Relevant bibliographies by topics / Binary output

Academic literature on the topic 'Binary output'

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Published: 13 April 2024

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Journal articles on the topic "Binary output"

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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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Moreno, E. G., B. Iniguez, M. Roca, J. Segura, and S. Sureda. "CMOS radiation sensor with binary output." IEEE Transactions on Nuclear Science 42, no. 3 (June 1995): 174–78. http://dx.doi.org/10.1109/23.387358.

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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 (November 1993): 471–76. http://dx.doi.org/10.1002/qre.4680090603.

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Yang, Sibo, Shusheng Wang, Lanyin Sun, Zhongxuan Luo, and Yuan Bao. "Output Layer Structure Optimization for Weighted Regularized Extreme Learning Machine Based on Binary Method." Symmetry 15, no. 1 (January 16, 2023): 244. http://dx.doi.org/10.3390/sym15010244.

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In this paper, we focus on the redesign of the output layer for the weighted regularized extreme learning machine (WRELM). For multi-classification problems, the conventional method of the output layer setting, named “one-hot method”, is as follows: Let the class of samples be r; then, the output layer node number is r and the ideal output of s-th class is denoted by the s-th unit vector in Rr (1≤s≤r). Here, in this article, we propose a “binarymethod” to optimize the output layer structure: Let 2p−1<r≤2p, where p≥2, and p output nodes are utilized and, simultaneously, the ideal outputs are encoded in binary numbers. In this paper, the binary method is employed in WRELM. The weights are updated through iterative calculation, which is the most important process in general neural networks. While in the extreme learning machine, the weight matrix is calculated in least square method. That is, the coefficient matrix of the linear equations we solved is symmetric. For WRELM, we continue this idea. And the main part of the weight-solving process is a symmetry matrix. Compared with the one-hot method, the binary method requires fewer output layer nodes, especially when the number of sample categories is high. Thus, some memory space can be saved when storing data. In addition, the number of weights connecting the hidden and the output layer will also be greatly reduced, which will directly reduce the calculation time in the process of training the network. Numerical experiments are conducted to prove that compared with the one-hot method, the binary method can reduce the output nodes and hidden-output weights without damaging the learning precision.
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Gurevich, Yuri, and Saharon Shelah. "Time polynomial in input or output." Journal of Symbolic Logic 54, no. 3 (September 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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Xue, Aijun, and Xiaodan Wang. "Cost-sensitive design of error correcting output codes." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 232, no. 10 (May 12, 2017): 1871–81. http://dx.doi.org/10.1177/0954406217709303.

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Many real world applications involve multiclass cost-sensitive learning problems. However, some well-worked binary cost-sensitive learning algorithms cannot be extended into multiclass cost-sensitive learning directly. It is meaningful to decompose the complex multiclass cost-sensitive classification problem into a series of binary cost-sensitive classification problems. So, in this paper we propose an alternative and efficient decomposition framework, using the original error correcting output codes. The main problem in our framework is how to evaluate the binary costs for each binary cost-sensitive base classifier. To solve this problem, we proposed to compute the expected misclassification costs starting from the given multiclass cost matrix. Furthermore, the general formulations to compute the binary costs are given. Experimental results on several synthetic and UCI datasets show that our method can obtain comparable performance in comparison with the state-of-the-art methods.
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Ren, Xiao Guang, Yu Hua Tang, and Xin Hai Xu. "Format Optimization for Periodical Snapshot Output in CFD Simulation." Applied Mechanics and Materials 457-458 (October 2013): 910–18. http://dx.doi.org/10.4028/www.scientific.net/amm.457-458.910.

