were ready for greater program integration across schools, health care systems, and communities. MCAN supported a community-based approach that was tailored to the needs of each program site. As a result, each site was unique in its combination of interventions, but all sites served common goals of integration of care, incorporation of evidence-based programs, and improvement in knowledge, self-management, health, and quality of life. This case study of the MCAN cross-site evaluation discusses the challenges associated with evaluating interventions involving multiple stakeholders that have been adjusted to fit the unique needs of specific communities. The evaluation triangulates data from site-specific monitoring and evaluation data; site documents, site visits, and cross-site meetings; qualitative assessments of families, organizational partners, and other stakeholders; and quantitative data from a common instrument on health indicators before and after the intervention. The evaluation employs the RE-AIM framework—reach, effectiveness, adoption, implementation, and maintenance—to assess the barriers and facilitators of translation from theory into practice. Our experience suggests trade-offs between rigor of evaluation and burden of assessment that have applicability for other community-based translational efforts.
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O'Rourke, Brian, Sophie Söderholm Werkö, Tracy Merlin, Li Ying Huang, and Tara Schuller. "The ‘Top 10’ Challenges for Health Technology Assessment: INAHTA Viewpoint." International Journal of Technology Assessment in Health Care 36, no. 1 (November 28, 2019): 1–4. http://dx.doi.org/10.1017/s0266462319000825.
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The International Network of Agencies for Health Technology Assessment (INAHTA) spans the globe as a network of 50 publicly-funded health technology assessment (HTA) agencies supporting health system decision making for 1.4 billion people in thirty countries. Agency members are non-profit HTA organizations that are part of, or directly support, regional or national governments. Recently, INAHTA surveyed its members to gather perspectives from agency leadership on the most important issues in HTA today. This paper describes the top 10 challenges identified by INAHTA members. Addressing these challenges requires a call for action from INAHTA member agencies and the many other actors involved in the HTA ecosystem. In opening this call for action, INAHTA will lead the way; however, a comprehensive undertaking from all players is needed to effectively address these challenges and to continue to evolve HTA in its role as a strong and effective contributor to health systems.
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Esmaeily, Ali, and Katina Kralevska. "Small-Scale 5G Testbeds for Network Slicing Deployment: A Systematic Review." Wireless Communications and Mobile Computing 2021 (May 10, 2021): 1–26. http://dx.doi.org/10.1155/2021/6655216.
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Developing specialized cloud-based and open-source testbeds is a practical approach to investigate network slicing functionalities in the fifth-generation (5G) mobile networks. This paper provides a comprehensive review of most of the existing cost-efficient and small-scale testbeds that partially or fully deploy network slicing. First, we present relevant software packages for the three main functional blocks of the ETSI NFV MANO framework and for emulating the access and core network domains. Second, we define primary and secondary design criteria for deploying network slicing testbeds. These design criteria are later used for comparison between the testbeds. Third, we present the state-of-the-art testbeds, including their design objectives, key technologies, network slicing deployment, and experiments. Next, we evaluate the testbeds according to the defined design criteria and present an in-depth summary table. This assessment concludes with the superiority of some of them over the rest and the most dominant software packages satisfying the ETSI NFV MANO framework. Finally, challenges, potential solutions, and future works of network slicing testbeds are discussed.
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Doljenko, Alexey, Irina Shpolianskaya, and Sergey Glushenko. "Fuzzy production network model for quality assessment of an information system based on microservices." Business Informatics 14, no. 4 (December 31, 2020): 36–46. http://dx.doi.org/10.17323/2587-814x.2020.4.36.46.
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This article describes the analysis of the quality of microservice architectures, which are one of the main approaches to the creation and maintenance of modern information systems capable of quickly respond to changes in business demands. The implementation of continuous delivery of software components for dynamic business processes of information systems can be carried out by various sets of microservices, the optimal choice of which is a complex multi-alternative task. The paper presents a review of existing approaches to solving the problem, which showed that the development of models for assessing the quality of microservices of information systems requires further elaboration in terms of accounting for uncertainty in the initial data and modes of operation. The authors have proposed an approach to solving the problem of analyzing the quality of a microservice architecture which is implemented on the basis of a fuzzy production network model. The model allows for comprehensive accounting of various parameters (qualitative and quantitative). The article shows the implementation process of the fuzzy production network that was developed to analyze the functional quality of the microservice architecture for processing customer orders using fuzzy modeling software. The results of the analysis will allow managers and system architects to make an informed choice of the microservice architecture of the information system, as well as use it in their reports when arguing the need for scaling the system and increasing the availability of microservices.
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Lee, Eunsu. "Revamping Tribal Road Networks from Various Sources and Improving Quality." Transportation Research Record: Journal of the Transportation Research Board 2605, no. 1 (January 2017): 124–32. http://dx.doi.org/10.3141/2605-13.
