DPM-based method for tracking maneuvering targets in wireless sensor networks by LIN Jin-zhao1, LI Guo-jun2, ZHOU Xiao-na2, ZHOU Dao-jun 2, JIANG Yong 2

“…Focused on energy efficiency issues under tracking targets within WSN,a new dynamic power management（DPM） method for tracking distributed targets was proposed combining with the network energy consumption model and wake-up mechanism.With precedent location information of maneuvering target,the algorithm involved both cancelling noise by wavelet filter and predicting target state by autoregressive transformation is introduced to awaken wireless sensor nodes so that their sleep time is prolonged and energy consumption is reduced.According to the current location of maneuvering target,related nodes in an appointed cluster of WSN constitute a distributed dynamic tracking unit,and the cluster head is responsible for collecting the measurement information from the nodes in the tracking unit.A locating algorithm based on the relative posi-tion of two circulars formed on the bases of measurement information is adopted to simplify the process of locatiny and tracking target.Simulation results show that the DPM-based method can reduce the nodes’ energy consumption,meet the locating and tracking accuracy,and can be applied to locate and track the maneuvering targets on the earth surface.…”
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Study on Angular Velocity Measurement for Characterizing Viscous Resistance in a Ball Bearing by Kyungmok Kim

“…Verification of the proposed method was carried out through a direct comparison between the predicted rotational speeds and measured ones by a commercial tachometer. …”
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Research on Passenger Flow Assignment of High-Speed Trains Based on Personalized Itinerary Choice by Jinzi Zheng

“…Under the condition that ticket fare for high-speed train could fluctuate around a benchmark price in China, aimed at predicting how the passengers will distribute among different trains given a ticket fare, the passenger flow assignment method for high-speed trains is studied. …”
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Temporal dependent rate-distortion optimization based on distortion backward propagation by Hongwei GUO, Ce ZHU, Xu YANG, Lei LUO

“…Rate-distortion optimization (RDO) is a crucial technique in block based hybrid video encoders.However, the widely used independent RDO is far from obtaining optimal coding performance.To improve the rate-distortion (R-D) performance of high efficiency video coding (HEVC), a temporal dependent RDO algorithm was proposed.Firstly, the formula to calculate temporal distortion propagation factor was derived by using an exponential R-D function.Then, the coding distortion and motion compensation predicted error were obtained by pre-encoding, and the temporal distortion propagation factor was estimated by using distortion backward propagation.Finally, the Lagrange multiplier and quantization parameter of coding tree unit were adaptively adjusted to optimize bit resources allocation.Experimental results show that compared with the original RDO method in HEVC under the low-delay configuration, the proposed algorithm achieves an average 4.4% bit rate reduction for all test sequences, and up to 13.0% bit rate reduction for test sequence BasketballDrill, at the same reconstructed video quality.…”
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BDS Multipath Parameter Estimation in the Presence of Impulsive Noise by Jicheng Ding, Lin Zhao, Chun Jia, Zhibin Luo

“…A modified least mean p-norm (LMP) algorithm is developed to reduce the convergence time with the same steady-state error by predicting the updating trend of weights. …”
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Modelling and optimisation of the surface‐mounted permanent magnet machine with multi‐level array magnets by Longxuan Li, Zhaoliang Chen, Wenliang Zhao, Chengwu Diao, Byung‐il Kwon

