WLAN indoor positioning algorithm based on skewness-kurtosis testing by Zhen-long SONG, Gang-yi JIANG, Chao HUANG, Mei YU, Jia-le ZHANG

“…Focused on the issues that large positioning errors produced by the inconsistency of received signal strength (RSS)sample population distributions under indoor wireless local area network (WLAN),an indoor positioning algorithm based on skewness-kurtosis testing was proposed.By using the testing method of skewness and kurtosis,whether the RSS samples come from the normal population or not was checked.The distribution functions of the samples accepting null hypothesis were approximated with normal distribution,and the probability density functions of the samples refusing null hypothesis were estimated by kernel function.Experimental results show that the proposed algorithm leads to a 15 percent improvement over the previous methods.Moreover,the proposed algorithm can significantly reduce the workload of the off-line phase at the same positioning accuracy.…”
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Key distribution and recovery algorithm based on Shamir's secret sharing by Hui-gui RONG, Jin-xia MO, Bing-guo CHANG, Guang SUN, Fei LONG

“…The case of secret sharing problem was discussed based on Shamir's secret sharing scheme and reconstructs the secret by introducing a linear combination of shadows—Lagrange factor. Then, the improved algorithm of key distribu-tion and recovery was proposed and extended to a multi-secret sharing scheme. …”
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An Adaptive Chaotic Sine Cosine Algorithm for Constrained and Unconstrained Optimization by Yetao Ji, Jiaze Tu, Hanfeng Zhou, Wenyong Gui, Guoxi Liang, Huiling Chen, Mingjing Wang

“…Sine cosine algorithm (SCA) is a new meta-heuristic approach suggested in recent years, which repeats some random steps by choosing the sine or cosine functions to find the global optimum. …”
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Deployment of Sensors to Optimize the Network Coverage Using Genetic Algorithm by Fozia Hanif Khan, Rehan Shams, M. Umair, M. Waseem

Subjects: “…Wireless Sensor Networks, genetic algorithm, deployment.…”
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Magnetic Moment Estimation Algorithm Based on Convolutional Neural Network by Xiuzhi You, Junqian Zhang, Bingyang Chen, Ke Zhang, Xiaodong Liu, Bin Yan, Wanhua Zhu

“…The simulation results demonstrate that the proposed algorithm performs well in noise environments with a signal-to-noise ratio (SNR) greater than −5 dB. …”
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Algorithmic Collusion: Corporate Accountability and the Application of Art. 101 TFEU by Maria Giacalone

Subjects: “…algorithmic collusion…”
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Cloud Removal Algorithm by Combining MODIS and VIIRS Snow Products by Xiaoyan Wang, Shi Liang, Yanlong Shen, Hui Guo, Zhiqi Ouyang

“…However, differences in cloud identification algorithms lead to significant discrepancies in cloud and snow distribution between MODIS and VIIRS snow products. …”
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Gravitation search algorithm: Application to the optimal IIR filter design by Suman Kumar Saha, Rajib Kar, Durbadal Mandal, S.P. Ghoshal

“…This paper presents a global heuristic search optimization technique known as Gravitation Search Algorithm (GSA) for the design of 8th order Infinite Impulse Response (IIR), low pass (LP), high pass (HP), band pass (BP) and band stop (BS) filters considering various non-linear characteristics of the filter design problems. …”
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An algorithm for matching original experimental records based on improved CDC by CAI Yina, CHEN Xin, QIN Zhiwu, WANG Xin, BAO Xianyu, PENG Jinxue, LIN Yongqi, LI Junlin

Subjects: “…content-defined chunking algorithm…”
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Improved Epidemic algorithm based on trust mechanism in opportunistic networks by Guang-hua ZHANG, Shao-bo PANG, Yao-hong YANG, Zhen-guo CHEN

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Chronic Kidney Disease Prediction Based On Machine Learning Algorithms by Kethineni Likitha., Nithinchandra, Kumar Narendra, Sk Sajida Sultana.

