Efficient PAPR reduction algorithm in OFDM based on nonlinear piecewise companding by Zhitong XING, Yun LI, Deyi PENG, Bensi ZHANG, Kaiming LIU, Yuan’an LIU

“…Focusing on the high peak-to-average power ratio （PAPR） problem in orthogonal frequency division multiplexing （OFDM） systems， a generalized hybrid of rayleigh and sine distribution based nonlinear companding algorithm for PAPR reduction in OFDM systems was provided.For the proposed algorithm， signal samples with small amplitudes remain unchanged.For the signal samples with large amplitudes， their probability density function were changed from rayleigh distribution to sine-based distribution.The proposed algorithm can effectively reduce the PAPR， and at the same time， maintain the bit error rate performance and power spectral density performance.Simulation results indicate that with the same PAPR performance， compared with referred companding schemes， the proposed algorithm has lower bit error rate and out of band radiation.…”
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GENETIC ALGORITHM-PID CONTROLLER FOR MODEL ORDER REDUCTION PANTOGRAPHCATENARY SYSTEM by Nasir A. Al-Awad, Izz K. Abboud, Muaayed F. Al-Rawi

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N-Dimensional Reduction Algorithm for Learning from Demonstration Path Planning by Juliana Manrique-Cordoba, Miguel Ángel de la Casa-Lillo, José María Sabater-Navarro

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Reduction algorithm based on supervised discriminant projection for network security data by Fangfang GUO, Hongwu LYU, Weilin REN, Ruini WANG

“…In response to the problem that for dimensionality reduction, traditional manifold learning algorithm did not consider the raw data category information, and the degree of clustering was generally at a low level, a manifold learning dimensionality reduction algorithm with supervised discriminant projection (SDP) was proposed to improve the dimensionality reduction effects of network security data.On the basis of the nearest neighbor matrix, the label information of the raw data category was exploited to construct a supervised discriminant matrix in order to translate unsupervised popular learning into supervised learning.The target was to find a low dimensional projective space with both maximum global divergence matrix and minimum local divergence matrix, ensuring that the same kind of data was concentrated and heterogeneous data was scattered after dimensionality reduction projection.The experimental results show that the SDP algorithm, compared with the traditional dimensionality reduction algorithms, can effectively remove redundant data with low time complexity.Meanwhile the data after dimensionality reduction is more concentrated, and the heterogeneous samples are more dispersed, suitable for the actual network security data analysis model.…”
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A Fast Hybrid Classification Algorithm with Feature Reduction for Medical Images by Hanan Ahmed Hosni Mahmoud, Abeer Abdulaziz AlArfaj, Alaaeldin M. Hafez

“…In this paper, we are introducing a fast hybrid fuzzy classification algorithm with feature reduction for medical images. …”
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EduGuard RetainX: An advanced analytical dashboard for predicting and improving student retention in tertiary education by Nornina J. Dia, Joseph C. Sieras, Suhaina A. Khalid, Amer Hussien T. Macatotong, Jeffrey M. Mondejar, Elizabeth R. Genotiva, Reymark D. Delena

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Predicting Diabetes Mellitus with Machine Learning Techniques by Heba Ahmed Jassim, Omar R. Kadhim, Zahraa Khduair Taha, Johnny Koh Siaw Paw, Yaw Chong Tak, Tiong Sieh Kiong

“…Utilizing machine learning algorithms to analyze appropriate datasets for early disease prediction could prove life-saving. …”
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Comparison of Noise Reduction Algorithms for Optical Coherence Tomography Images of Skin Melanoma by O. O. Myakinin

“…There are almost no systematic comparisons of noise reduction algorithms in the literature.Objective. To obtain comparative test results on a set of ОКТ images of skin melanoma using various noise reduction algorithms.Materials and methods. …”
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Unsupervised Attribute Reduction Algorithms for Multiset-Valued Data Based on Uncertainty Measurement by Xiaoyan Guo, Yichun Peng, Yu Li, Hai Lin