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Computational Fluid Dynamics (CFD) simulation often needs to periodically output the intermediate results to files in the form of snapshots for visualization or restart, which seriously impacts the performance. Traditional CFD simulation takes ASCII format with typesetting in the snapshot output process, which results in precision loss of the data in the snapshot array and more storage space occupancy than the original binary format. In this paper, we propose the binary non-typesetting format optimization for the snapshot output in CFD simulation, aiming at eliminating the impact of ASCII format. In our optimization method, the snapshot array is output in binary format without typesetting. On one hand, it reserves the original binary precision in the output files, while the ASCII format always has precision loss, which seriously impacts the accuracy of CFD simulation; On the other hand, non-typesetting provide the opportunity of output the snapshot as a continuous memory block, which will signally improve the efficiency of the output. We design the multiply output mode framework for CFD applications through the combination of ASCII typesetting format and binary non-typesetting format. We implement this multiply output mode framework in the open source CFD software OpenFOAM. Experimental results on Tianhe-2 supercomputer demonstrate that our binary non-typesetting format optimization technique can achieve good optimization effect for the periodical snapshot output in CFD application.
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PÉREZ ARCILA, MAURICIO, and MARTIN ALONSO TAMAYO VELEZ. "IMPLEMENTATION OF LEBESGUE SAMPLING METHOD AND DIGITAL SENSORS FOR CONTROLLING THE LEVEL VARIABLE IN A CONTINUOUS SYSTEM." DYNA NEW TECHNOLOGIES 8, no. 1 (November 11, 2021): [14 P.]. http://dx.doi.org/10.6036/nt10248.

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This study aims to show that the continuous control from a level system can be efficiently measured and controlled using capacitive digital binary sensors, which in this case, replace the measurement signal from an analog differential pressure transmitter in a level control system. The binary sensors low cost and the digital output they process allow the reproduction of a correct signal and the estimation of a variable for controlling the water level inside the process tank through a proportional pneumatic level control valve, which receives the control signal from the Lebesgue sampling estimation algorithm applied herein for processing digital measurements. In this particular case, the Lebesgue algorithm is applied to reproduce the estimation of values obtained from the continuous signal in the real level process for the measurement and control. Also, are compared both, simulated and real outputs obtained using the Lebesgue algorithm and digital sensors, which were applied to a state observer controller that relates digital signals for controlling the real level system output. The application of the Lebesgue algorithm in the real level process concludes that the analog level signal can be efficiently reproduced using this method. In addition, the controller enables the system to smoothly conduct digital output processing using digital sensors to control the system output correctly, validating that not only analog sensors should be applied for controlling the output of proportional actuators, because it is shown that digital binary signals can be used for controlling and emulating continuous signals, which were processed and applied to the pneumatic valve. Keywords: Lebesgue sampling, estimation, binary sensor, observer controller, finite state machine, continuous system, control, LTI systems, identification, state variable, estimated output, proportional actuator
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Silva, Carla, Ana Aguiar, and Inês Dutra. "Quantum Binary Classification (Student Abstract)." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 18 (May 18, 2021): 15889–90. http://dx.doi.org/10.1609/aaai.v35i18.17941.

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We implement a quantum binary classifier where given a dataset of pairs of training inputs and target outputs our goal is to predict the output of a new input. The script is based in a hybrid scheme inspired in an existing PennyLane's variational classifier and to encode the classical data we resort to PennyLane's amplitude encoding embedding template. We use the quantum binary classifier applied to the well known Iris dataset and to a car traffic dataset. Our results show that the quantum approach is capable of performing the task using as few as 2 qubits. Accuracies are similar to other quantum machine learning research studies, and as good as the ones produced by classical classifiers.
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Rahmadhany, Sri. "IDENTIFIKASI POLA KARAKTER ANAK DENGAN ALGORITMA PERCEPTRON." JURNAL TEKNOLOGI INFORMASI 3, no. 1 (June 13, 2019): 86. http://dx.doi.org/10.36294/jurti.v3i1.695.

