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Journal articles on the topic 'Random Network Codes'

Author: Grafiati

Published: 6 September 2023

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1

Gabidulin, E. M., N. I. Pilipchuk, and M. Bossert. "Decoding of random network codes." Problems of Information Transmission 46, no. 4 (2010): 300–320. http://dx.doi.org/10.1134/s0032946010040034.

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Chen, Chao, Hongmei Xie, and Baoming Bai. "Layered subspace codes for random network coding." Transactions on Emerging Telecommunications Technologies 26, no. 3 (2013): 461–68. http://dx.doi.org/10.1002/ett.2648.

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3

Riemensberger, Maximilian, Yalin Sagduyu, Michael Honig, and Wolfgang Utschick. "Training overhead for decoding random linear network codes in wireless networks." IEEE Journal on Selected Areas in Communications 27, no. 5 (2009): 729–37. http://dx.doi.org/10.1109/jsac.2009.090613.

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Li, Ye, Jun Zhu, and Zhihua Bao. "Sparse Random Linear Network Coding With Precoded Band Codes." IEEE Communications Letters 21, no. 3 (2017): 480–83. http://dx.doi.org/10.1109/lcomm.2016.2632731.

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5

Wang, Shiheng, Quan Zhou, Siyuan Yang, Chaoyuan Bai, and Heng Liu. "Wireless Communication Strategy with BATS Codes for Butterfly Network." Journal of Physics: Conference Series 2218, no. 1 (2022): 012003. http://dx.doi.org/10.1088/1742-6596/2218/1/012003.

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Abstract In this paper, two transmission schemes for batched sparse(BATS) codes based on a multicast protocol in a butterfly network are studied. For both of the schemes, a source file is first segmented into several packets at the source node, which are then coded with outer coder of the BATS codes to generate potentially unlimited batches. Rather than the linear network, in which the packets are directly transmitted to the next node, the packets will be forwarded to multiple nodes in the butterfly network. All the intermediate nodes which receive the packets recode them with random linear ne

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Chen, Siguang, Meng Wu, and Weifeng Lu. "Compressed error and erasure correcting codes via rank-metric codes in random network coding." International Journal of Communication Systems 25, no. 11 (2011): 1398–414. http://dx.doi.org/10.1002/dac.1316.

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7

Nazer, Bobak, and Michael Gastpar. "The case for structured random codes in network capacity theorems." European Transactions on Telecommunications 19, no. 4 (2008): 455–74. http://dx.doi.org/10.1002/ett.1284.

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LARASATI, SOLICHAH, and KHOIRUN NI’AMAH. "Sub-Optimal Degree Distribution untuk Prioritas Komunikasi Manusia menggunakan Proyeksi EXIT Chart pada Jaringan Masa Depan." ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika 7, no. 3 (2019): 442. http://dx.doi.org/10.26760/elkomika.v7i3.442.

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ABSTRAKPada jaringan masa depan melibatkan komunikasi antara mesin dan manusia. Penelitian ini mengusulkan konsep coding dalam jaringan menggunakan Maximum Distance Separable (MDS) codes. Desain sub-optimal degree distribution untuk memprioritaskan manusia menggunakan proyeksi EXIT Chart. Pada penelitian ini dasar dari skema multiple akses untuk jaringan super-padat menggunakan Coded Random Access (CRA). Usulan model jaringan menggunakan Binary Erasure Channel (BEC). Evaluasi performansi untuk grup manusia dan mesin diukur berdasarkan throughput dan packet-loss-rate dan hasilnya juga dibuktika

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Wachter-Zeh, Antonia, Markus Stinner, and Vladimir Sidorenko. "Convolutional Codes in Rank Metric With Application to Random Network Coding." IEEE Transactions on Information Theory 61, no. 6 (2015): 3199–213. http://dx.doi.org/10.1109/tit.2015.2424930.

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Xiao, Ming, Muriel Medard, and Tor Aulin. "Cross-Layer Design of Rateless Random Network Codes for Delay Optimization." IEEE Transactions on Communications 59, no. 12 (2011): 3311–22. http://dx.doi.org/10.1109/tcomm.2011.112311.100366.

