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Journal articles on the topic 'Selection network (SN)'

Author: Grafiati

Published: 14 March 2023

Last updated: 31 July 2025

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1

Di Tella, Sonia, Matteo De Marco, Isabella Anzuino, Davide Quaranta, Francesca Baglio, and Maria Caterina Silveri. "The Contribution of Cognitive Control Networks in Word Selection Processing in Parkinson’s Disease: Novel Insights from a Functional Connectivity Study." Brain Sciences 14, no. 9 (2024): 913. http://dx.doi.org/10.3390/brainsci14090913.

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Parkinson’s disease (PD) patients are impaired in word production when the word has to be selected among competing alternatives requiring higher attentional resources. In PD, word selection processes are correlated with the structural integrity of the inferior frontal gyrus, which is critical for response selection, and the uncinate fasciculus, which is necessary for processing lexical information. In early PD, we investigated the role of the main cognitive large-scale networks, namely the salience network (SN), the central executive networks (CENs), and the default mode network (DMN), in word

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Mesodiakaki, Agapi, Ferrán Adelantado, Luis Alonso, and Christos Verikoukis. "Performance Analysis of a Cognitive Radio Contention-Aware Channel Selection Algorithm." IEEE Transactions on Vehicular Technologies 64, no. 5 (2015): 1958–72. https://doi.org/10.1109/TVT.2014.2341115.

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In cognitive radio (CR) networks, due to the ever increasing traffic demands and the limited spectrum resources, it is very likely for several secondary networks (SNs) to coexist and opportunistically use the same primary user (PU) resources. In such scenarios, the ability to distinguish whether a licensed channel is occupied by a PU or by other SNs can significantly improve the spectrum efficiency of the network, while the contention among the SNs already operating on licensed channels with no PU activity may further affect its throughput and energy efficiency. Therefore, the proper selection

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Höfinger, Gerhard, and Stefan Brunner. "Network-based Simulation in Water Construction – a Flexible Tool for Equipment Selection." SNE Simulation Notes Europe 26, no. 1 (2016): 55–58. http://dx.doi.org/10.11128/sne.26.sn.10329.

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Zakariyya, Aliyu, Umar Iliyasu, and Bashir Ahmad Jamilu. "Optimal selection of cluster head in wireless sensor networks using particle swarm optimization (PSO)." Dutse Journal of Pure and Applied Sciences 9, no. 3a (2023): 226–36. http://dx.doi.org/10.4314/dujopas.v9i3a.23.

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In a wide range of applications, such as the military, healthcare, and environmental monitoring, wireless sensor networks (WSNs) have emerged as a key player. Cluster-based WSNs are a viable method for enhancing the life of the sensor network. Choosing the proper cluster head for wireless sensor networks (WSNs) is a key undertaking that affects the network's performance. Current approaches for selecting the cluster head have a number of drawbacks, such as nodes dying too quickly, uneven energy utilization, and shorter network lifespan. Additionally, conventional techniques like fixed Cluster H

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Karchev, Konstantin, and Roberto Trotta. "STAR NRE: solving supernova selection effects with set-based truncated auto-regressive neural ratio estimation." Journal of Cosmology and Astroparticle Physics 2025, no. 07 (2025): 031. https://doi.org/10.1088/1475-7516/2025/07/031.

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Abstract Accounting for selection effects in supernova type Ia (SN Ia) cosmology is crucial for unbiased cosmological parameter inference — even more so for the next generation of large, mostly photometric-only surveys. The conventional “bias correction” procedure has a built-in systematic bias towards the fiducial model used to derive it and fails to account for the additional Eddington bias that arises in the presence of significant redshift uncertainty. On the other hand, likelihood-based analyses within a Bayesian hierarchical model, e.g. using MCMC, scale poorly with the data set size and

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Deepa, C., B. Latha, and I. Jenish. "Development and Performance Evaluation of a New Energy-Efficient Double Cluster-Head Routing (EEDCR) Protocol for Wireless Sensor Networks." Wireless Communications and Mobile Computing 2022 (June 21, 2022): 1–13. http://dx.doi.org/10.1155/2022/5041153.

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Utilization of energy and the lifetime increment are the big issues in designing of routing algorithms for wireless sensor networks (WSNs). Many routing algorithms have been developed by various researchers to achieve energy efficiency and to improve the lifetime of the network. But, the way to route the information from the sensor node (SN) to the base station (BS) and vice versa is an important issue, because of resource constraints. In this paper, we have proposed a low energy consumed, cluster-based routing protocol named an energy-efficient and double cluster-head routing (EEDCR) protocol

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Nasimifar, Mahdi, Senthilmurugan Thyagarajan, Sarah Chaudhari, and Nadarajah Sivaneswaran. "Pavement Structural Capacity from Traffic Speed Deflectometer for Network Level Pavement Management System Application." Transportation Research Record: Journal of the Transportation Research Board 2673, no. 2 (2019): 456–65. http://dx.doi.org/10.1177/0361198118825122.