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The objectives of this study were to integrate road networks to provide a comprehensive road network through the use of multiple public sources and to provide guides for performing a quality control assessment before delivering data and using the data for geospatial analysis. The study focused on the Fort Berthold Reservation in western North Dakota. A method is proposed to integrate multiple public road networks to support a tribal transportation agency. The workflow and techniques proposed are transferrable to other tribal transportation agencies. Depending on current data used for transportation planning and operations, the workflow and processes are subject to change from agency to agency, but the study provided general guidance for the agency. The study recommended that the tribal transportation agencies develop linear referencing systems on the proposed road network to adopt efficient asset management and version control. The linear referencing system should comply with state or federal guidelines for improved communication. To develop appropriate applications, the road network should include additional attributes based on the needs of the reservation.
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Ľupták, Vladimír, Paweł Droździel, Ondrej Stopka, Mária Stopková, and Iwona Rybicka. "Approach Methodology for Comprehensive Assessing the Public Passenger Transport Timetable Performances at a Regional Scale." Sustainability 11, no. 13 (June 27, 2019): 3532. http://dx.doi.org/10.3390/su11133532.
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The paper is focused on the issue of assessing the quality of transport connectivity on a predesignated transport network in regular public passenger transport at a regional scale. Comprehensively, using the defined key qualitative indicators, it assesses the performance of passenger transport timetables, in both ways of ex ante, as well as ex post. Existing methodologies in a given issue have only dealt with a partial assessment of the transport connectivity quality on specific transport network. However, unlike them, the objective of this manuscript was to propose a new unified methodology to assess the passenger transport timetables in terms of transport connectivity, and subsequently to complexly evaluate the whole predesignated regional transport network from a qualitative point of view. In this paper, the proposed methodology is demonstrated on a particular regional transport network, specifically an existing railway network in the Slovak Republic, whereby the data related to regional passenger transport timetables for a certain day is an input factor. The purpose of this study was to design and verify a draft methodological procedure to assess the quality of transport connectivity on a certain transport network, thus moving towards more effective evaluation of integrated transport systems. Its practical applicability consists in comparison of existing and proposed timetables, which is considered one of the crucial factors in terms of public passenger transport quality.
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Dementiev, Andrei N., Mikhail V. Aralkin, and Yevgeny E. Krivobokov. "Assessment of the resistance of technical means of space systems and complexes to the effects of electrostatic discharges." Physics of Wave Processes and Radio Systems 24, no. 2 (September 6, 2021): 32–40. http://dx.doi.org/10.18469/1810-3189.2021.24.2.32-40.
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In order to further improve the methods of protecting the onboard spacecraft equipment from the effects ofelectrostatic discharges, based on a comprehensive study of the problem of the occurrence of electrostatic discharges, theauthors carried out the studies described in this article to analyze the functioning of the onboard spacecraft equipment under the influence of electrostatic discharges. In the course of the research, the methodology for assessing the resistance ofthe onboard equipment of the spacecraft to the effects of electrostatic discharges was refined, based on the generalization of the calculation and analytical work. The analysis of the resistance of the onboard equipment of the spacecraft was carried out taking into account the main mechanisms of the effect of electrostatic discharges on the onboard space network. Taking into account the need to assess the resistance of the onboard space network equipment to electrostatic discharges outside real operating conditions, the authors assess the resistance of the onboard space network equipment on the basis of mathematical and physical modeling. Asaresult of the study, an algorithm was developed for assessing the resistance of the onboard equipment of a spacecraft to the effects of electrostatic discharges, which is described in detail in this article.
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Шишацький, А. В., Ю. В. Журавський, В. М. Остапчук, М. В. Сова, О. Д. Гаращук, and О. І. Пікуль. "Complex methodology of parameters management of military radio networks in the conditions of uncertainty of the radioelectronic situation." Системи обробки інформації, no. 3(162), (September 30, 2020): 73–85. http://dx.doi.org/10.30748/soi.2020.162.08.
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The experience of the Joint Forces operation (Anti-terrorist operation in Donetsk and Luhansk oblasts) shows that the current order of management of military radio communication systems does not always meet the modern requirements for them. The classic centralized approach to the management of channel and network resources of military radio systems does not quite meet modern requirements, so the authors of this article proposed to take mobile self-organizing networks as a basic principle of construction. The authors propose a comprehensive method of managing the parameters of military radio networks in conditions of uncertainty of the electronic environment, the essence of which is to ensure the maintenance of the specified values of the performance of military radio communication systems at the appropriate level. The article is based on the control principle, which is described in the reference network model of open systems interaction, but with some additions and changes. This approach generally allows for end-to-end management of channel and network resources of military radio systems in a complex electronic environment. In the article, the device of fuzzy logic, the theory of electronic suppression, neural networks, the theory of noise protection, the theory of antennas, noise-resistant coding are used. The proposed complex methodology should be used in the development of software for modules (units) for the assessment of advanced radio communications, based on open architecture interfaces version SCA 2.2, which will: use effective signal-code structures to ensure noise immunity of channels; to ensure efficient use of the radio frequency resource of programmable radio communication means; increase the speed of evaluation of communication channels; reduce the use of computing resources of radio communications with programmable architecture.