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Abstract - Artificial Neural Network is a computational method that works like a human brain. The Perceptron algorithm is one method that exists in Artificial Neural Networks. The research carried out was the identification of children's character patterns using the Perceptron algorithm. The Perceptron algorithm is very reliable in recognizing patterns, one of which is the child's character pattern as was done in this study. The Perceptron algorithm identifies the character patterns of children through three inputs and two outputs. The three outputs are taken from nature variables, attitude variables and behavioral variables. The output is four human temperaments according to Hipocrates, namely sanguin, melancholy, choleric and plegamatic. All inputs and outputs will be converted into binary numbers to be trained with Matlab software.Keywords - Artificial Neural Networks, Perceptron Algorithms, child character patterns, input, output, binary numbers. Abstrak - Jaringan Syaraf Tiruan merupakan salah satu metode komputasi yang dapat bekerja seperti layaknya otak manusia. Algortima Perceptron merupakan salah satu metode yang ada pada Jaringan Syaraf Tiruan. Penelitian yang dilakukan adalah identifikasi pola karakter anak dengan menggunakan algoritma Perceptron. Algoritma Perceptron sangat handal dalam mengenali pola salah satunya yaitu pola karakter anak seperti yang dilakukan dalam penelitian ini. Algoritma Perceptron mengidentifikasi pola karakter anak melalui tiga input dan dua output. Tiga output tersebut diambil dari variabel sifat, variabel sikap dan variabel tingkah laku. Adapun output merupakan empat temperamen manusia menurut Hipocrates yaitu sanguin, melankolis, koleris dan plegamatis. Seluruh input dan output akan diubah menjadi bilangan biner untuk dilatih dengan software Matlab.Kata Kunci - Jaringan Syaraf Tiruan, Algoritma Perceptron, pola karakter anak, input, output, bilangan biner.
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Dissertations / Theses on the topic "Binary output"

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Grama, Keshava. "Binary matrix for pedestrian tracking in infrared images." Thesis, Edinburgh Napier University, 2013. http://researchrepository.napier.ac.uk/Output/6153.

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The primary goal of this thesis is to present a robust low compute cost pedestrian tracking system for use with thermal infra-red images. Pedestrian tracking employs two distinct image analysis tasks, pedestrian detection and path tracking. This thesis will focus on benchmarking existing pedestrian tracking systems and using this to evaluate the proposed pedestrian detection and path tracking algorithm. The first part of the thesis describes the imaging system and the image dataset collected for evaluating pedestrian detection and tracking algorithms. The texture content of the images from the imaging system are evaluated using fourier maps following this the locations at which the dataset was collected are described. The second part of the thesis focuses on the detection and tracking system. To evaluate the performance of the tracking system, a time per target metric is described and is shown to work with existing tracking systems. A new pedestrian aspect ratio based pedestrian detection algorithm is proposed based on a binary matrix dynamically constrained using potential target edges. Results show that the proposed algorithm is effective at detecting pedestrians in infrared images while being less resource intensive as existing algorithms. The tracking system proposed uses deformable, dynamically updated codebook templates to track pedestrians in an infrared image sequence. Results show that this tracker performs as well as existing tracking systems in terms of accuracy, but requires fewer resources.
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Chapin, Patrick Samuel. "Analysis of experiments to validate computer models with binary output." [Ames, Iowa : Iowa State University], 2009. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3389285.

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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.
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
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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Ataman, Kaan. "Learning to rank by maximizing the AUC with linear programming for problems with binary output." Diss., University of Iowa, 2007. http://ir.uiowa.edu/etd/151.

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Chaudhari, Pragat. "Analytical Methods for the Performance Evaluation of Binary Linear Block Codes." Thesis, University of Waterloo, 2000. http://hdl.handle.net/10012/904.

