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Journal articles on the topic 'Sequential processing (Computer science)'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 August 2024

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1

Carmesin, H. O., and H. Schwegler. "Parallel versus sequential processing of relational stimulus structures." Biological Cybernetics 71, no. 6 (October 1994): 523–29. http://dx.doi.org/10.1007/bf00198470.

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2

Carmesin, H. O., and H. Schwegler. "Parallel versus sequential processing of relational stimulus structures." Biological Cybernetics 71, no. 6 (October 1, 1994): 523–29. http://dx.doi.org/10.1007/s004220050111.

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3

Lee, Yong-Joo, and Paul Zipkin. "Processing Networks with Inventories: Sequential Refinement Systems." Operations Research 43, no. 6 (December 1995): 1025–36. http://dx.doi.org/10.1287/opre.43.6.1025.

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4

Korde, P. S., and P. B. Khanale. "Cache Oblivious Matrix Multiplication Algorithm using Sequential Access Processing." Research Journal of Information Technology 3, no. 1 (January 1, 2011): 61–67. http://dx.doi.org/10.3923/rjit.2011.61.67.

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5

Sharma, Shalini, and Angshul Majumdar. "Sequential Transform Learning." ACM Transactions on Knowledge Discovery from Data 15, no. 5 (June 26, 2021): 1–18. http://dx.doi.org/10.1145/3447394.

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This work proposes a new approach for dynamical modeling; we call it sequential transform learning. This is loosely based on the transform (analysis dictionary) learning formulation. This is the first work on this topic. Transform learning, was originally developed for static problems; we modify it to model dynamical systems by introducing a feedback loop. The learnt transform coefficients for the t th instant are fed back along with the t + 1st sample, thereby establishing a Markovian relationship. Furthermore, the formulation is made supervised by the label consistency cost. Our approach keeps the best of two worlds, marrying the interpretability and uncertainty measure of signal processing with the function approximation ability of neural networks. We have carried out experiments on one of the most challenging problems in dynamical modeling - stock forecasting. Benchmarking with the state-of-the-art has shown that our method excels over the rest.

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LeBron Paige, A., Ö. Özdamar, and R. E. Delgado. "Two-dimensional spectral processing of sequential evoked potentials." Medical & Biological Engineering & Computing 34, no. 3 (May 1996): 239–43. http://dx.doi.org/10.1007/bf02520080.

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7

ROBERGE, VINCENT, and MOHAMMED TARBOUCHI. "COMPARISON OF PARALLEL PARTICLE SWARM OPTIMIZERS FOR GRAPHICAL PROCESSING UNITS AND MULTICORE PROCESSORS." International Journal of Computational Intelligence and Applications 12, no. 01 (March 2013): 1350006. http://dx.doi.org/10.1142/s1469026813500065.

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In this paper, we present a parallel implementation of the particle swarm optimization (PSO) on graphical processing units (GPU) using CUDA. By fully utilizing the processing power of graphic processors, our implementation (CUDA-PSO) provides a speedup of 167× compared to a sequential implementation on CPU. This speedup is significantly superior to what has been reported in recent papers and is achieved by four optimizations we made to better adapt the parallel algorithm to the specific architecture of the NVIDIA GPU. However, because today's personal computers are usually equipped with a multicore CPU, it may be unfair to compare our CUDA implementation to a sequential one. For this reason, we implemented a parallel PSO for multicore CPUs using MPI (MPI-PSO) and compared its performance against our CUDA-PSO. The execution time of our CUDA-PSO remains 15.8× faster than our MPI-PSO which ran on a high-end 12-core workstation. Moreover, we show with statistical significance that the results obtained using our CUDA-PSO are of equal quality as the results obtained by the sequential PSO or the MPI-PSO. Finally, we use our parallel PSO for real-time harmonic minimization of multilevel power inverters with 20 DC sources while considering the first 100 harmonics and show that our CUDA-PSO is 294× faster than the sequential PSO and 32.5× faster than our parallel MPI-PSO.

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Zhuo, Youwei, Jingji Chen, Gengyu Rao, Qinyi Luo, Yanzhi Wang, Hailong Yang, Depei Qian, and Xuehai Qian. "Distributed Graph Processing System and Processing-in-memory Architecture with Precise Loop-carried Dependency Guarantee." ACM Transactions on Computer Systems 37, no. 1-4 (June 2021): 1–37. http://dx.doi.org/10.1145/3453681.