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Sarkar, Sudhangshu, Ushnik Chakrabarti, Suvamoy Bhattacharyya, and Amlan Chakrabarti. "A Comprehensive Assessment of the Need and Availability of Smart Grid Technologies in an Electricity Distribution Grid Network." Journal of The Institution of Engineers (India): Series B 101, no. 6 (September 12, 2020): 753–61. http://dx.doi.org/10.1007/s40031-020-00486-1.
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AbstractThe electrical distribution grids face major problems such as aggregate technical and commercial losses and integration of distributed energy resources. There are also several operational problems such as inaccurate meter reading, blackouts and outages, huge data compilation, etc. With the availability of automatic metering infrastructure and phasor monitoring units, many of these problems can be addressed. With the rapid progress in power electronic converter technology, the problems in integration of distributed energy resources can be efficiently resolved. However, the necessary prerequisite for getting all these benefits is remote monitoring and control. For effective demand response and price responsive demand, transparency and communication with the consumer and consumer—end systems are essential. For interoperability between the devices of various smart grid technologies, the rapid advances in communication technologies on Zig Bee, cellular communication WiMAX, power line communication are being used. In spite of the smart grid communication standards being not in place, the present standards from various bodies are being used. This has given shape to several data analytics applications with crunching of huge data from smart grid network operations.
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Lyons, Torrey, and Dong-ah Choi. "Transit Economic Equity Index: Developing a Comprehensive Measure of Transit Service Equity." Transportation Research Record: Journal of the Transportation Research Board 2675, no. 3 (January 7, 2021): 288–300. http://dx.doi.org/10.1177/0361198120970529.
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In this study an index is developed called the Transit Economic Equity Index, to enable quantitative assessment of transit service equity. The index measures convenience of travel for work trips for advantaged and disadvantaged populations, based on travel speed, using a multimodal network that includes transit lines, stop locations, transit schedules, and pedestrian connections via the street network. Non-peak hour service is compared with peak hour service to determine the degree to which operating resources are concentrated in times that might have greater benefits to advantaged populations. Finally, accessibility to the transit system is compared in relation to the number of transit stops in neighborhoods and employment centers, and these figures are compared between advantaged and disadvantaged locations. The scores for these three components are combined to create a single measure of transit economic equity. Disadvantage is defined using criteria established in Title VI of the Civil Rights Act of 1964. The index is constructed in a way that balances a robust and meaningful measure of transit equity that is decipherable by practitioners so that they can assess the equity of their systems as well as how potential service changes affect equity.
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Al-Zadjali, Saira, Ahmed Al Maashri, Amer Al-Hinai, Rashid Al Abri, Swaroop Gajare, Sultan Al Yahyai, and Mostafa Bakhtvar. "A Fast and Accurate Wind Speed and Direction Nowcasting Model for Renewable Energy Management Systems." Energies 14, no. 23 (November 24, 2021): 7878. http://dx.doi.org/10.3390/en14237878.
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To plan operations and avoid any grid disturbances, power utilities require accurate power generation estimates for renewable generation. The generation estimates for wind power stations require an accurate prediction of wind speed and direction. This paper proposes a new prediction model for nowcasting the wind speed and direction, which can be used to predict the output of a wind power plant. The proposed model uses perturbed observations to train the ensemble networks. The trained model is then used to predict the wind speed and direction. The paper performs a comparative assessment of three artificial neural network models. It also studies the performance of introducing perturbed observations to the model using six different interpolation techniques. For each technique, the computational efficiency is measured and assessed. Furthermore, the paper presents an exhaustive investigation of the performance of neural network types and several techniques in training, data splitting, and interpolation. To check the efficacy of the proposed model, the power output from a real wind farm is predicted and compared with the actual recorded measurements. The results of the comprehensive analysis show that the proposed model outperforms contending models in terms of accuracy and execution time. Therefore, this model can be used by operators to reliably generate a dispatch plan.
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Yu, Fandong, Fei Liu, Zhijun Xia, Pengcheng Lin, Chunsen Xu, Jianwei Wang, Miaomiao Hou, and Xinhua Zou. "Classification and Assessment Methods for Mountain Channel Habitats in the Chishui River Basin, China." Water 14, no. 4 (February 9, 2022): 515. http://dx.doi.org/10.3390/w14040515.
