Relevant bibliographies by topics / Binary input

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Binary input'

Author: Grafiati
Published: 13 April 2024

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Journal articles on the topic "Binary input"

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HOLDERBAUM, William. "Control of Binary Input Systems." IOSR Journal of Engineering 02, no. 12 (2012): 01–15. http://dx.doi.org/10.9790/3021-021210115.

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Vieira, M. A., M. Vieira, V. Silva, P. Louro, and M. Barata. "Optoelectronic logic functions using optical bias controlled SiC multilayer devices." MRS Proceedings 1536 (2013): 91–96. http://dx.doi.org/10.1557/opl.2013.703.

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ABSTRACTThe purpose of this paper is the design of simple combinational optoelectronic circuit based on SiC technology, able to act simultaneously as a 4-bit binary encoder or a binary decoder in a 4-to-16 line configurations. The 4-bit binary encoder takes all the data inputs, one by one, and converts them to a single encoded output. The binary decoder decodes a binary input pattern to a decimal output code.The optoelectronic circuit is realized using a a-SiC:H double pin/pin photodetector with two front and back optical gates activated trough steady state violet background. Four red, green, blue and violet input channels impinge on the device at different bit sequences allowing 16 possible inputs. The device selects, through the violet background, one of the sixteen possible input logic signals and sends it to the output.Results show that the device acts as a reconfigurable active filter and allows optical switching and optoelectronic logic functions development. A relationship between the optical inputs and the corresponding digital output levels is established. A binary color weighted code that takes into account the specific weights assigned to each bit position establish the optoelectronic functions. A truth table of an encoder that performs 16-to-1 multiplexer (MUX) function is presented.
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Anashin, Vladimir. "Discreteness causes waves." Facta universitatis - series: Physics, Chemistry and Technology 14, no. 3 (2016): 143–96. http://dx.doi.org/10.2298/fupct1603143a.

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In the paper, we show that matter waves can be derived from discreteness and causality. Namely we show that matter waves can naturally be ascribed to finite discrete causal systems, the Mealy automata having binary input/output which are bit sequences. If assign real numerical values (?measured quantities?) to bit sequences, the waves arise as a correspondence between the numerical values of input sequences (?impacts?) and output sequences (?system-evoked responses?). We show that among all discrete causal systems with arbitrary (not necessarily binary) inputs/outputs, only the ones with binary input/output can be ascribed to matter waves ?(x,t) = ei(kx??t).
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Rakitin, Vladimir, Sergey Rusakov, and Sergey Ulyanov. "The Coupled Reactance-Less Memristor Based Relaxation Oscillators for Binary Oscillator Networks." Micromachines 14, no. 2 (2023): 365. http://dx.doi.org/10.3390/mi14020365.

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This paper discusses the application of coupled reactance-less memristor-based oscillators (MBO) with binary output signals in oscillatory networks. A class of binary-coupled memristor oscillators provides simple integration with standard CMOS logic elements. Сombining MBOs with binary logic elements ensures the operation of complex information processing algorithms. The analysis of the simplest networks based on MBOs is performed. The typical reactance-less MBO with current and potential inputs is considered. The output responses for input control signals are analyzed. It is shown that the current input signal impacts primarily the rate of memristor resistance variation, while the potential input signal changes the thresholds. The exploit of the potential input for the synchronization of coupled MBOs and current control input in order to provide the necessary encoding of information is suggested. The example of the application of coupled MBOs in oscillatory networks is given, and results of simulation are presented.
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Xu, Luhang, Liangze Yin, Wei Dong, Weixi Jia, and Yongjun Li. "Expediting Binary Fuzzing with Symbolic Analysis." International Journal of Software Engineering and Knowledge Engineering 28, no. 11n12 (2018): 1701–18. http://dx.doi.org/10.1142/s0218194018400247.

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Fuzzing is an important method for binary vulnerability mining. It can analyze binary programs without their source codes, which is not easy to do by other technologies. But due to the blindness of input generation, binary fuzzing often falls into traps for a long time when the new mutated inputs cannot generate unexplored paths. In this paper, we propose an efficient and flexible fuzzing framework named Tinker. It defines the growth rate of path coverage to measure the current state of fuzzing. If the fuzzing falls into low-speed or blocked states, a symbolic analysis procedure is invoked to generate a new input which can help the fuzzing jump out of the trap. In the symbolic analysis procedure, we employ dynamic execution to track the traversed nodes. The untraversed branches are then identified according to the recorded data of American Fuzzy Lop (AFL) [M. Zalewski, American Fuzzy Lop (2014), http://lcamtuf.coredump.cx/afl/ ]. At last, we employ control flow graph (CFG) to construct complete paths to these branches and a new input is generated using symbolic execution. Moreover, to expedite the detection of vulnerabilities, we generate inputs which trigger more high-risk system calls first, such that the possibility of finding vulnerabilities can be improved. Tinker has been implemented and the experiments on DARPA CGC benchmark show that Tinker is more efficient in vulnerability mining than state-of-the-art binary vulnerability mining tools.
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Yum, Bong-Jin, and Seong-Jun Kim. "On parameter design of binary-input-and-binary-output dynamic systems." Quality and Reliability Engineering International 9, no. 6 (1993): 471–76. http://dx.doi.org/10.1002/qre.4680090603.

