Interference Management in UAV-Assisted Multi-Cell Networks by Muchen Jiang, Honglin Ren, Yongxing Qi, Ting Wu

“…This article considers a multi-cell wireless network comprising of conventional user equipment (UE), sensor devices and unmanned aerial vehicles (UAVs) or drones. …”
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Drug-therapy-related problems and pharmacist interventions in the medical ward in northeast Ethiopia: focus on types, acceptability, and impacts by Bedilu Linger Endalifer, Yared Dergu Ayta, Abate Wondesen Tsigie, Yehualashet Teshome Wondmkun, Mekuanint Terefe Kassa, Gedefaw Getnet Amare, Yenesew Wudu Ejigu, Manaye Tamrie Derseh, Abyou Seyfu Ambaye

“…The drug-therapy-related problems, interventions, and acceptability of the interventions were categorized on the basis of the Pharmaceutical Care Network Europe V.9.1 tool. …”
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An indoor positioning system based on distributed LTE network by Yu YANG, Ming CHEN, Daqing LIU

“…Indoor positioning technology has important applications in the business and security fields,but there are still existing problems with low positioning accuracy and high deployment costs.An indoor positioning system based on long term evolution ( LTE ) network was introduced.The system was defined on the Huawei distributed pico base station and was used to measure the reference signal strength (RSRP) or time of arrival (ToA) of mobile terminals to multiple access points.To overcome the uplink power control in LTE network,the absolute RSRP or ToA was converted to differential values.The system relied on widely deployed LTE networks to provide seamless location services to terminal devices in a wireless network connection state.It didn’t rely on third-party software or affect network performance.The experimental results show that the average positioning accuracy of Huawei indoor positioning system using time difference of arrival (TDoA) can reach 3~5 m in indoor scenarios such as shopping malls,showing good application potential.…”
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Assessing Losses of Power and Electrical Energy in Unbalanced Medium Voltage Distribution Networks by Toader C., Golovanov N., Porumb R., Trishtiu I., Bulac C., Mandish Al., Tirsu M.

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Computation offloading scheme for RIS-empowered UAV edge network by Bin LI, Wenshuai LIU, Wancheng XIE, Zesong FEI

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Delay-constrained data aggregation scheduling in wireless sensor networks by Cheng Feng, Zhijun Li, Shouxu Jiang, Weipeng Jing

“…This article focuses on data aggregation scheduling problem with delay constraint in wireless sensor networks. …”
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Fair Probabilistic Multi-Armed Bandit With Applications to Network Optimization by Zhiwu Guo, Chicheng Zhang, Ming Li, Marwan Krunz

“…Online learning, particularly Multi-Armed Bandit (MAB) algorithms, has been extensively adopted in various real-world networking applications. In certain applications, such as fair heterogeneous networks coexistence, multiple links (individual arms) are selected in each round, and the throughputs (rewards) of these arms depend on the chosen set of links. …”
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Introducing an Evolutionary Method to Create the Bounds of Artificial Neural Networks by Ioannis G. Tsoulos, Vasileios Charilogis, Dimitrios Tsalikakis

“…In recent years, a multitude of scientific publications have been presented on the effective training of their parameters, but in many cases overfitting problems appear, where the artificial neural network shows poor results when used on data that were not present during training. …”
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Research on load-balanced construction algorithm of logical carrying network by Hao-xue WANG, Ming JIANG, Ji FU

“…To improve the extensibility of network service,constructing algorithm of logical carrying network was pro-posed by mapping the demands of network service into substrate network.To solve the problem of construction efficiency,on-demand carrying strategy was introduced to provide different resources to meet different service requirements.Based on available resource and current link load,an improved multi-commodity flow model was proposed to compute the re-source allocation.Simulation results indicate this al ithm can improve network service capability from construction success rate and average construction profit.…”
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Network slicing resource allocation strategy based on joint optimization by Zaijian WANG, Huimin GU

