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1
Pearce, Daniel M., Ryoji Matsunaka, and Tetsuharu Oba. "Analysing the Impact of Pedestrian Network Centrality on Segment-Level Pedestrian Density." Journal of Advanced Transportation 2021 (December 21, 2021): 1–13. http://dx.doi.org/10.1155/2021/3061567.
Повний текст джерелаАнотація:
Studies have shown that street network centrality measures are capable of explaining a significant proportion of pedestrian activity. These studies typically employ street centreline networks that differ significantly from the networks that pedestrians use to traverse the built environment. Presently, centrality approaches are rarely applied to dedicated pedestrian network (DPNs). This creates uncertainty regarding their ability to explain pedestrian activity when derived from DPNs. This study addresses that gap by investigating the extent to which centrality metrics derived from DPNs can explain observed pedestrian densities, both alone and when controlling for other built environment variables in metro station environments in Asia. In total, four DPNs were created centred on metro stations in Bangkok, Manila, Osaka, and Taipei chosen to represent different urban typologies. Multivariate results show that centrality metrics alone explain a mere 6–24% of observed pedestrian densities when calculated on DPNs. When all factors are considered, the contribution of centrality remained consistent in most study sites but is somewhat reduced with land-use variables and proximity to rail transit revealed as the strongest predictors of pedestrian density. Pedestrian design factors were also frequently associated with pedestrian density. Finally, stronger associations between centrality and pedestrian densities were observed in the denser, more complex pedestrian environments. These findings provide insight into the performance of centrality measures applied to DPNs expanding pedestrian network research in this area.
2
S., Annie Christila, and Dr Sivakumar R. "An Empirical Review of DDOS Attack Mitigation System on SDN Using Cloud Environment." Webology 19, no. 1 (January 20, 2022): 283–94. http://dx.doi.org/10.14704/web/v19i1/web19022.
Повний текст джерелаАнотація:
The separation of the control plane and the network data plane from the network defined by the software is making it easier for network management. As a result, SDN can be used in a variety of network settings, including network hiring networks. However, the construction of the novel network raises new security issues. Dedicated Shared Denial (DDoS) is easy to distribute and hard to protect on standard networks; on SDN networks, it can bypass the central controllers and bring the entire network down. Cloud computing has emerged as a modern and exciting computer space over the past decade, providing an affordable and awesome computer space. SDN technology combined with cloud computing highlights the challenges of cloud communication and enhances cloud adaptability, configuration, intelligence, and extreme density. Sensitive features of SDN, such as global network coverage, software-based traffic analysis, integrated network management, etc., greatly enhance the acquisition of DDoS cloud capabilities and scalability capabilities. In this study, a major effort was made to compare the various solutions currently available for programs to reduce DDoS attacks in cloud environments using SDN and provided performance tests such as detection rate, recovery time and False positive Rate.
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Mittal, Archak, Hani S. Mahmassani, and Alireza Talebpour. "Network Flow Relations and Travel Time Reliability in a Connected Environment." Transportation Research Record: Journal of the Transportation Research Board 2622, no. 1 (January 2017): 24–37. http://dx.doi.org/10.3141/2622-03.
Повний текст джерелаАнотація:
Connected vehicle technology provides the opportunity to create a connected network of vehicles and infrastructure. In such a network, individual vehicles can communicate with each other and with the infrastructure, including a traffic management center. The effects of connectivity on reducing congestion and improving throughput and reliability have been extensively investigated at the segment (facility) level. To complement the segment-level studies and to assess the large-scale effects of connectivity, this paper presents a networkwide evaluation of the effect of connectivity on travel time reliability. This study uses a microscopic simulation framework to establish the speed–density relationships at different market penetration rates (MPRs) of connected vehicles. Calibrated speed–density relationships are then used as inputs to the mesoscopic simulation tools to simulate the networkwide effects of connectivity. The Chicago, Illinois, and Salt Lake City, Utah, networks are simulated. Numerical results from the simulations confirm that the linear relationship between distance-weighted travel time rate and standard deviation holds for both networks and is not affected by either the demand level or the MPR of connected vehicles. In addition, with an increase in the MPR of connected vehicles, the network attains a lower maximum density and gets an increased flow rate for the same density level. Highly connected environment has the potential to help a congested network to recover from a breakdown and avoid gridlock. It is shown that a connected environment can improve a system’s performance by providing increased traffic flow rate and better travel time reliability at all demand levels.
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Goutam, Siddharth, and Srija Unnikrishnan. "Algorithm for Vertical Handover Decision in Vehicular Environment." Journal of Information Technology Research 14, no. 1 (January 2021): 92–109. http://dx.doi.org/10.4018/jitr.2021010106.
Повний текст джерелаАнотація:
In the present scenario, co-existence of various wireless networks necessitates efficient vertical handover decision algorithms to maintain cost effective seamless connectivity across various networks, as the user is moving from one place to another. In this paper, the authors have presented a vertical handover decision algorithm which calculates a fitness value for each available network based on received signal strength, channel capacity, cost, battery life, velocity, and quality of service (QoS). In addition, the travelling speed of the user and the vehicular density at that time is used to capture the handover track of the user for network management. An alternate model using fuzzy inference system is also presented.
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Rauf, Moina, and Zahid Pervaiz. "Replacing Contracts with Handshakes: A Study of Social Networks of Entrepreneurs in the Weaving Sector." Pakistan Development Review 55, no. 4I-II (December 1, 2016): 331–48. http://dx.doi.org/10.30541/v55i4i-iipp.331-348.
Повний текст джерелаАнотація:
Informal institutions like kinship based networks play a crucial role in business activity. The flow of information in such networks, based on trust and reciprocity helps in creating an environment where opportunism is curtailed and relational based governance mechanism prevails. This paper studies, whether such factors play a role as an alternative governance mechanism for contracts as opposed to the formal institutions or not. The effectiveness of such network factors hinges on the network structure, and therefore network density and network size are taken as independent variables. Though network density was positively and significantly related to the use of social networks for management of breach of contracts, network size was negatively related to management of breach of contracts. Network size and network density were positively related to ex-post transaction costs of dispute resolutions however, they were not statistically significant. JEL Classification: D850, O17, L14 Keywords: Social Capital, SMEs, Transaction Costs, Entrepreneurship, Networks
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Kang, Qinqing. "A High Density WSN Cluster Positioning Approach." International Journal of Mobile Computing and Multimedia Communications 12, no. 2 (April 2021): 1–17. http://dx.doi.org/10.4018/ijmcmc.2021040101.
Повний текст джерелаАнотація:
Node self-positioning is one of the supporting technologies for wireless sensor network applications. In this paper, a clustering localization algorithm is proposed for large-scale high-density wireless sensor networks. Firstly, the potential of the node is defined as the basis for the election of the cluster head. The distance between the nodes in the network is calculated indirectly by the relationship between the received signal strength and the communication radius. The topology information in each cluster is saved by the cluster head, and the linear programming method is used in the cluster head to implement the cluster internal relative positioning. Then, from the sink node, the inter-cluster location fusion is gradually implemented, and finally the absolute positioning of the whole network is realized. Compared with the centralized convex programming algorithm, the proposed algorithm has low computational complexity, small traffic, high positioning accuracy, and does not need to know the signal attenuation factor in the environment in advance, and there is anti-noise ability.
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Wu, Zhizhou, Yiming Zhang, Guishan Tan, and Jia Hu. "The research of traffic density extraction method under vehicular ad hoc network environment." Journal of Intelligent and Connected Vehicles 2, no. 1 (August 29, 2019): 25–32. http://dx.doi.org/10.1108/jicv-01-2019-0003.