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Mountain channels have received relatively little study compared to lowland rivers due to their complicated fluvial geomorphology and inconvenient traffic. Classification schemes and habitat assessments in mountain channels should be strengthened to provide a scientific basis for river ecological restoration. Therefore, we tried to simplify the habitat assessment of mountain channels using a suitable habitat classification scheme based on high-resolution satellite imagery. We used China’s Chishui River basin because it is a typical mountain river system. Five parameters (stream order, elevation, slope, sinuosity and river network density) and 120 sites were used for habitat classification. In addition, we recorded 20 metrics in four categories (water environmental status, river morphology, riparian zone and human disturbance). Our results identified a total of 40 representative sampling sections belonging to six habitat types that were useful for habitat assessment across the Chishui River basin. The basin was given a mean comprehensive habitat quality index (CHQI) score of 130.66 ± 24.14 and classified under the status “good.” However, the headwaters, Tongmin River, Tongzi River and Xishui River were disturbed by various human activities. We conclude that the process of developing and simplifying our habitat assessment systems can be regarded as a reference for biomonitoring in other mountain river systems.
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Yu, Zhihui, Sitong Liu, and Weimin Wang. "Dynamic Threat Weight of Network Security Communication Based on Multisource Data Analysis." Wireless Communications and Mobile Computing 2022 (March 10, 2022): 1–11. http://dx.doi.org/10.1155/2022/6729827.
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While the internet brings convenience to people, there are also many security problems. This study mainly discusses network security communication and ideological security technology based on multisource data analysis. The situation awareness model based on dynamic threat weight is mainly composed of the fusion module, evaluation module, and prediction module. The situation fusion module is mainly based on the fusion algorithm of distance vector optimal classification to fuse multisource data. The situation assessment module is based on the situation assessment method based on a dynamic threat weight to quantitatively evaluate the situation value. The situation understanding part is the basis of situation awareness. Firstly, a large amount of original security data is merged at the data level to obtain a standardized dataset. Then, the relationship between the data is analyzed by the method of correlation analysis, and the security incident information and threat propagation network are obtained. The knowledge training module accurately feeds back the relevant parameters and data, and the knowledge training module adjusts the data accuracy according to the received data accuracy. The main function of the situation fusion module is to process the multisource data and use the fusion algorithm for data fusion. The situation assessment module uses the fused data combined with a specific method for comprehensive assessment and uses visualization technology to show the final results in front of the administrator, which is convenient for more efficient operation. Based on the data fusion module, the situation assessment module judges the current network security status, detects the assessment results through error checking, and feeds back to the knowledge training module. From the trend of the overall network situation, we can see that the probability of the overall network at 4 is the highest, followed by 5. This study makes an effective evaluation of the overall network security.
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Srivastava, Rajendra P., and Chan Li. "Risk and Reliability Formulas for Systems Security under Dempster-Shafer Theory of Belief Functions." Journal of Emerging Technologies in Accounting 5, no. 1 (January 1, 2008): 189–219. http://dx.doi.org/10.2308/jeta.2008.5.1.189.
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ABSTRACT: This paper develops comprehensive formulas for assessing the risk and reliability of “Systems Security” under the Dempster-Shafer theory of belief functions, using the Trust Services framework as proposed by the American Institute of Certified Public Accountants (AICPA) and Canadian Institute of Chartered Accountants (CICA). In addition, we discuss how these formulas can be used for planning and evaluation of “Systems Security” risk under the SysTrust services. The analytical formulas are derived for a tree-structured evidential diagram which is constructed by converting the exact network-structured evidential diagram. The use of an analytical formula eliminates the computational complexities of propagating beliefs in a network and allows the assurance provider to use a simple spreadsheet to combine evidence. We provide theoretical justification and perform sensitivity analyses to show that the analytical formula based on a tree-type evidential diagram is a good approximation of the exact network model under realistic situations. However, as shown theoretically and also through the sensitivity analysis, the analytical formula provides significantly different results when input beliefs are significantly negative. It should be noted that the analytical formula based on the tree model provides a more conservative assessment of information systems risk than the exact network model.
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Jin, Yong, Yiwen Yang, Baican Yang, and Yunfu Zhang. "An Adaptive BP Neural Network Model for Teaching Quality Evaluation in Colleges and Universities." Wireless Communications and Mobile Computing 2021 (August 10, 2021): 1–7. http://dx.doi.org/10.1155/2021/4936873.