“…To improve network resource utilization that was decreased by different applications with different requirements in 5G networks, a network slicing resource allocation strategy based on joint optimization was proposed, which was utilized to maximize both network resource utilization and network revenue by comprehensively considering in tra-slice and inter-slice resource schedule.Firstly, the user’s average satisfaction function was defined in the inter-slicing resource allocation problem.Furthermore, in terms of the number of users, slicing schedule delay and priority, a proportional fair resource allocation algorithm based on quality of service (QoS) was proposed, which was employed to achieve the best tradeoff between fairness and the users’ requirements among slices.Secondly, after two functions (service degradation and resource migration) were introduced in the inter-slice resource schedule problem, two price models were established for internal access users and external access users respectively, where congestion and non-congestion conditions were analyzed.According to the proposed price models, a Stackelberg game between the base station and users was constructed, and a global search algorithm with low complexity was leveraged to obtain the best response of the game, where the best tradeoff between the base station revenue and user utility was obtained.Simulation results show that the proposed strategy can effectively improve resource utilization and network revenue while reducing network congestion.Therefore, it can better realize fairness in resource allocation.…”
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Embedding and classifying test execution traces using neural networks by Foivos Tsimpourlas, Gwenyth Rooijackers, Ajitha Rajan, Miltiadis Allamanis

“…Abstract Classifying test executions automatically as pass or fail remains a key challenge in software testing and is referred to as the test oracle problem. It is being attempted to solve this problem with supervised learning over test execution traces. …”
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The Study on Media Access Control Protocol for Wireless Network in Library by Wen Zeng, Junsheng Zhang, Ying Li, Peng Qu

“…Wireless technology will be widely used in libraries with the development of the mobile network in the near future. This paper focuses on MAC protocol for wireless network based on ultra-wideband band (UWB) to solve the problems of real-time and reliability in the wireless transmitting. …”
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A Data Item Selection Mechanism for Mobile Opportunistic Networks by Lei You, Jianbo Li, Changjiang Wei, Jixing Xu, Chenqu Dai

“…The nonexistence of an end-to-end path poses great challenges to directly adapting the traditional routing algorithms for Internet and mobile ad hoc networks (MANETs) to mobile opportunistic networks (MONs). …”
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Attractor and Boundedness of Switched Stochastic Cohen-Grossberg Neural Networks by Chuangxia Huang, Jie Cao, Peng Wang

“…We address the problem of stochastic attractor and boundedness of a class of switched Cohen-Grossberg neural networks (CGNN) with discrete and infinitely distributed delays. …”
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A Reconfigurable Access Scheme for Massive-MIMO MTC Networks by Atoosa Dalili Shoaei, Duc Tuong Nguyen, Tho Le-Ngoc

“…This paper presents an efficient reconfigurable access scheme for massive machine-type communication networks, where to provide massive connectivity, the base station is equipped with a large-scale antenna array. …”
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Using ensemble neural network based on sampling for multiclass classification by Khotimah Bain Khusnul, Setiawan Eko, Anamisa Devie Rosa, Puspitarini Oktavia Rahayu

“…This study aims to overcome the problem of data imbalance in the ensemble neural network method by comparing the oversampling method with undersampling, so that more representative synthetic data is obtained. …”
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Author name disambiguation based on heterogeneous graph neural network. by Ge Wang, Zikai Sun, Weiyang Hu, MengHuan Cai

“…The current mainstream methods for author disambiguation are mainly divided into two methods: feature-based clustering and connection-based clustering, but none of the current mainstream methods can efficiently deal with the author name disambiguation problem, For this reason, this paper proposes the author name ablation method based on the relational graph heterogeneous attention neural network, first extract the semantic and relational information of the paper, use the constructed graph convolutional embedding module to train the splicing to get a better feature representation, and input the constructed network to get the vector representation. …”
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Graph Neural Networks for Pressure Estimation in Water Distribution Systems by Huy Truong, Andrés Tello, Alexander Lazovik, Victoria Degeler

“…In this work, we combine physics‐based modeling and graph neural networks (GNN), a data‐driven approach, to address the pressure estimation problem. …”
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An automatic modulation recognition network based on multi-channel lightweighting by WAN Jinhua, SHANG Junna, ZHANG Huadi

“…Existing automatic modulation recognition models perform well in recognition accuracy, but most methods have difficulty in achieving an ideal balance between the number of parameters and model performance. To solve this problem, a multi-channel lightweight modulation recognition (MCLMR) network was designed. …”
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Improved Lightweight Convolutional Networks for Classification of Grape Diseased Leaves by HUANG Yinglai, LI Ning, LIU Zhenbo, ZHANG Yanhua

“… Aiming at the problem of low accuracy and efficiency of traditional manual detection of types of grape leaf diseases, a grape leaf disease image classification method with improved lightweight convolutional network model is proposed First, the ReLU activation function in the original network is replaced by the ELU activation function; second, a new fully connected layer is designed, and the global average pooling layer is replaced by the global maximum pooling layer, and the output layer is improved; and then the channel attention mechanism is embedded in the network. …”
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