Повний текст джерелаАнотація:
Purpose Traffic density is one of the most important parameters to consider in the traffic operation field. Owing to limited data sources, traditional methods cannot extract traffic density directly. In the vehicular ad hoc network (VANET) environment, the vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) interaction technologies create better conditions for collecting the whole time-space and refined traffic data, which provides a new approach to solving this problem. Design/methodology/approach On that basis, a real-time traffic density extraction method has been proposed, including lane density, segment density and network density. Meanwhile, using SUMO and OMNet++ as traffic simulator and network simulator, respectively, the Veins framework as middleware and the two-way coupling VANET simulation platform was constructed. Findings Based on the simulation platform, a simulated intersection in Shanghai was developed to investigate the adaptability of the model. Originality/value Most research studies use separate simulation methods, importing trace data obtained by using from the simulation software to the communication simulation software. In this paper, the tight coupling simulation method is applied. Using real-time data and history data, the research focuses on the establishment and validation of the traffic density extraction model.
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Xu, Meng. "The Influence of Alliance Innovation Network Structure upon Enterprise Innovation: A Case Study of China’s Energy-Saving and Environment-protection Industry." International Journal of Business and Management 13, no. 2 (January 14, 2018): 208. http://dx.doi.org/10.5539/ijbm.v13n2p208.
Повний текст джерелаАнотація:
The Energy-saving and environment-protection industry, an important strategic and emerging industry in China, will develop into a pillar industry. In view of global climate change, environmental pollution, resource depletion and the defects and deficiencies in traditional technology, technology and product innovation constitute the lifeline of energy-saving and environment-protection industry. The alliance network of enterprises will influence, stimulate, and regulate enterprise innovation greatly. A comprehensive analysis of alliance data of China's energy-saving and environment-protection industry from 2000 to 2013 by using Ucinet software can reveal the network structure parameters such as degree, clique number, average path length, clustering coefficient, and betweenness centrality, which reflects different types of enterprise networks and different positions of enterprises in different types of networks. A negative regression analysis of enterprise patent data and network structure parameters by using Stata software can make some conclusions that the influences of network characteristics on enterprise innovation reach the maximum in the second year of the window period end, that innovation accumulation, clustering coefficient, betweenness centrality are related to the enterprise innovation, that clique number, network density are negatively related to the enterprise innovation, and that there is an inverted U relationship between average path length and enterprise innovation. It is suggested to increase the accumulation level of innovation, appropriately control the network density, reduce the average path length, improve the betweenness centrality and clustering coefficient of enterprises, so as to improve the overall innovation level.
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Celaya-Echarri, Azpilicueta, López-Iturri, Aguirre, and Falcone. "Performance Evaluation and Interference Characterization of Wireless Sensor Networks for Complex High-Node Density Scenarios." Sensors 19, no. 16 (August 11, 2019): 3516. http://dx.doi.org/10.3390/s19163516.
Повний текст джерелаАнотація:
The uncontainable future development of smart regions, as a set of smart cities’ networks assembled, is directly associated with a growing demand of full interactive and connected ubiquitous smart environments. To achieve this global connection goal, large numbers of transceivers and multiple wireless systems will be involved to provide user services and applications anytime and anyplace, regardless the devices, networks, or systems they use. Adequate, efficient and effective radio wave propagation tools, methodologies, and analyses in complex indoor and outdoor environments are crucially required to prevent communication limitations such as coverage, capacity, speed, or channel interferences due to high-node density or channel restrictions. In this work, radio wave propagation characterization in an urban indoor and outdoor wireless sensor network environment has been assessed, at ISM 2.4 GHz and 5 GHz frequency bands. The selected scenario is an auditorium placed in an open free city area surrounded by inhomogeneous vegetation. User density within the scenario, in terms of inherent transceivers density, poses challenges in overall system operation, given by multiple node operation which increases overall interference levels. By means of an in-house developed 3D ray launching (3D-RL) algorithm with hybrid code operation, the impact of variable density wireless sensor network operation is presented, providing coverage/capacity estimations, interference estimation, device level performance and precise characterization of multipath propagation components in terms of received power levels and time domain characteristics. This analysis and the proposed simulation methodology, can lead in an adequate interference characterization extensible to a wide range of scenarios, considering conventional transceivers as well as wearables, which provide suitable information for the overall network performance in crowded indoor and outdoor complex heterogeneous environments.
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Luo, Hongling, Jun Sang, Weiqun Wu, Hong Xiang, Zhili Xiang, Qian Zhang, and Zhongyuan Wu. "A High-Density Crowd Counting Method Based on Convolutional Feature Fusion." Applied Sciences 8, no. 12 (November 23, 2018): 2367. http://dx.doi.org/10.3390/app8122367.
Повний текст джерелаАнотація:
In recent years, the trampling events due to overcrowding have occurred frequently, which leads to the demand for crowd counting under a high-density environment. At present, there are few studies on monitoring crowds in a large-scale crowded environment, while there exists technology drawbacks and a lack of mature systems. Aiming to solve the crowd counting problem with high-density under complex environments, a feature fusion-based deep convolutional neural network method FF-CNN (Feature Fusion of Convolutional Neural Network) was proposed in this paper. The proposed FF-CNN mapped the crowd image to its crowd density map, and then obtained the head count by integration. The geometry adaptive kernels were adopted to generate high-quality density maps which were used as ground truths for network training. The deconvolution technique was used to achieve the fusion of high-level and low-level features to get richer features, and two loss functions, i.e., density map loss and absolute count loss, were used for joint optimization. In order to increase the sample diversity, the original images were cropped with a random cropping method for each iteration. The experimental results of FF-CNN on the ShanghaiTech public dataset showed that the fusion of low-level and high-level features can extract richer features to improve the precision of density map estimation, and further improve the accuracy of crowd counting.
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Boessen, Adam, John R. Hipp, Carter T. Butts, Nicholas N. Nagle, and Emily J. Smith. "The built environment, spatial scale, and social networks: Do land uses matter for personal network structure?" Environment and Planning B: Urban Analytics and City Science 45, no. 3 (February 1, 2017): 400–416. http://dx.doi.org/10.1177/2399808317690158.
Повний текст джерелаАнотація:
In this study, we examine how different features of the built environment—density, diversity of land uses, and design—have consequences for personal networks. We also consider whether different features of the built environment have consequences for the spatial location of persons to whom one is tied by considering their distribution in local area, broader city region, and a more macro spatial scale. We test these ideas with a large sample of the Western United States for three different types of ties. Our findings suggest that the built environment is crucial for personal network structure, both in the number of social ties and where they are located.
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Hollenstein, D., and S. Bleisch. "WALKABILITY FOR DIFFERENT URBAN GRANULARITIES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B2 (June 8, 2016): 703–8. http://dx.doi.org/10.5194/isprsarchives-xli-b2-703-2016.
Повний текст джерелаАнотація:
The positive effects of low-intensity physical activity are widely acknowledged and in this context walking is often promoted as an active form of transport. Under the concept of walkability the role of the built environment in encouraging walking is investigated. For that purpose, walkability is quantified area-wise by measuring a varying set of built environment attributes. In purely GIS-based approaches to studying walkability, indices are generally built using existing and easily accessible data. These include street network design, population density, land use mix, and access to destinations. Access to destinations is usually estimated using either a fixed radius, or distances in the street network. In this paper, two approaches to approximate a footpath network are presented. The two footpath networks were built making different assumptions regarding the walkability of different street types with respect to more or less restrictive safety preferences. Information on sidewalk presence, pedestrian crossings, and traffic restrictions were used to build both networks. The first network comprises car traffic free areas only. The second network includes streets with low speed limits that have no sidewalks. Both networks are compared to the more commonly used street network in an access-to-distance analysis. The results suggest that for the generally highly walkable study area, access to destination mostly depends on destination density within the defined walkable distance. However, on single street segments access to destinations is diminished when only car traffic free spaces are assumed to be walkable.
