Journal articles on the topic 'Core kernel operations'
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Nadim, Mohammad, Wonjun Lee, and David Akopian. "Characteristic Features of the Kernel-level Rootkit for Learning-based Detection Model Training." Electronic Imaging 2021, no. 3 (June 18, 2021): 34–1. http://dx.doi.org/10.2352/issn.2470-1173.2021.3.mobmu-034.
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The core part of the operating system is the kernel, and it plays an important role in managing critical data structure resources for correct operations. The kernel-level rootkits are the most elusive type of malware that can modify the running OS kernel in order to hide its presence and perform many malicious activities such as process hiding, module hiding, network communication hiding, and many more. In the past years, many approaches have been proposed to detect kernel-level rootkit. Still, it is challenging to detect new attacks and properly categorize the kernel-level rootkits. Memory forensic approaches showed efficient results with the limitation against transient attacks. Cross-view-based and integrity monitoring-based approaches have their own weaknesses. A learning-based detection approach is an excellent way to solve these problems. In this paper, we give an insight into the kernel-level rootkit characteristic features and how the features can be represented to train learning-based models in order to detect known and unknown attacks. Our feature set combined the memory forensic, cross-view, and integrity features to train learning-based detection models. We also suggest useful tools that can be used to collect the characteristics features of the kernel-level rootkit.
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GE, MING, and YANGSHENG XU. "KERNEL-BASED DATA COMPRESSION FOR ADVANCED MANUFACTURING SYSTEM." Journal of Advanced Manufacturing Systems 02, no. 01 (June 2003): 89–104. http://dx.doi.org/10.1142/s021968670300023x.
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Manufacturing system is becoming larger and more complicated. Global manufacturing chains have become common in the new millennium. Internet and intranet integrate the advanced manufacturing system. To perform remote monitoring and diagnosis in such chains and systems, real-time data compression has become a core factor in the efficient and effective exchange of information exchange via computer networks. This paper presents a new technique for compressing data using a kernel-based method. Overcoming the drawbacks of support vector techniques — that is, fast decompression but slow compression — the new method exhibits high speed in both phases. In addition, the new method can also be applied for pattern classification. Based on strain signal example tests derived from sheet metal stamping operations, the new method is very effective. The proposed technology has enormous potential in the application of advanced manufacturing system monitoring and control through internet or intranet.
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Driessen, T., S. Muto, and M. Nakayama. "A cooperative game of information trading: The core, the nucleolus and the kernel." ZOR Zeitschrift für Operations Research Methods and Models of Operations Research 36, no. 1 (January 1992): 55–72. http://dx.doi.org/10.1007/bf01541032.
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Savran, I., M. Demirci, and A. H. Yılmaz. "Accelerating Shor’s factorization algorithm on GPUs." Canadian Journal of Physics 96, no. 7 (July 2018): 759–61. http://dx.doi.org/10.1139/cjp-2017-0768.
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Shor’s quantum algorithm is very important for cryptography, because it can factor large numbers much faster than classical algorithms. In this study, we implement a simulator for Shor’s quantum algorithm on graphic processor units (GPU) and compare our results with Liquid, which is a Microsoft quantum simulation platform, and two classical CPU implementations. We evaluate 10 benchmarks for comparing our GPU implementation with Liquid and single-core implementation. The analysis shows that GPU vector operations are more suitable for Shor’s quantum algorithm. Our GPU kernel function is compute-bound, due to all threads in a block reaching the same element of the state vector. Our implementation has 52.5× speedup over single-core algorithm and 20.5× speedup over Liquid.
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Chiang, Mei-Ling, and Wei-Lun Su. "Thread-Aware Mechanism to Enhance Inter-Node Load Balancing for Multithreaded Applications on NUMA Systems." Applied Sciences 11, no. 14 (July 14, 2021): 6486. http://dx.doi.org/10.3390/app11146486.
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NUMA multi-core systems divide system resources into several nodes. When an imbalance in the load between cores occurs, the kernel scheduler’s load balancing mechanism then migrates threads between cores or across NUMA nodes. Remote memory access is required for a thread to access memory on the previous node, which degrades performance. Threads to be migrated must be selected effectively and efficiently since the related operations run in the critical path of the kernel scheduler. This study focuses on improving inter-node load balancing for multithreaded applications. We propose a thread-aware selection policy that considers the distribution of threads on nodes for each thread group while migrating one thread for inter-node load balancing. The thread is selected for which its thread group has the least exclusive thread distribution, and thread members are distributed more evenly on nodes. This has less influence on data mapping and thread mapping for the thread group. We further devise several enhancements to eliminate superfluous evaluations for multithreaded processes, so the selection procedure is more efficient. The experimental results for the commonly used PARSEC 3.0 benchmark suite show that the modified Linux kernel with the proposed selection policy increases performance by 10.7% compared with the unmodified Linux kernel.
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Ping, Yuan, Bin Hao, Xiali Hei, Jie Wu, and Baocang Wang. "Maximized Privacy-Preserving Outsourcing on Support Vector Clustering." Electronics 9, no. 1 (January 17, 2020): 178. http://dx.doi.org/10.3390/electronics9010178.
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Despite its remarkable capability in handling arbitrary cluster shapes, support vector clustering (SVC) suffers from pricey storage of kernel matrix and costly computations. Outsourcing data or function on demand is intuitively expected, yet it raises a great violation of privacy. We propose maximized privacy-preserving outsourcing on SVC (MPPSVC), which, to the best of our knowledge, is the first all-phase outsourceable solution. For privacy-preserving, we exploit the properties of homomorphic encryption and secure two-party computation. To break through the operation limitation, we propose a reformative SVC with elementary operations (RSVC-EO, the core of MPPSVC), in which a series of designs make selective outsourcing phase possible. In the training phase, we develop a dual coordinate descent solver, which avoids interactions before getting the encrypted coefficient vector. In the labeling phase, we design a fresh convex decomposition cluster labeling, by which no iteration is required by convex decomposition and no sampling checks exist in connectivity analysis. Afterward, we customize secure protocols to match these operations for essential interactions in the encrypted domain. Considering the privacy-preserving property and efficiency in a semi-honest environment, we proved MPPSVC’s robustness against adversarial attacks. Our experimental results confirm that MPPSVC achieves comparable accuracies to RSVC-EO, which outperforms the state-of-the-art variants of SVC.
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Polievoda, Yurii. "INVESTIGATION OF THE PROCESS OF CHIPPING OF THE WALNUT SHELL AS A RESULT OF THE FORCE ACTION OF HEMISPHERICAL SURFACES." Vibrations in engineering and technology, no. 3(98) (October 30, 2020): 111–19. http://dx.doi.org/10.37128/2306-8744-2020-3-12.