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The modeling of the soft-output decoding of a binary linear block code using a Binary Phase Shift Keying (BPSK) modulation system (with reduced noise power) is the main focus of this work. With this model, it is possible to provide bit error performance approximations to help in the evaluation of the performance of binary linear block codes. As well, the model can be used in the design of communications systems which require knowledge of the characteristics of the channel, such as combined source-channel coding. Assuming an Additive White Gaussian Noise channel model, soft-output Log Likelihood Ratio (LLR) values are modeled to be Gaussian distributed. The bit error performance for a binary linear code over an AWGN channel can then be approximated using the Q-function that is used for BPSK systems. Simulation results are presented which show that the actual bit error performance of the code is very well approximated by the LLR approximation, especially for low signal-to-noise ratios (SNR). A new measure of the coding gain achievable through the use of a code is introduced by comparing the LLR variance to that of an equivalently scaled BPSK system. Furthermore, arguments are presented which show that the approximation requires fewer samples than conventional simulation methods to obtain the same confidence in the bit error probability value. This translates into fewer computations and therefore, less time is needed to obtain performance results. Other work was completed that uses a discrete Fourier Transform technique to calculate the weight distribution of a linear code. The weight distribution of a code is defined by the number of codewords which have a certain number of ones in the codewords. For codeword lengths of small to moderate size, this method is faster and provides an easily implementable and methodical approach over other methods. This technique has the added advantage over other techniques of being able to methodically calculate the number of codewords of a particular Hamming weight instead of calculating the entire weight distribution of the code.
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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.
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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FALEH, MOHAMAD SALEH. "Conception, realisation et caracterisation de transistors bipolaires de puissance a heterojonction gainp/gaas et comparaison avec les tbh's gaalas/gaas." Toulouse 3, 1998. http://www.theses.fr/1998TOU30027.

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L'objet de cette these est la conception, la realisation et la caracterisation de transistors bipolaires de puissance a heterojonction gainp/gaas et la comparaison avec les tbhs gaalas/gaas. Le premier chapitre presente d'abord un rappel des principales proprietes des materiaux gainp et gaas utilises dans la fabrication des tbh etudies. Il examine ensuite les parametres physiques et technologiques qui influent sur les performances statiques et dynamiques. Un modele electrique petit signal permettant la description precise du comportement du transistor est presente. L'influence des effets thermiques qui constituent la principale limitation des tbhs de puissance sur arseniure de gallium est enfin analysee. La technologie mise en oeuvre pour realiser les tbhs gainp/gaas est decrite dans le deuxieme chapitre. Deux familles de dispositifs presentant une surface d'emetteur elementaire de 10x200 m#2 et 6x60 m#2 sont realisees dans des technologies triple mesa classique ou autoalignee, avec une prise du contact d'emetteur utilisant un pont a air. Le troisieme chapitre rapporte les resultats des caracterisations statique et dynamique ainsi que les performances des transistors realises. L'analyse des mecanismes qui regissent le courant principal d'electrons dans la structure permet de proposer une nouvelle caracterisation de la discontinuite de la bande de conduction e#c=17016 mev dans l'heterojonction ga#0#. #5in#0#. #5p/gaas. La caracterisation du comportement electrothermique, avec notamment l'identification de la resistance thermique et l'etude du gain en courant qui depend du niveau d'injection, a permis d'interpreter un comportement specifique de nos transistors. Les performances obtenues pour les transistors classiques sont f#t=18 ghz, f#m#a#x=20 ghz, et la reduction de la resistance de base par autoalignement du contact de base sur l'emetteur a conduit au doublement de la frequence maximale d'oscillation (f#m#a#x=42ghz). Pour l'application a l'amplification de puissance, il a ete releve a une frequence de 1ghz une puissance r. F de sortie de l'ordre de 1w avec un rendement en puissance ajoutee de 49% et a 10ghz, une puissance et un rendement de 170mw et 29% respectivement.
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Hui-LiangYu and 游輝亮. "Dual Path Binary Neural Network with Adaptive Output Range." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/nuydfp.

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碩士
國立成功大學
資訊工程學系
106
In recent years, deep neural networks (DNNs) have achieved state-of-the-art results in the fields of image recognition, semantic segmentation and machine translation. However, powerful DNNs usually have a large number of parameters and complex calculations. For instance, ImageNet classification challenge winner in 2012, Alex Net, has a model size of about 249MB and 60 million parameters, which needs to perform about 1.5 billion FLOPs to classify a 224 x 224 image. While perform such complex computations, GPUs based machines usually used to speed up training process and inference time. However, for embedded devices, such as smart phones or Internet of Things, there is only a small amount of memory, battery power and computing resources, so it is difficult to deploy DNN to these devices. In the field of model compression, the binary neural network (BNN) is a very promising method, which features are low power consumption and low storage usage, but there is a large gap in prediction accuracy compared with full-precision networks. This thesis proposed a BNN that about the same storage usage as other BNNs and prediction accuracy is close to full-precision network. The method proposed in this thesis has three characteristics: First, the convolution layers have two input sources by dual path method. Second, round the batch normalization output. Third, adjust each layer output by a trainable parameter. The experiments show, our model size is about equal to other BNNs, but the prediction accuracy is much higher. In CIFAR-10 dataset, the prediction accuracy is at least 2.85% higher than other BNNs, even better than ternary network, only 0.69% loss compared to full-precision network. In SVHN dataset, the prediction accuracy is at least 0.21% higher than other BNNs, and even more than 0.58% compared to full-precision network.
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"Analysis of experiments to validate computer models with binary output." IOWA STATE UNIVERSITY, 2010. http://pqdtopen.proquest.com/#viewpdf?dispub=3389285.