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Hollenstein, D., and S. Bleisch. "WALKABILITY FOR DIFFERENT URBAN GRANULARITIES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B2 (June 8, 2016): 703–8. http://dx.doi.org/10.5194/isprs-archives-xli-b2-703-2016.
Повний текст джерелаАнотація:
The positive effects of low-intensity physical activity are widely acknowledged and in this context walking is often promoted as an active form of transport. Under the concept of walkability the role of the built environment in encouraging walking is investigated. For that purpose, walkability is quantified area-wise by measuring a varying set of built environment attributes. In purely GIS-based approaches to studying walkability, indices are generally built using existing and easily accessible data. These include street network design, population density, land use mix, and access to destinations. Access to destinations is usually estimated using either a fixed radius, or distances in the street network. In this paper, two approaches to approximate a footpath network are presented. The two footpath networks were built making different assumptions regarding the walkability of different street types with respect to more or less restrictive safety preferences. Information on sidewalk presence, pedestrian crossings, and traffic restrictions were used to build both networks. The first network comprises car traffic free areas only. The second network includes streets with low speed limits that have no sidewalks. Both networks are compared to the more commonly used street network in an access-to-distance analysis. The results suggest that for the generally highly walkable study area, access to destination mostly depends on destination density within the defined walkable distance. However, on single street segments access to destinations is diminished when only car traffic free spaces are assumed to be walkable.
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Celaya-Echarri, Mikel, Leyre Azpilicueta, Peio Lopez-Iturri, Erik Aguirre, and Francisco Falcone. "Performance Evaluation and Interference Characterization of Wireless Sensor Networks for Complex High-Node Density Scenarios." Proceedings 4, no. 1 (November 14, 2018): 28. http://dx.doi.org/10.3390/ecsa-5-05729.
Повний текст джерелаАнотація:
The uncontainable future development of smart regions, as a set of smart cities’ assembled networks, is directly associated with a growing demand of full interactive and connected ubiquitous smart environments. To achieve this goal of global connection, a large number of transceivers and multiple wireless systems will be involved to provide user services and applications (i.e., Ambient Assisted Living, emergency situations, e-health monitoring, or Intelligent Transportation Systems) anytime and anyplace, regardless of the devices, networks, or systems used. Adequate, efficient, and effective radio wave propagation tools, methodologies, and analyses in complex environments (indoor and outdoor) are crucial to prevent communication limitations such as coverage, capacity, speed, or channel interferences due to nodes’ density or channel restrictions. In this work, radio wave propagation characterization in an urban indoor and outdoor environment, at ISM 2.4 GHZ and 5 GHz Wireless Sensor Networks (WSNs), has been assessed. The selected scenario is an auditorium placed in a free open area surrounded by inhomogeneous vegetation. User density within the scenario, in terms of inherent transceivers density, poses challenges to the overall system operation, given by multiple node operation which increases overall interference levels. By means of an in-house developed 3D ray launching algorithm, the impact of variable density wireless sensor network operation within this complex scenario is presented. This analysis and the proposed simulation methodology can lead in an adequate interference characterization, considering conventional transceivers as well as wearables, which provide suitable information for the overall network performance in complex crowded indoor and outdoor scenarios.
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Wang, Rujuan, and Gang Wang. "Web Text Categorization Based on Statistical Merging Algorithm in Big Data Environment." International Journal of Ambient Computing and Intelligence 10, no. 3 (July 2019): 17–32. http://dx.doi.org/10.4018/ijaci.2019070102.
Повний текст джерелаАнотація:
In the field of modern information technology, how to find information quickly, accurately and comprehensively that users really needed has become the focus of research in this field. In this article, a feature selection method based on a complex network is proposed for the structure and content characteristics of large-scale web text information. The preprocessed web text is converted into a complex network. The nodes in the network correspond to the entries in the text. The edges of the network correspond to the links between the entries in the text, and the degree of nodes and the aggregation system are used. Second, the text classification method is studied from the point of view of data sampling, and a text classification method based on density statistics is proposed. This method uses not only the density information of the text feature set in the classification process, but also the use of statistical merging criteria to get the text. The difference information of each feature has a better classification effect for large text collections.
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C.O, Arinze, Idigo V.E, Akpado K.A, Agu V.N, and Nwalozie G.C. "RTC-GWLAN: A Real Time Characterization of Generic IEEE 802.11 for High Density Services." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 12, no. 6 (June 30, 2013): 3522–35. http://dx.doi.org/10.24297/ijct.v12i6.3145.
Повний текст джерелаАнотація:
This research investigates and analysed generic Wireless Local Area Networks (IEEE 802.11a/b/g) in the context of their Quality of Service (QoS) in high density networks using some generic Key Performance Indicators (KPI) such as throughput (Bytes/Sec), Received Signal Strength Indicator (RSSI), and latency response (secs). The study focused on University of Nigeria Nsukka (UNN) which houses several hostels and faculties. Using Applied Research Methodology (ARM), this work characterized a real life generic hotspot testbed (UNN) for Received Signal Strength (RSS), mobile node distance, latency and throughput using Tranzio-Wavion Minipop Infrastructure in UNN as the network testbed. In this study, after sampling the selected KPIs, data were collected via our testbed measurements from the test nodes, Network Switching system/Network Operating Centres (NOCs) and their values were evaluated for an assessment study. The KPI results obtained showed that the traditional generic WLAN will scarcely scale in high density traffic environment in terms of scalability, speed performance (network convergence), cost, and other selected KPIs. This will lead to a proposal on a conceptual framework for Cognitive High Density Hotspot (CHDN) in our future work, which will address the limitations of generic WLANs for enterprise computing.
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Malekzadeh, Mina. "Link Quality Improvement of Long-Term Evolution and 802.11ax in High-Density Areas." Wireless Communications and Mobile Computing 2020 (September 15, 2020): 1–28. http://dx.doi.org/10.1155/2020/8817246.
Повний текст джерелаАнотація:
The 802.11ax high-efficiency wireless (HEW) particularly designed for high-density areas. However, dense areas have specific requirements that demand precise deployment strategies by network developers. In dense networks, a large number of users are simultaneously connected to the same channel; hence, the available bandwidth is divided among the users in such a way that joining more users can eventually saturate the network. Furthermore, in dense areas, a large number of closely spaced users are transmitting data at the same time. In such a heavily frequency interfered environment, the wireless link quality extremely degrades, which can practically render the network unavailable. Thereby, it is essential to determine the appropriate deployment options regarding the specific networks’ settings and configurations. Hence, this work proposes a network architecture model to determine the dual-band HEW performance in dense deployments. The model additionally includes long-term evolution (LTE) as the cellular alternative for high-density areas which is utilized by the model as the reference point for corresponding comparison purposes with HEW. The model is implemented, and link quality parameters are measured based on different aspects of the deployment options. To further validate the model and determine the optimization levels provided by the options, the simulation and analytical results are compared.
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Yang, Hongtai, Zhihao Zhao, Chaozhe Jiang, Yi Wen, and Malik Muneeb Abid. "Spatially Varying Relation between Built Environment and Station-Level Subway Passenger-Distance." Journal of Advanced Transportation 2022 (January 20, 2022): 1–18. http://dx.doi.org/10.1155/2022/7542560.