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11

Li, Ye, Wai-Yip Chan, and Steven D. Blostein. "On Design and Efficient Decoding of Sparse Random Linear Network Codes." IEEE Access 5 (2017): 17031–44. http://dx.doi.org/10.1109/access.2017.2741972.

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Mao, Licheng, Shenghao Yang, Xuan Huang, and Yanyan Dong. "Design and Analysis of Systematic Batched Network Codes." Entropy 25, no. 7 (2023): 1055. http://dx.doi.org/10.3390/e25071055.

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Systematic codes are of important practical interest for communications. Network coding, however, seems to conflict with systematic codes: although the source node can transmit message packets, network coding at the intermediate network nodes may significantly reduce the number of message packets received by the destination node. Is it possible to obtain the benefit of network coding while preserving some properties of the systematic codes? In this paper, we study the systematic design of batched network coding, which is a general network coding framework that includes random linear network co

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13

Si, Jing Jing. "A Hierarchical Multicast Scheme for Heterogeneous Receivers." Advanced Materials Research 108-111 (May 2010): 57–62. http://dx.doi.org/10.4028/www.scientific.net/amr.108-111.57.

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We investigate inter-session network coding for networks with heterogeneous receivers in this paper. Based on layered source coding, we define the hierarchical inter-layer random network codes, and propose a hierarchical multicast scheme. Moreover, we compare our hierarchical multicast scheme with the layered multicast schemes in theory and with simulations. Simulation results show that our hierarchical multicast scheme can achieve the optimal aggregate throughput for some networks where the layered multicast schemes are suboptimal.

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Emran, A., M. Elsabrouty, O. Muta, and H. Furukawa. "ACK based partial random selection encoding for uplink distributed LDPC network codes." Electronics Letters 51, no. 17 (2015): 1328–29. http://dx.doi.org/10.1049/el.2015.2132.

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15

Chen, Siguang, Meng Wu, and Weifeng Lu. "Secret Error Control Codes Against Malicious Attacks in Random Multisource Network Coding." Wireless Personal Communications 69, no. 4 (2012): 1847–64. http://dx.doi.org/10.1007/s11277-012-0666-7.

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Do-Duy, Tan, and Maria Ángeles Vázquez-Castro. "Finite-length performance comparison of network codes using random vs Pascal matrices." AEU - International Journal of Electronics and Communications 114 (February 2020): 153012. http://dx.doi.org/10.1016/j.aeue.2019.153012.

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Nazir, Sajid, Vladimir Stanković, Ivan Andonović, and Dejan Vukobratović. "Application Layer Systematic Network Coding for Sliced H.264/AVC Video Streaming." Advances in Multimedia 2012 (2012): 1–9. http://dx.doi.org/10.1155/2012/916715.

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Application Layer Forward Error Correction (AL-FEC) with rateless codes can be applied to protect the video data over lossy channels. Expanding Window Random Linear Codes (EW RLCs) are a flexible unequal error protection fountain coding scheme which can provide prioritized data transmission. In this paper, we propose a system that exploits systematic EW RLC for H.264/Advanced Video Coding (AVC) slice-partitioned data. The system prioritizes slices based on their PSNR contribution to reconstruction as well as temporal significance. Simulation results demonstrate usefulness of using relative sli

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Bioglio, Valerio, Marco Grangetto, Rossano Gaeta, and Matteo Sereno. "A practical Random Network Coding scheme for data distribution on peer-to-peer networks using rateless codes." Performance Evaluation 70, no. 1 (2013): 1–13. http://dx.doi.org/10.1016/j.peva.2012.09.001.

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19

Gallego, Antonio-Javier, Antonio Pertusa, and Jorge Calvo-Zaragoza. "Improving Convolutional Neural Networks’ Accuracy in Noisy Environments Using k-Nearest Neighbors." Applied Sciences 8, no. 11 (2018): 2086. http://dx.doi.org/10.3390/app8112086.