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Knowledge of the technical properties of walnuts is essential to facilitate and improve the design of processing equipment and procedures and equipment for collection, packaging and storage. In the process of obtaining the fruit of a walnut and its derivatives, the kernels are subjected to a number of single operations. At each stage, based on the mechanical properties of walnuts, various types of equipment operate, including vibration equipment for cleaning, sorting, separating and peeling. Thus, the detailed results presented in this study provide useful data that can be used by engineers to design appropriate walnut processing machines, thereby improving process and quality control. To reduce mechanical damage and improve the Knowledge of the technical properties of walnuts is necessary to facilitate and improve the design of process equipment, as well as to mechanize the operations of collection, packaging and storage. In the process of obtaining walnuts, namely the kernels are subjected to a number of single operations. At each stage, based on the mechanical properties of walnuts, different types of equipment work, including vibrating for cleaning, sorting, separation and peeling. Thus, the detailed results presented in this study provide useful data that can be used by engineers in the design of appropriate machines for processing walnuts, thereby improving the process and quality control. The article provides a detailed review of the process of splitting the walnut kernel. Examples of many ways to split the shell, all their disadvantages and advantages are given. The mechanical method of peeling is theoretically investigated and substantiated. To reduce mechanical damage and improve the quality of extraction of walnut kernels during peeling, the object of study was selected 1 variety of walnut. The results of compression tests showed that the relationship between the breaking force and the deformation of the walnut was nonlinear, and the process of peeling (chipping) of the shell mainly consisted of three stages. The best method of splitting a walnut was «spherical compression» (between two spherical inserts), and the maximum value of the destructive force was also determined. The results showed that «spherical compression» was an appropriate way to destroy the walnut, which led to obvious trends in the spread of cracks in the shell and, moreover, to better integrity of the removed core. The article considers a number of small and large equipment designed for splitting nuts, both at home and in industrial conditions, of different design and performance.
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Blanchfield, Paul J., Lori S. Tate, and Cheryl L. Podemski. "Survival and behaviour of rainbow trout (Oncorhynchus mykiss) released from an experimental aquaculture operationThis paper is part of the series “Forty Years of Aquatic Research at the Experimental Lakes Area”." Canadian Journal of Fisheries and Aquatic Sciences 66, no. 11 (November 2009): 1976–88. http://dx.doi.org/10.1139/f09-127.
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The potential for farmed fish that have escaped from open-cage aquaculture operations to affect native populations will depend on their survival and behaviour in the wild. We used standard commercial practices to rear 10 tonnes of rainbow trout ( Oncorhynchus mykiss ) in a 23 ha lake at the Experimental Lakes Area (Ontario, Canada). Each fall (2003–2005), we released farmed rainbow trout (escapees) into the study lake and monitored their movements using automated positioning telemetry. Rainbow trout experienced high annual mortality (~50%), with none surviving beyond 3 years. Farmed fish had narrowly defined pelagic distributions that comprised the upper few metres of the water column, even when at the cage site. Although released rainbow trout dispersed throughout the study lake, most spent significant portions of time at the cage site, especially during normal operation when commercial feed was available. Core use areas (50% Kernel) included the farm for half of the released fish. Surviving rainbow trout showed continued reliance upon the cage site in their second year. However, wide dispersal, high growth rate, and lack of reliance on the cage site by some escaped fish warrant further research to assess potential effects of open-cage aquaculture in the water bodies where the industry occurs.
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Ge, Fen, Ning Wu, Hao Xiao, Yuanyuan Zhang, and Fang Zhou. "Compact Convolutional Neural Network Accelerator for IoT Endpoint SoC." Electronics 8, no. 5 (May 5, 2019): 497. http://dx.doi.org/10.3390/electronics8050497.
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As a classical artificial intelligence algorithm, the convolutional neural network (CNN) algorithm plays an important role in image recognition and classification and is gradually being applied in the Internet of Things (IoT) system. A compact CNN accelerator for the IoT endpoint System-on-Chip (SoC) is proposed in this paper to meet the needs of CNN computations. Based on analysis of the CNN structure, basic functional modules of CNN such as convolution circuit and pooling circuit with a low data bandwidth and a smaller area are designed, and an accelerator is constructed in the form of four acceleration chains. After the acceleration unit design is completed, the Cortex-M3 is used to construct a verification SoC and the designed verification platform is implemented on the FPGA to evaluate the resource consumption and performance analysis of the CNN accelerator. The CNN accelerator achieved a throughput of 6.54 GOPS (giga operations per second) by consuming 4901 LUTs without using any hardware multipliers. The comparison shows that the compact accelerator proposed in this paper makes the CNN computational power of the SoC based on the Cortex-M3 kernel two times higher than the quad-core Cortex-A7 SoC and 67% of the computational power of eight-core Cortex-A53 SoC.
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MERRILL, DUANE, and ANDREW GRIMSHAW. "HIGH PERFORMANCE AND SCALABLE RADIX SORTING: A CASE STUDY OF IMPLEMENTING DYNAMIC PARALLELISM FOR GPU COMPUTING." Parallel Processing Letters 21, no. 02 (June 2011): 245–72. http://dx.doi.org/10.1142/s0129626411000187.
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The need to rank and order data is pervasive, and many algorithms are fundamentally dependent upon sorting and partitioning operations. Prior to this work, GPU stream processors have been perceived as challenging targets for problems with dynamic and global data-dependences such as sorting. This paper presents: (1) a family of very efficient parallel algorithms for radix sorting; and (2) our allocation-oriented algorithmic design strategies that match the strengths of GPU processor architecture to this genre of dynamic parallelism. We demonstrate multiple factors of speedup (up to 3.8x) compared to state-of-the-art GPU sorting. We also reverse the performance differentials observed between GPU and multi/many-core CPU architectures by recent comparisons in the literature, including those with 32-core CPU-based accelerators. Our average sorting rates exceed 1B 32-bit keys/sec on a single GPU microprocessor. Our sorting passes are constructed from a very efficient parallel prefix scan "runtime" that incorporates three design features: (1) kernel fusion for locally generating and consuming prefix scan data; (2) multi-scan for performing multiple related, concurrent prefix scans (one for each partitioning bin); and (3) flexible algorithm serialization for avoiding unnecessary synchronization and communication within algorithmic phases, allowing us to construct a single implementation that scales well across all generations and configurations of programmable NVIDIA GPUs.
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Sledevič, Tomyslav, Artūras Serackis, and Darius Plonis. "FPGA Implementation of a Convolutional Neural Network and Its Application for Pollen Detection upon Entrance to the Beehive." Agriculture 12, no. 11 (November 4, 2022): 1849. http://dx.doi.org/10.3390/agriculture12111849.