Повний текст джерелаАнотація:
As a sustainable mode of transportation, subways bring great convenience to the society. Although there have been many studies examining the relationship between the built environment and the station-level ridership, those studies focused mainly on the ridership, which is defined as the number of trips for each station. While ridership is an important indicator for evaluating subway demand, passenger-distance is another critical indicator that incorporates distance into demand evaluation, which has not yet been fully explored. To fill this gap, this paper investigates the relationship between the built environment around stations and the station-level passenger-distance (SLPD). As noted in previous studies, the relationship between the built environment and travel demand can vary by space. Therefore, a geographically weighted regression (GWR) model and a mixed geographically weighted regression (MGWR) model have been used to explore this spatially varying relationship using Chengdu, China, as an example case. The results were compared with that of an ordinary least squares (OLS) model. The comparison shows that the MGWR model that considers both global and local variables has the best goodness of fit. Results also show that 11 of the 25 potential variables are significantly related to SLPD. The accessibility of the station, station type, such as transfer or terminal, number of bus stops, number of restaurants, density of building area, density of the national road network, and density of the provincial road network, all have a positive correlation with SLPD. Meanwhile, the variables, whether it is a newly opened subway station, density of living points of interest (POIs), and density of railroad network, are all negatively correlated with SLPD. Ten of the eleven significant variables (except accessibility) have spatially varying relationships with SLPD. These findings can serve a useful reference for transportation planners for the demand evaluation.
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Yan, Yao, and Rui Xu. "DDoS Attacks for Ad Hoc Network Based on Attack Cluster." Advanced Materials Research 546-547 (July 2012): 1371–76. http://dx.doi.org/10.4028/www.scientific.net/amr.546-547.1371.
Повний текст джерелаАнотація:
Show the definition of Ad Hoc network attack cluster, and propose a new method of DDoS attacks for Ad Hoc Networks, which can accurately attack the target node, demonstrate no redundant aggressive behavior compared with the traditional attack and reduce the detection rate of aggressive behavior. Use NS2 simulation platform to build Ad Hoc network simulation scenarios with dynamic topology, and simulate DDoS attacks in this environment; The simulation results show that the new DDoS attack method can effectively reduce the communication ability of the Ad Hoc network, and increasing the attack node density will strengthen the attack effect.
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Lou, Shumei, Gautam Srivastava, and Shuai Liu. "A Node Density Control Learning Method for the Internet of Things." Sensors 19, no. 15 (August 5, 2019): 3428. http://dx.doi.org/10.3390/s19153428.
Повний текст джерелаАнотація:
When examining density control learning methods for wireless sensor nodes, control time is often long and power consumption is usually very high. This paper proposes a node density control learning method for wireless sensor nodes and applies it to an environment based on Internet of Things architectures. Firstly, the characteristics of wireless sensors networks and the structure of mobile nodes are analyzed. Combined with the flexibility of wireless sensor networks and the degree of freedom of real-time processing and configuration of field programmable gate array (FPGA) data, a one-step transition probability matrix is introduced. In addition, the probability of arrival of signals between any pair of mobile nodes is also studied and calculated. Finally, the probability of signal connection between mobile nodes is close to 1, approximating the minimum node density at T. We simulate using a fully connected network identifying a worst-case test environment. Detailed experimental results show that our novel proposed method has shorter completion time and lower power consumption than previous attempts. We achieve high node density control as well at close to 90%.
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Ambarwari, Agus, Yeni Herdiyeni, and Irman Hermadi. "Identification of Venation Type Based on Venation Density using Digital Image Processing." Jurnal Teknoinfo 12, no. 2 (July 15, 2018): 87. http://dx.doi.org/10.33365/jti.v12i2.127.
Повний текст джерелаАнотація:
Leaf venation is one biometric feature of leaves that have an important role in growth processes of the plant, and to determine the relationship of the plant physiology and the environment in which plants grow. At every different environment, plants have different types of leaf venation. It can be seen from the level of the leaf vein density. In this study, the feature of leaf vein density was used to identify the leaves based on venation type. The venation density features obtained from segmentation, vein detection, and density feature extraction of leaf venation. Identification of the venation type was made using the artificial neural network (ANN). The results of this study indicate that the proposed method can classify the leaf correctly image based on the venation type. On the dataset with 324 samples, the accuracy of 82.71% was obtained. This shows that the leaf vein density features allow use as a plant identifier.Keywords: leaf vein density, vein detection, density feature extraction, artificial neural network
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Han, Xu, Lei Xue, and Ying Xu. "A PSD Maps Estimation Algorithm for Underlay Cognitive Radio Networks Based on the Convolutional Neural Network." Mathematical Problems in Engineering 2020 (July 29, 2020): 1–10. http://dx.doi.org/10.1155/2020/4024631.
Повний текст джерелаАнотація:
In the underlay cognitive radio networks (CRNs), the power spectral density (PSD) maps play a foundational role in detecting the idle radio resources. However, it is hard to get a high-accurate PSD map estimation result because of the complicated radio environment. For this reason, we propose a novel convolutional neural network- (CNN-) based PSD map estimation algorithm named map reconstruction CNN (MRCNN). Using the CNN to estimate PSD maps for underlay CRNs has not been reported until now. First, on the basis of the proposed color mapping process, we transform the PSD map estimation task to the image reconstruction task. Then, we train the MRCNN to learn the radio environment characteristics from the training data, rather than making direct biased or imprecise wireless environment hypotheses as in the conventional methods. We utilize the extracted knowledge in the training process to reconstruct the PSD map images. As demonstrated in the simulations, the proposed MRCNN method has a better PSD map estimation performance than the conventional methods.
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Bhuyan, Nasimul Hyder Maruf, and Sabrina Alam. "Network Performance of Contention Window in VANET." European Journal of Engineering Research and Science 3, no. 2 (February 28, 2018): 43. http://dx.doi.org/10.24018/ejers.2018.3.2.611.
Повний текст джерелаАнотація:
In this paper, we tried to presented the effect of different contention window (CW) size in a realistic road environment with mobility management and different propagation loss model was implemented in ns-3. We focus on the WAVE module of ns-3. Our contribution is to create a realistic two-lane both way highway road environment surrounding by fields, low-rise commercial buildings, street lamps and road signs for vehicular safety messages are Cooperative Awareness Message (CAM) and Decentralized Event Notification Message (DENM). Medium to low traffic density. On the other section, we describe in detail the simulation setup scenario during the implementation. Finally, we present our simulation results that we obtained from the highway scenario.
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Bhuyan, Nasimul Hyder Maruf, and Sabrina Alam. "Network Performance of Contention Window in VANET." European Journal of Engineering and Technology Research 3, no. 2 (February 28, 2018): 43–47. http://dx.doi.org/10.24018/ejeng.2018.3.2.611.
Повний текст джерелаАнотація:
In this paper, we tried to presented the effect of different contention window (CW) size in a realistic road environment with mobility management and different propagation loss model was implemented in ns-3. We focus on the WAVE module of ns-3. Our contribution is to create a realistic two-lane both way highway road environment surrounding by fields, low-rise commercial buildings, street lamps and road signs for vehicular safety messages are Cooperative Awareness Message (CAM) and Decentralized Event Notification Message (DENM). Medium to low traffic density. On the other section, we describe in detail the simulation setup scenario during the implementation. Finally, we present our simulation results that we obtained from the highway scenario.
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Molina-García, Javier, Xavier García-Massó, Isaac Estevan, and Ana Queralt. "Built Environment, Psychosocial Factors and Active Commuting to School in Adolescents: Clustering a Self-Organizing Map Analysis." International Journal of Environmental Research and Public Health 16, no. 1 (December 29, 2018): 83. http://dx.doi.org/10.3390/ijerph16010083.