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There is currently no fair, rational, or scientific approach for evaluating college teachers’ teaching abilities. Mathematical methods are frequently used to measure the teaching capacity of college instructors in order to make it more scientific. Traditional statistical analysis evaluation models, fuzzy evaluation methods, grey decision methods, and the analytic hierarchy process (AHP) are only a few examples. Because teacher assessment is a nonlinear problem, even though the preceding methods have produced some positive results, they are vulnerable to some subjectivity. In this paper, the neural network model is incorporated into the adaptive vector and momentum of the modified BP neural network of a gradient descent method to boost the model’s convergence speed, and the model is thoroughly researched to evaluate university teaching quality, and the network structure is omitted to address the complex nonlinear problem of college and university teaching quality assessment. The model’s comprehensive evaluation of teaching activities is then bolstered by the addition of new evaluation indexes to the existing ones.
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Lan, Qi, and Jinbo Pang. "Risk Identification and Application of Farmland Management Right Mortgage Loan Based on Neural Network." Wireless Communications and Mobile Computing 2022 (May 4, 2022): 1–12. http://dx.doi.org/10.1155/2022/1941360.
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There are a series of problems in China, such as low farmers’ income, difficulty in financing for farmers, and relatively lag in rural financial reform. The mortgage financing of farmland management rights is one of the important ways to solve these thorny problems and promote economic development. From the perspective of farmers, combined with empirical analysis, this paper fully considers farmers’ ideas, carries out risk identification and risk assessment for the mortgage loan of farmland management rights, and continuously improves the relevant risk prevention mechanism to reduce the operation risk of farmers’ farmland mortgage. This paper expounds the establishment principles of the risk evaluation index system in detail, lays a theoretical foundation for the selection of indicators, determines the risk evaluation system of land management right mortgage financing from the perspective of farmers, and builds a fuzzy-level comprehensive evaluation model. Based on the practical research data, the fuzzy hierarchy (F-AHP) comprehensive evaluation method is used to conduct an empirical comprehensive evaluation on the risk of the mortgage loan of the farmland management right and analyze the evaluation results. Among the surveyed farmers in the survey area, 242 have not actually participated in the mortgage loan of farmland management rights, accounting for 94.16% of the sample farmers. However, there are only 15 farmers who actually use the farmland management right for mortgage financing, accounting for 5.84% of the sample.
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Cavalieri, Francesco, and Paolo Franchin. "Seismic Risk of Infrastructure Systems with Treatment of and Sensitivity to Epistemic Uncertainty." Infrastructures 5, no. 11 (November 18, 2020): 103. http://dx.doi.org/10.3390/infrastructures5110103.
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Modern society’s very existence is tied to the proper and reliable functioning of its Critical Infrastructure (CI) systems. In the seismic risk assessment of an infrastructure, taking into account all the relevant uncertainties affecting the problem is crucial. While both aleatory and epistemic uncertainties affect the estimate of seismic risk to an infrastructure and should be considered, the focus herein is on the latter. After providing an up-to-date literature review about the treatment of and sensitivity to epistemic uncertainty, this paper presents a comprehensive framework for seismic risk assessment of interdependent spatially distributed infrastructure systems that accounts for both aleatory and epistemic uncertainties and provides confidence in the estimate, as well as sensitivity of uncertainty in the output to the components of epistemic uncertainty in the input. The logic tree approach is used for the treatment of epistemic uncertainty and for the sensitivity analysis, whose results are presented through tornado diagrams. Sensitivity is also evaluated by elaborating the logic tree results through weighted ANOVA. The formulation is general and can be applied to risk assessment problems involving not only infrastructural but also structural systems. The presented methodology was implemented into an open-source software, OOFIMS, and applied to a synthetic city composed of buildings and a gas network and subjected to seismic hazard. The gas system’s performance is assessed through a flow-based analysis. The seismic hazard, the vulnerability assessment and the evaluation of the gas system’s operational state are addressed with a simulation-based approach. The presence of two systems (buildings and gas network) proves the capability to handle system interdependencies and highlights that uncertainty in models/parameters related to one system can affect uncertainty in the output related to dependent systems.
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Sakr, Sherif. "Towards a comprehensive assessment for selectivity estimation approaches of XML queries." International Journal of Web Engineering and Technology 6, no. 1 (2010): 58. http://dx.doi.org/10.1504/ijwet.2010.034760.
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Tabesh, M., J. Soltani, R. Farmani, and D. Savic. "Assessing pipe failure rate and mechanical reliability of water distribution networks using data-driven modeling." Journal of Hydroinformatics 11, no. 1 (January 1, 2009): 1–17. http://dx.doi.org/10.2166/hydro.2009.008.