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To hide the complexity of the underlying system, graph processing frameworks ask programmers to specify graph computations in user-defined functions (UDFs) of graph-oriented programming model. Due to the nature of distributed execution, current frameworks cannot precisely enforce the semantics of UDFs, leading to unnecessary computation and communication. It exemplifies a gap between programming model and runtime execution. This article proposes novel graph processing frameworks for distributed system and Processing-in-memory (PIM) architecture that precisely enforces loop-carried dependency; i.e., when a condition is satisfied by a neighbor, all following neighbors can be skipped. Our approach instruments the UDFs to express the loop-carried dependency, then the distributed execution framework enforces the precise semantics by performing dependency propagation dynamically. Enforcing loop-carried dependency requires the sequential processing of the neighbors of each vertex distributed in different nodes. We propose to circulant scheduling in the framework to allow different nodes to process disjoint sets of edges/vertices in parallel while satisfying the sequential requirement. The technique achieves an excellent trade-off between precise semantics and parallelism—the benefits of eliminating unnecessary computation and communication offset the reduced parallelism. We implement a new distributed graph processing framework SympleGraph, and two variants of runtime systems— GraphS and GraphSR —for PIM-based graph processing architecture, which significantly outperform the state-of-the-art.

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9

CHANG, C. Y., and K. YAO. "SYSTOLIC ARRAY PROCESSING OF THE SEQUENTIAL DECODING ALGORITHM." International Journal of High Speed Computing 01, no. 03 (September 1989): 465–80. http://dx.doi.org/10.1142/s0129053389000251.

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10

KRITHIVASAN, KAMALA, N. SAKTHI BALAN, and PRAHLADH HARSHA. "DISTRIBUTED PROCESSING IN AUTOMATA." International Journal of Foundations of Computer Science 10, no. 04 (December 1999): 443–63. http://dx.doi.org/10.1142/s0129054199000319.

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With distributed computing beginning to play a major role in modern Computer Science, the theory of grammar systems and distributed automata has been developed in order to model distributed computing. In this paper, we introduce the notion of distributed automata in the sequential sense. Distributed Automata are a group of automata working in unison to accept one language. We build the theory of distributed for FSA and PDA in different modes of acceptance like the t-mode, *-mode, =k-mode, ≤k-mode and ≥k-mode. We then analyze the acceptance power of each automata in all the above modes. We present proofs that distributed FSAs do not have any additional power over "centralized" FSAs in any of the modes, while distributed PDAs with only two components are as powerful as Turing Machines in all of the modes. We give proofs for the equivalence of all modes in the case of PDAs. We also study a restricted version of distributed PDA called k-turn distributed PDA.

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11

Ha, Ok-Kyoon, Keonpyo Lee, Wan-Jin Kim, and Kun Su Yoon. "Effective Parallelization Method for Object Recognition in 2D Sonar Images Based on Task Partitioning." Scientific Programming 2019 (March 3, 2019): 1–9. http://dx.doi.org/10.1155/2019/8908950.

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Techniques for analyzing and avoiding hazardous objects and situations on the seabed are being developed to ensure the safety of ships and submersibles from various hazards. Improvements in accuracy and real-time response are critical for underwater object recognition, which rely on underwater sonar detection to remove noises and analyze the data. Therefore, parallel processing is being introduced for real-time processing of two-dimensional (2D) underwater sonar detector images for seabed monitoring. However, this requires optimized parallel processing between the modules for image processing and the data processing of a vast amount of data. This study proposes an effective parallel processing method, called Task Partitioning, based on central and graphical processing units for monitoring and identifying underwater objects in real time based on 2D-imaging sonar. The practicality of the proposed method is evaluated experimentally by comparing it to the sequential processing method. The experimental results show that the Task Partitioning method significantly improves the processing time for sonar images because it reduces the average execution time to 1% and 5% of the sequential processing method and general parallelization, respectively.

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Lee, Min-Seong, Jee-Tae Park, Ui-Jun Baek, Jung-woo Choi, Chang-Yui Shin, and Myung-Sup Kim. "Deep Learning-Based Traffic Classification Speed Improvement Through Sequential Data Processing." Journal of Korean Institute of Communications and Information Sciences 47, no. 12 (December 31, 2022): 2096–103. http://dx.doi.org/10.7840/kics.2022.47.12.2096.

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13

Itai, Alon, and Yoav Raz. "The number of buffers required for sequential processing of a disk file." Communications of the ACM 31, no. 11 (November 1988): 1338–42. http://dx.doi.org/10.1145/50087.50095.

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14

Frank, Stefan L., Rens Bod, and Morten H. Christiansen. "How hierarchical is language use?" Proceedings of the Royal Society B: Biological Sciences 279, no. 1747 (September 12, 2012): 4522–31. http://dx.doi.org/10.1098/rspb.2012.1741.