Повний текст джерелаАнотація:
Although the built environment and certain psychosocial factors are related to adolescents’ active commuting to and from school (ACS), their interrelationships have not been explored in depth. This study describes these interrelationships and behavioral profiles via a self-organizing map (SOM) analysis. The sample comprised 465 adolescents from the IPEN (International Physical Activity and the Environment Network) Adolescent study in Valencia, Spain. ACS, barriers to ACS, physical self-efficacy, social support and sociodemographics were measured by questionnaire. Street-network distance to school, net residential density and street intersection density were calculated from the Geographic Information System. The clustering of the SOM outcomes resulted in eight areas or clusters. The clusters which correspond to the lowest and highest ACS levels were then explored in depth. The lowest ACS levels presented interactions between the less supportive built environments (i.e., low levels of residential density and street connectivity in the neighborhood and greater distances to school) and unfavorable psychosocial variables (i.e., low values of physical self-efficacy and medium social support for ACS) and good access to private motorized transport at home. The adolescents with the lowest ACS values exhibited high ACS environment/safety and planning/psychosocial barrier values. Future interventions should be designed to encourage ACS and change multiple levels of influence, such as individual, psychosocial and environmental factors.
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NORGAARD, JULIA R., HAROLD J. WALBERT, and R. AUGUST HARDY. "Shadow markets and hierarchies: comparing and modeling networks in the Dark Net." Journal of Institutional Economics 14, no. 5 (January 14, 2018): 877–99. http://dx.doi.org/10.1017/s1744137417000613.
Повний текст джерелаАнотація:
AbstractThis paper analyzes the determinants of network structure, as measured by hierarchy and monopolization, by examining various black market networks. We examine structures of networks on the Internet Dark Net (Virtual) and compare it to network structures of traditional black markets (Ground), using agent-based modeling. The purpose of modeling these two different types of illicit markets is to understand the network structure that emerges from the interactions of the agents in each environment. Traditional black markets are relatively hierarchical, with high degree and high betweenness. We compare the density and average length of the shortest path of the simulated Ground black market networks with our simulated Virtual network. We find that hierarchy and monopolization tendencies in networks are products of different transaction costs and information asymmetries. The Internet is an effective way to lower multiple aspects of network structure. We observe that the network structure surrounding the interactions in the Virtual black market is less hierarchical and slightly more monopolistic than the network structure of the Ground market.
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Peng, Zhihao, Raziyeh Daraei, Seyed Mojtaba Ahmadpanahi, Amir Seyed Danesh, Safieh Siadat, Poria Pirozmand, and Rozita Jamili Oskouei. "Proposing a Density-Based Clustering Approach (DBCA) to Aggregate Data Collected from the Environment in Arid Area for Desertification." Wireless Communications and Mobile Computing 2021 (February 10, 2021): 1–16. http://dx.doi.org/10.1155/2021/6627771.
Повний текст джерелаАнотація:
Nowadays, the expansion of desert areas has become one of the main problems in arid areas due to various reasons such as rising temperatures and vegetation fires. Establishment of wireless sensor networks in these areas can accelerate the process of environmental monitoring and integrate temperature and humidity information sending to base stations in order to make basic decisions on desertification. The main problem in this regard is the energy limitation of sensor nodes in wireless sensor networks, which is one of the main challenges in using these nodes due to the lack of a fixed power supply. Because the node consumes the most energy during data transmission, the node that transmits the most data or sends the packets over long distances runs out of energy faster than the others and the network work process is disrupted. Therefore, in this study, a density-based clustering approach is proposed to integrate data collected from the environment in arid areas for desertification. In the proposed method at each step, the node that has the most residual energy and is highly centralized will be selected to transfer information. The results of experiments for evaluating the performance of the proposed method show that the proposed method balances the energy consumption of the nodes and optimizes the lifespan of the nodes in the wireless sensor network installed in the arid area.
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Nian, Guangyue, Jian Sun, and Jianyun Huang. "Exploring the Effects of Urban Built Environment on Road Travel Speed Variability with a Spatial Panel Data Model." ISPRS International Journal of Geo-Information 10, no. 12 (December 10, 2021): 829. http://dx.doi.org/10.3390/ijgi10120829.
Повний текст джерелаАнотація:
Road traffic congestion is a common problem in most large cities, and exploring the root causes is essential to alleviate traffic congestion. Travel behavior is closely related to the built environment, and affects road travel speed. This paper investigated the direct effect of built environment on the average travel speed of road traffic. Taxi trajectories were divided into 30 min time slot (48 time slots throughout the day) and matched to the road network to obtain the average travel speed of road segments. The Points of Interest (POIs) in the buffer zone on both sides of the road segment were used to calculate the built environment indicators corresponding to the road segment, and then a spatial panel data model was proposed to assess the influence of the built environment adjacent to the road segment on the average travel speed of the road segment. The results demonstrated that the bus stop density, healthcare service density, sports and leisure service density, and parking entrance and exit density are the key factors that positively affect the average road travel speed. The residential community density and business building density are the key factors that negatively affect the average travel speed. Built environments have spatial correlation and spatial heterogeneity in their influence on the average travel speed of road segments. Findings of this study may provide useful insights for understanding the correlation between road travel speed and built environment, which would have important implications for urban planning and governance, traffic demand forecasting and traffic system optimization.
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Shi, Jian Jun, Ling Bin Lu, and Jing Ying Zhang. "An Environment-Friendly Thermal Insulation Material from Porous Cellulose Aerogel." Advanced Materials Research 773 (September 2013): 487–91. http://dx.doi.org/10.4028/www.scientific.net/amr.773.487.
Повний текст джерелаАнотація:
Cellulose hydrogel was prepared by using the NaOH/ Thiourea/ H2O as solvent system, cellulose aerogels were obtained by freeze-drying technology. The results showed that cellulose aerogel had porous network structure. Freeze-drying method was an effective way to prepare cellulose aerogel, and the volume shrinkage was 20.41%-28.36%. Bulk cellulose aerogel had low density, high porosity and fine mechanical strength. The density was low to 0.233g/cm3, and the porosity was up to 84.88%. The compressive strength was 5.7-8.2MPa. Cellulose aerogel had good heat insulation performance and thermal conductivity could be as low as 0.029 W/ (m·K). This work provided a foundation for the possibility of applying cellulose aerogels in the insulating material field.
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Al Alam, Pamela, Joseph Constantin, Ibtissam Constantin, and Clelia Lopez. "Partitioning of Transportation Networks by Efficient Evolutionary Clustering and Density Peaks." Algorithms 15, no. 3 (February 24, 2022): 76. http://dx.doi.org/10.3390/a15030076.
Повний текст джерелаАнотація:
Road traffic congestion has became a major problem in most countries because it affects sustainable mobility. Partitioning a transport network into homogeneous areas can be very useful for monitoring traffic as congestion is spatially correlated in adjacent roads, and it propagates at different speeds as a function of time. Spectral clustering has been successfully applied for the partitioning of transportation networks based on the spatial characteristics of congestion at a specific time. However, this type of classification is not suitable for data that change over time. Evolutionary spectral clustering represents a state-of-the-art algorithm for grouping objects evolving over time. However, the disadvantages of this algorithm are the cubic time complexity and the high memory demand, which make it insufficient to handle a large number of data sets. In this paper, we propose an efficient evolutionary spectral clustering algorithm that solves the drawbacks of evolutionary spectral clustering by reducing the size of the eigenvalue problem. This algorithm is applied in a dynamic environment to partition a transportation network into connected homogeneous regions that evolve with time. The number of clusters is selected automatically by using a density peak algorithm adopted for the classification of traffic congestion based on the sparse snake similarity matrix. Experiments on the real network of Amsterdam city demonstrate the superiority of the proposed algorithm in robustness and effectiveness.
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Gu, Musong, Chaobang Gao, Jingjing Lyu, Wenjie Fan, and Lei You. "Study of Node Distribution and Density Optimization in Mobile Sensor Network 3D Space." Wireless Communications and Mobile Computing 2021 (August 19, 2021): 1–7. http://dx.doi.org/10.1155/2021/6978812.