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Books on the topic "Binary output"

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Behrooz, Anahit. Mapping Middle-earth. Bloomsbury Publishing Plc, 2024. http://dx.doi.org/10.5040/9781350290792.

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In this cutting-edge study of Tolkien’s most critically neglected maps, Anahit Behrooz examines how cartography has traditionally been bound up in facilitating power. Far more than just illustrations to aid understanding of the story, Tolkien’s corpus of maps are crucial to understanding the broader narratives between humans and their political and environmental landscapes within his legendarium. Undertaking a diegetic literary analysis of the maps as examples of Middle-earth’s own cultural output, Behrooz reveals a sub-created tradition of cartography that articulates specific power dynamics between mapmaker, map reader, and what is being mapped, as well as the human/nonhuman binary that represents human’s control over the natural world. Mapping Middle-earth surveys how Tolkien frames cartography as an inherently political act that embodies a desire for control of that which it maps. In turn, it analyses harmful contemporary engagements with land that intersect with, but also move beyond, cartography such as environmental damage; human-induced geological change; and the natural and bodily costs of political violence and imperialism. Using historical, eco-critical, and postcolonial frameworks, and such theorists as Michel Foucault, Donna Haraway and Edward Said, this book explores Tolkien’s employment of particular generic tropes including medievalism, fantasy, and the interplay between image and text to highlight, and at times correct, his contemporary socio-political epoch and its destructive relationship with the wider world.
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Nakai, You. Reminded by the Instruments. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780190686765.001.0001.

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David Tudor (1926–1996) is remembered today in two guises: as an extraordinary pianist of postwar avant-garde music who worked closely with composers like John Cage and Karlheinz Stockhausen, influencing the development of graphic notation and indeterminacy; and as a spirited pioneer of live-electronic music who realized idiosyncratic performances based on the interaction of homemade modular instruments, inspiring an entire generation of musicians. However, the fact that Tudor himself did not talk or write much about what he was doing, combined with the esoteric nature of electronic circuits and schematics (for musicologists), has prevented any comprehensive approach to the entirety of his output which actually began with the organ and ended in visual art. As a result, Tudor has remained a puzzle of sorts in spite of his profound influence—perhaps a pertinent status for a figure who was known for his deep love of puzzles. This book sets out to solve the puzzle of David Tudor as a puzzle that David Tudor made, applying Tudor’s own methods for approaching other people’s materials to the unusually large number of materials that he himself left behind. Patching together instruments, circuits, sketches, notes, diagrams, recordings, receipts, letters, custom declaration forms, testimonies, and recollections like modular pieces of a giant puzzle, the narrative skips over the misleading binary of performer/composer to present a lively portrait of Tudor as a multi-instrumentalist who always realized his music from the nature of specific instruments.
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Hoste, Eric A. J., John A. Kellum, and Norbert Lameire. Definitions, classification, epidemiology, and risk factors of acute kidney injury. Edited by Norbert Lameire. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780199592548.003.0220_update_001.