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The condition of a bee colony can be predicted by monitoring bees upon hive entrance. The presence of pollen grains gives beekeepers significant information about the well-being of the bee colony in a non-invasive way. This paper presents a field-programmable-gate-array (FPGA)-based pollen detector from images obtained at the hive entrance. The image dataset was acquired at native entrance ramps from six different hives. To evaluate and demonstrate the performance of the system, various densities of convolutional neural networks (CNNs) were trained and tested to find those suitable for pollen grain detection at the chosen image resolution. We propose a new CNN accelerator architecture that places a pre-trained CNN on an SoC FPGA. The CNN accelerator was implemented on a cost-optimized Z-7020 FPGA with 16-bit fixed-point operations. The kernel binarization and merging with the batch normalization layer were applied to reduce the number of DSPs in the multi-channel convolutional core. The estimated average performance was 32 GOPS for a single convolutional core. We found that the CNN with four convolutional and two dense layers gave a 92% classification accuracy, and it matched those declared for state-of-the-art methods. It took 8.8 ms to classify a 512 × 128 px frame and 2.4 ms for a 256 × 64 px frame. The frame rate of the proposed method outperformed the speed of known pollen detectors. The developed pollen detector is cost effective and can be used as a real-time image classification module for hive status monitoring.
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Orekhov, Sergey, and Hennadiy Malyhon. "METRICS OF VIRTUAL PROMOTION OF A PRODUCT." Bulletin of National Technical University "KhPI". Series: System Analysis, Control and Information Technologies, no. 2 (6) (December 28, 2021): 23–26. http://dx.doi.org/10.20998/2079-0023.2021.02.04.
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An approach to the mathematical description of the criterion for the effectiveness of a new object of research – virtual promotion is presented in thepaper. The emergence of this new object of research is connected, on the one hand, with the classical theory of marketing, and on the other withmodern Internet technologies. Marketing is based on the 4P principle: product, price, location and promotion. Promotion is a component of thisprinciple. But in modern conditions, this phenomenon is changing under the influence of the Internet. Now this 4P component is becoming a fullyvirtual instrument. The traditional scheme of promotion functioning is as follows. A message is created to a potential buyer and the delivery channel ofthis message undergoes a change. It is based on the principle: money – goods – money. While the new sales scheme is described by the scheme: weattract a client, make money on a client, we spend money. In the new scheme, we deal with product knowledge in the form of the so-called semanticcore of web content. Knowledge describes for a potential client how a given product can cover his need for something. Using the logistic principles ofthe transfer of goods, this semantic core is loaded into the specified Internet nodes. That is, virtual promotion is formed as two channels: logistics andmarketing. The first one performs three operations: concentration, formatting and distribution of semantic cores on the Internet. The second managesthis process, forming a virtual promotion map. This map is a graph of Internet nodes. It is required to define such a tree of Internet nodes so that virtualpromotion has maximum efficiency. The paper analyzes modern metrics related to the processes of search engine optimization on the Internet.Unfortunately, these metrics evaluate only statistically after the fact of visiting a web resource or the budget of the Internet site in which theadvertising message about the product was placed. Therefore, based on the conversion metric, a criterion for the effectiveness of virtual promotion wasproposed in the work, which takes into account both the attractiveness of the semantic core and the attractiveness of the Internet site where thesemantic core will be located. The criterion reflects the income that we receive depending on the attractiveness of the semantic kernel and the Internetsite.
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Wei, Zhen Qi, Pei Lin Liu, Ji Kong, and Ren Dong Ying. "Design of Arithmetic Operation Core in Embedded Processor for High Definition Audio Applications." Applied Mechanics and Materials 538 (April 2014): 289–92. http://dx.doi.org/10.4028/www.scientific.net/amm.538.289.
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To meet requirements of wider data width, higher throughput, and more flexibility, a specific arithmetic operation core (AOC) is designed for high definition audio application specific processors. The proposed core is capable of processing long bit-width operations, as well as short bit-width operations in parallel. A six-stage pipeline is applied in the architecture of AOC to support amounts of DSP operations, and a novel stage-skipping technique is used to improve the execution efficiency of instructions passing through the deep pipeline. Several DSP kernels and audio data decoding applications are used in performance evaluation of AOC. Experiment results show that the proposed operation core can achieve over 50% higher execution efficiency in audio applications than conventional high performance DSPs, providing an appealing solution for design of operation core for high definition audio applications.
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Зверев, Сергей Васильевич. "Peeling of hemp seeds." Food processing industry, no. 5 (May 4, 2022): 32–35. http://dx.doi.org/10.52653/ppi.2022.5.5.010.
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В связи с проблемой дефицита белка, в первую очередь животного, внимание пищевиков обратилось к растительным белкам, более доступным и дешевым. Наряду с бобовыми культурами повышенное содержание белка имеют семена масличных культур, в том числе и семена конопли. Конопляное семя - ценная пищевая добавка. Кроме масла ценной компонентой является белок. При этом конопля содержит мало усвояемых углеводов, что делает ее перспективной для балансировки белков и углеводов в комбинированных продуктах. В качестве пищевой добавки на рынке предлагается конопляная мука, которая, в зависимости от того, из чего она получена - например, из обезжиренного семени, - содержит 30,0 % белка, 7,9 % жиров и 24,7 % углеводов. Содержание белка в муке из обезжиренного ядра достигает 50 %. Однако содержание этих компонент неравномерно по анатомическим частям семени. Масло и белок в основном сосредоточены в ядре, клетчатка - в оболочке. Для эффективного извлечения белка и жира желательно анатомические части семян разделить. Например, для получения высокобелкового продукта с минимальным содержанием пищевых волокон и максимальным содержанием масла необходимо оболочки отделить от ядра. Процесс включает традиционные для зернопереработки операции сушки, дробления, ситового и пневмосепарирования. Для дробления семян использовался центробежный шелушитель. Далее применялись операции рассева на ситах на фракции и пневмосепарирование. Варьировались количество сит (фракций) и скорости воздуха в канале при пофракционном пневмосепарировании. В простейшем случае получено три вида продукта: относы крупной фракции (оболочки с низким содержанием белка), относы мелкой фракции с содержанием белка около 20 % и высокобелковое ядро с белком около 30 % и повышенным содержанием масла. Суммарный выход дробленого ядра после пневмосепарирования (проход сита 1,8 мм) составил 44 %. Содержание в ядре белка - около 30 %, клетчатки - 0,9 %, жира - 53 %. Отжим или экстракция жира позволяет получить продукт, близкий к белковому концентрату (около 50 % белка). Hemp seed is a valuable food additive. In addition to oil, protein is a valuable component. At the same time, hemp contains few digestible carbohydrates, which makes it promising for balancing proteins and carbohydrates in combined products. However, the content of these components is uneven in the anatomical parts of the seed. Oil and protein are mainly concentrated in the core, fiber - in the shell. For effective extraction of protein and fat, it is desirable to separate the anatomical parts of the seeds. For example, to obtain a high-protein product with a minimum content of dietary fiber and a maximum content of oil, it is necessary to separate the shells from the core. The process includes traditional grain processing operations of drying, crushing, sieve and pneumatic separation. A centrifugal husker was used to crush the seeds. Further, sieving operations on sieves into fractions and pneumoseparation were used. The number of sieves (fractions) and the air velocity in the channel varied during fractional pneumoseparation. In the simplest case, three types of product were obtained: large fraction ratios (shells with a low protein content), small fraction ratios with a protein content of about 20 % and a high-protein core with a protein of about 30 % and an increased oil content. The total yield of the crushed core after pneumoseparation (1.8 mm sieve passage) was 44 %. The content of protein in the kernel is about 30 %, fiber 0.9 %, fat 53 %. Pressing or extraction of fat allows you to get a product close to a protein concentrate (about 50 % protein). hemp nutritional value.