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Structural number (SN) represents the structural capacity of a flexible pavement system to sustain anticipated traffic and is among the structural indices most commonly used by pavement design engineers in the U.S. Effective structural number (SNeff) is an indicator of structural capacity of in-service pavement sections and is conventionally estimated from nondestructive testing (NDT) device data such as falling weight deflectometers (FWDs) using methods such as suggested by AASHTO. In addition to pavement design, structural condition is a critical input for the selection of maintenance and re

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He, Yixin, Daosen Zhai, Dawei Wang, Xiao Tang, and Ruonan Zhang. "A Relay Selection Protocol for UAV-Assisted VANETs." Applied Sciences 10, no. 23 (2020): 8762. http://dx.doi.org/10.3390/app10238762.

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In this paper, we investigate the relay selection problem for the unmanned aerial vehicle (UAV)-assisted vehicular ad-hoc networks (VANETs). For the considered network, we first model and analyze the link quality of service (LQoS) from the source node (SN) to the neighbor node and the node forward capacity (NFC) from the neighbor node to the destination node (DN). Then, the relay selection problem is formulated as a multi-objective optimization problem by jointly considering the LQoS and the NFC. Afterward, we decompose the problem into two subproblems and propose a relay selection protocol wi

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Xiao, Xingxing, and Haining Huang. "A Clustering Routing Algorithm Based on Improved Ant Colony Optimization Algorithms for Underwater Wireless Sensor Networks." Algorithms 13, no. 10 (2020): 250. http://dx.doi.org/10.3390/a13100250.

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Because of the complicated underwater environment, the efficiency of data transmission from underwater sensor nodes to a sink node (SN) is faced with great challenges. Aiming at the problem of energy consumption in underwater wireless sensor networks (UWSNs), this paper proposes an energy-efficient clustering routing algorithm based on an improved ant colony optimization (ACO) algorithm. In clustering routing algorithms, the network is divided into many clusters, and each cluster consists of one cluster head node (CHN) and several cluster member nodes (CMNs). This paper optimizes the CHN selec

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D. Mohanapriya. "Gaussian Distributive Clustering Based Multi-Objective Truncated Grasshopper Optimal Path Selection for Energy Efficient Routing in WSN." Journal of Information Systems Engineering and Management 10, no. 44s (2025): 911–29. https://doi.org/10.52783/jisem.v10i44s.8689.

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WSN is network that contain numerous SN deployed within a specific region for sensing and collecting data as well as transmitting to the BS. WSNs consistently face challenges in delivering the information to the base station with minimal delay, energy utilization, and packet loss. Energy efficiency is also considered one of the major issues in the WSNs through the routing process. An efficient routing protocol is required to mention these constraints as well as enhance effectiveness of WSNs. Motivated by these challenges, a Gaussian Distributive Clustering-based Multi-Objective Truncated Grass

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Pise, Anil Audumbar, Byungun Yoon, Saurabh Singh, and Jude Imuede. "Dodecagonal Parameter-Based Energy-Efficient Routing in Wireless Sensor Networks." Journal of High-Frequency Communication Technologies 2, no. 03 (2024): 186–200. http://dx.doi.org/10.58399/nvdh415.

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Wireless Sensor Networks (WSNs) are composed of several sensor nodes (SN) that are dispersed geographically and interact with one another over wireless media in order to track and log physical data from their environment. At the moment, WSNs frequently use routing and clustering strategies to extend the life of their networks. This paper proposes a DODECAGONAL parameter-based Energy-Efficient Routing in WSN (DOPE-WSN) for improvement of network lifetime and saving the energy consumption. Initially the cluster is selected using Agglomerative clustering. In the second phase, Pelican optimization

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Pise, Anil Audumbar, Byungun Yoon, Saurabh Singh, and Jude Imuede. "Dodecagonal Parameter-Based Energy-Efficient Routing in Wireless Sensor Networks." Journal of High-Frequency Communication Technologies 2, no. 03 (2024): 186–200. http://dx.doi.org/10.58399/nvdh4158.

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Wireless Sensor Networks (WSNs) are composed of several sensor nodes (SN) that are dispersed geographically and interact with one another over wireless media in order to track and log physical data from their environment. At the moment, WSNs frequently use routing and clustering strategies to extend the life of their networks. This paper proposes a DODECAGONAL parameter-based Energy-Efficient Routing in WSN (DOPE-WSN) for improvement of network lifetime and saving the energy consumption. Initially the cluster is selected using Agglomerative clustering. In the second phase, Pelican optimization

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Orlandi, Andrea, and Alice Mado Proverbio. "Left-Hemispheric Asymmetry for Object-Based Attention: an ERP Study." Brain Sciences 9, no. 11 (2019): 315. http://dx.doi.org/10.3390/brainsci9110315.