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Gurevich, Yuri, and Saharon Shelah. "Time polynomial in input or output." Journal of Symbolic Logic 54, no. 3 (1989): 1083–88. http://dx.doi.org/10.2307/2274767.

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AbstractWe introduce the class PIO of functions computable in time that is polynomial in max {the length of input, the length of output}, observe that there is no notation system for total PIO functions but there are notation systems for partial PIO functions, and give an algebra of partial PIO functions from binary strings to binary strings.
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LEPORATI, ALBERTO, CLAUDIO ZANDRON, and MIGUEL A. GUTIÉRREZ-NARANJO. "P SYSTEMS WITH INPUT IN BINARY FORM." International Journal of Foundations of Computer Science 17, no. 01 (2006): 127–46. http://dx.doi.org/10.1142/s0129054106003735.

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Current P systems which solve NP–complete numerical problems represent the instances of the problems in unary notation. However, in classical complexity theory, based upon Turing machines, switching from binary to unary encoded instances generally corresponds to simplify the problem. In this paper we show that, when working with P systems, we can assume without loss of generality that instances are expressed in binary notation. More precisely, we propose a simple method to encode binary numbers using multisets, and a family of P systems which transforms such multisets into the usual unary notation. Such a family could thus be composed with the unary P systems currently proposed in the literature to obtain (uniform) families of P systems which solve NP–complete numerical problems with instances encoded in binary notation. We introduce also a framework which can be used to design uniform families of P systems which solve NP–complete problems (both numerical and non-numerical) working directly on binary encoded instances, i.e., without first transforming them to unary notation. We illustrate our framework by designing a family of P systems which solves the 3-SAT problem. Next, we discuss the modifications needed to obtain a family of P systems which solves the PARTITION numerical problem.
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Kurkoski, Brian M., and Hideki Yagi. "Quantization of Binary-Input Discrete Memoryless Channels." IEEE Transactions on Information Theory 60, no. 8 (2014): 4544–52. http://dx.doi.org/10.1109/tit.2014.2327016.

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Horn, D. "Frustrated spin Hamiltonians with binary input vectors." Physical Review A 33, no. 4 (1986): 2595–601. http://dx.doi.org/10.1103/physreva.33.2595.

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Dissertations / Theses on the topic "Binary input"

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Ozkan, Ugur. "Application of the constrained implicants set concept to the minimization of binary functions." Thesis, Monterey, California : Naval Postgraduate School, 1990. http://handle.dtic.mil/100.2/ADA239470.

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Thesis (M.S. in Electrical and Computer Engineering)--Naval Postgraduate School, September 1990.<br>Thesis Advisor(s): Yang, Chyan ; Butler, Jon T. "September 1990." Description based on title screen as viewed on March 22, 2010. Author(s) subject terms: Constrained Implicants Set Concept, Binary Minimization. Includes bibliographical references (p. 75-76). Also available in print.
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Oualla, Hicham. "Contributions à l'identification en boucle ouverte/fermée des systèmes à base de données binaires." Electronic Thesis or Diss., Normandie, 2022. http://www.theses.fr/2022NORMC229.

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Cette thèse est consacrée à l'identification des systèmes à base de données binaires. Dans un premier temps, une présentation succincte de l'ensemble des méthodes d'identification des systèmes basé sur l'utilisation des données binaires existant dans la littérature est donnée. Dans la suite nous nous sommes intéressé au problème d'identification en boucle ouverte des systèmes à sortie et entrée binaires. Nous proposons des méthodes permettant l'identification des systèmes RIF et plus complexes les RII ayant une entrée et sortie binaires. Ces méthodes sont analysées et testées par des exemples numériques. Dans le reste de ce travail, nous proposons des premières solutions aux problèmes d'identification en boucle fermée des systèmes à base de données binaires. Les premières solutions sont dédiées aux systèmes à sortie binaire, l'excitation de la boucle fermée est supposée être à haute résolution. Enfin, deux méthodes sont proposées pour les systèmes en boucle fermée à sortie et entrée binaires. Ces solutions sont testées sur des exemples numériques pour mesurer leurs performances<br>This thesis is devoted to the identification of systems based on binary data. First, a brief presentation of all the methods of identification of systems based on the use of binary data existing in the literature is given. In the following, we are interested in the problem of open loop identification of systems with binary output and input. We propose methods for the identification of FIR systems and more complex IIR systems with binary input and output. These methods are analyzed and tested by numerical examples. In the rest of this work, we propose first solutions to the problems of closed-loop identification of systems based on binary data. The first solutions are dedicated to binary output systems, the closed loop excitation is assumed to be high resolution. Finally, two methods are proposed for closed loop systems with binary output and input. These solutions are tested on numerical examples to quantify their performances
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Montagner, Igor dos Santos. "W-operator learning using linear models for both gray-level and binary inputs." Universidade de São Paulo, 2017. http://www.teses.usp.br/teses/disponiveis/45/45134/tde-21082017-111455/.