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Bramas, Bérenger, and Pavel Kus. "Computing the sparse matrix vector product using block-based kernels without zero padding on processors with AVX-512 instructions." PeerJ Computer Science 4 (April 30, 2018): e151. http://dx.doi.org/10.7717/peerj-cs.151.
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The sparse matrix-vector product (SpMV) is a fundamental operation in many scientific applications from various fields. The High Performance Computing (HPC) community has therefore continuously invested a lot of effort to provide an efficient SpMV kernel on modern CPU architectures. Although it has been shown that block-based kernels help to achieve high performance, they are difficult to use in practice because of the zero padding they require. In the current paper, we propose new kernels using the AVX-512 instruction set, which makes it possible to use a blocking scheme without any zero padding in the matrix memory storage. We describe mask-based sparse matrix formats and their corresponding SpMV kernels highly optimized in assembly language. Considering that the optimal blocking size depends on the matrix, we also provide a method to predict the best kernel to be used utilizing a simple interpolation of results from previous executions. We compare the performance of our approach to that of the Intel MKL CSR kernel and the CSR5 open-source package on a set of standard benchmark matrices. We show that we can achieve significant improvements in many cases, both for sequential and for parallel executions. Finally, we provide the corresponding code in an open source library, called SPC5.
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Mego, Roman, and Tomas Fryza. "Instruction mapping techniques for processors with very long instruction word architectures." Journal of Electrical Engineering 73, no. 6 (December 1, 2022): 387–95. http://dx.doi.org/10.2478/jee-2022-0053.
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Abstract This paper presents an instruction mapping technique for generating a low-level assembly code for digital signal processing algorithms. This technique helps developers to implement retargetable kernel functions with the performance benefits of the low-level assembly languages. The approach is aimed at exceptionally long instruction word (VLIW) architectures, which benefits the most from the proposed method. Mapped algorithms are described by the signal-flow graphs, which are used to find possible parallel operations. The algorithm is converted into low-level code and mapped to the target architecture. This process also introduces the optimization of instruction mapping priority, which leads to the more effective code. The technique was verified on selected kernels, compared to the common programming methods, and proved that it is suitable for VLIW architectures and for portability to other systems.
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Blakely, Derrick, Eamon Collins, Ritambhara Singh, Andrew Norton, Jack Lanchantin, and Yanjun Qi. "FastSK: fast sequence analysis with gapped string kernels." Bioinformatics 36, Supplement_2 (December 2020): i857—i865. http://dx.doi.org/10.1093/bioinformatics/btaa817.
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Abstract Motivation Gapped k-mer kernels with support vector machines (gkm-SVMs) have achieved strong predictive performance on regulatory DNA sequences on modestly sized training sets. However, existing gkm-SVM algorithms suffer from slow kernel computation time, as they depend exponentially on the sub-sequence feature length, number of mismatch positions, and the task’s alphabet size. Results In this work, we introduce a fast and scalable algorithm for calculating gapped k-mer string kernels. Our method, named FastSK, uses a simplified kernel formulation that decomposes the kernel calculation into a set of independent counting operations over the possible mismatch positions. This simplified decomposition allows us to devise a fast Monte Carlo approximation that rapidly converges. FastSK can scale to much greater feature lengths, allows us to consider more mismatches, and is performant on a variety of sequence analysis tasks. On multiple DNA transcription factor binding site prediction datasets, FastSK consistently matches or outperforms the state-of-the-art gkmSVM-2.0 algorithms in area under the ROC curve, while achieving average speedups in kernel computation of ∼100× and speedups of ∼800× for large feature lengths. We further show that FastSK outperforms character-level recurrent and convolutional neural networks while achieving low variance. We then extend FastSK to 7 English-language medical named entity recognition datasets and 10 protein remote homology detection datasets. FastSK consistently matches or outperforms these baselines. Availability and implementation Our algorithm is available as a Python package and as C++ source code at https://github.com/QData/FastSK Supplementary information Supplementary data are available at Bioinformatics online.
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Li, Jia Jian, Jian Qun Liu, Ping Zhang, and Wei Qiang Gao. "Hardware Development of CNC System Based on OMAPL138 and FPGA." Key Engineering Materials 620 (August 2014): 575–80. http://dx.doi.org/10.4028/www.scientific.net/kem.620.575.
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In order to realize high speed, high precision, high reliability, miniaturization performance of the CNC (Computer numerical control) system, this paper proposed a hardware platform of embedded CNC system based on OMAPL138 and FPGA. OMAPL138 is a SOC using C6748 DSP kernel and ARM9 kernel dual-core structure, the kernel frequency can achieve up to 375/456 MHz. ARM kernel of the CNC system which runs the Linux operation system is responsible for task management, DSP kernel is in charge of real-time interpolation and look-ahead algorithm, and FPGA module generates pulses to control the movement of the servo motor. Firstly, the overall hardware architecture of the embedded CNC system was designed. Meanwhile the hardware circuit design of CPU core module based on OMAPL138, human-computer interaction module, EMIFA bus interface of the FPGA core module were emphasized in detail, and also the serial port, Ethernet, USB communication interface module were introduced. A serial test experiments have been conducted and the results have shown that this embedded CNC system is powerful and stable.
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Bsebsu, F. M., and G. Bede. "Thermal hydraulic analysis and design of the WWR-M2 nuclear research reactor – power upgrading." Kerntechnik 67, no. 2-3 (April 1, 2002): 102–10. http://dx.doi.org/10.1515/kern-2002-0044.
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Abstract This paper presents the outline of the core thermal hydraulic design and analysis (Operational Safety Analysis) of the Budapest nuclear research reactor (WWR-M2 type), which is a tank-type, light water-cooled nuclear research reactor with 36% enriched uranium coaxial annuli fuel. The research reactor is currently upgraded to 10 MWth of thermal power, while the cooling capacity of the reactor was designed and constructed for 20 MWth. This reserve in the cooling capacity serves redundancy today but can be used for future upgrading too. The core thermal hydraulic design was, therefore, done for the normal operation conditions so that fuel elements have enough safety margins both against nucleate boiling anywhere in the reactor core. Thermal hydraulic performance was studied. It is shown that the 36% enriched UAlx-Al fuel elements in WWR-SM fuel coolant channel do not allow to force up the reactor power to 20 MWth. The study was carried out for an equilibrium core, with compact load (223 fuel assemblies) under normal operation conditions only (steady state condition).