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The lack of a precise biochemical definition of acute kidney injury (AKI) resulted in at least 35 definitions in the medical literature, which gave rise to a wide variation in reported incidence and clinical significance of AKI, impeded a meaningful comparison of studies.The first part of this chapter describes and discusses different definitions and classification systems of AKI. Patient outcome and the need for renal replacement therapy are directly related to the severity of AKI, an observation that supports the use of a categorical staging system rather than a simple binary descriptor. The severity of AKI is commonly characterized using the relative changes in serum creatinine and urine output. Recently introduced staging systems including the RIFLE classification and the Acute Kidney Injury Network (AKIN) use these relatively simple and readily available parameters allowing the assignment of individual patients to different AKI stages. More recently, a Kidney Disease: Improving Global Outcomes (KDIGO) workgroup developed a consensus-based AKI staging system drawing elements of both RIFLE and AKIN. The potential pitfalls and limitations of the proposed definitions and classifications are briefly described.The second part of the chapter describes the epidemiology of AKI in different clinical settings; the intensive care unit (ICU), the hospitalized population, and the community. The different spectrum of AKI in the emerging countries is discussed and the most important causes and aetiologies of the major clinical types of AKI, prerenal, renal, and post-renal are summarized in table form. Finally the patient survival and renal functional outcome of AKI are briefly discussed
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Khatun, Samia. Australianama. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780190922603.001.0001.

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Australian deserts remain dotted with the ruins of old mosques. Beginning with a Bengali poetry collection discovered in a nineteenth-century mosque in the town of Broken Hill, Samia Khatun weaves together the stories of various peoples colonized by the British Empire to chart a history of South Asian diaspora. Australia has long been an outpost of Anglo empires in the Indian Ocean world, today the site of military infrastructure central to the surveillance of 'Muslim-majority' countries across the region. Imperial knowledges from Australian territories contribute significantly to the Islamic-Western binary of the post- Cold War era. In narrating a history of Indian Ocean connections from the perspectives of those colonized by the British, Khatun highlights alternative contexts against which to consider accounts of non-white people. Australianama challenges a central idea that powerfully shapes history books across the Anglophone world: the colonial myth that European knowledge traditions are superior to the epistemologies of the colonized. Arguing that Aboriginal and South Asian language sources are keys to the vast, complex libraries that belie colonized geographies, Khatun shows that stories in colonized tongues can transform the very ground from which we view past, present and future.
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Book chapters on the topic "Binary output"

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Ye, Tao, and Xuefeng Zhu. "Binary Coded Output Support Vector Machine." In Intelligent Computing Theories and Technology, 47–55. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39482-9_6.

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Babu, Hafiz Md Hasan. "Multiple-Valued Input Binary-Valued Output Functions." In VLSI Circuits and Embedded Systems, 107–20. Boca Raton: CRC Press, 2022. http://dx.doi.org/10.1201/9781003269182-11.

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Sun, Qilin, Yan Liu, Zhengxue Li, Sibo Yang, Wei Wu, and Jiuwu Jin. "The Binary Output Units of Neural Network." In Advances in Neural Networks – ISNN 2013, 250–57. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39065-4_31.

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Laisney, François, Michael Lechner, and Winfried Pohlmeier. "Semi-Nonparametric Estimation of Binary Choice Models Using Panel Data: An Application to the Innovative Activity of German Firms." In Output and Employment Fluctuations, 87–101. Heidelberg: Physica-Verlag HD, 1994. http://dx.doi.org/10.1007/978-3-642-57989-9_7.

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Morvai, Gusztáv. "Guessing the Output of a Stationary Binary Time Series." In Contributions to Statistics, 207–15. Heidelberg: Physica-Verlag HD, 2003. http://dx.doi.org/10.1007/978-3-642-57410-8_18.

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Lin, Yi, Lucas M. Tabajara, and Moshe Y. Vardi. "ZDD Boolean Synthesis." In Tools and Algorithms for the Construction and Analysis of Systems, 64–83. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-99524-9_4.