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We present a hybrid approach to improve the accuracy of Convolutional Neural Networks (CNN) without retraining the model. The proposed architecture replaces the softmax layer by a k-Nearest Neighbor (kNN) algorithm for inference. Although this is a common technique in transfer learning, we apply it to the same domain for which the network was trained. Previous works show that neural codes (neuron activations of the last hidden layers) can benefit from the inclusion of classifiers such as support vector machines or random forests. In this work, our proposed hybrid CNN + kNN architecture is eval

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Wang, Ming, Yong Li, Rui Liu, Huihui Wu, Youqiang Hu, and Francis C. M. Lau. "Decoding Quadratic Residue Codes Using Deep Neural Networks." Electronics 11, no. 17 (2022): 2717. http://dx.doi.org/10.3390/electronics11172717.

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In this paper, a low-complexity decoder based on a neural network is proposed to decode binary quadratic residue (QR) codes. The proposed decoder is based on the neural min-sum algorithm and the modified random redundant decoder (mRRD) algorithm. This new method has the same asymptotic time complexity as the min-sum algorithm, which is much lower than the difference on syndromes (DS) algorithm. Simulation results show that the proposed algorithm achieves a gain of more than 0.4 dB when compared to the DS algorithm. Furthermore, a simplified approach based on trapping sets is applied to reduce

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21

Sundaram, Varun, Rosita Zakeri, Klaus K. Witte, and Jennifer kathleen Quint. "Development of algorithms for determining heart failure with reduced and preserved ejection fraction using nationwide electronic healthcare records in the UK." Open Heart 9, no. 2 (2022): e002142. http://dx.doi.org/10.1136/openhrt-2022-002142.

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BackgroundDetermining heart failure (HF) phenotypes in routine electronic health records (EHR) is challenging. We aimed to develop and validate EHR algorithms for identification of specific HF phenotypes, using Read codes in combination with selected patient characteristics.MethodsWe used The Healthcare Improvement Network (THIN). The study population included a random sample of individuals with HF diagnostic codes (HF with reduced ejection fraction (HFrEF), HF with preserved ejection fraction (HFpEF) and non-specific HF) selected from all participants registered in the THIN database between 1

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22

Zhang, Wenyue, and Min Zhu. "Weighted BATS Codes with LDPC Precoding." Entropy 25, no. 4 (2023): 686. http://dx.doi.org/10.3390/e25040686.

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Batched Sparse (BATS) codes are a type of network coding scheme that use a combination of random linear network coding (RLNC) and fountain coding to enhance the reliability and efficiency of data transmission. In order to achieve unequal error protection for different data, researchers have proposed unequal error protection BATS (UEP-BATS) codes. However, current UEP-BATS codes suffer from high error floors in their decoding performance, which restricts their practical applications. To address this issue, we propose a novel UEP-BATS code scheme that employs a precoding stage prior to the weigh

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23

Sun, Yu Qiang, Xiao Kang Wang, Yu Wan Gu, and Qiang Zhu. "Study of RFID Anti-Collision Based on Token Ring Network Model." Applied Mechanics and Materials 182-183 (June 2012): 1013–16. http://dx.doi.org/10.4028/www.scientific.net/amm.182-183.1013.

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Models of Computer Network Anti-collision can’t be used in the area of RFID Anti-collision Algorithm, because the limit of tag’s structure. The paper discusses the anti-collision model of computer network----Token Ring Network Model, which lets the orthogonal codes act as token, proposed a strategy for RFID Anti-collision. Currently, the popular RFID Anti-collision Algorithms are based on the idea of random access, when collision happens, the reader tells the collision tags to send ID, waiting for any time. When the number of tag is large, two or more tags will be waiting for the same random t

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24

Rinke, Michael L., Dominique Jan, Janelle Nassim, Jaeun Choi, and Steven J. Choi. "Surgical Site Infections Following Pediatric Ambulatory Surgery: An Epidemiologic Analysis." Infection Control & Hospital Epidemiology 37, no. 8 (2016): 931–38. http://dx.doi.org/10.1017/ice.2016.98.