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Abdel-Latif, S. H. "Severe accident simulation for VVER-1000 reactor using ASTEC-V2.1.1.3." Kerntechnik 86, no. 6 (December 1, 2021): 454–69. http://dx.doi.org/10.1515/kern-2021-0017.
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Abstract The station black-out (SBO) is one of the main accident sequences to be considered in the field of severe accident research. To evaluate a nuclear power plant’s behavior in the context of this accident, the integral ASTEC-V2.1.1.3 code “Accident Source Term Evaluation Code” covers sequences of SBO accidents that may lead to a severe accident. The aim of this work is to discuss the modelling principles for the core melting and in-vessel melt relocation phenomena of the VVER-1000 reactor. The scenario of SBO is simulated by ASTEC code using its basic modules. Then, the simulation is performed again by the same code after adding and activating the modules; ISODOP, DOSE, CORIUM, and RCSMESH to simulate the ex-vessel melt. The results of the two simulations are compared. As a result of SBO, the active safety systems are not available and have not been able to perform their safety functions that maintain the safety requirements to ensure a secure operation of the nuclear power plant. As a result, the safety requirements will be violated causing the core to heat-up. Moreover potential core degradation will occur. The present study focuses on the reactor pressure vessel failure and relocation of corium into the containment. It also discusses the transfer of Fission Products (FPs) from the reactor to the containment, the time for core heat-up, hydrogen production and the amount of corium at the lower plenum reactor pressure vessel is determined.
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Li, R., M. Peng, G. Xia, and H. Li. "The simulation research on the natural circulation operation characteristic of FNPP in rolling and inclined condition." Kerntechnik 86, no. 1 (March 1, 2021): 4–16. http://dx.doi.org/10.1515/kern-2020-0058.
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Abstract Recently, the FNPP (Floating Nuclear Power Plant) has got more and more attention and rapid development due to very wide prospect application on remote areas or islands. In general, the IPWR (Integral Pressurized Water Reactor) is adopted to meet the requirements of the limited space, the nuclear safety and the maneuverability in marine. The IPWR could depend on natural circulation operation to remove the residual heat of core under accident or low load operation condition. Because the driving head is low, the natural circulation flow is likely to be influenced by rolling and inclined condition. To clarify the natural circulation flow characteristics of the core in FNPP rolling motion and inclined condition, based on the modified THEATRe code by adding the ocean motion module and spatial coordinate convert module, the main thermal-hydraulic parameters variation in rolling and inclined condition were obtained. The effect of inclined angle, rolling amplitude and period on the natural circulation flow were discussed. The natural circulation flow in the core fluctuates periodically with rolling motion. And the inclination and rolling will also cause the degree of steam superheat of OTSG secondary side fluctuate, which could impact on the stable operation of secondary side system.
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Mihajlenko, Kristina, Mikhail Lukin, and Andrey Stankevich. "A method for decompilation of AMD GCN kernels to OpenCL." Information and Control Systems, no. 2 (April 29, 2021): 33–42. http://dx.doi.org/10.31799/1684-8853-2021-2-33-42.
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Introduction: Decompilers are useful tools for software analysis and support in the absence of source code. They are available for many hardware architectures and programming languages. However, none of the existing decompilers support modern AMD GPU architectures such as AMD GCN and RDNA. Purpose: We aim at developing the first assembly decompiler tool for a modern AMD GPU architecture that generates code in the OpenCL language, which is widely used for programming GPGPUs. Results: We developed the algorithms for the following operations: preprocessing assembly code, searching data accesses, extracting systemvalues, decompiling arithmetic operations and recovering data types. We also developed templates for decompilation of branching operations. Practical relevance: We implemented the presented algorithms in Python as a tool called OpenCLDecompiler, which supports a large subset of AMD GCN instructions. This tool automatically converts disassembled GPGPU code into the equivalent OpenCL code, which reduces the effort required to analyze assembly code.
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Lu, Yonghua. "Research on the establishment and operation mode of virtual e-commerce entrepreneurial organization under the background of innovation and entrepreneurship." Advances in Education, Humanities and Social Science Research 1, no. 1 (May 9, 2022): 231. http://dx.doi.org/10.56028/aehssr.1.1.231.
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With the development of E-commerce in China, in order to quickly seize the fleeting market opportunities, many market entities using modern information technology to form trans-regional, cross-industry, benefit sharing, risk sharing Virtual E-commerce Entrepreneurial Organizations. However, many virtual e-commerce entrepreneurial organizations have not successfully completed their entrepreneurial projects and failed due to various reasons. In this paper, the characteristics and operation process of Virtual E-commerce Entrepreneurial Organizations were analyzed, and the operation mode of Giants Alliance Inside with Non-core Members Outside (GAI-NMO) was proposed, which is the members engaged in core business constitute the core of virtual entrepreneurial organization which can maintain competitive advantage, and members engaged in non-core business form a flexible network structure around the kernel.
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Bramas, Berenger. "Inastemp: A Novel Intrinsics-as-Template Library for Portable SIMD-Vectorization." Scientific Programming 2017 (2017): 1–18. http://dx.doi.org/10.1155/2017/5482468.
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The development of scientific applications requires highly optimized computational kernels to benefit from modern hardware. In recent years, vectorization has gained key importance in exploiting the processing capabilities of modern CPUs, whose evolution is characterized by increasing register-widths and core numbers, but stagnating clock frequencies. In particular, vectorization allows floating point operations to be performed at a higher rate than the processor’s frequency. However, compilers often fail to vectorize complex codes and pure assembly/intrinsic implementations often suffer from software engineering issues, such as readability and maintainability. Moreover, it is difficult for domain scientists to write optimized code without technical support. To address these issues, we propose Inastemp, a lightweight open-source C++ library. Inastemp offers a solution to develop hardware-independent computational kernels for the CPU. These kernels are portable across compilers and floating point precision and vectorized targeting SSE(3,4.1,4.2), AVX(2), AVX512, or ALTIVEC/VMX instructions. Inastemp provides advanced features, such as an if-else statement that vectorizes branches that cannot be removed. Our performance study shows that Inastemp has the same efficiency as pure intrinsic approaches on modern architectures. As side-results, this study provides micro benchmarks on the latest HPC architectures for three different computational kernels, emphasizing comparisons between scalar and intrinsic-based codes.
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Yu, Yajun, Liangshan Li, Jiale Zhao, and Xiaogeng Wang. "Discrete Element Simulation Based on Elastic–Plastic Damping Model of Corn Kernel–Cob Bonding Force for Rotation Speed Optimization of Threshing Component." Processes 9, no. 8 (August 16, 2021): 1410. http://dx.doi.org/10.3390/pr9081410.