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It has been shown that selective attention enhances the activity in visual regions associated with stimulus processing. The left hemisphere seems to have a prominent role when non-spatial attention is directed towards specific stimulus features (e.g., color, spatial frequency). The present electrophysiological study investigated the time course and neural correlates of object-based attention, under the assumption of left-hemispheric asymmetry. Twenty-nine right-handed participants were presented with 3D graphic images representing the shapes of different object categories (wooden dummies, chai

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Lo, Serigne N., Jiawen Ma, Richard A. Scolyer, et al. "Improved Risk Prediction Calculator for Sentinel Node Positivity in Patients With Melanoma: The Melanoma Institute Australia Nomogram." Journal of Clinical Oncology 38, no. 24 (2020): 2719–27. http://dx.doi.org/10.1200/jco.19.02362.

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PURPOSE For patients with primary cutaneous melanoma, the risk of sentinel node (SN) metastasis varies according to several clinicopathologic parameters. Patient selection for SN biopsy can be assisted by National Comprehensive Cancer Network (NCCN) and ASCO/Society of Surgical Oncology (SSO) guidelines and the Memorial Sloan Kettering Cancer Center (MSKCC) online nomogram. We sought to develop an improved online risk calculator using alternative clinicopathologic parameters to more accurately predict SN positivity. PATIENTS AND METHODS Data from 3,477 patients with melanoma who underwent SN b

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Sambu Anitha, Et al. "Energy Aware Clustering System for Wireless Sensor Networks utilizing Rider Sunflower Optimization Approach." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 9 (2023): 1498–505. http://dx.doi.org/10.17762/ijritcc.v11i9.9131.

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Wireless Sensor Networks (WSN) are spatially disseminated sensors that are utilized for monitoring physical or environmental factors, like sound, temperature, pressure, and so on, to collectively drive their information from the networking to the base station. The WSN is composed of hundreds or thousands, where all the nodes are interconnected with other Sensor Node (SN). Clustering is the most popular topology management technique in WSN, grouping nodes to manage them or execute different tasks in a distributed manner, like resource management. It includes grouping sensors and selecting Clust

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Tsvetanov, Filip Atanasov, and Martin Pandurski. "Selection of Protocols for Integration of Sensory Data Networks in Cloud Structures." International Journal of Online and Biomedical Engineering (iJOE) 18, no. 09 (2022): 29–40. http://dx.doi.org/10.3991/ijoe.v18i09.31321.

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The striving to obtain more detailed information about the environment and control various processes leads to an increase in the number of connected sensor devices in various industrial areas. The collected large amount of data can be analysed in real-time. The sensors that build up the WSN have limited hardware resources and cannot process large amounts of data. The integration between WSN and cloud structures is an excellent method for storing, processing, accessing data via the Internet and solves the issue of the limited capacity of WSN. The big challenge to designing the WSN - cloud syste

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Antonio, Castrillo, Fasci Eugenio, Furtenbacher Tibor, et al. "On the 12C2H2 near-infrared spectrum: absolute transition frequencies and an improved spectroscopic network at the kHz accuracy level." Phys. Chem. Chem. Phys., 25 (September 26, 2023): 23614. https://doi.org/10.1039/d3cp01835k.

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Lamb dips of twenty lines in the P, Q, and R branches of the n1 + n3 + n4 1 vibrational band of 12C2H2, in the spectral window of 7125–7230 cm1, have been measured using an upgraded comb-calibrated frequency-stabilized cavity ring-down spectrometer, designed for extensive sub-Doppler measurements. Due to the large number of carefully executed Lamb-dip experiments, and to the extrapolation of absolute frequencies to zero pressure in each case, the combined average uncertainty of the measured line-center positions is 15 kHz (5 107 cm1) with a 2-s confidence level. Selection of the twenty l

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Uddin Ahmed Zihan, Zia, Mostafa A. Elseifi, Kevin Gaspard, and Zhongjie Zhang. "Development of a Structural Capacity Prediction Model Based on Traffic Speed Deflectometer Measurements." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 40 (2018): 315–25. http://dx.doi.org/10.1177/0361198118758058.

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The importance of incorporating pavement structural conditions in the selection of maintenance and rehabilitation strategies along with functional indices has been recognized by state agencies. To measure in-service pavement structural capacity, surface deflection under a defined load has been typically used. The traffic speed deflectometer (TSD) has emerged as a continuous deflection-measuring device as it operates at traffic speed and reduces lane closure and user delays. The present study developed a nonlinear regression model to predict pavement structural number (SN) based on surface defl

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S.Saritha. "A Cross-Layer-Routing Protocol with Malicious node detection using BiRNN in WSN." Communications on Applied Nonlinear Analysis 32, no. 8s (2025): 811–28. https://doi.org/10.52783/cana.v32.3824.

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A wireless sensor network (WSN) is a standalone device that consists of a discrete group of sensor nodes (SN) for information gathering, device monitoring, and environmental position sensing. The main challenge is to present an energy-efficient framework and conserve energy while building a route path alongside each sensor node at SN due to the limited energy resources available. Nonetheless, a great deal of energy-efficient methods concentrated heavily on energy harvesting and decreased energy usage, but they were unable to enable energy-efficient routing in WSNs with low energy usage. The re

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Chen, Haifeng, Zheqi Hu, Zhihong Ke, Yun Xu, Feng Bai, and Zhuo Liu. "Aberrant Multimodal Connectivity Pattern Involved in Default Mode Network and Limbic Network in Amyotrophic Lateral Sclerosis." Brain Sciences 13, no. 5 (2023): 803. http://dx.doi.org/10.3390/brainsci13050803.