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Image Processing techniques can be used to solve a broad range of problems, such as medical imaging, document processing and object segmentation. Image operators are usually built by combining basic image operators and tuning their parameters. This requires both experience in Image Processing and trial-and-error to get the best combination of parameters. An alternative approach to design image operators is to estimate them from pairs of training images containing examples of the expected input and their processed versions. By restricting the learned operators to those that are translation invariant and locally defined ($W$-operators) we can apply Machine Learning techniques to estimate image transformations. The shape that defines which neighbors are used is called a window. $W$-operators trained with large windows usually overfit due to the lack sufficient of training data. This issue is even more present when training operators with gray-level inputs. Although approaches such as the two-level design, which combines multiple operators trained on smaller windows, partly mitigates these problems, they also require more complicated parameter determination to achieve good results. In this work we present techniques that increase the window sizes we can use and decrease the number of manually defined parameters in $W$-operator learning. The first one, KA, is based on Support Vector Machines and employs kernel approximations to estimate image transformations. We also present adequate kernels for processing binary and gray-level images. The second technique, NILC, automatically finds small subsets of operators that can be successfully combined using the two-level approach. Both methods achieve competitive results with methods from the literature in two different application domains. The first one is a binary document processing problem common in Optical Music Recognition, while the second is a segmentation problem in gray-level images. The same techniques were applied without modification in both domains.<br>Processamento de imagens pode ser usado para resolver problemas em diversas áreas, como imagens médicas, processamento de documentos e segmentação de objetos. Operadores de imagens normalmente são construídos combinando diversos operadores elementares e ajustando seus parâmetros. Uma abordagem alternativa é a estimação de operadores de imagens a partir de pares de exemplos contendo uma imagem de entrada e o resultado esperado. Restringindo os operadores considerados para o que são invariantes à translação e localmente definidos ($W$-operadores), podemos aplicar técnicas de Aprendizagem de Máquina para estimá-los. O formato que define quais vizinhos são usadas é chamado de janela. $W$-operadores treinados com janelas grandes frequentemente tem problemas de generalização, pois necessitam de grandes conjuntos de treinamento. Este problema é ainda mais grave ao treinar operadores em níveis de cinza. Apesar de técnicas como o projeto dois níveis, que combina a saída de diversos operadores treinados com janelas menores, mitigar em parte estes problemas, uma determinação de parâmetros complexa é necessária. Neste trabalho apresentamos duas técnicas que permitem o treinamento de operadores usando janelas grandes. A primeira, KA, é baseada em Máquinas de Suporte Vetorial (SVM) e utiliza técnicas de aproximação de kernels para realizar o treinamento de $W$-operadores. Uma escolha adequada de kernels permite o treinamento de operadores níveis de cinza e binários. A segunda técnica, NILC, permite a criação automática de combinações de operadores de imagens. Este método utiliza uma técnica de otimização específica para casos em que o número de características é muito grande. Ambos métodos obtiveram resultados competitivos com algoritmos da literatura em dois domínio de aplicação diferentes. O primeiro, Staff Removal, é um processamento de documentos binários frequente em sistemas de reconhecimento ótico de partituras. O segundo é um problema de segmentação de vasos sanguíneos em imagens em níveis de cinza.
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Medvedieva, S. O., I. V. Bogach, V. A. Kovenko, С. О. Медведєва, І. В. Богач, and В. А. Ковенко. "Neural networks in Machine learning." Thesis, ВНТУ, 2019. http://ir.lib.vntu.edu.ua//handle/123456789/24788.

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В статті розглянуті основи роботи з нейронними мережами, особливу увагу приділено моделі мережі під назвою «перцептрон», запровадженої Френком Розенблаттом. До того ж було розкрито тему найпоширеніших мов програмування, що дозволяють втілити нейронні мережі у життя, шляхом створення програмного забезпечення, пов`язаного з ними.<br>The paper covers the basic principles of Neural Networks’ work. Special attention is paid to Frank Rosenblatt’s model of the network called “perceptron”. In addition, the article touches upon the main programming languages used to write software for Neural Networks.
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Binti, Zainul Abidin Fatin Nurzahirah. "Flexible model-based joint probabilistic clustering of binary and continuous inputs and its application to genetic regulation and cancer." Thesis, University of Leeds, 2017. http://etheses.whiterose.ac.uk/18883/.