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In this paper two models are presented based on Data-Driven Modeling (DDM) techniques (Artificial Neural Network and neuro-fuzzy systems) for more comprehensive and more accurate prediction of the pipe failure rate and an improved assessment of the reliability of pipes. Furthermore, a multivariate regression approach has been developed to enable comparison with the DDM-based methods. Unlike the existing simple regression models for prediction of pipe failure rates in which only few factors of diameter, age and length of pipes are considered, in this paper other parameters such as pressure and pipe depth, are also included. Furthermore, an investigation is carried out on most commonly used mechanical reliability relationships and the results of incorporation of the proposed pipe failure models in the reliability index are compared. The proposed models are applied to a real case study involving a large water distribution network in Iran and the results of model predictions are compared with measured pipe failure data. Compared with the results of neuro-fuzzy and multivariate regression models, the outcomes of the artificial neural network model are more realistic and accurate in the prediction of pipe failure rates and evaluation of mechanical reliability in water distribution networks.
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Drovnikova, I. G., Е. S. Ovchinnikova, and V. V. Konobeevsky. "ANALYSIS OF TYPICAL NETWORK ATTACKS ON AUTOMATED SYSTEMS OF INTERNAL AFFAIRS DEPARTMENTS." Herald of Dagestan State Technical University. Technical Sciences 47, no. 1 (April 21, 2020): 72–85. http://dx.doi.org/10.21822/2073-6185-2020-47-1-72-85.
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Abstract. Aim Important contemporary trends in the theory and functional practice of secure automated systems at informatisation facilities of internal affairs bodies include an increase in the number of threats realised through remote unauthorised access (network attacks) on confidential in-formation resources, as well as the increasing complexity of implementing mechanisms aimed at providing protection from such attacks. In order to increase the effectiveness of existing and prospective automated security systems at the informatisation facilities of internal affairs bodies, it is necessary to identify and analyse typical network attacks aimed at components and software comprising these systems.Method. The method for solving this problem consists in a comprehensive analysis of the process of implementing network attacks on automated systems when they are used in secure mode in the informatisation facilities of internal affairs bodies.Results. Based on the analysis of information held in the security threat database developed by the Russian Federal Service for Technical and Export Control (FSTEC), modern features and operations of secure automated systems on the informatisation facilities of bodies of internal affairs and the results of a survey of experts in the field of information protection of allocated in accordance with the classification typology, eight types of dan-gerous attacks on automated systems of the internal affairs bodies are described taking into account their sources, objects, effects and possible consequences of implementation.Conclusion. The presented results are of use in further studies to conduct a quantitative assessment of the danger of typical attacks and for developing a private model of actual attacks for a specific automated system, taking into account their functional features in secure mode operations at the informatisation facility of the internal affairs body.
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Franke, Stefan, and Thomas Neumuth. "Towards structuring contextual information for workflow-driven surgical assistance functionalities." Current Directions in Biomedical Engineering 1, no. 1 (September 1, 2015): 168–71. http://dx.doi.org/10.1515/cdbme-2015-0042.
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AbstractA workflow-driven cooperative working environment needs to be established in order to successfully unburden the surgeon and the OR staff from technical configuration and information-seeking tasks. An important prerequisite for autonomous situationaware adaptation of medical devices is a comprehensive representation of the operating context regarding the surgical process and situation.We propose a hierarchical structuring of process-related and situation-related information entities and include assessment scores that intraoperative workflow information systems may provide via OR networks. The conducted experiments on the proposed assessment scores included sixty recorded brain tumour removal procedures and considered 344 distinguishable surgical situations.A comprehensive modelling of surgical situations and process context will be a significant pre-requisite for reliable autonomous adaptation of medical devices and systems in digital operating rooms.
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Ociepa, Ewa, Maciej Mrowiec, and Iwona Deska. "Analysis of Water Losses and Assessment of Initiatives Aimed at Their Reduction in Selected Water Supply Systems." Water 11, no. 5 (May 17, 2019): 1037. http://dx.doi.org/10.3390/w11051037.