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Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder that progressively affects bulbar and limb function. Despite increasing recognition of the disease as a multinetwork disorder characterized by aberrant structural and functional connectivity, its integrity agreement and its predictive value for disease diagnosis remain to be fully elucidated. In this study, we recruited 37 ALS patients and 25 healthy controls (HCs). High-resolution 3D T1-weighted imaging and resting-state functional magnetic resonance imaging were, respectively, applied to construct multimodal connectomes. Fol

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Narayan, Vipul, and A. K. Daniel. "CHOP: Maximum Coverage Optimization and Resolve Hole Healing Problem using Sleep and Wake-up Technique for WSN." ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal 11, no. 2 (2022): 159–78. http://dx.doi.org/10.14201/adcaij.27271.

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The Sensor Nodes (SN) play an important role in various hazardous applications environments such as military surveillance, forests, battlefield, etc. The Wireless Sensor Network (WSN) comprised multiple numbers of sensor nodes which are used to perform sensing the physical conditions and subsequently transmitting data to the Base Station (BS). The nodes have limited batteries. The random distribution of nodes in the hazardous areas causes overlapping of nodes and coverage hole issues in the network. The Coverage Optimization and Resolve Hole Healing (CHOP) Protocol is proposed to optimize the

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Sri Murugharaj B R, Shakthy B, Sabari L, and Kamaraj K. "Speech Based Emotion Recognition System." international journal of engineering technology and management sciences 7, no. 1 (2023): 332–37. http://dx.doi.org/10.46647/ijetms.2023.v07i01.050.

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Emotion reputation from speech alerts is a crucial yet difficult part of human-computer interaction (HCI). Several well-known speech assessment and type processes were employed in the literature on speech emotion reputation (SER) to extract emotions from warnings. Deep learning algorithms have recently been proposed as an alternative to conventional ones for SER. We develop a SER system that is totally based on exclusive classifiers and functions extraction techniques. Features from the speech alerts are utilised to train exclusive classifiers. To identify the broadest feasible appropriate cha

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Al-Mahdi, Hassan, Mohamed Elshrkawey, Shymaa Saad, and Safa Abdelaziz. "An Intelligent Energy-Efficient Data Routing Scheme for Wireless Sensor Networks Utilizing Mobile Sink." Wireless Communications and Mobile Computing 2024 (March 18, 2024): 1–20. http://dx.doi.org/10.1155/2024/7384537.

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Data collection and energy consumption are critical concerns in Wireless sensor networks (WSNs). To address these issues, both clustering and routing algorithms are utilized. Therefore, this paper proposes an intelligent energy-efficient data routing scheme for WSNs utilizing a mobile sink (MS) to save energy and prolong network lifetime. The proposed scheme operates in two major modes: configure and operational modes. During the configure mode, a novel clustering mechanism is applied once, and a prescheduling cluster head (CH) selection is introduced to ensure uniform energy expenditure among

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Alromema, Nashwan, Hussnain Arshad, Sharaf J. Malebary, Faisal Binzagr, and Yaser Daanial Khan. "PhageVir: An evaluation of computational intelligence models for the precise identification of phage virion proteins." International Journal of ADVANCED AND APPLIED SCIENCES 12, no. 5 (2025): 129–47. https://doi.org/10.21833/ijaas.2025.05.013.

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This study presents PhageVir, an enhanced computational model developed to predict Phage Virion Proteins (PVPs), which are essential for bacteriophage infection and replication. PhageVir integrates advanced feature selection methods, including the Position Relative Incidence Matrix (PRIM) and the Reverse Position Relative Incidence Matrix (RPRIM), to effectively capture key sequence features and positional dependencies within protein sequences. Several machine learning and deep learning algorithms were employed, including LightGBM, Random Forest, Convolutional Neural Network (CNN), Long Short-

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Qu, Helen, and Masao Sako. "Photo-zSNthesis: Converting Type Ia Supernova Lightcurves to Redshift Estimates via Deep Learning." Astrophysical Journal 954, no. 2 (2023): 201. http://dx.doi.org/10.3847/1538-4357/aceafa.

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Abstract Upcoming photometric surveys will discover tens of thousands of Type Ia supernovae (SNe Ia), vastly outpacing the capacity of our spectroscopic resources. In order to maximize the scientific return of these observations in the absence of spectroscopic information, we must accurately extract key parameters, such as SN redshifts, with photometric information alone. We present Photo-zSNthesis, a convolutional neural network-based method for predicting full redshift probability distributions from multi-band supernova lightcurves, tested on both simulated Sloan Digital Sky Survey (SDSS) an

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Balister, Paul, Béla Bollobás, Amites Sarkar, and Mark Walters. "Sentry Selection in Wireless Networks." Advances in Applied Probability 42, no. 1 (2010): 1–25. http://dx.doi.org/10.1239/aap/1269611141.