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OBJECTIVETo identify surgical site infection (SSI) rates following pediatric ambulatory surgery, SSI outcomes and risk factors, and sensitivity and specificity of SSI administrative billing codes.DESIGNRetrospective chart review of pediatric ambulatory surgeries with International Classification of Disease, Ninth Revision (ICD-9) codes for SSI, and a systematic random sampling of 5% of surgeries without SSI ICD-9 codes, all adjudicated for SSI on the basis of an ambulatory-adapted National Healthcare Safety Network definition.SETTINGUrban pediatric tertiary care center April 1, 2009-March 31,

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25

Didier, Gilles, Christine Brun, and Anaïs Baudot. "Identifying communities from multiplex biological networks." PeerJ 3 (December 22, 2015): e1525. http://dx.doi.org/10.7717/peerj.1525.

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Various biological networks can be constructed, each featuring gene/protein relationships of different meanings (e.g., protein interactions or gene co-expression). However, this diversity is classically not considered and the different interaction categories are usually aggregated in a single network. The multiplex framework, where biological relationships are represented by different network layers reflecting the various nature of interactions, is expected to retain more information. Here we assessed aggregation, consensus and multiplex-modularity approaches to detect communities from multipl

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26

Gadouleau, Maximilien, and Zhiyuan Yan. "Packing and Covering Properties of Subspace Codes for Error Control in Random Linear Network Coding." IEEE Transactions on Information Theory 56, no. 5 (2010): 2097–108. http://dx.doi.org/10.1109/tit.2010.2043780.

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27

Yang, Ximing, Yuan Wu, Kaiyi Zhang, and Cheng Jin. "CPCGAN: A Controllable 3D Point Cloud Generative Adversarial Network with Semantic Label Generating." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 4 (2021): 3154–62. http://dx.doi.org/10.1609/aaai.v35i4.16425.

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Generative Adversarial Networks (GAN) are good at generating variant samples of complex data distributions. Generating a sample with certain properties is one of the major tasks in the real-world application of GANs. In this paper, we propose a novel generative adversarial network to generate 3D point clouds from random latent codes, named Controllable Point Cloud Generative Adversarial Network(CPCGAN). A two-stage GAN framework is utilized in CPCGAN and a sparse point cloud containing major structural information is extracted as the middle-level information between the two stages. With their

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28

Khalil, Amaad, Nasruminallah, Irfan Ahmed, and Salman Ilahi Siddiqui. "Design of Robust Video Transmission System by Using Efficient Forward Error Correction Scheme." Proceedings of the Pakistan Academy of Sciences: A. Physical and Computational Sciences 58, no. 4 (2022): 27–34. http://dx.doi.org/10.53560/ppasa(58-4)767.

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The advent of modern digital technologies has made multimedia communication systems one of the most demanding technologies of the time. The use of available bandwidth for efficient and errorless multimedia communication is the key challenge for the wireless communication research community. However, a wireless network has the disadvantage of being prone to random channel noise and data contamination. This paper proposes a robust video transmission framework by using an efficient forward error correction technique. In this work, the experimental performance of widely used forward error correcti

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29

Long, Yahui, Min Wu, Chee Keong Kwoh, Jiawei Luo, and Xiaoli Li. "Predicting human microbe–drug associations via graph convolutional network with conditional random field." Bioinformatics 36, no. 19 (2020): 4918–27. http://dx.doi.org/10.1093/bioinformatics/btaa598.

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Abstract Motivation Human microbes play critical roles in drug development and precision medicine. How to systematically understand the complex interaction mechanism between human microbes and drugs remains a challenge nowadays. Identifying microbe–drug associations can not only provide great insights into understanding the mechanism, but also boost the development of drug discovery and repurposing. Considering the high cost and risk of biological experiments, the computational approach is an alternative choice. However, at present, few computational approaches have been developed to tackle th

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30

Panyapanuwat, Petcharat, Suwatchai Kamonsantiroj, and Luepol Pipanmaekaporn. "Similarity-preserving hash for content-based audio retrieval using unsupervised deep neural networks." International Journal of Electrical and Computer Engineering (IJECE) 11, no. 1 (2021): 879. http://dx.doi.org/10.11591/ijece.v11i1.pp879-891.