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This paper presents the analysis and assessment of water losses in water distribution systems of three water supply companies operating water supply networks in the area of effect of underground mining. The analysis of water losses was conducted based on numerous indices allowing for obtaining objective information on the condition of the water supply system. The method of the analysis of percentage water loss index was extended by the methods of determination of losses according to the International Water Association. The results of the analysis lead to the conclusion that with regular actions, the companies have reduced water losses in recent years to a level considered to be good compared to national data and average compared to international standards. The value of the failure intensity index for all companies in 2011 was over 1.0 while currently it is about 0.5. The decrease in Non-Revenue Water basic loss index (NRWB) from more than 20% for all analysed companies in 2008 to a few percent in 2017 and the decrease in Infrastructure Leakage Index (ILI) for companies A and C to less than 2.0 are evidence of the good condition of the network. This is also confirmed by the unit water loss index per capita, with its value in 2017 being 9.1 dm3/(inhabitant day) for company A, 11 dm3/(inhabitant·day) for B and 7.4 dm3/(inhabitant·day) for C. The several years of analysis and evaluation of numerous indices of water loss presented in the paper reveals the effectiveness of the adopted strategies of reducing leakages in the distribution system. It should be emphasized that the analysed companies have been involved in comprehensive initiatives aimed at reducing water leakages, resulting in a substantial reduction in water losses. GIS monitoring systems and databases are particularly helpful in reducing water losses. The basis of the activities is monitoring of flow and pressure in water supply networks and active leakage control. Network zoning with simultaneous observation of minimum night-time flows allows for preliminary location of the failure. Equipping companies with special leakage detection devices such as geophones, stethophones or correlators enables quick detection of leakages. The next step is to replace water meters with more and more accurate ones and to implement radio reading of water meters. All analysed companies perform systematic replacement of old steel and cast iron pipes which cause a large number of leakages that are often difficult to identify, thus leading to water losses.
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Santos, Brena, André Soares, Tuan-Anh Nguyen, Dug-Ki Min, Jae-Woo Lee, and Francisco-Airton Silva. "IoT Sensor Networks in Smart Buildings: A Performance Assessment Using Queuing Models." Sensors 21, no. 16 (August 23, 2021): 5660. http://dx.doi.org/10.3390/s21165660.
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Smart buildings in big cities are now equipped with an internet of things (IoT) infrastructure to constantly monitor different aspects of people’s daily lives via IoT devices and sensor networks. The malfunction and low quality of service (QoS) of such devices and networks can severely cause property damage and perhaps loss of life. Therefore, it is important to quantify different metrics related to the operational performance of the systems that make up such computational architecture even in advance of the building construction. Previous studies used analytical models considering different aspects to assess the performance of building monitoring systems. However, some critical points are still missing in the literature, such as (i) analyzing the capacity of computational resources adequate to the data demand, (ii) representing the number of cores per machine, and (iii) the clustering of sensors by location. This work proposes a queuing network based message exchange architecture to evaluate the performance of an intelligent building infrastructure associated with multiple processing layers: edge and fog. We consider an architecture of a building that has several floors and several rooms in each of them, where all rooms are equipped with sensors and an edge device. A comprehensive sensitivity analysis of the model was performed using the Design of Experiments (DoE) method to identify bottlenecks in the proposal. A series of case studies were conducted based on the DoE results. The DoE results allowed us to conclude, for example, that the number of cores can have more impact on the response time than the number of nodes. Simulations of scenarios defined through DoE allow observing the behavior of the following metrics: average response time, resource utilization rate, flow rate, discard rate, and the number of messages in the system. Three scenarios were explored: (i) scenario A (varying the number of cores), (ii) scenario B (varying the number of fog nodes), and (iii) scenario C (varying the nodes and cores simultaneously). Depending on the number of resources (nodes or cores), the system can become so overloaded that no new requests are supported. The queuing network based message exchange architecture and the analyses carried out can help system designers optimize their computational architectures before building construction.
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Hernandez, Paul D., and Peter J. Haas. "Estimating Workforce Needs for High-Speed Rail in California and the United States." Transportation Research Record: Journal of the Transportation Research Board 2328, no. 1 (January 2013): 25–31. http://dx.doi.org/10.3141/2328-04.
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This study assesses the overall impact of job creation associated with the anticipated construction of a high-speed rail (HSR) network in the United States, particularly in California, which was scheduled to begin construction as early as September 2012. Using variations of a bottom-up construction estimation technique, the study provides estimates of the quantity and type of workers needed during the design, construction, and operation of high-speed rail infrastructure, as well as education and training needs and level of this forecasted workforce. Given the high profile of state and national commitment to HSR initiatives, as well as its potential opportunity to generate employment, a comprehensive analysis that discusses the education, training, and attendant needs produced during the creation of HSR networks is timely. By using a refined bottom-up approach to estimate labor, education, and training needs required for the California HSR network, and with general application of this model across assessment of other corridors, this report seeks to identify the magnitude of workforce development challenges that lie ahead in the implementation of national HSR systems.
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Ajjaj, Souad, Souad El Houssaini, Mustapha Hain, and Mohammed-Alamine El Houssaini. "Performance Assessment and Modeling of Routing Protocol in Vehicular Ad Hoc Networks Using Statistical Design of Experiments Methodology: A Comprehensive Study." Applied System Innovation 5, no. 1 (February 2, 2022): 19. http://dx.doi.org/10.3390/asi5010019.