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Let be a Poisson process of intensity one in the infinite plane ℝ2. We surround each point x of by the open disc of radius r centred at x. Now let Sn be a fixed disc of area n, and let Cr(Sn) be the set of discs which intersect Sn. Write Erk for the event that Cr(Sn) is a k-cover of Sn, and Frk for the event that Cr(Sn) may be partitioned into k disjoint single covers of Sn. We prove that P(Erk ∖ Frk) ≤ ck / logn, and that this result is best possible. We also give improved estimates for P(Erk). Finally, we study the obstructions to k-partitionability in more detail. As part of this study, we

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Natesan, Sathishkumar, and Rajakumar Krishnan. "FLCEER." International Journal of Information Technology and Web Engineering 15, no. 3 (2020): 76–101. http://dx.doi.org/10.4018/ijitwe.2020070105.

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Underwater acoustic sensor networks (UASN) play a crucial role in various applications such as tsunami detection, surveillance of the ocean by the defense department, monitoring offshore oil, and identifying gas basins underwater. UASNs can be one of the supporting infrastructures for the Internet of Things (IoT). UASNs have the problems of long latency, high bit error rate, and low bandwidth. These pose various challenges such as high consumption of energy, low reliability, low packet retransmission, and high delay for UASNs. To overcome the shortcomings mentioned above, various approaches ar

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Eltagy, Louay, Alex O'Neill-Kerr, and Nadia Hristova. "Using Qualitative-Electroencephalogram (Q-EEG) Mapping to Aid the Selection of Suitable Areas to Target Repetitive Transcranial Magnetic Stimulation (rTMS) Treatment in a Case of Depression With Comorbid Obsessive Compulsive Disorder (OCD)." BJPsych Open 8, S1 (2022): S4. http://dx.doi.org/10.1192/bjo.2022.82.

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AimsWe present the case of SN, a 25-year-old woman with diagnosis of anorexia nervosa, OCD, Generalized Anxiety Disorder (GAD) and depression. She has extensive history of contact with mental health services spanning more than 10 years. She has had 1 inpatient stay in an eating disorders unit lasting more than 6 months. Her treatment included various classes of medications, psychological therapy and social prescribing with little or no benefit. She has been referred to rTMS. The aims of the study are to determine the effect of rTMS in treatment of a patient with depression comorbid with OCD, u

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Borysov, O. "Scientific Publications’ Bibliometric Analysis of Application-Level TCP/IP Models’ Communication Protocols for the Internet of Things." Visnyk of Kharkiv State Academy of Culture, no. 66 (December 26, 2024): 17–25. https://doi.org/10.31516/2410-5333.066.02.

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A bibliometric analysis of publications on application-layer communication protocols in the context of the Internet of Things technologies have been conducted. The study highlights significant disparities in scientific attention given to various protocols, emphasizing the dominance of MQTT and CoAP in the scientific literature. Data from the Scopus bibliometric database were used to evaluate the level of research activity and the scientific community’s interest in MQTT, MQTT-SN, CoAP, STOMP, XMPP, WAMP, AMQP, DDS, OPC UA, and LwM2M protocols. The findings reveal which protocols are at the fore

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ZAWODNIAK, Józef J., Wiesław PIEKARSKI, and Mirosław GLISZCZYŃSKI. "Principles of Selection Surge Protection Device (SPD) in Medium Voltage Networks." AUTOMATYKA, ELEKTRYKA, ZAKLOCENIA 11, no. 1(39)2020 (2020): 44–53. http://dx.doi.org/10.17274/aez.2020.39.03.

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Maurya, Sandeep Kumar, Hyeondong Kim, and Sang Yeol Lee. "Amorphous Si-Zn-Sn-O/Si-in-Zn-O Bilayer Transistors with P(VDF-TrFE) for Synaptic Integration in Neuromorphic Systems." ECS Meeting Abstracts MA2024-02, no. 40 (2024): 5003. https://doi.org/10.1149/ma2024-02405003mtgabs.

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Synaptic devices, such as memristors and transistors, are at the forefront of neuromorphic computing, designed to replicate the complex functions of the human brain. Unlike traditional computing systems (von Neumann architecture) that rely on the sequential processing, these synaptic devices excel in performing highly efficient parallel computations. This makes them particularly well-suited for tasks that require vast amounts of data processing, similar to how the brain processes information. Field-effect transistors (FETs), in particular, offer significant advantages in emulating synaptic beh

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Ren, Qian, and Guangshun Yao. "An Energy-Efficient Cluster Head Selection Scheme for Energy-Harvesting Wireless Sensor Networks." Sensors 20, no. 1 (2019): 187. http://dx.doi.org/10.3390/s20010187.