“…This paper analyses the suitability of several machine learning algorithms for CKD prediction in consideration of health-related parameters like age, blood pressure, and blood glucose levels. …”
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Action of G and Q(√ m) and algorithmic implementation for group actions by F. Afza, I. Shaban Bhatti, M. Aslam Malik

“…We have also generated an algorithm by using Visual Basic for calculating the congruence classes of different Moduli and manipulating the group actions.…”
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SSCANL decoder based joint iterative detection and decoding algorithm by Chongyang LIU, Rui GUO

“…In order to improve the receiver performance of the sparse code multiple access (SCMA) system based on polar codes, the cyclic redundancy check (CRC) aided joint iterative detection and decoding receiver scheme based on simplify soft cancellation list (SSCANL) decoder (C-JIDD-SSCANL) was proposed.A polar code decoder in the C-JIDD-SSCANL receiver used the SSCANL algorithm.In this algorithm, decoding node deletion technology was used to simplify L times of soft cancellation (SCAN) decoding required by soft cancellation list (SCANL) algorithm by deleting frozen bit nodes, then the computational process of soft information update between nodes was simplified, and the computational complexity of decoding algorithm was reduced.The simulation results show that the SSCANL algorithm can obtain the same performance as the SCANL algorithm, and its computational complexity is reduced compared with the SCANL algorithm.Compared with the joint iterative detection and decoding scheme based on SCAN decoder (JIDD-SCAN) and the CRC aided joint iterative detection and decoding scheme based on SCAN decoder (C-JIDD-SCAN), the performance of C-JIDD-SSCANL receiver scheme based on SSCANL decoder is improved by about 0.65 dB and 0.59 dB respectively when the bit error rate is 10^-4.…”
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Determination of the FIFO-stack size for the algorithm of the image region growing by V. Yu. Tsviatkou

“…The aim of the work is to derive an expression that allows determining the size of the FIFO-stack for storing the coordinates of adjacent pixels depending on the image size for the segmentation algorithm based on region growing. The FIFO stack, organized on the principle of a ring multi-bit shift register, is considered. …”
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Learning attribute network algorithm based on high-order similarity by Shaoqing WU, Yihong DONG, Xiong WANG, Yan CAO, Yu XIN

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Detection of Malicious Executables Using Rule Based Classification Algorithms by Neeraj Bhargava, Aakanksha Jain, Abhishek Kumar, Dac-Nhuong Le

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YOLO-Dynamic: A Detection Algorithm for Spaceborne Dynamic Objects by Haiying Zhang, Zhengyang Li, Chunyan Wang

“…The proposed algorithm introduces two newly designed modules: the SC_Block_C2f and the LASF_Neck. …”
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An Improved Northern Goshawk Optimization Algorithm for Mural Image Segmentation by Jianfeng Wang, Zuowen Bao, Hao Dong

“…In the process of mural protection and restoration, using optimization algorithms for image segmentation is a common method for restoring mural details. …”
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Genetic Algorithm Based Hybrid Fuzzy System for Assessing Morningness by Animesh Biswas, Debasish Majumder

“…This paper describes a real life case example on the assessment process of morningness of individuals using genetic algorithm based hybrid fuzzy system. It is observed that physical and mental performance of human beings in different time slots of a day are majorly influenced by morningness orientation of those individuals. …”
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Low-complexity ATPM-VSIMM algorithm with adaptive model parameters by Hao ZENG, Wangqiang MU, Yang JIANG, Shunping YANG

“…Aiming at the problem that for maneuvering target tracking, the accuracy of tracking degraded in interacting multiple model algorithms due to the fixed model sets and the fixed transition probability matrix, a low-complexity ATPM-VSIMM algorithm was proposed, which could update the model parameters adaptively.The maneuvering situation of the target was judged according to the innovation changes of the system, and the state noise of the model sets was adjusted to realize the adaptive update of the model sets.Then, the more accurate transition probability matrix was computed through the change of the model posterior probability and the inter-model switching relationship.Therefore, the matching degree between the system motion model and the target motion trajectory was improved.Finally, the high filtering accuracy and the fast response speed of the tracking system were guaranteed.The effectiveness of the proposed algorithm was verified through three aspects that are the initial value of the model posterior probability, the initial value of the transition probability matrix, and the state noise.Simulation results demonstrate that the filtering accuracy of the ATPM-VSIMM algorithm is improved about 8% compared with the existing algorithms.…”
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