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Due to its efficiency in storage and search speed, binary hashing has become an attractive approach for a large audio database search. However, most existing hashing-based methods focus on data-independent scheme where random linear projections or some arithmetic expression are used to construct hash functions. Hence, the binary codes do not preserve the similarity and may degrade the search performance. In this paper, an unsupervised similarity-preserving hashing method for content-based audio retrieval is proposed. Different from data-independent hashing methods, we develop a deep network to

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31

Kamal, Md Sarwar, and Mohammad Ibrahim Khan. "Chapman–Kolmogorov equations for global PPIs with Discriminant-EM." International Journal of Biomathematics 07, no. 05 (2014): 1450053. http://dx.doi.org/10.1142/s1793524514500533.

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Ongoing improvements in Computational Biology research have generated massive amounts of Protein–Protein Interactions (PPIs) dataset. In this regard, the availability of PPI data for several organisms provoke the discovery of computational methods for measurements, analysis, modeling, comparisons, clustering and alignments of biological data networks. Nevertheless, fixed network comparison is computationally stubborn and as a result several methods have been used instead. We illustrate a probabilistic approach among proteins nodes that are part of various networks by using Chapman–Kolmogorov (

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32

Ngeth, Rithea, Brian Kurkoski, Yuto Lim, and Yasuo Tan. "A Design of Overlapped Chunked Code over Compute-and-Forward for Multi-Source Multi-Relay Networks." Sensors 18, no. 10 (2018): 3225. http://dx.doi.org/10.3390/s18103225.

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This paper investigates the design of overlapped chunked codes (OCC) for multi-source multi-relay networks where a physical-layer network coding approach, compute-and-forward (CF) based on nested lattice codes (NLC), is applied for the simultaneous transmissions from the sources to the relays. This code is called OCC/CF. In this paper, OCC is applied before NLC before transmitting for each source. Random linear network coding is applied within each chunk. A decodability condition to design OCC/CF is provided. In addition, an OCC with a contiguously overlapping, but non-rounded-end fashion is e

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33

Gicev, Spiro, Lloyd C. L. Hollenberg, and Muhammad Usman. "A scalable and fast artificial neural network syndrome decoder for surface codes." Quantum 7 (July 12, 2023): 1058. http://dx.doi.org/10.22331/q-2023-07-12-1058.

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Surface code error correction offers a highly promising pathway to achieve scalable fault-tolerant quantum computing. When operated as stabilizer codes, surface code computations consist of a syndrome decoding step where measured stabilizer operators are used to determine appropriate corrections for errors in physical qubits. Decoding algorithms have undergone substantial development, with recent work incorporating machine learning (ML) techniques. Despite promising initial results, the ML-based syndrome decoders are still limited to small scale demonstrations with low latency and are incapabl

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34

Allahgholi, Milad, Hossein Rahmani, Delaram Javdani, et al. "DDREL: From drug-drug relationships to drug repurposing." Intelligent Data Analysis 26, no. 1 (2022): 221–37. http://dx.doi.org/10.3233/ida-215745.

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Analyzing the relationships among various drugs is an essential issue in the field of computational biology. Different kinds of informative knowledge, such as drug repurposing, can be extracted from drug-drug relationships. Scientific literature represents a rich source for the retrieval of knowledge about the relationships between biological concepts, mainly drug-drug, disease-disease, and drug-disease relationships. In this paper, we propose DDREL as a general-purpose method that applies deep learning on scientific literature to automatically extract the graph of syntactic and semantic relat

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35

Kim, Junhong, Hyungseok Kim, Jaesun Park, Kyounghyun Mo, and Pilsung Kang. "Bin2Vec: A Better Wafer Bin Map Coloring Scheme for Comprehensible Visualization and Effective Bad Wafer Classification." Applied Sciences 9, no. 3 (2019): 597. http://dx.doi.org/10.3390/app9030597.