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Clustering is used widely in ‘omics’ studies and is often tackled with standard methods such as hierarchical clustering or k-means which are limited to a single data type. In addition, these methods are further limited by having to select a cut-off point at specific level of dendrogram- a tree diagram or needing a pre-defined number of clusters respectively. The increasing need for integration of multiple data sets leads to a requirement for clustering methods applicable to mixed data types, where the straightforward application of standard methods is not necessarily the best approach. A particularly common problem involves clustering entities characterized by a mixture of binary data, for example, presence or absence of mutations, binding, motifs, and/or epigenetic marks and continuous data, for example, gene expression, protein abundance and/or metabolite levels. In this work, we presented a generic method based on a probabilistic model for clustering this mixture of data types, and illustrate its application to genetic regulation and the clustering of cancer samples. It uses penalized maximum likelihood (ML) estimation of mixture model parameters using information criteria (model selection objective function) and meta-heuristic searches for optimum clusters. Compatibility of several information criteria with our model-based joint clustering was tested, including the well-known Akaike Information Criterion (AIC) and its empirically determined derivatives (AICλ), Bayesian Information Criterion (BIC) and its derivative (CAIC), and Hannan-Quinn Criterion (HQC). We have experimentally shown with simulated data that AIC and AIC (λ=2.5) worked well with our method. We show that the resulting clusters lead to useful hypotheses: in the case of genetic regulation these concern regulation of groups of genes by specific sets of transcription factors and in the case of cancer samples combinations of gene mutations are related to patterns of gene expression. The clusters have potential mechanistic significance and in the latter case are significantly linked to survival.
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Lin, Hsuan-Yin, and 林玄寅. "Optimal Ultra-Small Block-Codes for Binary Input Discrete Memoryless Channels." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/20041495285802019942.

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博士<br>國立交通大學<br>電信工程研究所<br>101<br>Optimal block-codes with a very small number of codewords are investigated for the binary input discrete memoryless channels. Those channels are the binary asymmetric channel (BAC), including the two special cases of the binary symmetric channel (BSC) and the Z-channel (ZC). The binary erasure channel (BEC) is a common used channel with ternary output. For the asymmetric channels, a general BAC, it is shown that so-called flip codes are optimal codes with two codewords. The optimal (in the sense of minimum average error probability, using maximum likelihood decoding) code structure is derived for the ZC in the cases of two, three, and four codewords and an arbitrary finite blocklength. For the symmetric channels, the BSC and the BEC, the optimal code structure is derived with at most three codewords and an arbitrary finite blocklength, a statement for linear optimal codes with four codes is also given. The derivation of these optimal codes relies heavily on a new approach of constructing and analyzing the codebook matrix not row-wise (codewords), but column-wise. This new tool allows an elegant definition of interesting code families that is recursive in the blocklength n and admits their exact analysis of error performance that is not based on the union bound or other approximations.
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"On the evaluation of Marton's inner bound for binary input broadcast channels." 2012. http://library.cuhk.edu.hk/record=b5549570.

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本論文考慮對於二值輸入廣播信道在沒有公共信息要求的情況下，如何評估Marton 內界。對於雙用戶廣播信道而言，該內界是最好的，而最好的外界是UV 外界。最近我們證明了UV 外界不是容量區域，但是Marton 內界是否是容量區域尚未可知。<br>在論文的第一部份，我們介紹了一個由Jog 和Nair 獲得的基於二值輸入斜對稱廣播信道的不等式，該不等式被用於首次證明Marton 內界嚴格包含在UV 外界里。我們將該不等式推廣到任意二值輸入廣播信道。在證明中，我們採用擾動分析的方法，幫助刻劃了不等式在非平凡情況下的性質。<br>在第二部份，我們專注于研究輸出對稱的二值輸入廣播信道。我們證明了Marton 內界是否嚴格包含于UV 外界里是與特定偏序密切相關的，同時找到了另一個嚴格包含的例子。<br>對於評估內界而不僅僅是其中的總傳輸率，我們考慮邊界的支撐超平面，然後提出一個猜想，利用凸包的概念推廣了之前提及的不等式。對於大部份情況，我們證明了該猜想。<br>本論文的主要貢獻在於，我們拓展了評估特定可達傳輸率的新工具和方法，同時證明了某些非基於凸性質的不等式。<br>This thesis concerns the evaluation of Marton's inner bound for binary input broadcast channel without common message.This inner bound is the best one for two-receiver broadcast channel, while the best outer bound is UV outer bound. Recently we have shown that UV outer bound is not optimal, however the optimality of Marton's inner bound is still unknown.<br>In the first part, we introduce a binary inequality obtained by Jog and Nair for binary-skew symmetric broadcast channel, which helps to show for the first time that Marton's inner bound is strictly included in UV outer bound. We generalize this inequality to be true for arbitrary binary input broadcast channel. The method applied here is perturbation analysis, which helps to characterize the properties of non-trivial cases in the proof.<br>In the second part, we study a class of broadcast channel consisting of binary input symmetric-output channels. We show that whether Marton's inner bound is strictly included in UV outer bound is closely related to the more capable partial order, and we find a second example that demonstrates the strict inclusion.<br>To evaluate the inner bound beyond the sum-rate, we consider the supporting hyperplanes of the boundary points and conjecture the binary inequality to a stronger one, where we utilize the notion of concave envelope. We prove the extended inequality for certain cases.<br>The main contribution of the thesis is in the development of new tools and techniques for evaluating certain achievable regions as well as for proving certain information inequalities that are not based on convexity.<br>Detailed summary in vernacular field only.<br>Detailed summary in vernacular field only.<br>Detailed summary in vernacular field only.<br>Detailed summary in vernacular field only.<br>Detailed summary in vernacular field only.<br>Geng, Yanlin.<br>Thesis (Ph.D.)--Chinese University of Hong Kong, 2012.<br>Includes bibliographical references (leaves 64-66).<br>Abstract also in Chinese.<br>Abstract --- p.i<br>Acknowledgement --- p.iv<br>Chapter 1 --- Introduction --- p.1<br>Chapter 1.1 --- Broadcast channel and capacity region --- p.2<br>Chapter 1.2 --- Inner bounds to capacity region --- p.3<br>Chapter 1.3 --- Outer bounds to capacity region --- p.6<br>Chapter 1.4 --- Partial orders --- p.7<br>Chapter 1.5 --- Examples where inner and outer bounds differ --- p.11<br>Chapter 2 --- A binary inequality --- p.14<br>Chapter 2.1 --- Proof of special settings --- p.20<br>Chapter 2.2 --- Two nontrivial cases --- p.20<br>Chapter 2.3 --- Proof of XOR case --- p.22<br>Chapter 2.4 --- Proof of AND case --- p.26<br>Chapter 3 --- BISO broadcast channel --- p.30<br>Chapter 3.1 --- BISO channel --- p.32<br>Chapter 3.2 --- Partial orders on BISO broadcast channel --- p.34<br>Chapter 3.2.1 --- More capable comparability --- p.34<br>Chapter 3.2.2 --- More capable and essentially less noisy --- p.39<br>Chapter 3.3 --- Comparison of bounds for BISO broadcast channel --- p.42<br>Chapter 3.4 --- A new partial order --- p.46<br>Chapter 4 --- Extended binary inequality --- p.56<br>Chapter 4.1 --- Proof of XOR case --- p.57<br>Chapter 4.2 --- A conjecture on extending the inequality --- p.61<br>Chapter 5 --- Conclusion --- p.62<br>Bibliography --- p.64
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Lin, Sin-Fu, and 林信甫. "Applying Intel SGX for Multi-Input Functional Encryption on Binary Classification of Machine Learning." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/48ts98.

