Outcomes among children and adults at risk of severe dengue in Sri Lanka: Opportunity for outpatient case management in countries with high disease burden. by Champica K Bodinayake, Ajith DeS Nagahawatte, Vasantha Devasiri, Niroshana J Dahanayake, Gaya B Wijayaratne, Nayani P Weerasinghe, Madureka Premamali, Tianchen Sheng, Bradly P Nicholson, Harshanie A Ubeysekera, Ruvini Mp Kurukulasooriya, Aruna D de Silva, Truls Østbye, Christopher W Woods, L Gayani Tillekeratne

“…<h4>Conclusions</h4>One-half of patients hospitalized with acute dengue progressed to develop DHF and a very small number developed DSS or severe dengue. Developing an algorithm for triaging patients to ambulatory versus inpatient management should be the future goal to optimize utilization of healthcare resources in dengue-endemic countries.…”
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Fast Processing of Massive Hyperspectral Image Anomaly Detection Based on Cloud-Edge Collaboration by Yunchang Wang, Jin Sun, Yang Xu, Zhihui Wei, Shangdong Zheng, Zebin Wu

“…With the improvement of hyperspectral image resolution, existing anomaly detection algorithms find it challenging to quickly process large volumes of hyperspectral data while fully exploiting spectral information. …”
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A grid-based sectoring for energy-efficient wireless sensor networks by Nubunga Ishaya, Mustapha Aminu Bagiwa

“…This research improves CH selection by organizing sensor nodes into square grid clusters and employing a routing algorithm for randomized CH selection. Game theory (GT) and Ad hoc on Demand Vectors (AODV) were used to choose the optimal routing path, while Grey Wolf Optimization (GWO) was used to determine the optimal CHs. …”
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Research on GNNs with stable learning by Wenbin Li, Wenxuan Wei, Peiyang Wang, Li Pan, Bo Yang, Yanling Xu

“…The aim is to extract genuine causal features while eliminating spurious causal features. By introducing a feature sample weighting decorrelation technique in the random Fourier transform space and combining it with a baseline GNN model, a Stable-GNN model and a constrained sampling weight gradient update algorithm are designed. …”
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Generalized Singular Value Decomposition-Based Secure Beam Hybrid Precoding for Millimeter Wave Massive Multiple-Input Multiple-Output Systems by Boqing Chen, Lijun Yang, Meng Wu

“…In a hybrid precoding system, the low-complexity GSVD-Sparsity algorithm can achieve a spectral efficiency close to that of the GSVD-based scheme in a fully digital system while maintaining anti-eavesdropping capabilities.…”
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IoT intrusion detection method for unbalanced samples by ANTONG P, Wen CHEN, Lifa WU

“…In recent years, network traffic increases exponentially with the iteration of devices, while more and more attacks are launched against various applications.It is significant to identify and classify attacks at the traffic level.At the same time, with the explosion of Internet of Things (IoT) devices in recent years, attacks on IoT devices are also increasing, causing more and more damages.IoT intrusion detection is able to distinguish attack traffic from such a large volume of traffic, secure IoT devices at the traffic level, and stop the attack activity.In view of low detection accuracy of various attacks and sample imbalance at present, a random forest based intrusion detection method (Resample-RF) was proposed, which consisted of three specific methods: optimal sample selection algorithm, feature merging algorithm based on information entropy, and multi-classification greedy transformation algorithm.Aiming at the problem of unbalanced samples in the IoT environment, an optimal sample selection algorithm was proposed to increase the weight of small samples.Aiming at the low efficiency problem of random forest feature splitting, a feature merging method based on information entropy was proposed to improve the running efficiency.Aiming at the low accuracy problem of random forest multi-classification, a multi-classification greedy transformation method was proposed to further improve the accuracy.The method was evaluated on two public datasets.F1 reaches 0.99 on IoT-23 dataset and 1.0 on Kaggle dataset, both of which have good performance.The experimental results show that the proposed model can effectively identify the attack traffic from the massive traffic, better prevent the attack of hackers on the application, protect the IoT devices, and thus protect the related users.…”
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The Impact of AI Software on Financial Transactions by Li Boyang

“…The rapid advancement of artificial intelligence (AI) has profoundly transformed financial trading, enhanced efficiency, accuracy, and customer service while introducing new challenges. This paper explores AI’s applications in quantitative trading, risk forecasting, and intelligent customer interactions, demonstrating its ability to optimize decision-making and reduce operational costs. …”
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Turning Energy-Aware Route Planning With an Extended TSP and Double-Layer State Graph: Experimental Evaluation With a Crawler Mobile Robot by Namihei Adachi, Hisashi Date