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The performance assessment of routing protocols in vehicular ad hoc networks (VANETs) plays a critical role in testing the efficiency of the routing algorithms before deployment in real conditions. This research introduces the statistical design of experiments (DOE) methodology as an innovative alternative to the one factor at a time (OFAT) approach for the assessment and the modeling of VANET routing protocol performance. In this paper, three design of experiments methods are applied, namely the two-level full factorial method, the Plackett–Burman method and the Taguchi method, and their outcomes are comprehensively compared. The present work considers a case study involving four factors namely: node density, number of connections, black hole and worm hole attacks. Their effects on four measured outputs called responses are simultaneously evaluated: throughput, packet loss ratio, average end-to-end delay and routing overhead of the AODV routing protocol. Further, regression models using the least squares method are generated. First, we compare the main effects of factors resulted from the three DOE methods. Second, we perform analysis of variance (ANOVA) to explore the statistical significance and compare the percentage contributions of each factor. Third, the goodness of fit of regression models is assessed using the adjusted R-squared measure and the fitting plots of measured versus predicted responses. VANET simulations are implemented using the network simulator (NS-3) and the simulator of urban mobility (SUMO). The findings reveal that the design of experiments methodology offers powerful mathematical, graphical and statistical techniques for analyzing and modeling the performance of VANET routing protocols with high accuracy and low costs. The three methods give equivalent results in terms of the main effect and ANOVA analysis. Nonetheless, the Taguchi models show higher predictive accuracy.
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Peppa, M. V., J. Hall, J. Goodyear, and J. P. Mills. "PHOTOGRAMMETRIC ASSESSMENT AND COMPARISON OF DJI PHANTOM 4 PRO AND PHANTOM 4 RTK SMALL UNMANNED AIRCRAFT SYSTEMS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W13 (June 4, 2019): 503–9. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w13-503-2019.
Full textAbstract:
<p><strong>Abstract.</strong> Consumer-grade Unmanned Aircraft Systems (UAS), and particularly Small Unmanned Aircraft (SUA) weighing less than 20&thinsp;kg, have recently become very attractive for photogrammetric data acquisition across a wide range of applications. Compared to other more expensive remote-sensing technology, DJI Phantom series SUA provide a trade-off between cost, sensor quality, functionality and portability. Because of the significant interest in such systems, rigorous accuracy assessment of metric performance is crucial. This research investigates the capabilities of the Phantom 4 Pro (P4P) and the recently launched Phantom 4 RTK (P4RTK) SUA through both laboratory and in-situ assessments with multi-scale photogrammetric blocks. The study adopts self-calibrating bundle adjustments from conventional photogrammetry and from a Structure-from-Motion (SfM)-photogrammetric approach. Both systems deliver planimetric and vertical absolute accuracies of better than one and two pixels ground sampling distance, respectively, against independent check points. This can be achieved if the imaging network configuration includes a mixed range of nadir and oblique imagery and several ground control points are established as reference information. Ongoing analysis is investigating the strength of all bundle adjustment solutions. It is also evaluating the GNSS capabilities of the P4RTK SUA after post-processing raw observations of its trajectory. Findings from a comprehensive accuracy assessment can support non-experts in designing the pre-flight photogrammetric data acquisition plan and aid understanding of the performance of such popular off-the-shelf SUA.</p>
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Tahir, Ghalib Ahmed, and Chu Kiong Loo. "A Comprehensive Survey of Image-Based Food Recognition and Volume Estimation Methods for Dietary Assessment." Healthcare 9, no. 12 (December 3, 2021): 1676. http://dx.doi.org/10.3390/healthcare9121676.
Full textAbstract:
Dietary studies showed that dietary problems such as obesity are associated with other chronic diseases, including hypertension, irregular blood sugar levels, and increased risk of heart attacks. The primary cause of these problems is poor lifestyle choices and unhealthy dietary habits, which are manageable using interactive mHealth apps. However, traditional dietary monitoring systems using manual food logging suffer from imprecision, underreporting, time consumption, and low adherence. Recent dietary monitoring systems tackle these challenges by automatic assessment of dietary intake through machine learning methods. This survey discusses the best-performing methodologies that have been developed so far for automatic food recognition and volume estimation. Firstly, the paper presented the rationale of visual-based methods for food recognition. Then, the core of the study is the presentation, discussion, and evaluation of these methods based on popular food image databases. In this context, this study discusses the mobile applications that are implementing these methods for automatic food logging. Our findings indicate that around 66.7% of surveyed studies use visual features from deep neural networks for food recognition. Similarly, all surveyed studies employed a variant of convolutional neural networks (CNN) for ingredient recognition due to recent research interest. Finally, this survey ends with a discussion of potential applications of food image analysis, existing research gaps, and open issues of this research area. Learning from unlabeled image datasets in an unsupervised manner, catastrophic forgetting during continual learning, and improving model transparency using explainable AI are potential areas of interest for future studies.