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碩士<br>國立政治大學<br>資訊科學系<br>107<br>Due to the fact that mobile devices and the usage of the internet have become integral parts of our lives, various kinds of private data have been collected and uploaded to the cloud for analysis. Followed by, hackers attack cloud OS, VMM(Virtual Machine Monitor); cloud administrators take on unauthorized action, all leave privacy data at risk. This research aims to resolve the issue by conducting SGX (Software Guard Extensions), Intel’s software and hardware trusted execution environment solution, to propose a software architecture. The designed architecture contains four characters, Users, Cloud Service Provider, Security as a Service and Machine Learning as a Service, which then designed data flow, encryption/decryption flow as well as computation flow between the characters. To explain how the architecture meets the privacy protection demands of data at all time (at-rest, in-transit, and in-use), the research takes Multi-Input Functional Encryption on binary classification of Machine Learning as examples.
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Tsai, Yu-Han, and 蔡羽涵. "The Cramming, Softening and Integrating Learning Algorithm with ReLU activation function for Binary Input/Output Problems." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/ymzgt7.

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碩士<br>國立政治大學<br>資訊管理學系<br>107<br>Rare Artificial Neural Networks studies address simultaneously the challenges of (1) systematically adjusting the amount of used hidden layer nodes within the learning process, (2) adopting ReLU activation function instead of tanh function for fast learning, and (3) guaranteeing learning all training data. This study will address these challenges through deriving the CSI (Cramming, Softening and Integrating) learning algorithm for the single-hidden layer feed-forward neural networks with ReLU activation function and the binary input/output, and further making the technical justification. For the purpose of verifying the proposed learning algorithm, this study conducts an empirical experiment using SPECT heart diagnosis data set from UCI Machine Learning repository. The learning algorithm is implemented via the advanced TensorFlow and GPU.
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Syu, Ming-Sheng, and 許名勝. "The Design and Analysis of Turbo Codes Based on Nonbinary Time-Varying Accumulate Codes under Binary-Input AWGN Channels." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/12145438376510645480.

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碩士<br>國立中正大學<br>通訊工程研究所<br>101<br>According to the results of other research, random-coset low-density parity-check (LDPC) codes and irregular repeat-accumulate (IRA) codes with q-ary nonuniform signal constellations, under belief-propagation (BP) decoding, will approach the unrestricted Shannon limit. It has been shown that, random-coset LDPC codes has much higher encoding complexity than the IRA code, because IRA code can be encoded using the concept of time-varying accumulate code as proposed in [19]. And the simulation results show that, the best SNR thresholds of random-coset LDPC or IRA codes are obtained when the average variable node degree as close as possible to 2. This also means that we can get good performance, as long as repeat the information twice, which implies the turbo codes with two branches encoded by two independent time-varying accumulate (RA) codes may have good potential to construct good codes. In addition, compared with conventional repeat accumulate codes with input and output from the entire Galois field , we also proposed a time-varying accumulate codes with input and output restricted to a small-sized alphabet (smaller than ).This construction allows better flexibility of modulation and coding scheme (MCS) for rate matching in modern communication systems.
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Books on the topic "Binary input"

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Tennant, Neil. Transmission of Truthmakers. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198777892.003.0009.