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Concerning the large amount of energy consumption during the cluster head selection stage and the unequal harvested energy among nodes in energy-harvesting wireless sensor networks (EH-WSNs), an energy- efficient cluster head selection scheme called EECHS is proposed in this paper. The scheme divides all nodes from one cluster into three types: cluster head (CH), cluster member (CM), and scheduling node (SN). The SN is designed to monitor and store real-time information about the residual energy of all nodes, including CMs and the CH, in the same cluster. In the CH selection stage, the SN spec

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Ali, Syed Asif, Mubashar Sarfraz, Sajjad A. Ghauri, et al. "A Weighted Cluster Head Selection Algorithm for Energy Efficient Wireless Sensor Networks." Journal of Sensors 2022 (May 6, 2022): 1–13. http://dx.doi.org/10.1155/2022/3055178.

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The wireless sensor network’s (WSNs) lifetime is mainly dependent on the RE of the sensor nodes (SeN). In recent years, energy minimization in a WSN has been a prominent research topic, and numerous solutions have been proposed. This research focuses on the energy minimization of the SeNs where firstly, K-medoid clustering algorithm is applied to create clusters. Second, a weighted cluster head selection technique is used to choose a cluster head (CH) by integrating three independent weights associated with an SeN: energy, distance from the centroid, and distance from the sink node (SN). Accor

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Jain, Khushboo, Anoop Kumar, and Vaibhav Vyas. "A Resilient Steady Clustering Technique for Sensor Networks." International Journal of Applied Evolutionary Computation 11, no. 4 (2020): 1–12. http://dx.doi.org/10.4018/ijaec.2020100101.

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In wireless sensor networks (WSNs), each sensor node is proficient to transmit data packets dynamically deprived of any constraint of fixed infrastructure. Sensor nodes (SNs) intermittently travels within the network from one cluster to another, which makes the network topology unsteady, uncertain, and unreliable. Consequently, it turns to be an immense challenge to sustain network stability and durability. In this work, the authors have presented a resilient steady clustering technique (RSCT) that will maintain durability and steadiness to the sensor network by reducing the unnecessary and av

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Xiao, Xingxing, Haining Huang, and Wei Wang. "Underwater Wireless Sensor Networks: An Energy-Efficient Clustering Routing Protocol Based on Data Fusion and Genetic Algorithms." Applied Sciences 11, no. 1 (2020): 312. http://dx.doi.org/10.3390/app11010312.

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Due to the limited battery energy of underwater wireless sensor nodes and the difficulty in replacing or recharging the battery underwater, it is of great significance to improve the energy efficiency of underwater wireless sensor networks (UWSNs). We propose a novel energy-efficient clustering routing protocol based on data fusion and genetic algorithms (GAs) for UWSNs. In the clustering routing protocol, the cluster head node (CHN) gathers the data from cluster member nodes (CMNs), aggregates the data through an improved back propagation neural network (BPNN), and transmits the aggregated da

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Aalsalem, Mohammed Y. "An effective hotspot mitigation system for Wireless Sensor Networks using hybridized prairie dog with Genetic Algorithm." PLOS ONE 19, no. 4 (2024): e0298756. http://dx.doi.org/10.1371/journal.pone.0298756.

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Wireless Sensor Networks (WSNs) consist of small, multifunctional nodes distributed across various locations to monitor and record parameters. These nodes store data and transmit signals for further processing, forming a crucial topic of study. Monitoring the network’s status in WSN applications using clustering systems is essential. Collaboration among sensors from various domains enhances the precision of localised information reporting. However, nodes closer to the data sink consume more energy, leading to hotspot challenges. To address these challenges, this research employs clustering and

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Stahl, Benjamin E., Jorge Martínez-Palomera, WeiKang Zheng, Thomas de Jaeger, Alexei V. Filippenko, and Joshua S. Bloom. "deepSIP: linking Type Ia supernova spectra to photometric quantities with deep learning." Monthly Notices of the Royal Astronomical Society 496, no. 3 (2020): 3553–71. http://dx.doi.org/10.1093/mnras/staa1706.

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ABSTRACT We present deepSIP (deep learning of Supernova Ia Parameters), a software package for measuring the phase and – for the first time using deep learning – the light-curve shape of a Type Ia supernova (SN Ia) from an optical spectrum. At its core, deepSIP consists of three convolutional neural networks trained on a substantial fraction of all publicly available low-redshift SN Ia optical spectra, on to which we have carefully coupled photometrically derived quantities. We describe the accumulation of our spectroscopic and photometric data sets, the cuts taken to ensure quality, and our s

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Shen, Shigen, Longjun Huang, En Fan, Keli Hu, Jianhua Liu, and Qiying Cao. "Trust Dynamics in WSNs: An Evolutionary Game-Theoretic Approach." Journal of Sensors 2016 (2016): 1–10. http://dx.doi.org/10.1155/2016/4254701.