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Current corn kernel-cob bonding mechanics models (LSD models) uniformly consider the bonding force changes during the maize threshing operation as an elastic change, resulting in computational errors of up to 10% or more in discrete element simulations. Due to the inability to perform high-precision discrete element simulation of the mechanics characteristics during the corn threshing operation, the core operating parameters of the corn thresher (rotation speed of the threshing component) rely mainly on empirical settings, resulting in a consistent difficulty in exceeding 85% of the corn ear threshing rate. In this paper, by testing the mechanics characteristics of corn kernels, the bonding force is found to have both elastic and plastic changes during the threshing process. An elastic–plastic (EP) damping model of the corn kernel–cob bonding force was established by introducing a bonding restitution coefficient e to achieve an integrated consideration of the two changes. By testing the relationship between the properties of the corn ear itself and the model parameters, the pattern of the effect of the corn ear moisture content and the loading direction of the ear by force on the EP model parameters was found. By establishing a model of the relationship between the corn cob’s own properties and the model parameters, the EP model parameter values can be determined by simply determining the moisture content of the ear. In this paper, the EP model was established and the high-precision simulation and analysis of the process of bonding force variation between corn kernel and cob is realized on the self-developed AgriDEM software. At the meantime, the optimal values of the threshing component rotation speed under different conditions of moisture content of corn ear were obtained by establishing an optimization model of threshing component rotation speed. The test results showed that the corn ear threshing rate could reach more than 92.40% after adopting the optimized speed value of the threshing component in this paper. Meanwhile, the test results showed that the discrete element simulation results based on the EP model did not significantly differ from the measured results of the thresher. Compared with the most widely used LSD model, the EP model can reduce the computational error by 3.35% to 6.05%.
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Chen, Kuan-Ting, Wei-Hsuan Ma, Yin-Tsung Hwang, and Kuan-Ying Chang. "A Low Complexity, High Throughput DoA Estimation Chip Design for Adaptive Beamforming." Electronics 9, no. 4 (April 13, 2020): 641. http://dx.doi.org/10.3390/electronics9040641.
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Direction of Arrival (DoA) estimation is essential to adaptive beamforming widely used in many radar and wireless communication systems. Although many estimation algorithms have been investigated, most of them focus on the performance enhancement aspect but overlook the computing complexity or the hardware implementation issues. In this paper, a low-complexity yet effective DoA estimation algorithm and the corresponding hardware accelerator chip design are presented. The proposed algorithm features a combination of signal sub-space projection and parallel matching pursuit techniques, i.e., applying signal projection first before performing matching pursuit from a codebook. This measure helps minimize the interference from noise sub-space and makes the matching process free of extra orthogonalization computations. The computing complexity can thus be reduced significantly. In addition, estimations of all signal sources can be performed in parallel without going through a successive update process. To facilitate an efficient hardware implementation, the computing scheme of the estimation algorithm is also optimized. The most critical part of the algorithm, i.e., calculating the projection matrix, is largely simplified and neatly accomplished by using QR decomposition. In addition, the proposed scheme supports parallel matches of all signal sources from a beamforming codebook to improve the processing throughput. The algorithm complexity analysis shows that the proposed scheme outperforms other well-known estimation algorithms significantly under various system configurations. The performance simulation results further reveal that, subject to a beamforming codebook with a 5° angular resolution, the Root Mean Square (RMS) error of angle estimations is only 0.76° when Signal to Noise Ratio (SNR) = 20 dB. The estimation accuracy outpaces other matching pursuit based approaches and is close to that of the classic Estimation of Signal Parameters Via Rotational Invariance Techniques (ESPRIT) scheme but requires only one fifth of its computing complexity. In developing the hardware accelerator design, pipelined Coordinate Rotation Digital Computer (CORDIC) processors consisting of simple adders and shifters are employed to implement the basic trigonometric operations needed in QR decomposition. A systolic array architecture is developed as the computing kernel for QR decomposition. Other computing modules are also realized using various linear systolic arrays and chained together seamlessly to maximize the computing throughput. A Taiwan Semiconductor Manufacturing Company (TSMC) 40 nm CMOS process was chosen as the implementation technology. The gate count of the chip design is 454.4k, featuring a core size of 0.76 mm 2 , and can operate up to 333 MHz. This suggests that one DoA estimation, with up to three signal sources, can be performed every 2.38 μs.
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PEYGHAMI, M. REZA. "AN INTERIOR POINT APPROACH FOR SEMIDEFINITE OPTIMIZATION USING NEW PROXIMITY FUNCTIONS." Asia-Pacific Journal of Operational Research 26, no. 03 (June 2009): 365–82. http://dx.doi.org/10.1142/s0217595909002250.
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Kernel functions play an important role in interior point methods (IPMs) for solving linear optimization (LO) problems to define a new search direction. In this paper, we consider primal-dual algorithms for solving Semidefinite Optimization (SDO) problems based on a new class of kernel functions defined on the positive definite cone [Formula: see text]. Using some appealing and mild conditions of the new class, we prove with simple analysis that the new class-based large-update primal-dual IPMs enjoy an [Formula: see text] iteration bound to solve SDO problems with special choice of the parameters of the new class.
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Sun, Xiaoli, Daniel R. Cremons, Erwan Mazarico, Guangning Yang, James B. Abshire, David E. Smith, Maria T. Zuber, et al. "Small All-Range Lidar for Asteroid and Comet Core Missions." Sensors 21, no. 9 (April 28, 2021): 3081. http://dx.doi.org/10.3390/s21093081.
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We report the development of a new type of space lidar specifically designed for missions to small planetary bodies for both topographic mapping and support of sample collection or landing. The instrument is designed to have a wide dynamic range with several operation modes for different mission phases. The laser transmitter consists of a fiber laser that is intensity modulated with a return-to-zero pseudo-noise (RZPN) code. The receiver detects the coded pulse-train by correlating the detected signal with the RZPN kernel. Unlike regular pseudo noise (PN) lidars, the RZPN kernel is set to zero outside laser firing windows, which removes most of the background noise over the receiver integration time. This technique enables the use of low peak-power but high pulse-rate lasers, such as fiber lasers, for long-distance ranging without aliasing. The laser power and the internal gain of the detector can both be adjusted to give a wide measurement dynamic range. The laser modulation code pattern can also be reconfigured in orbit to optimize measurements to different measurement environments. The receiver uses a multi-pixel linear mode photon-counting HgCdTe avalanche photodiode (APD) array with near quantum limited sensitivity at near to mid infrared wavelengths where many fiber lasers and diode lasers operate. The instrument is modular and versatile and can be built mostly with components developed by the optical communication industry.