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It is generally assumed that hierarchical phrase structure plays a central role in human language. However, considerations of simplicity and evolutionary continuity suggest that hierarchical structure should not be invoked too hastily. Indeed, recent neurophysiological, behavioural and computational studies show that sequential sentence structure has considerable explanatory power and that hierarchical processing is often not involved. In this paper, we review evidence from the recent literature supporting the hypothesis that sequential structure may be fundamental to the comprehension, production and acquisition of human language. Moreover, we provide a preliminary sketch outlining a non-hierarchical model of language use and discuss its implications and testable predictions. If linguistic phenomena can be explained by sequential rather than hierarchical structure, this will have considerable impact in a wide range of fields, such as linguistics, ethology, cognitive neuroscience, psychology and computer science.

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15

Oba, Takanobu, Takaaki Hori, and Atsushi Nakamura. "Sequential dependency analysis for online spontaneous speech processing." Speech Communication 50, no. 7 (July 2008): 616–25. http://dx.doi.org/10.1016/j.specom.2008.04.008.

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16

Cachin, Christian, Idit Keidar, and Alexander Shraer. "Fork sequential consistency is blocking." Information Processing Letters 109, no. 7 (March 2009): 360–64. http://dx.doi.org/10.1016/j.ipl.2008.12.004.

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17

Martin, Maria Angélica Bonadiman, Edgard Moreira Ganzarolli, Arilson Lehmkuhl, Ivan Gonçlves de Souza, and Roldão Roosevelt Urzêdo de Queiróz. "Sequential determination of free and total cyanide by flow injection." Journal of Automated Methods and Management in Chemistry 21, no. 1 (1999): 23–26. http://dx.doi.org/10.1155/s1463924699000048.

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This study presents a flow injection system for the sequential determination of free (CN-) and total (CN-+ HCN) cyanide using a potentiometric method which employs two different processes for the determination of these two chemical species. The first process is based on direct detection of CN-using an ion-selective electrode for cyanide. In the second process, the sample is mixed with acid, and the released HCN is transferred across a PTFE membrane. The flow system employs three solenoid valves, a gas diffusion chamber, an ion-selective electrode, a potentiometer, and a computer with an AID conversion card. A Turbo Pascal®computer program automatically performs all the steps involved in data acquisition and processing. The standard deviation for the results obtained with the proposed method was 0.5%.

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18

Tijsseling, A. G. "Sequential Information Processing Using Time-Delay Connections in Ontogenic CALM Networks." IEEE Transactions on Neural Networks 16, no. 1 (January 2005): 145–59. http://dx.doi.org/10.1109/tnn.2004.839355.

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19

Swanda, Lilis, Ainun Mutia, and Wisnu Kurniadi. "Membuat Aplikasi Penginputan Data Siswa pada Taman Kanak Kanak Harith Foundation Berbasis AppSheet." Journal Software, Hardware and Information Technology 3, no. 1 (January 30, 2023): 16–23. http://dx.doi.org/10.24252/shift.v3i1.45.

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The development of informatics technology and science is very rapid and affects the field of information and management, especially in the field of data processing using computer technology. Computer technology is something that is highly coveted by every organization, because it will produce accurate and perfect information. The need for computers as a means of solving problems quickly and precisely cannot be denied. Currently, the Harith Foundation Kindergarten manages data. Managing Student and Student data, especially in recapitulating and filtering Student and Student data, is still using MS Excel and writing manually. Therefore the purpose of this study is to make an Apsheet-based application for entering student data at the Harith Foundation Kindergarten. The method used in this study is the Waterfall method. The waterfall method is a work method that emphasizes sequential and systematic phases. This application uses the AppSheet platform to process Student and Student data at Harith Foundation Kindergarten which can be used with computers and Android operating system, with the results of making Student and Student data collection applications at Harith Foundation Kindergarten making it easier for Kindergarten Secretaries and Teachers to collect data.

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20

OKAMURA, HIROYUKI, KAZUKI IWAMOTO, and TADASHI DOHI. "A DP-BASED CHECKPOINTING SCHEME IN REAL-TIME APPLICATIONS." International Journal of Reliability, Quality and Safety Engineering 13, no. 04 (August 2006): 323–40. http://dx.doi.org/10.1142/s0218539306002288.

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In this paper, we consider computation algorithms for checkpoint placement in real-time applications. Under the condition that the processing time is bounded by a time limit, we derive sequentially the optimal checkpoint time based on the dynamic programming. In numerical examples, we examine the dependence of optimal checkpoint sequence on both failure time and processing time distributions, and investigate the effectiveness of sequential checkpoint placement.

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21

Broy, Manfred. "Denotational semantics of communicating sequential programs." Information Processing Letters 23, no. 5 (November 1986): 253–59. http://dx.doi.org/10.1016/0020-0190(86)90082-7.

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22

Manolopoulos, Yannis. "Batched search of index sequential files." Information Processing Letters 22, no. 5 (April 1986): 267–72. http://dx.doi.org/10.1016/0020-0190(86)90105-5.