Повний текст джерелаАнотація:
Mobile sensor network is applied in information collection in emergencies. As the mobile sensor network in real environment is widely deployed with different height and the redundancy of the sensor node needs to be as low as possible, therefore, it is necessary to effectively deploy mobile sensor nodes in the 3D space to have reasonable layout and optimized density. To this end, we established the optimization model of mobile sensor network deployment and solved the model with chemical reaction optimization (CRO). The experimental results have shown that compared with traditional particle swarm optimization (PSO), CRO algorithm can achieve reasonable deployment more rapidly and enhance the network performance evaluation value effectively. The reasonable deployment of mobile sensor network node is very significant to information collecting, postperiod decision-making, and rapid rescuing work in emergencies.
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Palamakumbura, Romesh, Maarten Krabbendam, Katie Whitbread, and Christian Arnhardt. "Data acquisition by digitizing 2-D fracture networks and topographic lineaments in geographic information systems: further development and applications." Solid Earth 11, no. 5 (September 4, 2020): 1731–46. http://dx.doi.org/10.5194/se-11-1731-2020.
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Abstract. Understanding the impact of fracture networks on rock mass properties is an essential part of a wide range of applications in geosciences from understanding permeability of groundwater aquifers and hydrocarbon reservoirs to erodibility properties and slope stability of rock masses for geotechnical engineering. However, gathering high-quality, oriented-fracture datasets in the field can be difficult and time-consuming, for example, due to constraints on field work time or access (e.g. cliffs). Therefore, a method for obtaining accurate, quantitative fracture data from photographs is a significant benefit. In this paper we describe a method for generating a series of digital fracture traces in a geographic information system (GIS) environment, in which spatial analysis of a fracture network can be carried out. The method is not meant to replace the gathering of data in the field but to be used in conjunction with it, and it is well suited when field work time is limited or when the section cannot be accessed directly. The basis of the method is the generation of the vector dataset (shapefile) of a fracture network from a georeferenced photograph of an outcrop in a GIS environment. From that shapefile, key parameters such as fracture density and orientation can be calculated. Furthermore, in the GIS environment more complex spatial calculations and graphical plots can be carried out such as heat maps of fracture density. Advantages and limitations compared to other fracture network capture methods are discussed.
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Krishnaswamy, Smita, Matthew H. Spitzer, Michael Mingueneau, Sean C. Bendall, Oren Litvin, Erica Stone, Dana Pe’er, and Garry P. Nolan. "Conditional density-based analysis of T cell signaling in single-cell data." Science 346, no. 6213 (October 23, 2014): 1250689. http://dx.doi.org/10.1126/science.1250689.
Повний текст джерелаАнотація:
Cellular circuits sense the environment, process signals, and compute decisions using networks of interacting proteins. To model such a system, the abundance of each activated protein species can be described as a stochastic function of the abundance of other proteins. High-dimensional single-cell technologies, such as mass cytometry, offer an opportunity to characterize signaling circuit-wide. However, the challenge of developing and applying computational approaches to interpret such complex data remains. Here, we developed computational methods, based on established statistical concepts, to characterize signaling network relationships by quantifying the strengths of network edges and deriving signaling response functions. In comparing signaling between naïve and antigen-exposed CD4+ T lymphocytes, we find that although these two cell subtypes had similarly wired networks, naïve cells transmitted more information along a key signaling cascade than did antigen-exposed cells. We validated our characterization on mice lacking the extracellular-regulated mitogen-activated protein kinase (MAPK) ERK2, which showed stronger influence of pERK on pS6 (phosphorylated-ribosomal protein S6), in naïve cells as compared with antigen-exposed cells, as predicted. We demonstrate that by using cell-to-cell variation inherent in single-cell data, we can derive response functions underlying molecular circuits and drive the understanding of how cells process signals.
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Rong, Yu, Zhong Zhuang, Zhengwei He, and Xuming Wang. "A Maritime Traffic Network Mining Method Based on Massive Trajectory Data." Electronics 11, no. 7 (March 23, 2022): 987. http://dx.doi.org/10.3390/electronics11070987.
Повний текст джерелаАнотація:
Intelligent ships are the future direction of maritime transportation. Route design and route planning of intelligent ships require high-precision, real-time maritime traffic network information, which changes dynamically as the traffic environment changes. At present, there is a lack of high-precision and accurate information extraction methods for maritime traffic networks. Based on the massive trajectory data of vessels, the adaptive waypoint extraction model (ANPG) is proposed to extract the critical waypoints on the traffic network, and the improved kernel density estimation method (KDE-T) is constructed to mine the spatial–temporal characteristics of marine lanes. Then, an automatic traffic network generation model (NNCM), based on the pix2pix network, is put forward to reconstruct the maritime traffic network. NNCM has been tested on the historical trajectory data of Humen waters and Dongping waters in China, the experimental results show that the NNCM model improves the extraction accuracy by 13% and 33% compared to the geometric analysis method and density clustering method. It is of great significance to improve the navigation accuracy of intelligent ships. This method can also provide important technical support for waterway design and monitoring and maritime traffic supervision.
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Deng, Changjian. "The Robustness Analysis of Wireless Sensor Networks under Uncertain Interference." Scientific World Journal 2013 (2013): 1–8. http://dx.doi.org/10.1155/2013/185970.
Повний текст джерелаАнотація:
Based on the complex network theory, robustness analysis of condition monitoring wireless sensor network under uncertain interference is present. In the evolution of the topology of sensor networks, the density weighted algebraic connectivity is taken into account, and the phenomenon of removing and repairing the link and node in the network is discussed. Numerical simulation is conducted to explore algebraic connectivity characteristics and network robustness performance. It is found that nodes density has the effect on algebraic connectivity distribution in the random graph model; high density nodes carry more connections, use more throughputs, and may be more unreliable. Moreover, the results show that, when network should be more error tolerant or robust by repairing nodes or adding new nodes, the network should be better clustered in median and high scale wireless sensor networks and be meshing topology in small scale networks.
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Zhao, Jun. "Research on Wireless Sensor Network in Aquaculture." Applied Mechanics and Materials 686 (October 2014): 397–401. http://dx.doi.org/10.4028/www.scientific.net/amm.686.397.
Повний текст джерелаАнотація:
The paper design intelligent monitoring system of aquaculture based on CC2530 wireless sensor networks, combined with the actual situation, takes the tilapia as an example to analyze detailed of the process in intelligent high density culture. At the same time, the paper introduced each function module of aquaculture for the intelligent monitoring system and formulate control standard according to the aquatic products in different growth stages of demand, through the real-time monitoring of aquaculture environment, measured the standard parameter setting of parameters and the system automatically adjusts the aquaculture environment comparison. The test results show that the temperature error is in the range of 0.5°C, dissolved oxygen amount of error is in the range of 0.3mg/L, the error of pH value is within 0.3, system data transmission correct rate is more than 98%.
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J Elias, Shamsul, M. N. M. Warip, M. Elshaikh, M. Yusof Darus, and R. Badlishah Ahmad. "802.11p Optimization for Delay Sensitive in Non-Safety Messages in VANETs." Indonesian Journal of Electrical Engineering and Computer Science 12, no. 1 (October 1, 2018): 201. http://dx.doi.org/10.11591/ijeecs.v12.i1.pp201-207.
Повний текст джерелаАнотація:
<span>Vehicle density and high vehicle mobility are variables that measured the performance of Vehicular Ad Hoc Network (VANET) in unpredictable traffic data transmission environment. This paper is focused on non-safety messages transmission mainly for delay in time in test-bed simulation environment. Network optimization is an approach to evaluate the existing congestion control protocols and other network parameters for outlining a newly enhanced congestion control protocols. This paper presents a city and highway traffic data transmission scenarios for optimizing delay sensitivity utilizing the Taguchi method. The avareage data transmission on delay is performance indicator applying OMNeT++ simulation tools. The optimization process could be achieved once the best fit performance parameters are being identified. The best fit performance values could conclude the optimal and efficient congestion control networks. The packet sizes are the main control factors for this test-bed experiment focusing on non-safety messages which are delay sensitive.</span>
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Al-Absi, Mohammed Abdulhakim, Ahmed Abdulhakim Al-Absi, TaeYong Kim, and Hoon Jae Lee. "An environmental channel throughput and radio propagation modeling for vehicle-to-vehicle communication." International Journal of Distributed Sensor Networks 14, no. 4 (April 2018): 155014771877253. http://dx.doi.org/10.1177/1550147718772535.
