A Canadian algorithm for upper gastrointestinal cancer management by Frédéric Lemay, Amindeep S. Sandhu, Barry D. Stein, Rachel Goodwin

“…The algorithm is based on a novel approach comprising a case-based, accredited educational program with asynchronous discussion among clinicians practicing across Canada, with the input of expert medical oncologists and gastroenterologists. …”
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Environmental risk determination algorithm for veterinary medicinal products by Viviana Ciuca, Viorel V. Safta, Romeo T. Cristina

“…Based on the indication of use of the veterinary medicinal product, the exposure assessment begins with the release of the active substance into the environment, and while taking into account the drug's fate and distribution, develops a predicted environmental concentration (PEC). The effects assessment begins with toxicity data and applies an assessment factor (AF) to it resulting in a predicted no effect concentration (PNEC). …”
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An efficient parallel DCNN algorithm in big data environment by Yimin Mao, Yaser Ahangari Nanehkaran, Neelakandan Chandrasekaran, Ying Huo, Zhan Qing Wen, ke Gong, Miao Decheng

“…Big data plays a vital role in developing remote sensing, landslide prediction, and enabling applications, the integration of deep convolutional neural networks (DCNN) has significantly improved its prediction accuracy. …”
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Novel Back Propagation Optimization by Cuckoo Search Algorithm by Jiao-hong Yi, Wei-hong Xu, Yuan-tao Chen

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Research on Improving Camshift Algorithm about Target Tracking by QIN Yong, SHANG Meng-meng, ZHAO Xiao-hong, GAI Jian-xin

“…Finally, the accelerating object can be tracked accurately based on Camshift algorithm combined with Kalman filter prediction. It is shown with experimental data that the blocked or accelerating target can be accurately located by used the method proposed in this paper.…”
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An Improved Directional Broadcast Algorithm Based on Brownian Motion by Shibao Li, Linlin Lou, Yu Wang, Lu Sun, Li Hong

“…We bring Brownian motion into network model and gain the distribution of the nodes which encountered destination before. This algorithm uses encounter records to predict the direction to destination and forwards RREQ packets with reasonable probability according to the distribution just mentioned. …”
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An algorithm for indoor SARS-CoV-2 transmission by Daniel Maxin, Spencer Gannon

“…It is shown via several examples how this algorithmic modeling approach can be used to run various scenarios in order to predict the efficacy of the intervention.…”
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Machine learning algorithm for intelligent detection of WebShell by Hua DAI, Jing LI, Xin-dai LU, Xin SUN

“…WebShell is a common tool for network intrusions,which has the characteristics of great harm and good concealment.The current detection method is relatively simple,and easy to be bypassed,so it is difficult to deal with complex and flexible WebShell.To solve these problems,a supervised machine learning algorithm was put forward to detect WebShell intelligently.By learning the features of existing WebShell and non-existing WebShell pages,the algorithm can make prediction of the unknown pages,and the flexibility and adaptability were both very good.Compared with the traditional WebShell detection methods,the experiment proves that the algorithm has higher detection efficiency and accuracy,and at the same time there is a certain probability to detect new types of WebShell.…”
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Performance Analysis of the MUSIC Algorithm in the Presence of Correlated Noise by Hyeong Woo Ham, Hyuk-In Kwon, Joon-Ho Lee

“…Passive direction finding has been studied over the past decades and theoretic performance prediction is a fundamental problem. The performance of the MUSIC algorithm for Direction-of-arrival (DOA) estimation under measurement uncertainty is analyzed. …”
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A Recommendation Algorithm Based on Restricted Boltzmann Machine by WANG Weibing, ZHANG Lichao, XU Qian

“…In the case where the amount of data is too large, the recommended results output by the RBM model will be broader Besides, many collaborative filtering algorithms currently do not handle large data sets better So, we try to use the deep learning technology to strengthen the personalized recommendation model We propose a hybrid recommendation model combining the bound Boltzmann model and the hidden factor model First, we use the RBM algorithm to generate candidate sets, and score the sparse matrix of the candidate set Then we use the LFM model to sort the candidate results and select the optimal solution for recommendation The hybrid model is validated using used large public datasets It can be seen from the verification that compared with the traditional recommendation model, the proposed method can improve the accuracy of the score prediction…”
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Practical aspects of using of parallel computing in genetic algorithm by V. V. Frolov

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Local congestion control algorithm with fair channel allocation by Geng-ming ZHU, Zhi-qiang WANG, Zhe-tao LI, Ren-fa LI

“…A local congestion control algorithm with fair channel allocation (FCA) was presented to mitigate local congestion as well as to improve the fairness of channel utilization.In order to decrease the extra communication overhead for obtaining the real-time buffer length of neighbors and improve the accuracy of congestion detection model based on buffer occupancy of single node，FCA presented a new model considers the total buffer length of neighbors with predict-based mechanism for real-time buffer occupancy and the average transmission time of packet.To avoid deteriorating congestion with an explicit notified package，FCA embedded an additional node address to the ACK control frame to carry congestion information.During the congestion alleviation stage，FCA presented a fair channel allocation mechanism based on real-time buffer occupancy and queue priority to prevent some nodes from overflowing resulting in package loss due to the growth of buffer fast.Simulation results show that the proposed protocol has comparative advantages compare with 802.11，CODA and PCCP in terms of collision，package delivery ratio，throughput and fairness.…”
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Intelligent Recommendation Algorithm Combining RNN and Knowledge Graph by Fengsheng Zeng, Qin Wang

“…At the same time, the algorithm’s rating prediction error values are small (less than 2%) in extracting different users’ ratings for different books. …”
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An Efficient Recommendation Algorithm Based on Heterogeneous Information Network by Ying Yin, Wanning Zheng

“…At present, a large number of recommendation algorithms based on heterogeneous information networks have been proposed. …”
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Skeletonization algorithm FOR OBJECTS ON THREE-DIMENSIONAL RASTER IMAGES by D. A. Goncharov, A. M. Nedzved, S. V. Ablameyko

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REAL-TIME ALGORITHM of OBJECT TRACKING with ERROR HANDLING by O. P. Solovey, N. N. Ivanov

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Algorithm of measuring signal processing in vector analyzers of circuits by A. A. Kopshaj, A. V. Gusinskij, A. V. Voroshen', D. A. Kondrashov

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Genetic Algorithm-Enhanced Direct Method in Protein Crystallography by Ruijiang Fu, Wu-Pei Su, Hongxing He

“…Direct methods based on iterative projection algorithms can determine protein crystal structures directly from X-ray diffraction data without prior structural information. …”
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Algorithm of Development for Stabilization of Socio-Ecological Situation in Karakalpakstan by Alisher Abdullaev

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A Suggested Algorithm for Video Motion and Applicate It to Basketball by Basil Thanoon, Abeer Thanoon

“…Also Root Mean Square Error is adopted as a measure for the adjacent position to the real position of the ball within the video sequence and the position that is found by using algorithm. The experimental results show the efficiency of the suggested algorithm to estimate the ball position accurately.…”
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