“…The cogging torque is predicted with energy method by analysing the tangential magnetic field distribution at stator slots. …”
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First M87 Event Horizon Telescope Results. VI. The Shadow and Mass of the Central Black Hole by The Event Horizon Telescope Collaboration, Kazunori Akiyama, Antxon Alberdi, Walter Alef, Keiichi Asada, Rebecca Azulay, Anne-Kathrin Baczko, David Ball, Mislav Baloković, John Barrett, Dan Bintley, Lindy Blackburn, Wilfred Boland, Katherine L. Bouman, Geoffrey C. Bower, Michael Bremer, Christiaan D. Brinkerink, Roger Brissenden, Silke Britzen, Avery E. Broderick, Dominique Broguiere, Thomas Bronzwaer, Do-Young Byun, John E. Carlstrom, Andrew Chael, Chi-kwan Chan, Shami Chatterjee, Koushik Chatterjee, Ming-Tang Chen, Yongjun Chen, Ilje Cho, Pierre Christian, John E. Conway, James M. Cordes, Geoffrey B. Crew, Yuzhu Cui, Jordy Davelaar, Mariafelicia De Laurentis, Roger Deane, Jessica Dempsey, Gregory Desvignes, Jason Dexter, Sheperd S. Doeleman, Ralph P. Eatough, Heino Falcke, Vincent L. Fish, Ed Fomalont, Raquel Fraga-Encinas, Per Friberg, Christian M. Fromm, José L. Gómez, Peter Galison, Charles F. Gammie, Roberto García, Olivier Gentaz, Boris Georgiev, Ciriaco Goddi, Roman Gold, Minfeng Gu, Mark Gurwell, Kazuhiro Hada, Michael H. Hecht, Ronald Hesper, Luis C. Ho, Paul Ho, Mareki Honma, Chih-Wei L. Huang, Lei Huang, David H. Hughes, Shiro Ikeda, Makoto Inoue, Sara Issaoun, David J. James, Buell T. Jannuzi, Michael Janssen, Britton Jeter, Wu Jiang, Michael D. Johnson, Svetlana Jorstad, Taehyun Jung, Mansour Karami, Ramesh Karuppusamy, Tomohisa Kawashima, Garrett K. Keating, Mark Kettenis, Jae-Young Kim, Junhan Kim, Jongsoo Kim, Motoki Kino, Jun Yi Koay, Patrick M. Koch, Shoko Koyama, Michael Kramer, Carsten Kramer, Thomas P. Krichbaum, Cheng-Yu Kuo, Tod R. Lauer, Sang-Sung Lee, Yan-Rong Li, Zhiyuan Li, Michael Lindqvist, Kuo Liu, Elisabetta Liuzzo, Wen-Ping Lo, Andrei P. Lobanov, Laurent Loinard, Colin Lonsdale, Ru-Sen Lu, Nicholas R. MacDonald, Jirong Mao, Sera Markoff, Daniel P. Marrone, Alan P. Marscher, Iván Martí-Vidal, Satoki Matsushita, Lynn D. Matthews, Lia Medeiros, Karl M. Menten, Yosuke Mizuno, Izumi Mizuno, James M. Moran, Kotaro Moriyama, Monika Moscibrodzka, Cornelia Müller, Hiroshi Nagai, Neil M. Nagar, Masanori Nakamura, Ramesh Narayan, Gopal Narayanan, Iniyan Natarajan, Roberto Neri, Chunchong Ni, Aristeidis Noutsos, Hiroki Okino, Héctor Olivares, Tomoaki Oyama, Feryal Özel, Daniel C. M. Palumbo, Nimesh Patel, Ue-Li Pen, Dominic W. Pesce, Vincent Piétu, Richard Plambeck, Aleksandar PopStefanija, Oliver Porth, Ben Prather, Jorge A. Preciado-López, Dimitrios Psaltis, Hung-Yi Pu, Venkatessh Ramakrishnan, Ramprasad Rao, Mark G. Rawlings, Alexander W. Raymond, Luciano Rezzolla, Bart Ripperda, Freek Roelofs, Alan Rogers, Eduardo Ros, Mel Rose, Arash Roshanineshat, Helge Rottmann, Alan L. Roy, Chet Ruszczyk, Benjamin R. Ryan, Kazi L. J. Rygl, Salvador Sánchez, David Sánchez-Arguelles, Mahito Sasada, Tuomas Savolainen, F. Peter Schloerb, Karl-Friedrich Schuster, Lijing Shao, Zhiqiang Shen, Des Small, Bong Won Sohn, Jason SooHoo, Fumie Tazaki, Paul Tiede, Remo P. J. Tilanus, Michael Titus, Kenji Toma, Pablo Torne, Tyler Trent, Sascha Trippe, Shuichiro Tsuda, Ilse van Bemmel, Huib Jan van Langevelde, Daniel R. van Rossum, Jan Wagner, John Wardle, Jonathan Weintroub, Norbert Wex, Robert Wharton, Maciek Wielgus, George N. Wong, Qingwen Wu, André Young, Ken Young, Ziri Younsi, Feng Yuan, Ye-Fei Yuan, J. Anton Zensus, Guangyao Zhao, Shan-Shan Zhao, Ziyan Zhu, Joseph R. Farah, Zheng Meyer-Zhao, Daniel Michalik, Andrew Nadolski, Hiroaki Nishioka, Nicolas Pradel, Rurik A. Primiani, Kamal Souccar, Laura Vertatschitsch, Paul Yamaguchi

“…This measurement from lensed emission near the event horizon is consistent with the presence of a central Kerr black hole, as predicted by the general theory of relativity.…”
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A Comparative Study of Rhythmic Complexity Measures in Music Performance by Cihan Yaygın, Ozan Baysal, Yavuz Buruk, Barış Bozkurt

“…In the second study, the expert raters provided the most accurate predictions for rhythm repetition difficulty, followed by the WNBD scale and the Tanguiane scale. …”
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A scalable framework for soil property mapping tested across a highly diverse tropical data-scarce regionZENODO by Rodrigo de Q. Miranda, Rodolfo L.B. Nóbrega, Anne Verhoef, Estevão L.R. da Silva, Jadson F. da Silva, José C. de Araújo Filho, Magna S.B. de Moura, Alexandre H.C. Barros, Alzira G.S.S. Souza, Wanhong Yang, Hui Shao, Raghavan Srinivasan, Feras Ziadat, Suzana M.G.L. Montenegro, Maria do S.B. Araújo, Josiclêda D. Galvíncio

“…We developed a machine learning framework that integrates the Soil-Landscape Estimation and Evaluation Program (SLEEP) with gradient boosting to predict soil properties at regional scales and multiple depths. …”
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Ecological niche modelling using MaxEnt for riparian species in a Mediterranean context by Jean Stephan, Melissa Korban