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A sensor node (SN) in Wireless Sensor Networks (WSNs) can decide whether to collaborate with others based on a trust management system (TMS) by making a trust decision. In this paper, we study the trust decision and its dynamics that play a key role to stabilize the whole network using evolutionary game theory. When SNs are making their decisions to select actionTrustorMistrust, a WSNs trust game is created to reflect their utilities. An incentive mechanism bound with one SN’s trust degree is incorporated into this trust game and effectively promotes SNs to select actionTrust. The replicator d

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Alnaser, As’ad Mahmoud As’ad, Said S. Saloum, Ahmed A. M. Sharadqh, and Hazem (Moh’d Said) Hatamleh. "Optimizing Multi-Tier Scheduling and Secure Routing in Edge-Assisted Software-Defined Wireless Sensor Network Environment Using Moving Target Defense and AI Techniques." Future Internet 16, no. 11 (2024): 386. http://dx.doi.org/10.3390/fi16110386.

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Software Defined Wireless Sensor Networks (SDWSN) enable flexibility in Wireless Sensor Network (WSN) environments by defining the controllable functions to WSN nodes by the Software Defined Network (SDN) controller. Due to the rapid evolution of SDWSNs, adverse effects also have occurred in terms of interference, energy consumption, and security issues. Several state-of-the-art works lend their utmost best to the SDWSN environment. However, the complete picture (i.e., relatability and security in SDWSN) poses severe challenges. The state-of-the-art issues is addressed in this research by prop

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Suleiman, Husam. "𝑃c𝜀𝜅max-Means++: Adapt-𝑃 Driven by Energy and Distance Quality Probabilities Based on 𝜅-Means++ for the Stable Election Protocol (SEP)". Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications 14, № 4 (2023): 128–48. http://dx.doi.org/10.58346/jowua.2023.i4.010.

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Attaining a prolonged network lifetime, maximized coverage, and high performance are vital design factors that have to be maintained in a Wireless Sensor Networks (WSN). Such factors are dependent on the stability and optimality of the protocol employed to formulate Sensor Nodes (SNs) into mutual clusters that effectively work around fulfilling specific performance goals. SEP is a heterogeneity-aware protocol implemented based on Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol, designed to prolong the stability period of the network defined by the time interval before the death of th

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Huang, Xin, Yimin Wang, Peiqun Lin, Heng Yu, and Yue Luo. "Forecasting the All-Weather Short-Term Metro Passenger Flow Based on Seasonal and Nonlinear LSSVM." Promet - Traffic&Transportation 33, no. 2 (2021): 217–31. http://dx.doi.org/10.7307/ptt.v33i2.3561.

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Accurate metro ridership prediction can guide passengers in efficiently selecting their departure time and simultaneously help traffic operators develop a passenger organization strategy. However, short-term passenger flow prediction needs to consider many factors, and the results of the existing models for short-term subway passenger flow forecasting are often unsatisfactory. Along this line, we propose a parallel architecture, called the seasonal and nonlinear least squares support vector machine (SN-LSSVM), to extract the periodicity and nonlinearity characteristics of passenger flow. Vario

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NWAFOR, STEPHEN CHINEDU, DESTINY ONYEBUCHI EKOYO, and GIFT AMARACHUKWU JOSHUA. "PREDICTORS OF UNDERGRADUATE SCIENCE EDUCATION STUDENTS’ ENTREPRENEURIAL INTENTIONS IN GOVERNMENT OWNED UNIVERSITIES IN SOUTH-EAST NIGERIA." Journal Plus Education 35, no. 1 (2024): 116–29. http://dx.doi.org/10.24250/jpe/1/2024/scn/doe/gaj/.

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The study examined the predictors of undergraduate science education students’ entrepreneurial intentions in government owned universities in South-East Nigeria. Three research questions guided the study. Descriptive survey research design was used in the study. The population for the study consisted of all the 472 undergraduate science education students in two federal government owned universities in South-East Nigeria, this include Nnamdi Azikiwe University Awka (261 students) and University of Nigeria Nsukka (211 Students). Simple random sampling was used in selecting the sample for the st

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Wu, Liwen, Shiqi Li, and Congfen He. "Lipidomics Combined with Network Pharmacology to Explore Differences in the Mechanisms of Grey Hair Development Between Type 2 Diabetes Mellitus and Normal Populations (Female)." International Journal of Molecular Sciences 26, no. 5 (2025): 2034. https://doi.org/10.3390/ijms26052034.

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Type 2 diabetes is usually accompanied by premature grey hair. In this study, we analysed differences in the lipid composition of black and white hair follicles between women with type 2 diabetes and healthy populations, using lipidomic methods. We examined the correlation between the lipid composition of female grey hair follicles and type 2 diabetes mellitus, and we screened for potential grey-hair-delaying ingredients using network pharmacology. Forty-one female volunteers with type 2 diabetes (diabetes, D) and thirty-five healthy volunteers (healthy, H) aged 55–65 years were recruited. Hai

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Mehta, Arnav, Lynn Bi, Deepika Yeramosu, et al. "Abstract NG08: Dissecting and quantifying pancreatic cancer plasticity using single-cell multiomics, lineage tracing and functional genomics reveals novel mediators of therapy resistance." Cancer Research 84, no. 7_Supplement (2024): NG08. http://dx.doi.org/10.1158/1538-7445.am2024-ng08.