Повний текст джерелаАнотація:
Developing a secure and smart intelligent transport system for both safety and non-safety application services requires a certain guarantee of network performance, especially in terms of throughput and packet collision performance. The vehicular ad hoc network propagation is strongly affected due to varying nature of the environment. The existing radio propagation path loss models are designed by using mean additional attenuation sophisticated fading models. However, these models do not consider the obstacle caused due to the obstacle of the vehicle in line of sight of the transmitting and receiving vehicle. Thus, the attenuation signal at the receiving vehicles/devices is affected. To address this issue, we present an obstacle-based radio propagation model that considers the effect caused due to the presence of obstructing vehicle in line of sight. This model is evaluated under different environmental conditions (i.e. city, highway, and rural) by varying the speed of vehicles and vehicles’ density. The performance of the model is evaluated in terms of throughput, collision, transmission efficiency, and packet delivery ratio. The overall result shows that the proposed obstacle-based throughput model is efficient considering varied speed and density. For instance, in the city environment, the model achieves an average improvement of 9.98% and 25.02% for throughput performance over other environments by varying the speed and density of devices respectively and an improvement of 15.04% for packet delivery ratio performance over other environments considering varied speed of devices.
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Liu, Ping. "Information Dissemination Mechanism Based on Cloud Computing Cross-Media Public Opinion Network Environment." International Journal of Information Technologies and Systems Approach 14, no. 2 (July 2021): 70–83. http://dx.doi.org/10.4018/ijitsa.2021070105.
Повний текст джерелаАнотація:
As an important expression of social public opinion, network public opinion develops rapidly with the popularization of the internet and then affects the real society. Therefore, the use of computer technology to study the network public opinion information transmission mechanism has strong practical significance. The purpose of this paper is to use cloud computing to realize the research of information dissemination mechanism in the context of cross-media public opinion network. Researched from three aspects of operator supervision, number of media, and user density, the hotspot propagation mechanism of Storm platform given in this paper can solve the efficiency problems of traditional algorithms while ensuring accuracy, improve efficiency, and lay the foundation for the research on the monitoring of Internet public opinion propagation.
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Ahmed, Afaz Uddin, Mohammad Tariqul Islam, Mahamod Ismail, and Mohammad Ghanbarisabagh. "Dynamic Resource Allocation in Hybrid Access Femtocell Network." Scientific World Journal 2014 (2014): 1–7. http://dx.doi.org/10.1155/2014/539720.
Повний текст джерелаАнотація:
Intercell interference is one of the most challenging issues in femtocell deployment under the coverage of existing macrocell. Allocation of resources between femtocell and macrocell is essential to counter the effects of interference in dense femtocell networks. Advances in resource management strategies have improved the control mechanism for interference reduction at lower node density, but most of them are ineffective at higher node density. In this paper, a dynamic resource allocation management algorithm (DRAMA) for spectrum shared hybrid access OFDMA femtocell network is proposed. To reduce the macro-femto-tier interference and to improve the quality of service, the proposed algorithm features a dynamic resource allocation scheme by controlling them both centrally and locally. The proposed scheme focuses on Femtocell Access Point (FAP) owners’ satisfaction and allows maximum utilization of available resources based on congestion in the network. A simulation environment is developed to study the quantitative performance of DRAMA in hybrid access-control femtocell network and compare it to closed and open access mechanisms. The performance analysis shows that higher number of random users gets connected to the FAP without compromising FAP owners’ satisfaction allowing the macrocell to offload a large number of users in a dense heterogeneous network.
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Tang, Kunhao, Sanhua Zhang, and Youlong Wu. "Optimization and control of fuel cell thermal management system based on neural network." Thermal Science 25, no. 4 Part B (2021): 2933–39. http://dx.doi.org/10.2298/tsci2104933t.
Повний текст джерелаАнотація:
Aiming at the direct methanol fuel cell system is too complicated, difficult to model, and the thermal management system needs to be optimized. The article attempts to bypass the internal complexity of direct methanol fuel cell, based on experimental data, use neural networks to approximate arbitrarily complex non-linear functions ability to apply neural network identification methods to direct methanol fuel cell, a highly non-linear thermal management system optimization modelling. The paper uses 1000 sets of battery voltage and current density experimental data as training samples and uses an improved back propagation neural network to establish a battery voltage-current density dynamic response model at different temperatures. The simulation results show that this method is feasible, and the established model has high accuracy. It makes it possible to design the real-time controller of the direct methanol fuel cell and optimize the thermal energy manage?ment system?s efficiency.
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Vavilov, Viacheslav. "Investigation of random access computer networks operating in a diffusion environment with an increasing number of subscriber stations." Программные системы и вычислительные методы, no. 2 (February 2020): 8–21. http://dx.doi.org/10.7256/2454-0714.2020.2.29170.
Повний текст джерелаАнотація:
Improving the performance of various types of communication networks in the modern world remains an urgent task, in connection with which research is underway to create hardware that expands the throughput of physical channels, new network protocols are being developed and existing network protocols are being modified, mathematical and computer modeling of data transmission mechanisms in communication networks is being carried out. The speed and reliability of data transmission over networks also depends on a number of factors, the nature of the influence of which is random. The combination of such factors is called a random environment. If the change in the states of the medium is continuous, then we speak of a diffusion medium. The object of the research is communication networks controlled by multiple access protocols and functioning in a random (diffusion) environment. The research tool for multiple access networks is the mathematical apparatus of the theory of finite-difference and differential equations, the theory of random processes and the theory of queuing. The proposed mathematical model of communication networks in a diffusion environment is investigated by an asymptotic method. The scientific novelty of the work lies in the fact that for the first time a mathematical model of a multiple access network operating in a diffusion environment was proposed and an asymptotic study was carried out. The asymptotic average of the normalized number of claims in the orbit (the source of repeated calls) and the deviation from this average are found, and the probability density of the values of the process of changing the number of claims in the orbit is obtained.
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Wei, Kaibin. "The Intelligent Remote Control System Based on the Wireless Sensor Network." International Journal of Online Engineering (iJOE) 12, no. 02 (February 29, 2016): 51. http://dx.doi.org/10.3991/ijoe.v12i02.5048.
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Remote control system is mainly used for industrial applications, such as the wireless control of factory equipment, and monitor factory environment parameters, like temperature, humidity, light intensity. This paper explores the current development of wireless sensor network (WSN) , and then this paper aim to construct an overall architecture of the remote control system on the basis of RS485 platform, and analyze and design the intelligent remote control system. Finally by testing the system, it prove to meet the specific needs of factory environment parameters monitoring. The system can achieve all kinds of physical parameter monitoring requirement from a remote device, such as humidity and light density. This remote control system based on the wireless sensor network provide a safety monitoring environment to operators.
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Reese, Laura A., and Xiaomeng Li. "Change in Service Provision Networks: The Case of Animal Welfare Services." State and Local Government Review 53, no. 1 (March 2021): 14–42. http://dx.doi.org/10.1177/0160323x211009285.