“…Despite their key environmental role, riparian tree and shrub species gained little attention in ecological niche modeling (ENM), especially in semi-arid environments.This study examines the performance of selected climatic, topographic, and geographic predictors in ENM of obligate and non-obligate riparian tree and shrub species in perennial and intermittent streams in the Mediterranean biome.MaxEnt algorithm was used for ENM. Three models were designed with different sets of predictors with cropped and non-cropped backgrounds around the riparian zone.The models generated different predicted distribution maps by species and compared them with the presence points of the studied species. …”
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Weighted frequent gene co-expression network mining to identify genes involved in genome stability. by Jie Zhang, Kewei Lu, Yang Xiang, Muhtadi Islam, Shweta Kotian, Zeina Kais, Cindy Lee, Mansi Arora, Hui-Wen Liu, Jeffrey D Parvin, Kun Huang

“…Gene co-expression network analysis is an effective method for predicting gene functions and disease biomarkers. However, few studies have systematically identified co-expressed genes involved in the molecular origin and development of various types of tumors. …”
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A Novel Method for Noise Reduction and Jump Correction of Maglev Gyroscope Rotor Signals Under Instantaneous Perturbations by Di Liu, Zhen Shi, Chenxi Zou, Ziyi Yang, Jifan Li

“…Furthermore, we utilize the stable sampling trend data of the rotor signal as sample data, employing the ARIMA model to accurately predict the missing abnormal jump trend data, thereby ensuring the completeness and coherence of the rotor signal trend information. …”
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Artificial Neural Network Approach to Study Imprecisely Defined Nonlinear Systems With Case Studies by Lakshmi Durga Pathipati, Sukanta Nayak

“…A feed-forward neural network (FFNN) is used to generate outputs based on initial guesses for the field variables, and the ANN-LM algorithm optimizes the solution by minimizing the error between predicted and target values. …”
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Cooperative UAV Scheduling for Power Grid Deicing Using Fuzzy Learning and Evolutionary Optimization by Yu-Jun Zheng, Zhi-Yuan Zhang, Jia-Yu Yan, Wei-Guo Sheng

“…Uncertain outage risk, collapse risk, and deicing workload of each power line are modeled as fuzzy values predicted by fuzzy deep learning models, and we transform the fuzzy optimization problem into a crisp optimization problem based on fuzzy arithmetics and uncertain theory. …”
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Quantification of transplant-derived circulating cell-free DNA in absence of a donor genotype. by Eilon Sharon, Hao Shi, Sandhya Kharbanda, Winston Koh, Lance R Martin, Kiran K Khush, Hannah Valantine, Jonathan K Pritchard, Iwijn De Vlaminck

“…Our algorithm predicts heart and lung allograft rejection with an accuracy that is similar to conventional GTD. …”
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Yield Estimation in Banana Orchards Based on DeepSORT and RGB-Depth Images by Lei Zhou, Zhou Yang, Lanhui Fu, Jieli Duan

“…This system provides managers with bunch weight predictions and statistical plant information to achieve real-time yield estimations for banana orchards. …”
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Battle of Water Demand Forecasting: An Optimized Deep Learning Model by Mohammadali Geranmehr, Alemtsehay G. Seyoum, Mostapha Kalami Heris

“…Ensuring a steady supply of drinking water is crucial for communities, but predicting how much water will be needed is challenging because of uncertainties. …”
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Analysis of time series characteristics using machine learning model and correlation matrix in the tasks of forecasting the state of forest ecosystems by Gusev Pavel, Tavolzhanskij Alexander, Zolnikov Vladimir, Deniskina Antonina

“…Then linear regression models are trained and the quality of predictions for different sets of variables from the sorted list is compared. …”
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Alert processing based on attack graph and multi-source analyzing by Wei-xin LIU, Kang-feng ZHENG, Bin WU, Yi-xian YANG

“…Current attack graph-based alert correlation cannot deal with graph relation between alerts properly,and a large number of redundant attack paths may arise when trying to find out missing alerts and predict future attacks.A multi-source alert analyzing method was proposed,fully utilizing graph relation and threshold to correlate mapped alerts and eventually reduce false positive rate as well as true negative rate.To improve the speed of the algorithm,a parallel alert processing system (AG-PAP) was proposed.AG-PAP is tested on distributed environment which gets satisfied effec-tiveness and performance.…”
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MODELING ECONOMIC AGENTS’ EXPECTATIONS AS A TOOL OF FORECASTING SHORT-TERM ECONOMIC CYCLES by Leonid A. Elshin, Maxim V. Savushkin

“…The article shows the necessity to develop, substantiate (verify) and test models of cyclic fluctuations of economy built on the basis of such factors, which could have high sensitivity to changes in external and internal environment of the economic system and possess high predictability of cyclic trends. The authors prove that a possible way to resolve the problem is to model economic agents’ expectations and identify trends of their economic development. …”
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