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Abstract Pancreatic cancer (PDAC) is a lethal disease in part because tumor cells exist in distinct transcriptional states (e.g. basal/mesenchymal v.s. classical/epithelial) with unique phenotypic properties that contribute to tumor growth and treatment resistance. Two major mechanisms have been suggested for treatment evasion: (1) the intrinsic resistance of an existing state to a therapy regimen and (2) plasticity of therapy-sensitive states to adopt more resistant states. The relative contribution of these mechanisms to treatment resistance is still poorly understood. Historically, measurem

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Tošic, Aleksandar, and Jernej Vičič. "Spatial Path Selection and Network Topology Optimisation in P2P Anonymous Routing Protocols." Journal of Web Engineering, November 28, 2021. http://dx.doi.org/10.13052/jwe1540-9589.2115.

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To anonymous internet traffic, many popular protocols route traffic through a network of nodes in order to conceal information about the request. However, routing traffic through other nodes inherently introduces added latency. Over the past two decades, there were many attempts to improve the path selection in order to decrease latency with little or no trade-off in terms of security, and anonymity. In this paper, we show the potential use of geo-sharding in decentralized routing networks to improve fault-tolerance, and latency. Such networks can be used as a communication layer for Edge devi

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Tošić, Aleksandar, and Jernej Vičič. "Spatial path selection and network topology optimisation in P2P anonymous routing protocols." Journal of Web Engineering 21, no. 1 (2021). https://doi.org/10.13052/jwe1540-9589.2115.

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To anonymous internet traffic, many popular protocols route traffic through a network of nodes in order to conceal information about the request. However, routing traffic through other nodes inherently introduces added latency. Over the past two decades, there were many attempts to improve the path selection in order to decrease latency with little or no trade-off in terms of security, and anonymity. In this paper, we show the potential use of geo-sharding in decentralized routing networks to improve fault-tolerance, and latency. Such networks can be used as a communication layer for Edge devi

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Vijay, M. M., J. Sunil, V. G. Anisha Gnana Vincy, et al. "Underwater wireless sensor network-based multihop data transmission using hybrid cat cheetah optimization algorithm." Scientific Reports 13, no. 1 (2023). http://dx.doi.org/10.1038/s41598-023-37952-x.

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AbstractFor the conservation and sustainable use of the oceanic environment, monitoring of underwater regions is ineluctable and is effectuated with the aid of an underwater wireless sensor network. It is accoutered with smart equipment, vehicles and sensors and utilized for the transmission of acquired data from the monitoring region and forwarded to the sink nodes (SN) where the data are retrieved. Moreover, data transmission from sensor nodes to SN is complicated by the aquatic environment's inherent complexities. To surpass those issues, the work in this article focusesto propose a Hybrid

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Zhang, Gexiang, Xihai Zhang, Haina Rong, et al. "A Layered Spiking Neural System for Classification Problems." International Journal of Neural Systems, April 12, 2022. http://dx.doi.org/10.1142/s012906572250023x.

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Biological brains have a natural capacity for resolving certain classification tasks. Studies on biologically plausible spiking neurons, architectures and mechanisms of artificial neural systems that closely match biological observations while giving high classification performance are gaining momentum. Spiking neural P systems (SN P systems) are a class of membrane computing models and third-generation neural networks that are based on the behavior of biological neural cells and have been used in various engineering applications. Furthermore, SN P systems are characterized by a highly flexibl

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Kiran Kumar, G., S. K Prashanth, E. Padmalatha, et al. "An optimized meta‐heuristic clustering‐based routing scheme for secured wireless sensor networks." International Journal of Communication Systems, April 15, 2024. http://dx.doi.org/10.1002/dac.5791.

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SummaryPrivacy and security present significant challenges in wireless sensor networks (WSNs). In order to enhance security, the sensor network is equipped with high throughput. While the importance of both source node (SN) and base station (BS) location privacy and security is acknowledged, recent research has predominantly focused on location privacy. Addressing this gap, the geometric zigzag bidirectional tree effectively tackles privacy and security threats at both the SN and BS locations. Future iterations of WSN are anticipated to integrate additional functionalities to meet diverse requ

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Ravikumar, K., M. Mathivanan, A. Muruganandham, and L. Raja. "Attentive Dual Residual Generative Adversarial Network for Energy‐Aware Routing Through Golden Search Optimization Algorithm in Wireless Sensor Network Utilizing Cluster Head Selection." Transactions on Emerging Telecommunications Technologies 36, no. 1 (2025). https://doi.org/10.1002/ett.70035.

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ABSTRACTWireless Sensor Networks (WSNs) are extensively used in event monitoring and tracking, particularly in scenarios that require minimal human intervention. However, a key challenge in WSNs is the short lifespan of sensor nodes (SN), as continuous sensing leads to rapid battery depletion. In high‐traffic areas, sensors located near the sink node exhaust their energy quickly, creating an energy‐hole issue. As a result, optimizing energy usage is a significant challenge for WSN‐assisted applications. To address this, this paper proposes an Energy‐aware Routing and Cluster Head Selection in

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