Повний текст джерелаАнотація:
This research focuses on change within informal service provision networks, specifically examining the impact that changes within a key organization can have on the larger network. Employing a before and after survey design with a treatment at the midpoint and participant observation, it asks: What is the impact of a major change within one organization on the larger external network? What is the nature of the organizational ties? and, How do political factors exogenous to the network impact the network evolution process? The findings suggest that internal change within a focal actor can have ripple effects throughout the network increasing density. Public service provision at the local level can be enhanced through an increase in partnerships between the public and nonprofit sectors. However, network evolution can be limited by the larger political environment and lack of a coordinating role on the part of local government.
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Rivera, Redden Rose, and Allan Soriano. "Prediction of Density and Speed of Sound of Binary Ionic Liquid and Ketone Mixtures Using Artificial Neural Network." E3S Web of Conferences 120 (2019): 01003. http://dx.doi.org/10.1051/e3sconf/201912001003.
Повний текст джерелаАнотація:
The applications of ionic liquids solve a lot of major problems regarding green energy production and environment. Ionic liquids are solvents used as alternative to unfriendly traditional and hazardous solvents which reduces the negative impact to environment to a great extent. This study produced models to predict two of the basic physical properties of binary ionic liquid and ketone mixtures: density and speed of sound. The artificial neural network algorithm was used to predict these properties by varying the temperature, mole fraction, atom count in cation, methyl group count in cation, atom count in anion, hydrogen atom count in anion of ionic liquid and atom count in ketone. Total experimental data points of 2517 for density and 947 for speed of sound were used to train the algorithm and to test the network obtained. The optimum neural network structure determined for density and speed of sound of binary ionic liquid and ketone mixtures were 7-9-9-1 and 7-7-4-1 respectively; overall average percentage error of 2.45% and 2.17% respectively; and mean absolute error of 28.21 kg/m3 and 33.91 m/s respectively. The said algorithm was found applicable for the prediction of density and speed of sound of binary ionic liquid and ketone mixtures.
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Wang, Hao, and Tarek A. Elgohary. "A Simple and Accurate Apollo-Trained Neural Network Controller for Mars Atmospheric Entry." International Journal of Aerospace Engineering 2020 (September 9, 2020): 1–15. http://dx.doi.org/10.1155/2020/3793740.
Повний текст джерелаАнотація:
We present a new method to design the controller for Mars capsule atmospheric entry using deep neural networks and flight-proven Apollo entry data. The controller is trained to modulate the bank angle with data from the Apollo entry simulations. The neural network controller reproduces the classical Apollo results over a variation of entry state initial conditions. Compared to the Apollo controller as a baseline, the present approach achieves the same level of accuracy for both linear and nonlinear entry dynamics. The Apollo-trained controller is then applied to Mars entry missions. As in Earth environment, the controller achieves the desired level of accuracy for Mars missions using both linear and nonlinear entry dynamics with higher uncertainties in the entry states and the atmospheric density. The deep neural network is only trained with data from Apollo reentry simulation in an Earth model and works in both Earth and Mars environments. It achieves the desired landing accuracy for a Mars capsule. This method works with both linear and nonlinear integration and can generate the bank angle commands in real-time without a prestored trajectory.
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Wang, Fangshu, Shuai Wang, Xinzheng Niu, Jiahui Zhu, and Ting Chen. "Grid-Based Whole Trajectory Clustering in Road Networks Environment." Wireless Communications and Mobile Computing 2021 (November 24, 2021): 1–20. http://dx.doi.org/10.1155/2021/5295784.
Повний текст джерелаАнотація:
In the data mining of road networks, trajectory clustering of moving objects plays an important role in many applications. Most existing algorithms for this problem are based on every position point in a trajectory and face a significant challenge in dealing with complex and length-varying trajectories. This paper proposes a grid-based whole trajectory clustering model (GBWTC) in road networks, which regards the trajectory as a whole. In this model, we first propose a trajectory mapping algorithm based on grid estimation, which transforms the trajectories in road network space into grid sequences in grid space and forms grid trajectories by recognizing and eliminating redundant, abnormal, and stranded information of grid sequences. We then design an algorithm to extract initial clustering centers based on density weight and improve a shape similarity measuring algorithm to measure the distance between two grid trajectories. Finally, we dynamically allocate every grid trajectory to the best clusters by the nearest neighbor principle and an outlier function. For the evaluation of clustering performance, we establish a clustering criterion based on the classical Silhouette Coefficient to maximize intercluster separation and intracluster homogeneity. The clustering accuracy and performance superiority of the proposed algorithm are illustrated on a real-world dataset in comparison with existing algorithms.
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Marqués-Sánchez, Pilar, Isaías García-Rodríguez, José Alberto Benítez-Andrades, Iván Fulgueiras-Carril, Patricia Fernández-Sierra, and Elena Fernández-Martínez. "Networks and Emotions in Cooperative Work: A Quasi-Experimental Study in University Nursing and Computer Engineering Students." Healthcare 8, no. 3 (July 20, 2020): 220. http://dx.doi.org/10.3390/healthcare8030220.
Повний текст джерелаАнотація:
University students establish networks that impact on their behavior. Social Network Analysis (SNA) allows us to analyze the reticular structures formed and find patterns of interaction between university students. The main objective of this study was to observe the impact of interdisciplinary collaborative work between nursing and computer engineering students on the collaboration and friendship networks, emotions and performance of the participants. It is a quasi-experimental descriptive study with pre- and post-intervention measurements. The contact networks analyzed showed an increase in density in the post-intervention period. The most central people in the network corresponded with those who considered positive emotions most in their academic environment, while the less central people coincided with those who highlighted negative emotions. Academic performance was only significantly associated in the collaboration network, between this and OutdegreeN. This study shows the impact of interdisciplinary activities on teaching methodologies and the repercussions of emotions on curricular activity.
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Gadde, Nagaraja, Basavaraj Jakkali, Ramesh Babu Halasinanagenahalli Siddamallaih, and Gowrishankar Gowrishankar. "Quality of experience aware network selection model for service provisioning in heterogeneous network." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 2 (April 1, 2022): 1839. http://dx.doi.org/10.11591/ijece.v12i2.pp1839-1848.
Повний текст джерелаАнотація:
Heterogeneous wireless networks (HWNs) are capable of integrating the different radio access technologies that make it possible to connect mobile users based on the performance parameters. Further quality of service (QoS) is one of the major topics for HWNs, moreover existing radio access technology (RAT) methodology are designed to provide network QoS criteria. However, limited work has been carried out for the RAT selection mechanism considering user QoS preference and existing models are developed based on the multi-mode terminal under a given minimal density network. For overcoming research issues this paper present quality of experience (QoE) RAT (QOE-RAT) selection methodology, incorporating both network performance criteria and user preference considering multiple call and multi-mode HWNs environment. First, this paper presents fuzzy preference aware weight (FPAW) and multi-mode terminal preference aware TOPSIS (MMTPA-TOPSIS) for choosing the best RAT for gaining multi-services. Experiment outcomes show the QOE-RAT selection method achieves much superior packet transmission outcomes when compared with state-of-art Rat selection methodologies.
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Singh, Ankit, Smriti Mahajan, and Devika Shobhana. "Caught in the web: A tale of filament galaxies." Proceedings of the International Astronomical Union 15, S341 (November 2019): 304–6. http://dx.doi.org/10.1017/s1743921319001406.
Повний текст джерелаАнотація:
AbstractThe Coma supercluster is one of the largest, nearby (∼100h−1Mpc) gravitationally bound structures known in the universe. It comprises two large clusters of galaxies and several galaxy groups intersected by a complex network of filaments, providing the perfect laboratory for studying the evolution of galaxies in a range of ‘continuous’ environments. We characterised the different components of the environment to study the properties of galaxies in the optical and ultraviolet (UV) wavebands. Our analysis shows that galaxies experience accelerated evolution as they approach the spine of the filament, suggesting that the intermediate-density environment prevalent in the filaments can accelerate the evolution of galaxies.