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23

Sezgin, Ali, and Ganesh Gopalakrishnan. "On the definition of sequential consistency." Information Processing Letters 96, no. 6 (December 2005): 193–96. http://dx.doi.org/10.1016/j.ipl.2005.09.002.

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24

Seinstra, F. J., and D. Koelma. "User transparency: a fully sequential programming model for efficient data parallel image processing." Concurrency and Computation: Practice and Experience 16, no. 6 (April 2, 2004): 611–44. http://dx.doi.org/10.1002/cpe.765.

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25

Zahoor, Saniya, and Roohie Naaz Mir. "A Parallelization based Data Management Framework for Pervasive IoT Applications." Scalable Computing: Practice and Experience 21, no. 3 (August 1, 2020): 463–77. http://dx.doi.org/10.12694/scpe.v21i3.1746.

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Pervasive Internet of Things (IoT) is a research paradigm that has attracted considerable attention nowadays. The main aim of pervasive IoT is that in the future, the everyday objects (devices) would be accessible, sensed, and interconnected inside the global structure of the Internet. But in most of the pervasive IoT applications, the resources of an IoT device such as storage, processing, and energy are limited; as such there is a need for management of resources in such applications. Multiple aspects related to the data such as the type of data, size of data, number of transmission and reception of data packets, the structure of data, etc are taken into consideration while managing the resources of pervasive IoT applications. Therefore data management is essential for the management of limited resources in such applications. This paper presents the recent studies and related information in data management for pervasive IoT applications having limited resources. This paper also proposes a parallelization based data management framework for resource-constrained pervasive applications of IoT. The comparison of the proposed framework is done with the sequential approach through simulations and empirical data analysis. The results show an improvement in energy, processing, and storage requirements for the processing of data on the IoT device in the proposed framework as compared to the sequential approach.

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Meng, Lingyan, and Bingtao Zhang. "Evaluation of Private Enterprises Based on Deep Learning." Mobile Information Systems 2022 (September 27, 2022): 1–9. http://dx.doi.org/10.1155/2022/8593669.

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In this paper, we conduct an in-depth research on the corresponding enterprises, combined with some problems existing in the process of data processing and use. We establish a deep learning model on the extensive collection and comprehensive investigation of the research results of domestic and foreign enterprises in all aspects of the process of data processing and use, and determine the research directions. Firstly, in view of the increasing complexity and dimension of enterprise data, and the difficulties of enterprise data application, this paper studies the related data preprocessing methods. Secondly, aiming at the problems of enterprise cost control and customer relationship management, this paper studies the prediction based on enterprise data through the analysis of practical problems and the processing of corresponding data. Finally, in order to progress and advance the efficiency and scientific usefulness of enterprise management, we in this paper study the evaluation based on enterprise data. The model is verified through simulations and compared with several models i.e. cross hybrid and sequential hybrid models. Using certain assumptions, the attained outcomes confirm that the accuracy of the deep learning structure of the single model is sophisticated and greater than that of the cross hybrid model, but lower than that of the sequential hybrid model.

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27

Wang, Yongheng, Xiaozan Zhang, and Zengwang Wang. "A Proactive Decision Support System for Online Event Streams." International Journal of Information Technology & Decision Making 17, no. 06 (November 2018): 1891–913. http://dx.doi.org/10.1142/s0219622018500463.

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In-stream big data processing is an important part of big data processing. Proactive decision support systems can predict future system states and execute some actions to avoid unwanted states. In this paper, we propose a proactive decision support system for online event streams. Based on Complex Event Processing (CEP) technology, this method uses structure varying dynamic Bayesian network to predict future events and system states. Different Bayesian network structures are learned and used according to different event context. A networked distributed Markov decision processes model with predicting states is proposed as sequential decision making model. A Q-learning method is investigated for this model to find optimal joint policy. The experimental evaluations show that this method works well for congestion control in transportation system.

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28

Baqer, Zainab T. "Parallel Computing for Sorting Algorithms." Baghdad Science Journal 11, no. 2 (June 1, 2014): 292–302. http://dx.doi.org/10.21123/bsj.2014.11.2.292-302.

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The expanding use of multi-processor supercomputers has made a significant impact on the speed and size of many problems. The adaptation of standard Message Passing Interface protocol (MPI) has enabled programmers to write portable and efficient codes across a wide variety of parallel architectures. Sorting is one of the most common operations performed by a computer. Because sorted data are easier to manipulate than randomly ordered data, many algorithms require sorted data. Sorting is of additional importance to parallel computing because of its close relation to the task of routing data among processes, which is an essential part of many parallel algorithms. In this paper, sequential sorting algorithms, the parallel implementation of many sorting methods in a variety of ways using MPICH.NT.1.2.3 library under C++ programming language and comparisons between the parallel and sequential implementations are presented. Then, these methods are used in the image processing field. It have been built a median filter based on these submitted algorithms. As the parallel platform is unavailable, the time is computed in terms of a number of computations steps and communications steps

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Cruz, Henry, Martina Eckert, Juan M. Meneses, and J. F. Martínez. "Fast Evaluation of Segmentation Quality with Parallel Computing." Scientific Programming 2017 (2017): 1–9. http://dx.doi.org/10.1155/2017/5767521.