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A wafer bin map (WBM), which is the result of an electrical die-sorting test, provides information on which bins failed what tests, and plays an important role in finding defective wafer patterns in semiconductor manufacturing. Current wafer inspection based on WBM has two problems: good/bad WBM classification is performed by engineers and the bin code coloring scheme does not reflect the relationship between bin codes. To solve these problems, we propose a neural network-based bin coloring method called Bin2Vec to make similar bin codes are represented by similar colors. We also build a convo

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36

Tran, Steven, Luke Rasmussen, Jennifer Pacheco, et al. "802 An electronic health record-based approach to identify and characterize patients with immune checkpoint inhibitor-associated arthritis." Journal for ImmunoTherapy of Cancer 9, Suppl 2 (2021): A838—A839. http://dx.doi.org/10.1136/jitc-2021-sitc2021.802.

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BackgroundImmune checkpoint inhibitors (ICIs) are a pillar of cancer therapy with demonstrated efficacy in a variety of malignancies. However, they are associated with immune-related adverse events (irAEs) that affect many organ systems with varying severity, inhibiting patient quality of life and in some cases the ability to continue immunotherapy. Research into irAEs is nascent, and identifying patients with adverse events poses a critical challenge for future research efforts and patient care. This study's objective was to develop an electronic health record (EHR)-based model to identify an

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37

Partala, Juha. "Semantically Secure Symmetric Encryption with Error Correction for Distributed Storage." Security and Communication Networks 2017 (2017): 1–10. http://dx.doi.org/10.1155/2017/4321296.

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A distributed storage system (DSS) is a fundamental building block in many distributed applications. It applies linear network coding to achieve an optimal tradeoff between storage and repair bandwidth when node failures occur. Additively homomorphic encryption is compatible with linear network coding. The homomorphic property ensures that a linear combination of ciphertext messages decrypts to the same linear combination of the corresponding plaintext messages. In this paper, we construct a linearly homomorphic symmetric encryption scheme that is designed for a DSS. Our proposal provides simu

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Shahapur, Salma S., Rajashri Khanai, and Dattaprasad A. Torse. "Performance Analysis of Error Control Codes for Underwater Wireless Acoustic Communication." Trends in Sciences 19, no. 3 (2022): 2164. http://dx.doi.org/10.48048/tis.2022.2164.

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In underwater acoustic communication, the information transmitted from 1 sensor node to another is corrupted due to errors persuaded by the noisy channel and other issues. To reduce the bit error rate, it is essential to propose suitable error regulator structure. In this paper, we simulate the performance analysis of Orthogonal Frequency Division Multiplexing Interleaver Division Multiple Access Multiple Input Multiple Output scheme with different channel codes to improve bit error rate performance. Bit error rate and consumed power are measured by communicating arbitrarily generated informat

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Gao, Shang, Michael T. Young, John X. Qiu, et al. "Hierarchical attention networks for information extraction from cancer pathology reports." Journal of the American Medical Informatics Association 25, no. 3 (2017): 321–30. http://dx.doi.org/10.1093/jamia/ocx131.

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Abstract Objective We explored how a deep learning (DL) approach based on hierarchical attention networks (HANs) can improve model performance for multiple information extraction tasks from unstructured cancer pathology reports compared to conventional methods that do not sufﬁciently capture syntactic and semantic contexts from free-text documents. Materials and Methods Data for our analyses were obtained from 942 deidentiﬁed pathology reports collected by the National Cancer Institute Surveillance, Epidemiology, and End Results program. The HAN was implemented for 2 information extraction tas

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Liu, Zhenpeng, Xianwei Yang, Shichen Zhang, Yi Liu, Yonggang Zhao, and Weihua Zheng. "Automatic Generation of Test Cases Based on Genetic Algorithm and RBF Neural Network." Mobile Information Systems 2022 (May 23, 2022): 1–9. http://dx.doi.org/10.1155/2022/1489063.