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Akinfolarin, Femi, Buliaminu Kareem, and Oladunni Oyetola Alabi. "Development of iron ores sintering machine for blast furnace process." Analecta Technica Szegedinensia 15, no. 2 (December 15, 2021): 64–75. http://dx.doi.org/10.14232/analecta.2021.2.64-75.
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There must be proper means to sinter and, agglomerated iron ore concentrate before it can be further processed in the blast furnace. A Sintering machine of 5kg capacity of agglomerated ore was designed and fabricated using mild steel material, which was locally sourced. The machine was fabricated with a combustion chamber of 30 by 30 cm and with 15cm depth. It was also lined with refractory material to reduce the chamber to the volume of 3375 cm3. However, the sintering chamber was designed to have a truncated square pyramid shape to the volume of 2150 cm3 after lining with refractory material. The design was made to utilize coke and palm kernel shell char as fuel which will be ignited to produce heat into the sintered material by suction of the heat into the agglomerated sintered ore. Tests such as tumbler index, abrasion, and porosity test were carried out on the sintered products in agreement with ASTM E276 and E389 standards. The results from the test gave a tumbler index of 70.2% and 65.7% for coke and palm kernel shells respectively. Also, abrasion index of 5.1% and 4.6% for coke and palm kernel char, and porosity of 6.8% and 6.5% for coke and palm kernel char respectively. The results from the experimental test were in agreement with other research work. Therefore, the developed iron ore sintering machine has a better efficiency of producing sinter for blast furnace operation.
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Grgić, Davor, Štefica Vlahović, Mario Matijević, Paulina Dučkić, and Srđan Špalj. "Dose Calculation for Emergency Control Room HVAC Filter." Journal of Energy - Energija 68, no. 2-3 (July 8, 2022): 98–111. http://dx.doi.org/10.37798/2019682-3195.
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NPP Krsko is introducing Emergency Control Room (ECR) as part of safety upgrades. According to 10CFR50 Appendix A, GDC 19, both main control room and emergency control room should have adequate radiation protection to permit operators to shutdown the plant and keep it in safe shutdown conditions without receiving more than 50 mSv effective whole body dose, within 30 days from accident initiation. One of the important prerequisites to achieve that is proper operation of control room HVAC. In this work we are focused to calculation of gamma doses from radioactive materials accumulated in HEPA and charcoal filters during 30 days of HVAC operation. The dose at selected points around the filter was calculated using Microshield 10.0 point kernel code. The radioactive gamma source is calculated using RADTRAD 3.03 for plant's severe accident SGTR sequence calculated with MAAP 4.0.7 code. Calculated dose rates at peak filter activity are compared against results obtained with SCALE 6.2 MAVRIC shielding sequence (Monaco Monte Carlo functional module and CADIS methodology). The reasonable agreement between point kernel and hybrid Monte Carlo results was obtained.
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Vladislavić, Đani, Darko Huljenić, and Julije Ožegović. "Virtual Network Resource Optimization Model for Network Function Virtualization." Wireless Communications and Mobile Computing 2021 (August 17, 2021): 1–21. http://dx.doi.org/10.1155/2021/9928210.
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Network function virtualization (NFV) is a concept aimed at achieving telecom grade cloud ecosystem for new-generation networks focusing on capital and operational expenditure (CAPEX and OPEX) savings. This study introduces empirical throughput prediction model for the virtual network function (VNF) and network function virtualization infrastructure (NFVI) architectures based on Linux kernel. The model arises from the methodology for performance evaluation and modeling based on execution area (EA) distribution by CPU core pinning. EA is defined as a software execution unit that can run isolated on a compute resource (CPU core). EAs are derived from the elements and packet processing principles in NFVIs and VNFs based on Linux kernel. Performing measurements and observing linearity of the measured results open the possibility to apply model calibration technique to achieve general VNF and NFVI architecture model with performance prediction and environment setup optimization. The modeling parameters are derived from the cumulative packet processing cost obtained by measurements for collocated EAs on the CPU core hosting the bottleneck EA. The VNF and NFVI architecture model with performance prediction is successfully validated against the measurement results obtained in emulated environment and used to predict optimal system configurations and maximal throughput results for different CPUs.
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Zhang, Chunyuan, Qingxin Zhu, and Xinzheng Niu. "Kernel Recursive Least-Squares Temporal Difference Algorithms with Sparsification and Regularization." Computational Intelligence and Neuroscience 2016 (2016): 1–11. http://dx.doi.org/10.1155/2016/2305854.
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By combining with sparse kernel methods, least-squares temporal difference (LSTD) algorithms can construct the feature dictionary automatically and obtain a better generalization ability. However, the previous kernel-based LSTD algorithms do not consider regularization and their sparsification processes are batch or offline, which hinder their widespread applications in online learning problems. In this paper, we combine the following five techniques and propose two novel kernel recursive LSTD algorithms: (i) online sparsification, which can cope with unknown state regions and be used for online learning, (ii)L2andL1regularization, which can avoid overfitting and eliminate the influence of noise, (iii) recursive least squares, which can eliminate matrix-inversion operations and reduce computational complexity, (iv) a sliding-window approach, which can avoid caching all history samples and reduce the computational cost, and (v) the fixed-point subiteration and online pruning, which can makeL1regularization easy to implement. Finally, simulation results on two 50-state chain problems demonstrate the effectiveness of our algorithms.
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Refeat, Riham M., and Rania A. Fahmy. "Optimized fractional-order PID controller based on nonlinear point kinetic model for VVER-1000 reactor." Kerntechnik 87, no. 1 (February 1, 2022): 104–14. http://dx.doi.org/10.1515/kern-2021-0038.
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Abstract Nuclear reactor dynamics are nonlinear and time-varying, so the power level control is a challenging problem in nuclear power plants (NPPs) to ensure both its operation stability and efficiency. An important measure to improve the safety of the reactor core of NPP is the implementation of robust control for the core by adjusting the inserted reactivity of the control rods. Thus in the present paper, fractional-order PID (FOPID) controller is developed as it is well known for its simplicity and robustness against disturbances. A Genetic Algorithm (GA) is used to determine FOPID controller parameters to achieve the desired power level for the generation III+ reactor VVER-1000. Implementing the GA, a suitable objective function is proposed to search for the optimal FOPID parameters. The nonlinear model of the VVER-1000 nuclear reactor is presented based on the point kinetic equations with six delayed neutron groups and temperature feedback from lumped fuel and coolant temperatures. Two cases for the VVER-1000 reactor are investigated; the changes in the power loads and the control rod withdrawal that leads to reactivity disturbance. Moreover, the uncertainties that result from model parameters perturbation are added to examine the controller robustness. The simulation results show that the proposed optimized FOPID controller can track the desired power level of the VVER-1000 reactor and robustly cope with any load changes, disturbances, or any parameters uncertainties. Also, it proves the superiority of the proposed optimized FOPID controller over other PID controllers in ensuring the safe and effective operation of the VVER-1000 reactor.