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We begin by introducing the formal genus ‘conditional M-relative construct’, of which M-relative truthmakers and falsitymakers, and core proofs, are species. Fortunately they can stand in symbiotic relations, even though they cannot hybridize. We aim to generalize the earlier method we used in order to prove Cut-Elimination, so that the inputs P for the binary operation [P,P′] can be truthmakers (whereas P′ remains a core proof); and so that the reduct itself, when it is finally determined by recursive application of all the transformations called for, is a truthmaker for the conclusion of P′. This result can be understood as revealing that formal semantics can be carried out in a kind of infinitary proof-theory. Core proof transmits truth courtesy of normalization.
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Book chapters on the topic "Binary input"

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Babu, Hafiz Md Hasan. "Multiple-Valued Input Binary-Valued Output Functions." In VLSI Circuits and Embedded Systems. CRC Press, 2022. http://dx.doi.org/10.1201/9781003269182-11.

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Skubacz, Michał, and Jaakko Hollmén. "Quantization of Continuous Input Variables for Binary Classification." In Intelligent Data Engineering and Automated Learning — IDEAL 2000. Data Mining, Financial Engineering, and Intelligent Agents. Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/3-540-44491-2_7.

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Galán, Gerhard, and Juris Muñoz. "A new input-output function for binary hopfield neural networks." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/bfb0098187.

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Nuida, Koji. "Efficient Card-Based Millionaires’ Protocols via Non-binary Input Encoding." In Advances in Information and Computer Security. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-41326-1_13.

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Wickramasuriya, Dilranjan S., and Rose T. Faghih. "State-Space Model with One Binary and Two Continuous Observations." In Bayesian Filter Design for Computational Medicine. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-47104-9_5.

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AbstractIn this chapter, we will consider a more complicated form of the state equation—one that contains both a forgetting factor and an external input. We will also extend the earlier state-space model to the case where we now have one binary observation and two continuous observations. As before, however, we will first consider a scenario motivating the need for such a state-space model.
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Rüping, S., U. Rückert, and K. Goser. "Hardware design for self organizing feature maps with binary input vectors." In New Trends in Neural Computation. Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/3-540-56798-4_193.

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Adde, Patrick, Ramesh Pyndiah, and Sylvie Kerouedan. "Block Turbo Code with Binary Input for Improving Quality of Service." In Multiaccess, Mobility and Teletraffic for Wireless Communications, volume 6. Springer US, 2002. http://dx.doi.org/10.1007/978-1-4757-5918-1_14.

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Tempel, Sören, Vladimir Herdt, and Rolf Drechsler. "SISL: Concolic Testing of Structured Binary Input Formats via Partial Specification." In Automated Technology for Verification and Analysis. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-19992-9_5.

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Bryant, Randal E., Armin Biere, and Marijn J. H. Heule. "Clausal Proofs for Pseudo-Boolean Reasoning." In Tools and Algorithms for the Construction and Analysis of Systems. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-99524-9_25.

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AbstractWhen augmented with a Pseudo-Boolean (PB) solver, a Boolean satisfiability (SAT) solver can apply apply powerful reasoning methods to determine when a set of parity or cardinality constraints, extracted from the clauses of the input formula, has no solution. By converting the intermediate constraints generated by the PB solver into ordered binary decision diagrams (BDDs), a proof-generating, BDD-based SAT solver can then produce a clausal proof that the input formula is unsatisfiable. Working together, the two solvers can generate proofs of unsatisfiability for problems that are intractable for other proof-generating SAT solvers. The PB solver can, at times, detect that the proof can exploit modular arithmetic to give smaller BDD representations and therefore shorter proofs.
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Du, Huaiyu, and Rafał Jóźwiak. "Representation of Observations in Reinforcement Learning for Playing Arcade Fighting Game." In Digital Interaction and Machine Intelligence. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-37649-8_5.

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AbstractReinforcement learning (RL) is one of three basic machine learning paradigms, alongside supervised learning and unsupervised learning. Reinforcement learning algorithms have become very popular in simple computer games and games like chess and GO. However, playing classical arcade fighting games would be challenging because of the complexity of the command system (the character makes moves according to the sequence of input) and combo system. In this paper, a creation of a game environment of The King of Fighters ’97 (KOF ’97), which implements the open gym env interface, is described. Based on the characteristics of the game, an innovative approach to represent the observations from the last few steps has been proposed, which guarantees the preservation of Markov’s property. The observations are coded using the “one-hot encoding” technique to form a binary vector, while the sequence of stacked vectors from successive steps creates a binary image. This image encodes the character’s input and behavioural pattern, which are then retrieved and recognized by the CNN network. A network structure based on the Advantage Actor-Critic network was proposed. In the experimental verification, the RL agent performing basic combos and complex moves (including the so-called “desperation moves”) was able to defeat characters using the highest level of AI built into the game.
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Conference papers on the topic "Binary input"

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Wong, Wai Kin, Huaijin Wang, Zongjie Li, and Shuai Wang. "BinAug: Enhancing Binary Similarity Analysis with Low-Cost Input Repairing." In ICSE '24: 46th IEEE/ACM International Conference on Software Engineering. ACM, 2024. http://dx.doi.org/10.1145/3597503.3623328.