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Software testing plays an important role in improving the quality of software, but the design of test cases requires a lot of manpower, material resources, and time, and designers tend to be subjective when designing test cases. To solve this problem and make the test cases have objectivity and greater coverage, a branch coverage test case automatic generation method based on genetic algorithm and RBF neural network algorithm (GAR) is proposed. In terms of test case generation, based on the genetic algorithm optimized in this paper, a certain number of test case samples are randomly selected t

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Chung, Moo K., Hyekyoung Lee, Alex DiChristofano, Hernando Ombao, and Victor Solo. "Exact topological inference of the resting-state brain networks in twins." Network Neuroscience 3, no. 3 (2019): 674–94. http://dx.doi.org/10.1162/netn_a_00091.

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A cycle in a brain network is a subset of a connected component with redundant additional connections. If there are many cycles in a connected component, the connected component is more densely connected. Whereas the number of connected components represents the integration of the brain network, the number of cycles represents how strong the integration is. However, it is unclear how to perform statistical inference on the number of cycles in the brain network. In this study, we present a new statistical inference framework for determining the significance of the number of cycles through the K

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42

Debreceny, Roger S., Tawei Wang, and Mi (Jamie) Zhou. "Research in Social Media: Data Sources and Methodologies." Journal of Information Systems 33, no. 1 (2017): 1–28. http://dx.doi.org/10.2308/isys-51984.

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ABSTRACT This paper examines both the opportunities and limitations in the use of social media for accounting research. Given the dynamic nature of social media and the richness of the context, there are opportunities for researchers to directly observe communication and information exchanges, typically within the context of an observable social network. The paper provides an overview of the characteristics of four commonly used social network sites (SNSs): Facebook, Twitter, LinkedIn, and StockTwits. The data collection details, opportunities, and limitations are set out. The paper also provi

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43

Kim, So Yeon, Eun Kyung Choe, Manu Shivakumar, Dokyoon Kim, and Kyung-Ah Sohn. "Multi-layered network-based pathway activity inference using directed random walks: application to predicting clinical outcomes in urologic cancer." Bioinformatics 37, no. 16 (2021): 2405–13. http://dx.doi.org/10.1093/bioinformatics/btab086.

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Abstract Motivation To better understand the molecular features of cancers, a comprehensive analysis using multi-omics data has been conducted. In addition, a pathway activity inference method has been developed to facilitate the integrative effects of multiple genes. In this respect, we have recently proposed a novel integrative pathway activity inference approach, iDRW and demonstrated the effectiveness of the method with respect to dichotomizing two survival groups. However, there were several limitations, such as a lack of generality. In this study, we designed a directed gene–gene graph u

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Quenet, Brigitte, and David Horn. "The Dynamic Neural Filter: A Binary Model of Spatiotemporal Coding." Neural Computation 15, no. 2 (2003): 309–29. http://dx.doi.org/10.1162/089976603762552933.

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We describe and discuss the properties of a binary neural network that can serve as a dynamic neural filter (DNF), which maps regions of input space into spatiotemporal sequences of neuronal activity. Both deterministic and stochastic dynamics are studied, allowing the investigation of the stability of spatiotemporal sequences under noisy conditions. We define a measure of the coding capacity of a DNF and develop an algorithm for constructing a DNF that can serve as a source of given codes. On the basis of this algorithm, we suggest using a minimal DNF capable of generating observed sequences

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Wenderfer, Scott E., Joyce C. Chang, Amy Goodwin Davies, et al. "Using a Multi-Institutional Pediatric Learning Health System to Identify Systemic Lupus Erythematosus and Lupus Nephritis." Clinical Journal of the American Society of Nephrology 17, no. 1 (2021): 65–74. http://dx.doi.org/10.2215/cjn.07810621.