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In digital image processing and computer vision, a fairly frequent task is the performance comparison of different algorithms on enormous image databases. This task is usually time-consuming and tedious, such that any kind of tool to simplify this work is welcome. To achieve an efficient and more practical handling of a normally tedious evaluation, we implemented the automatic detection system, with the help of MATLAB®’s Parallel Computing Toolbox™. The key parts of the system have been parallelized to achieve simultaneous execution and analysis of segmentation algorithms on the one hand and the evaluation of detection accuracy for the nonforested regions, such as a study case, on the other hand. As a positive side effect, CPU usage was reduced and processing time was significantly decreased by 68.54% compared to sequential processing (i.e., executing the system with each algorithm one by one).

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30

Vestergaard, René. "A constructive approach to sequential Nash equilibria." Information Processing Letters 97, no. 2 (January 2006): 46–51. http://dx.doi.org/10.1016/j.ipl.2005.09.010.

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31

Israeli, Amos, and Oran Sharon. "An approximation algorithm for sequential rectangle placement." Information Processing Letters 108, no. 6 (November 2008): 407–11. http://dx.doi.org/10.1016/j.ipl.2008.08.001.

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32

Duarte, Rafael, Alexandre Mota, and Augusto Sampaio. "Introducing concurrency in sequential Java via laws." Information Processing Letters 111, no. 3 (January 2011): 129–34. http://dx.doi.org/10.1016/j.ipl.2010.11.004.

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Szcześniak, Adam, and Zbigniew Szcześniak. "Algorithmic Method for the Design of Sequential Circuits with the Use of Logic Elements." Applied Sciences 11, no. 23 (November 23, 2021): 11100. http://dx.doi.org/10.3390/app112311100.

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This article presents issues related to the design of sequential control systems. The algorithmic design method of sequential control systems is discussed, which allows the design of a diagram of any sequential system. The algorithmic method uses the description in the form of a connection formula. The connection formula defines the order of actuations of driver elements, in this case actuators. The algorithmic method is used, among others, for systems with actuators cooperating with distributors controlled electrically on both sides. The process of creating a system graph has been characterized. The operation of the system has been shown graphically. On the basis of the created graph describing the functions of signal processing, a method for rapid programming of sequential electro-pneumatic systems with the use of logic elements has been provided. A separate dedicated timing unit has been used to perform memory functions. Its operation is based on successive states, in such a way that the next state deletes the previous one. Graph-based systems have been validated through simulation using Festo’s FluidSim computer-aided design software.

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Alamareen, Abdullah, Omar Al-Jarrah, and Inad A. Aljarrah. "Image Mosaicing Using Binary Edge Detection Algorithm in a Cloud-Computing Environment." International Journal of Information Technology and Web Engineering 11, no. 3 (July 2016): 1–14. http://dx.doi.org/10.4018/ijitwe.2016070101.

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Image Mosaicing is an image processing technique that arises from the need of having a more realistic view of the real world wider than the view captured by the lenses of the available cameras. In this paper, a sequence of images will be mosaiced using binary edge detection algorithm in a cloud-computing environment to improve processing speed and accuracy. The authors have used Platform as a Service (PaaS) to provide a number of nodes in the cloud to run the computational intensive image processing and stitching algorithms. This increased the processing speed as most of image processing algorithms deal with every single pixel in the image. Message Passing Interface (MPI) is used for message passing among the compute-nodes in the cloud and a MapReduce technique is used for image distribution and collection, where the root node is used as reducer and the others as mappers. After applying the algorithm on different sequence of images and different machines on JUST cloud, the authors have achieved high mosaicing accuracy, and the execution time has been improved when comparing it with sequential execution on the images.

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Albagory, Yasser, and Fahad Alraddady. "An Efficient Approach for Sidelobe Level Reduction Based on Recursive Sequential Damping." Symmetry 13, no. 3 (March 15, 2021): 480. http://dx.doi.org/10.3390/sym13030480.