“…We propose unsupervised attribute reduction algorithms for multiset-valued data to address this gap. …”
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DATA MINING ALGORITHMS FOR PREDICTION OF STUDENT TEACHERS’ PERFORMANCE IN ICT: A SYSTEMATIC LITERATURE REVIEW by Juma Habibu Shindo, Mohamedi Mohamedi Mjahidi, Mohamed Dewa Waziri

Subjects: “…data mining algorithms…”
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Utilization in Microgrids through Advanced Predictive Algorithms by K Aravind, Lakhanpal Sorabh, Pushpa Rani K., Khattab Al-Rubaye Taqi Mohammed, Tewari Preeti, Shanmugasundaram Ravivarman

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Algorithmic Literacy and the Role of Librarians in Its Education by Shahnaz Khademizadeh, Mohammad Amin Sekhavatmanesh

“…Objective: Considering the increasing spread of artificial intelligence and its algorithm-oriented nature and the increasing interaction of users with these algorithms in various platforms such as social networks, online stores, and search engines, the present study intends to examine the concept and necessity of algorithmic literacy and, in the following, the role of librarians who are actually specialists in information science in the education and development of this literacy. …”
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Research on the Application of Genetic Algorithm in Physical Education by Haibo Wang

“…A large number of experiments have proved that the proposed algorithm meets all the requirements of physical education very well. …”
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Parallel Attribute Reduction Algorithm for Complex Heterogeneous Data Using MapReduce by Tengfei Zhang, Fumin Ma, Jie Cao, Chen Peng, Dong Yue

“…Thereafter, a quick parallel attribute reduction algorithm using MapReduce was developed. …”
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Regeneration Filter: Enhancing Mosaic Algorithm for Near Salt & Pepper Noise Reduction by Ratko M. Ivković, Ivana M. Milošević, Zoran N. Milivojević

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Unsustainable artificial intelligence and algorithmically facilitated emissions: The case for emissions-reduction-by-design by Jutta Haider, Malte Rödl, James White

“…It introduces the notion of algorithmically facilitated emissions to initiate a shift from a logic of ‘climate collapse by design’ to a logic of ‘emissions reduction by design’. …”
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Improved HLLL Lattice Basis Reduction Algorithm to Solve GNSS Integer Ambiguity by Kezhao Li, Chendong Tian, Yingxiang Jiao, Zhe Yue

“…Compared with the LLL reduction algorithm and HLLL reduction algorithm, the experimental results show that the PHLLL algorithm has higher reduction efficiency and effectiveness. …”
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Optimization Algorithm of Workflow’s Accuracy Based  on Serial Reduction under Constraint Time by LUO Zhi-yong, ZHU Zi-hao, YOU Bo, MIAO Shi-di

“…Finally，in the typical case，the traditional one-way target algorithm and the string reduction algorithm are used to solve the corresponding path respectively， and analyzed the other parameters that affect the performance of SＲA. …”
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Neighborhood conditional mutual information entropy attribute reduction algorithm for hybrid data by Haibo LAN

“…Attribute reduction is an important research content of the rough set theory.Its main purpose is to eliminate irrelevant attributes in information systems, reduce data dimensions and improve data knowledge discovery performance.However, most of the attribute reduction methods based on a rough set do not consider the dependence between attributes, which makes the final attribute reduction result have some redundant attributes.An attribute reduction algorithm based on neighborhood conditional mutual information entropy was proposed.Firstly, based on the traditional neighborhood entropy, a hybrid neighborhood mutual information entropy model and a hybrid neighborhood conditional mutual information entropy model were proposed for hybrid data.Then, the two entropy models were used to evaluate the attribute dependence and attribute heuristic search of the hybrid information system, and an attribute reduction algorithm was designed.Finally, through the experimental analysis of UCI data sets, it was proved that the algorithm had higher attribute reduction performance.…”
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Improved Crosstalk Reduction on Multiview 3D Display by Using BILS Algorithm by Xiaoyan Wang, Chunping Hou

“…In this paper, we present a system-introduced crosstalk measurement method and derive an improved crosstalk reduction method. The proposed measurement method is applied to measure the exact crosstalk among subpixels corresponding to different view images and the obtained results are very effective for crosstalk reduction method. …”
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