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AbstractMotivated by applications in boolean-circuit design, boolean synthesis is the process of synthesizing a boolean function with multiple outputs, given a relation between its inputs and outputs. Previous work has attempted to solve boolean functional synthesis by converting a specification formula into a Binary Decision Diagram (BDD) and quantifying existentially the output variables. We make use of the fact that the specification is usually given in the form of a Conjunctive Normal Form (CNF) formula, and we can perform resolution on a symbolic representation of a CNF formula in the form of a Zero-suppressed Binary Decision Diagram (ZDD). We adapt the realizability test to the context of CNF and ZDD, and show that the Cross operation defined in earlier work can be used for witness construction. Experiments show that our approach is complementary to BDD-based Boolean synthesis.
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Schirmer, Pascal A., and Iosif Mporas. "Binary versus Multiclass Deep Learning Modelling in Energy Disaggregation." In Springer Proceedings in Energy, 45–51. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-63916-7_6.

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AbstractThis paper compares two different deep-learning architectures for the use in energy disaggregation and Non-Intrusive Load Monitoring. Non-Intrusive Load Monitoring breaks down the aggregated energy consumption into individual appliance consumptions, thus detecting device operation. In detail, the “One versus All” approach, where one deep neural network per appliance is trained, and the “Multi-Output” approach, where the number of output nodes is equal to the number of appliances, are compared to each other. Evaluation is done on a state-of-the-art baseline system using standard performance measures and a set of publicly available datasets out of the REDD database.
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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, 311–20. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/bfb0098187.

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Belfiore, J. C. "A weighted-output symbol-by-symbol decoding algorithm of binary convolutional codes." In Coding Theory and Applications, 154–58. Berlin, Heidelberg: Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/3-540-19368-5_17.

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Chaudhari, Narendra S., and Aruna Tiwari. "Extension of Binary Neural Networks for Multi-class Output and Finite Automata." In Neural Information Processing: Research and Development, 211–37. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-39935-3_12.

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Conference papers on the topic "Binary output"

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Guo, Zhixia, Sitao Li, Jiaxiong Ye, Ruan Yu, Qiyang Xu, and Guoping Zhang. "Binary optical resonator with flattop output." In Optical Systems Design and Production, edited by Fritz Merkle. SPIE, 1999. http://dx.doi.org/10.1117/12.360043.

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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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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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Swanson, Gary J., James R. Leger, and Wilfrid B. Veldkamp. "Tandem Binary Structures for Increased Coupling Efficiency of Laser Beams." In Holography. Washington, D.C.: Optica Publishing Group, 1986. http://dx.doi.org/10.1364/holography.1986.tud5.

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Binary phase gratings have been investigated for use as beam splitters (1), multiplexers, and shapers (2). More recently, binary phase gratings have been used as beam couplers (3), coupling a large fraction of the outputs from an array of semiconductor lasers into a single gaussian output. The binary element is used to both split and combine the electric field inside of a complex external cavity. This technique overcomes the output power limitation of optical facet damage from single laser diodes.
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Cao, Jun, and Huimin Ma. "Regression-based parameter optimization for binary output systems." In 2015 3rd International Conference on Information and Communication Technology (ICoICT ). IEEE, 2015. http://dx.doi.org/10.1109/icoict.2015.7231473.

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Yue, Tinghai. "The characterizations of binary vector-output plateaued functions." In 2010 IEEE International Conference on Wireless Communications, Networking and Information Security (WCNIS). IEEE, 2010. http://dx.doi.org/10.1109/wcins.2010.5541807.

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Yue, Tinghai. "A construction of binary vector-output plateaued functions." In 2010 IEEE International Conference on Wireless Communications, Networking and Information Security (WCNIS). IEEE, 2010. http://dx.doi.org/10.1109/wcins.2010.5541808.

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Nguyen, Thuan, and Thinh Nguyen. "Structure of Optimal Quantizer for Binary-Input Continuous-Output Channels with Output Constraints." In 2020 IEEE International Symposium on Information Theory (ISIT). IEEE, 2020. http://dx.doi.org/10.1109/isit44484.2020.9174174.

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Reports on the topic "Binary output"

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Farhi, Edward, and Hartmut Neven. Classification with Quantum Neural Networks on Near Term Processors. Web of Open Science, December 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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Sinclair, Samantha, and Sally Shoop. Automated detection of austere entry landing zones : a “GRAIL Tools” validation assessment. Engineer Research and Development Center (U.S.), August 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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