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Recently, antenna array radiation pattern synthesis and adaptation has become an essential requirement for most wireless communication systems. Therefore, this paper proposes a new recursive sidelobe level (SLL) reduction algorithm using a sidelobe sequential damping (SSD) approach based on pattern subtraction, where the sidelobes are sequentially reduced to the optimum required levels with near-symmetrical distribution. The proposed SSD algorithm is demonstrated, and its performance is analyzed, including SLL reduction and convergence behavior, mainlobe scanning, processing speed, and performance under mutual coupling effects for uniform linear and planar arrays. In addition, the SSD performance is compared with both conventional tapering windows and optimization techniques, where the simulation results show that the proposed SSD approach has superior maximum and average SLL performances and lower processing speeds. In addition, the SSD is found to have a constant SLL convergence profile that is independent on the array size, working effectively on any uniform array geometry with interelement spacing less than one wavelength, and deep SLL levels of less than −70 dB can be achieved relative to the mainlobe level, especially for symmetrical arrays.

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Li, Zihao, Aixin Sun, and Chenliang Li. "DiffuRec: A Diffusion Model for Sequential Recommendation." ACM Transactions on Information Systems 42, no. 3 (December 29, 2023): 1–28. http://dx.doi.org/10.1145/3631116.

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Mainstream solutions to sequential recommendation represent items with fixed vectors. These vectors have limited capability in capturing items’ latent aspects and users’ diverse preferences. As a new generative paradigm, diffusion models have achieved excellent performance in areas like computer vision and natural language processing. To our understanding, its unique merit in representation generation well fits the problem setting of sequential recommendation. In this article, we make the very first attempt to adapt the diffusion model to sequential recommendation and propose DiffuRec for item representation construction and uncertainty injection. Rather than modeling item representations as fixed vectors, we represent them as distributions in DiffuRec , which reflect a user’s multiple interests and an item’s various aspects adaptively. In the diffusion phase, DiffuRec corrupts the target item embedding into a Gaussian distribution via noise adding, which is further applied for sequential item distribution representation generation and uncertainty injection. Afterward, the item representation is fed into an approximator for target item representation reconstruction. In the reverse phase, based on a user’s historical interaction behaviors, we reverse a Gaussian noise into the target item representation, then apply a rounding operation for target item prediction. Experiments over four datasets show that DiffuRec outperforms strong baselines by a large margin. 1

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37

PAVEL, SANDY, and SELIM G. AKL. "EFFICIENT ALGORITHMS FOR THE EUCLIDEAN DISTANCE TRANSFORM." Parallel Processing Letters 05, no. 02 (June 1995): 205–12. http://dx.doi.org/10.1142/s0129626495000187.

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The Euclidean Distance Transform is an important computational tool for the processing of binary images, with applications in many areas such as computer vision, pattern recognition and robotics. We investigate the properties of this transform and describe an O(n2) time optimal sequential algorithm. A deterministic EREW-PRAM parallel algorithm which runs in O( log n) time using O(n2) processors and O(n2) space is also derived. Further, a cost optimal randomized parallel algorithm which runs within the same time bounds with high probability, is given.

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38

Ivaschenko, Anton, Sergey Maslennikov, Anastasia Stolbova, and Oleg Golovnin. "Multi-Layer Data Model of a Complex Transportation Network." International Journal of Embedded and Real-Time Communication Systems 12, no. 2 (April 2021): 21–36. http://dx.doi.org/10.4018/ijertcs.2021040102.

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The paper presents an original multi-layer data model for software solutions to be used in transportation logistics. Versus the known technologies of data formalization based on their classification by similarity and conceptual consistency, there is proposed a new approach of information adaptive management oriented to application of parallel computing. As a basic decomposition approach, it is recommended to consider processing capacity characteristics and performance measures instead of objects and subjects classification typical for human perception. Two algorithms were proposed based on the method of criteria comparison. The sequential algorithm implements the classical approach to find a path on a graph, while the parallel one uses an approach that makes it possible to increase the efficiency of layer-by-layer task separation, taking into account the capabilities of computing system for simultaneous parallel calculations. A study conducted on real data showed an advantage in the execution time of the parallel computing algorithm over the usual sequential search of 38%.

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39

Wang, Yu, Yuan Wang, Zhenwan Peng, Feifan Zhang, and Fei Yang. "A Concise Relation Extraction Method Based on the Fusion of Sequential and Structural Features Using ERNIE." Mathematics 11, no. 6 (March 16, 2023): 1439. http://dx.doi.org/10.3390/math11061439.

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Relation extraction, a fundamental task in natural language processing, aims to extract entity triples from unstructured data. These triples can then be used to build a knowledge graph. Recently, pre-training models that have learned prior semantic and syntactic knowledge, such as BERT and ERNIE, have enhanced the performance of relation extraction tasks. However, previous research has mainly focused on sequential or structural data alone, such as the shortest dependency path, ignoring the fact that fusing sequential and structural features may improve the classification performance. This study proposes a concise approach using the fused features for the relation extraction task. Firstly, for the sequential data, we verify in detail which of the generated representations can effectively improve the performance. Secondly, inspired by the pre-training task of next-sentence prediction, we propose a concise relation extraction approach based on the fusion of sequential and structural features using the pre-training model ERNIE. The experiments were conducted on the SemEval 2010 Task 8 dataset and the results show that the proposed method can improve the F1 value to 0.902.