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Background and objectivesPerforming adequately powered clinical trials in pediatric diseases, such as SLE, is challenging. Improved recruitment strategies are needed for identifying patients.Design, setting, participants, & measurementsElectronic health record algorithms were developed and tested to identify children with SLE both with and without lupus nephritis. We used single-center electronic health record data to develop computable phenotypes composed of diagnosis, medication, procedure, and utilization codes. These were evaluated iteratively against a manually assembled database of p

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Zhang, Yuan Yuan, Shi Song Yang, and Peng Dong. "The Construction of Index System and Comprehensive Evaluation Model Based on Improved Genetic Algorithm and Fuzzy Neural Network." Applied Mechanics and Materials 20-23 (January 2010): 1229–35. http://dx.doi.org/10.4028/www.scientific.net/amm.20-23.1229.

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Artificial neural network(ANN) and genetic algorithm (GA) have both prevalent uses in large area. Along with the development of technology a method based on the combination of Artificial neural network (ANN) and genetic algorithm (GA) aroused. In such a case, the paper uses the combination of Artificial neural network(ANN) and genetic algorithm (GA) to solve the problems of costructing index system and comprehensive evaluation. Firstly establishing feedforward neural network model and make sure about the input and output variables. Secondly improved genetic algorithm is used to solve the probl

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Denburg, Michelle R., Hanieh Razzaghi, L. Charles Bailey, et al. "Using Electronic Health Record Data to Rapidly Identify Children with Glomerular Disease for Clinical Research." Journal of the American Society of Nephrology 30, no. 12 (2019): 2427–35. http://dx.doi.org/10.1681/asn.2019040365.

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BackgroundThe rarity of pediatric glomerular disease makes it difficult to identify sufficient numbers of participants for clinical trials. This leaves limited data to guide improvements in care for these patients.MethodsThe authors developed and tested an electronic health record (EHR) algorithm to identify children with glomerular disease. We used EHR data from 231 patients with glomerular disorders at a single center to develop a computerized algorithm comprising diagnosis, kidney biopsy, and transplant procedure codes. The algorithm was tested using PEDSnet, a national network of eight chi

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Henzler, Philipp, Valentin Deschaintre, Niloy J. Mitra, and Tobias Ritschel. "Generative modelling of BRDF textures from flash images." ACM Transactions on Graphics 40, no. 6 (2021): 1–13. http://dx.doi.org/10.1145/3478513.3480507.

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We learn a latent space for easy capture, consistent interpolation, and efficient reproduction of visual material appearance. When users provide a photo of a stationary natural material captured under flashlight illumination, first it is converted into a latent material code. Then, in the second step, conditioned on the material code, our method produces an infinite and diverse spatial field of BRDF model parameters (diffuse albedo, normals, roughness, specular albedo) that subsequently allows rendering in complex scenes and illuminations, matching the appearance of the input photograph. Techn

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Gao, Youtao, Guocang Dong, and Limin Jin. "Design of An Intelligent Demodulation Method for X-ray Spectrum Communication." Journal of Physics: Conference Series 2447, no. 1 (2023): 012001. http://dx.doi.org/10.1088/1742-6596/2447/1/012001.

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Abstract X-ray communication based on X-ray spectrum modulation information is a novel communication method, which can effectively improve communication ability and anti-interference ability. In this paper, four characteristic X-rays are chosen to modulate information. The influence of channel attenuation, random noise in space, and miss-shooting rate caused by adjacent targets are discussed. Based on error-correcting output codes and a 10-fold cross-validation method, a neural network intelligent classifier is designed to realize intelligent information demodulation. Simulation results show t

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Najafi, Fatemeh, Masoud Kaveh, Diego Martín, and Mohammad Reza Mosavi. "Deep PUF: A Highly Reliable DRAM PUF-Based Authentication for IoT Networks Using Deep Convolutional Neural Networks." Sensors 21, no. 6 (2021): 2009. http://dx.doi.org/10.3390/s21062009.

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Traditional authentication techniques, such as cryptographic solutions, are vulnerable to various attacks occurring on session keys and data. Physical unclonable functions (PUFs) such as dynamic random access memory (DRAM)-based PUFs are introduced as promising security blocks to enable cryptography and authentication services. However, PUFs are often sensitive to internal and external noises, which cause reliability issues. The requirement of additional robustness and reliability leads to the involvement of error-reduction methods such as error correction codes (ECCs) and pre-selection scheme

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