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Moskowitz, Ira S., Paul Cotae, Pedro N. Safier, and Daniel L. Kang. "Capacity bounds and stochastic resonance for binary input binary output channels." In 2012 Computing, Communications and Applications Conference (ComComAp). IEEE, 2012. http://dx.doi.org/10.1109/comcomap.2012.6154003.

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Shari, Shahrouz, A. Korhan Tanc, and Tolga M. Duman. "LDPC code design for binary-input binary-output Z interference channels." In 2015 IEEE International Symposium on Information Theory (ISIT). IEEE, 2015. http://dx.doi.org/10.1109/isit.2015.7282622.

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Amonchanchaigul, Thavit, and Worapoj Kreesuradej. "Input Selection Using Binary Particle Swarm Optimization." In 2006 International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce (CIMCA'06). IEEE, 2006. http://dx.doi.org/10.1109/cimca.2006.127.

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Qian, Jing, Feifei Gao, Shi Jin, Ling Xing, and Junhui Zhao. "Capacity of Ambient Backscatter Communications with Binary Input and Binary Output Channel." In GLOBECOM 2018 - 2018 IEEE Global Communications Conference. IEEE, 2018. http://dx.doi.org/10.1109/glocom.2018.8647136.

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Moskowitz, Ira S., Paul Cotae, and Pedro N. Safier. "Algebraic information theory and stochastic resonance for binary-input binary-output channels." In 2012 46th Annual Conference on Information Sciences and Systems (CISS). IEEE, 2012. http://dx.doi.org/10.1109/ciss.2012.6310786.

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Ueng, Yeong-Luh, Chung-Jay Yang, Shu-Wei Chen, and Wei-Xuan Wu. "A selective-input non-binary LDPC decoder architecture." In 2011 International SoC Design Conference (ISOCC 2011). IEEE, 2011. http://dx.doi.org/10.1109/isocc.2011.6138641.

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Li, Zhe, Peisong Wang, Hanqing Lu, and Jian Cheng. "Reading selectively via Binary Input Gated Recurrent Unit." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/705.

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Recurrent Neural Networks (RNNs) have shown great promise in sequence modeling tasks. Gated Recurrent Unit (GRU) is one of the most used recurrent structures, which makes a good trade-off between performance and time spent. However, its practical implementation based on soft gates only partially achieves the goal to control information flow. We can hardly explain what the network has learnt internally. Inspired by human reading, we introduce binary input gated recurrent unit (BIGRU), a GRU based model using a binary input gate instead of the reset gate in GRU. By doing so, our model can read selectively during interference. In our experiments, we show that BIGRU mainly ignores the conjunctions, adverbs and articles that do not make a big difference to the document understanding, which is meaningful for us to further understand how the network works. In addition, due to reduced interference from redundant information, our model achieves better performances than baseline GRU in all the testing tasks.
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Guoping Wang. "Implementation of a redundant binary input acceptable multiplier." In 2007 IEEE International Conference on Electro/Information Technology. IEEE, 2007. http://dx.doi.org/10.1109/eit.2007.4374437.

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Li, Longchuan, Shugen Ma, Isao Tokuda, et al. "Embodying Rather Than Encoding: Undulation with Binary Input." In 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2022. http://dx.doi.org/10.1109/iros47612.2022.9982001.

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Reports on the topic "Binary input"

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Hoch, Brendon, and Samantha Cook. A 10-Year monthly climatology of wind direction : case-study assessment. Engineer Research and Development Center (U.S.), 2023. http://dx.doi.org/10.21079/11681/46912.

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A 10-year monthly climatology of wind direction in compass degrees is developed utilizing datasets from the National Oceanic Atmospheric Administration, Climate Forecast System. Data retrieval methodologies, numerical techniques, and scientific analysis packages to develop the climatology are explored. The report describes the transformation of input data in Gridded Binary format to the Geographic Tagged Image File Format to support geospatial analyses. The specific data sources, software tools, and data-verification techniques are outlined.
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Farhi, Edward, and Hartmut Neven. Classification with Quantum Neural Networks on Near Term Processors. Web of Open Science, 2020. http://dx.doi.org/10.37686/qrl.v1i2.80.

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We introduce a quantum neural network, QNN, that can represent labeled data, classical or quantum, and be trained by supervised learning. The quantum circuit consists of a sequence of parameter dependent unitary transformations which acts on an input quantum state. For binary classification a single Pauli operator is measured on a designated readout qubit. The measured output is the quantum neural network’s predictor of the binary label of the input state. We show through classical simulation that parameters can be found that allow the QNN to learn to correctly distinguish the two data sets. We then discuss presenting the data as quantum superpositions of computational basis states corresponding to different label values. Here we show through simulation that learning is possible. We consider using our QNN to learn the label of a general quantum state. By example we show that this can be done. Our work is exploratory and relies on the classical simulation of small quantum systems. The QNN proposed here was designed with near-term quantum processors in mind. Therefore it will be possible to run this QNN on a near term gate model quantum computer where its power can be explored beyond what can be explored with simulation.
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Morales Sarriera, Javier, Tomás Serebrisky, Gonzalo Araya, Cecilia Briceño-Garmendia, and Jordan Schwartz. Benchmarking Container Port Technical Efficiency in Latin America and the Caribbean. Inter-American Development Bank, 2013. http://dx.doi.org/10.18235/0011526.