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Glass, C. A., C. N. Potts, and V. A. Strusevich. "Scheduling Batches with Sequential Job Processing for Two-Machine Flow and Open Shops." INFORMS Journal on Computing 13, no. 2 (May 2001): 120–37. http://dx.doi.org/10.1287/ijoc.13.2.120.10521.

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Byrne, Charles. "Sequential unconstrained minimization algorithms for constrained optimization." Inverse Problems 24, no. 1 (January 9, 2008): 015013. http://dx.doi.org/10.1088/0266-5611/24/1/015013.

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GRELCK, CLEMENS, SVEN-BODO SCHOLZ, and ALEX SHAFARENKO. "A GENTLE INTRODUCTION TO S-NET: TYPED STREAM PROCESSING AND DECLARATIVE COORDINATION OF ASYNCHRONOUS COMPONENTS." Parallel Processing Letters 18, no. 02 (June 2008): 221–37. http://dx.doi.org/10.1142/s0129626408003351.

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We present the design of S-NET, a coordination language and component technology based on stream processing. S-NET achieves a near-complete separation between application code, written in a conventional programming language, and coordination code, written in S-NET itself. S-NET boxes integrate existing sequential code as stream-processing components into streaming networks, whose construction is based on algebraic formulae built out of four network combinators. Subtyping on the level of boxes and networks and a tailor-made inheritance mechanism achieve flexible software reuse.

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Chen, Wanyu, Pengjie Ren, Fei Cai, Fei Sun, and Maarten De Rijke. "Multi-interest Diversification for End-to-end Sequential Recommendation." ACM Transactions on Information Systems 40, no. 1 (January 31, 2022): 1–30. http://dx.doi.org/10.1145/3475768.

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Sequential recommenders capture dynamic aspects of users’ interests by modeling sequential behavior. Previous studies on sequential recommendations mostly aim to identify users’ main recent interests to optimize the recommendation accuracy; they often neglect the fact that users display multiple interests over extended periods of time, which could be used to improve the diversity of lists of recommended items. Existing work related to diversified recommendation typically assumes that users’ preferences are static and depend on post-processing the candidate list of recommended items. However, those conditions are not suitable when applied to sequential recommendations. We tackle sequential recommendation as a list generation process and propose a unified approach to take accuracy as well as diversity into consideration, called multi-interest, diversified, sequential recommendation . Particularly, an implicit interest mining module is first used to mine users’ multiple interests, which are reflected in users’ sequential behavior. Then an interest-aware, diversity promoting decoder is designed to produce recommendations that cover those interests. For training, we introduce an interest-aware, diversity promoting loss function that can supervise the model to learn to recommend accurate as well as diversified items. We conduct comprehensive experiments on four public datasets and the results show that our proposal outperforms state-of-the-art methods regarding diversity while producing comparable or better accuracy for sequential recommendation.

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Wang, J., Z. Qian, and S. Liu. "Process Induced Stresses of a Flip-Chip Packaging by Sequential Processing Modeling Technique." Journal of Electronic Packaging 120, no. 3 (September 1, 1998): 309–13. http://dx.doi.org/10.1115/1.2792638.

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In this paper, a nonlinear finite element framework was established for processing mechanics modeling of flip-chip packaging assemblies and relevant layered manufacturing. In particular, topological change was considered in order to model the sequential steps during the flip-chip assembly. Geometric and material nonlinearity, which includes the viscoelastic properties of underfill and the viscoplastic properties of solder alloys, were considered. Different stress-free temperatures for different elements in the same model were used to simulate practical manufacturing process-induced thermal residual stress field in the chip assembly. As comparison, two FEM models (processing model and nonprocessing model) of the flip-chip package considered, associated with different processing schemes, were analyzed. From the finite element analysis, it is found that the stresses and deflections obtained from nonprocessing model are generally smaller than those obtained from the processing model due to the negligence of the bonding process-induced residual stresses and warpage. The stress values at the given point obtained from the processing model are about 20 percent higher than those obtained from the nonprocessing model. The deflection values at the given points obtained from the processing model are usually 25 percent higher than those obtained from the nonprocessing model. Therefore, a bigger error may be caused by using nonprocessing model in the analysis of process-induced residual stress field and warpage in the packaging assemblies.

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Lyakhov, Pavel, Nataliya Semyonova, Nikolay Nagornov, Maxim Bergerman, and Albina Abdulsalyamova. "High-Speed Wavelet Image Processing Using the Winograd Method with Downsampling." Mathematics 11, no. 22 (November 14, 2023): 4644. http://dx.doi.org/10.3390/math11224644.