“…The routes that minimized energy consumption showed an average 17 % reduction in energy consumption, while the routes that minimized travel time achieved an average 5 % reduction in travel time compared to the standard TSP algorithm.…”
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Federated deep reinforcement learning-based edge collaborative caching strategy in space-air-ground integrated network by LIU Liang, JING Tengxiang, DUAN Jie, MAO Wuping, YAN Hongcheng, MA Wenjie

“…Simulation results show that compared with other algorithm, the proposed algorithm can improve the cache hit rate of user requests by 18% and reduce the access latency of content by 25% while protecting user privacy.…”
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Calibration and Uncertainty Analysis of Freundlich and Langmuir Isotherms Using the Markov Chain Monte Carlo (MCMC) Approach by Haniyeh Sharifi Moghadam, Saeed Alimohammadi

“…First, their parameters were estimated and calibrated using a simple optimization model. To analyze parameter uncertainty, a Bayesian approach employing the Markov Chain Monte Carlo method was adopted, utilizing the Metropolis-Hastings and Gibbs algorithms, and the results were compared. …”
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Blood Scattering Model for Pulsed Doppler by Piotr KARWAT, Andrzej NOWICKI, Marcin LEWANDOWSKI

“…Generated data are used for optimization and validation of Doppler signals processing algorithms. …”
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Synthesizing Sum and Difference Patterns with Low Complexity Feeding Network by Sharing Element Excitations by Jafar Ramadhan Mohammed

“…Unlike the standard optimization approaches such as genetic algorithm (GA), the described algorithm performs repeatedly deterministic transformations on the initial field until the prescribed requirements are satisfied. …”
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Distributed Formation Control with Obstacle and Collision Avoidance for Hypersonic Gliding Vehicles Subject to Multiple Constraints by Zhen Zhang, Yifan Luo, Yaohong Qu

“…The actual control input solver adopts a feasible solution process to calculate the actual control signals while dealing with constraints. Finally, extensive numerical simulations are implemented to unveil the proposed algorithm’s performance and superiority.…”
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Efficient multiplication for finite fields of p characteristic by LI Yin 1, CHEN Gong-liang1, LI Jian-hua1

“…Based on residue arithmetic,a new form of polynomial named PAPB in Fp[x] had been constructed.The amount and distribution of such irreducible polynomials had also been investigated.Then,an efficient algorithm for multiplication modulo PAPB had been proposed using residue arithmetic and Chinese remainder theorem.In the end,the result analysis was given.The theoretic analysis and simulation experiment show that for some finite field of medium prime characteristic,the given algorithm only costs O（k1.5） operations in Fp while the multiplication modulo irreducible binomial cost O（k2） operations,which shows a better performance.As a result,the work presents an interesting perspective for optimal extension field and elliptic curve cryptography.…”
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A Distributed Q Learning Spectrum Decision Scheme for Cognitive Radio Sensor Network by Jian He, Jun Peng, Fu Jiang, Gaorong Qin, Weirong Liu

“…Cognitive spectrum management can improve the utilization efficiency of spectrum while increasing the energy consumption of sensor network nodes. …”
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Multi-Channel Sparse-Frequency-Scanning White-Light Interferometry with Adaptive Mode Locking for Pulse Wave Velocity Measurement by Yifei Xu, Laiben Gao, Cheng Qian, Yiping Wang, Wenyan Liu, Xiaoyan Cai, Qiang Liu

“…Compared to normal MLCC algorithm, the Fibonacci-optimized algorithm reduces the number of computational iterations by 57 times while maintaining sub-nanometer resolution under dynamic perturbations. …”
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Integrating artificial intelligence in nanomembrane systems for advanced water desalination by Anbarasu Krishnan, Thanigaivel Sundaram, Beemkumar Nagappan, Yuvarajan Devarajan, Bhumika

“…The increasing global demand for clean drinking water calls for innovative approaches to optimize desalination processes, making them more sustainable and efficient. …”
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Energy-Efficient Node Selection for Target Tracking in Wireless Sensor Networks by Yong Wang, Dianhong Wang

“…With this understanding, a dynamic node selection scheme based on genetic algorithms is proposed, which can optimize the tradeoff between the accuracy of tracking and the energy cost of nodes. …”
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Efficient and secure multi-party computation protocol supporting deep learning by Shancheng Zhang, Gang Qu, Zongyang Zhang, Minzhe Huang, Haochun Jin, Liqun Yang

“…Furthermore, current solutions often lack optimization for specific computational modules and rely on conventional methods ill-suited for MPC environments. …”
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Differentiable architecture search-based automatic modulation recognition for multi-carrier signals by LI Jie, LI Jing, LYU Lu, GONG Fengkui

“…Simulation results demonstrate that the proposed algorithm improves accuracy in urban multipath channels, especially at low SNR, while simultaneously providing better robustness to modulation parameter variations and small-sample scenarios.…”
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