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We developed a technical efficiency analysis of container ports in Latin America and the Caribbean using an input-oriented stochastic frontier model. We employed a 10-year panel with data on container throughput, port terminal area, berth length, and number of available cranes in 63 ports. The model has three innovations with respect to the available literature: (i) we treated ship-to-shore gantry cranes and mobile cranes separately, in order to account for the higher productivity of the former; (ii) we introduced a binary variable for ports using ships¿ cranes, treated as an additional source of port productivity; and (iii) we introduced a binary variable for ports operating as transshipment hubs. Their associated parameters are highly significant in the production function. The results show an improvement in the average technical efficiency of ports in the Latin American and Caribbean region from 36% to 50% between 1999 and 2009; the best performing port in 2009 achieved a technical efficiency of 94%with respect to the frontier. The paper also studies possible determinants of port technical efficiency, such as ownership, corruption, transshipment, income per capita, and location. The results revealed positive and significant associations between technical efficiency and both transshipment activities and lower corruption levels.
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Sinclair, Samantha, and Sally Shoop. Automated detection of austere entry landing zones : a “GRAIL Tools” validation assessment. Engineer Research and Development Center (U.S.), 2022. http://dx.doi.org/10.21079/11681/45265.

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The Geospatial Remote Assessment for Ingress Locations (GRAIL) Tools software is a geospatial product developed to locate austere entry landing zones (LZs) for military aircraft. Using spatial datasets like land classification and slope, along with predefined LZ geometry specifications, GRAIL Tools generates binary suitability filters that distinguish between suitable and unsuitable terrain. GRAIL Tools combines input suitability filters, searches for LZs at user‐defined orientations, and plots results. To refine GRAIL Tools, we: (a) verified software output; (b) conducted validation assessments using five unpaved LZ sites; and (c) assessed input dataset resolution on outcomes using 30 and 1‐m datasets. The software was verified and validated in California and the Baltics, and all five LZs were correctly identified in either the 30 or the 1‐m data. The 30‐m data provided numerous LZs for consideration, while the 1‐m data highlighted hazardous conditions undetected in the 30‐m data. Digital elevation model grid size affected results, as 1‐m data produced overestimated slope values. Resampling the data to 5 m resulted in more realistic slopes. Results indicate GRAIL Tools is an asset the military can use to rapidly assess terrain conditions.
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Gibbs, Holly, Sahoko Yui, and Richard Plevin. New Estimates of Soil and Biomass Carbon Stocks for Global Economic Models. GTAP Technical Paper, 2014. http://dx.doi.org/10.21642/gtap.tp33.

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We synthesized a range of geographically-explicit forest, grassland and cropland biomass and soil carbon input data sources and used geographic information systems (GIS) software to calculate new estimates of soil and biomass carbon stocks for use with global economic models, particularly for the Global Trade and Analysis Project (GTAP). Our results quantify the average amount of carbon stored in soil and biomass in each of the 246 countries, stratified by agro-ecological zones (available in the accompanying spreadsheet). We also provide the data aggregated to the 134 regions defined for the GTAP 8.1 database both in spreadsheet form and in GTAP’s native binary file format. Finally, we provide an add-on to FlexAgg2 program to further aggregate the 134 regions as desired. Our analysis makes substantial refinements to the estimates of carbon stocks used for modeling carbon emissions from indirect land use change. The spatial detail of our analysis is a major advantage over previous databases because it provides estimates tailored to the regions of interest and better accounts for the variation of carbon stocks across the landscape, and between wetland and non-wetland regions.
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Patel, Reena. Complex network analysis for early detection of failure mechanisms in resilient bio-structures. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/41042.

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Bio-structures owe their remarkable mechanical properties to their hierarchical geometrical arrangement as well as heterogeneous material properties. This dissertation presents an integrated, interdisciplinary approach that employs computational mechanics combined with flow network analysis to gain fundamental insights into the failure mechanisms of high performance, light-weight, structured composites by examining the stress flow patterns formed in the nascent stages of loading for the rostrum of the paddlefish. The data required for the flow network analysis was generated from the finite element analysis of the rostrum. The flow network was weighted based on the parameter of interest, which is stress in the current study. The changing kinematics of the structural system was provided as input to the algorithm that computes the minimum-cut of the flow network. The proposed approach was verified using two classical problems three- and four-point bending of a simply-supported concrete beam. The current study also addresses the methodology used to prepare data in an appropriate format for a seamless transition from finite element binary database files to the abstract mathematical domain needed for the network flow analysis. A robust, platform-independent procedure was developed that efficiently handles the large datasets produced by the finite element simulations. Results from computational mechanics using Abaqus and complex network analysis are presented.
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