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Wavelets are actively used to solve a wide range of image processing problems in various fields of science and technology. Modern image processing systems cannot keep up with the rapid growth in digital visual information. Various approaches are used to reduce the computational complexity and increase computational speeds. The Winograd method (WM) is one of the most promising. However, this method is used to obtain sequential values. Its use for wavelet image processing requires expanding the calculation methodology to cases of downsampling. This paper proposes a new approach to reduce the computational complexity of wavelet image processing based on the WM with decimation. Calculations have been carried out and formulas have been derived that implement digital filtering using the WM with downsampling. The derived formulas can be used for 1D filtering with an arbitrary downsampling stride. Hardware modeling of wavelet image filtering on an FPGA showed that the WM reduces the computational time by up to 66%, with increases in the hardware costs and power consumption of 95% and 344%, respectively, compared to the direct method. A promising direction for further research is the implementation of the developed approach on ASIC and the use of modular computing for more efficient parallelization of calculations and an even greater increase in the device speed.

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Netto, Marcelo Vaz, and Sahudy Montenegro González. "SSLC: A Search Algorithm Based on Linear Collisions and Poisson Probability Distribution." ACM Journal of Experimental Algorithmics 27 (December 31, 2022): 1–15. http://dx.doi.org/10.1145/3497876.

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This article proposes an algorithm, sequential search based on linear collisions ( SSLC ), based on Poisson probability distribution. SSLC works on large static volumes of data, whose keys are ordered and uniformly distributed. We proved that it takes a constant execution time with high probability. Experimental validation focuses on two metrics—processing time and memory resources. We compared SSLC with perfect hashing over various datasets. The experimentation reveals that our algorithm is three times faster with the use of three times fewer memory resources than perfect hashing. Its main contribution is to demonstrate that simple routines can have more powerful computational results.

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MALCHER, ANDREAS, CARLO MEREGHETTI, and BEATRICE PALANO. "SUBLINEARLY SPACE BOUNDED ITERATIVE ARRAYS." International Journal of Foundations of Computer Science 21, no. 05 (October 2010): 843–58. http://dx.doi.org/10.1142/s0129054110007581.

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Iterative arrays (IAs) are a parallel computational model with a sequential processing of the input. They are one-dimensional arrays of interacting identical deterministic finite automata. In this paper, realtime-IAs with sublinear space bounds are used to recognize formal languages. The existence of an infinite proper hierarchy of space complexity classes between logarithmic and linear space bounds is proved. Some decidability questions on logarithmically space bounded realtime-IAs are investigated, and an optimal logarithmic space lower bound for non-regular language recognition on realtime-IAs is shown. Finally, some non-recursive trade-offs between space bounded realtime-IAs are emphasized.

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Ring, Wolfgang, and Johannes Prix. "Sequential predictor-corrector regularization methods and their limitations." Inverse Problems 16, no. 3 (June 1, 2000): 619–33. http://dx.doi.org/10.1088/0266-5611/16/3/306.

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Schöpfer, F., and T. Schuster. "Fast regularizing sequential subspace optimization in Banach spaces." Inverse Problems 25, no. 1 (December 4, 2008): 015013. http://dx.doi.org/10.1088/0266-5611/25/1/015013.

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Son, Suhyune, Seonjeong Hwang, Sohyeun Bae, Soo Jun Park, and Jang-Hwan Choi. "A Sequential and Intensive Weighted Language Modeling Scheme for Multi-Task Learning-Based Natural Language Understanding." Applied Sciences 11, no. 7 (March 31, 2021): 3095. http://dx.doi.org/10.3390/app11073095.

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Multi-task learning (MTL) approaches are actively used for various natural language processing (NLP) tasks. The Multi-Task Deep Neural Network (MT-DNN) has contributed significantly to improving the performance of natural language understanding (NLU) tasks. However, one drawback is that confusion about the language representation of various tasks arises during the training of the MT-DNN model. Inspired by the internal-transfer weighting of MTL in medical imaging, we introduce a Sequential and Intensive Weighted Language Modeling (SIWLM) scheme. The SIWLM consists of two stages: (1) Sequential weighted learning (SWL), which trains a model to learn entire tasks sequentially and concentrically, and (2) Intensive weighted learning (IWL), which enables the model to focus on the central task. We apply this scheme to the MT-DNN model and call this model the MTDNN-SIWLM. Our model achieves higher performance than the existing reference algorithms on six out of the eight GLUE benchmark tasks. Moreover, our model outperforms MT-DNN by 0.77 on average on the overall task. Finally, we conducted a thorough empirical investigation to determine the optimal weight for each GLUE task.

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