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Varalakshmi, M., Amit Parashuram Kesarkar, and Daphne Lopez. "Embarrassingly Parallel GPU Based Matrix Inversion Algorithm for Big Climate Data Assimilation." International Journal of Grid and High Performance Computing 10, no. 1 (January 2018): 71–92. http://dx.doi.org/10.4018/ijghpc.2018010105.
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Attempts to harness the big climate data that come from high-resolution model output and advanced sensors to provide more accurate and rapidly-updated weather prediction, call for innovations in the existing data assimilation systems. Matrix inversion is a key operation in a majority of data assimilation techniques. Hence, this article presents out-of-core CUDA implementation of an iterative method of matrix inversion. The results show significant speed up for even square matrices of size 1024 X 1024 and more, without sacrificing the accuracy of the results. In a similar test environment, the comparison of this approach with a direct method such as the Gauss-Jordan approach, modified to process large matrices that cannot be processed directly within a single kernel call shows that the former is twice as efficient as the latter. This acceleration is attributed to the division-free design and the embarrassingly parallel nature of every sub-task of the algorithm. The parallel algorithm has been designed to be highly scalable when implemented with multiple GPUs for handling large matrices.
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Yuan, Xuyi, Yugang Fan, Chengjiang Zhou, Xiaodong Wang, and Guanghui Zhang. "Fault Diagnosis of Check Valve Based on KPLS Optimal Feature Selection and Kernel Extreme Learning Machine." Coatings 12, no. 9 (September 10, 2022): 1320. http://dx.doi.org/10.3390/coatings12091320.
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The check valve is the core part of high−pressure diaphragm pumps. It has complex operation conditions and has difficulty characterizing fault states completely with its single feature. Therefore, a fault signal diagnosis model based on the kernel extreme learning machine (KELM) was constructed to diagnose the check valve. The model adopts a multi−feature extraction method and reduces dimensionality through kernel partial least squares (KPLS). Firstly, we divided the check valve vibration signal into several non−overlapping samples. Then, we extracted 16 time−domain features, 13 frequency−domain features, 16 wavelet packet energy features, and energy entropy features from each sample to construct a multi−feature set characterizing the operation state of the check valve. Next, we used the KPLS method to optimize the 45 dimension multi−feature data and employed the processed feature set to establish a KELM fault diagnosis model. Experiments showed that the method based on KPLS optimal feature selection could fully characterize the operating state of the equipment with an accuracy rate of 96.88%. This result indicates the high accuracy and effectiveness of the multi−feature set constructed with the KELM fault diagnosis model.
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SOLIMAN, MOSTAFA I., and STANISLAV G. SEDUKHIN. "PERFORMANCE EVALUATION OF BLAS ON THE TRIDENT PROCESSOR." Parallel Processing Letters 15, no. 04 (December 2005): 407–14. http://dx.doi.org/10.1142/s0129626405002325.
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Different subtasks of an application usually have different computational, memory, and I/O requirements that result in different needs for computer capabilities. Thus, the more appropriate approach for both high performance and simple programming model is designing a processor having multi-level instruction set architecture (ISA). This leads to high performance and minimum executable code size. Since the fundamental data structures for a wide variety of existing applications are scalar, vector, and matrix, our research Trident processor has three-level ISA executed on zero-, one-, and two-dimensional arrays of data. These levels are used to express a great amount of fine-grain data parallelism to a processor instead of the dynamical extraction by a complicated logic or statically with compilers. This reduces the design complexity and provides high-level programming interface to hardware. In this paper, the performance of Trident processor is evaluated on BLAS, which represent the kernel operations of many data parallel applications. We show that Trident processor proportionally reduces the number of clock cycles per floating-point operation by increasing the number of execution datapaths.
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CHALI, YLLIAS. "Scalable generation of texts using causal and temporal expansions of sentences." Natural Language Engineering 7, no. 3 (August 29, 2001): 191–205. http://dx.doi.org/10.1017/s1351324901002716.
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This paper presents a exible bottom-up process to incrementally generate several versions of the same text, building up the core text from its kernel version into other versions varying of the levels of details. We devise a method for identifying the question/answer relations holding between the propositions of a text, we give rules for characterizing the kernel version of a text, and we provide a procedure, based on causal and temporal expansions of sentences, which distinguishes semantically these levels of details according to their importance. This is based on the assumption that we have a stock of information from the interpreter's knowledge base available. The sentence expansion operation is formally defined according to three principles: (1) the kernel principle ensures to obtain the gist information; (2) the expansion principle defines an incremental augmentation of a text; and (3) the subsume principle defines an importance-based order among the possible details of the information. The system developed allows users to generate in a follow-up way their own text version which meets their expectations and their demands expressed as questions about the text under consideration.
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Liang, Guangqi, Dongxiao Niu, and Yi Liang. "Core Competitiveness Evaluation of Clean Energy Incubators Based on Matter-Element Extension Combined with TOPSIS and KPCA-NSGA-II-LSSVM." Sustainability 12, no. 22 (November 17, 2020): 9570. http://dx.doi.org/10.3390/su12229570.
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Scientific and accurate core competitiveness evaluation of clean energy incubators is of great significance for improving their burgeoning development. Hence, this paper proposes a hybrid model on the basis of matter-element extension integrated with TOPSIS and KPCA-NSGA-II-LSSVM. The core competitiveness evaluation index system of clean energy incubators is established from five aspects, namely strategic positioning ability, seed selection ability, intelligent transplantation ability, growth catalytic ability and service value-added ability. Then matter-element extension and TOPSIS based on entropy weight is applied to index weighting and comprehensive evaluation. For the purpose of feature dimension reduction, kernel principal component analysis (KPCA) is used to extract momentous information among variables as the input. The evaluation results can be obtained by least squares support vector machine (LSSVM) optimized by NSGA-II. The experiment study validates the precision and applicability of this novel approach, which is conducive to comprehensive evaluation of the core competitiveness for clean energy incubators and decision-making for more reasonable operation.
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Li, Lu, Jingyu Zhang, Qingyang Guo, Xiaokang Zhang, Songlin Liu, and Yixue Chen. "Evaluation of ACPs in China Fusion Engineering Test Reactor Using CATE 2.1 Code." Science and Technology of Nuclear Installations 2017 (2017): 1–7. http://dx.doi.org/10.1155/2017/2936069.
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Activated corrosion products (ACPs) are the dominant radiation hazard in water-cooled fusion reactor under normal operation conditions and directly determine the occupational radiation exposure during operation and maintenance. Recently, the preliminary design of China Fusion Engineering Test Reactor (CFETR) has been just completed. Evaluation of ACPs is an important work for the safety of CFETR. In this paper, the ACPs analysis code CATE 2.1 was used to simulate the spatial distribution of ACPs along the blanket cooling loop of CFETR, in which the influence of adopting different pulse handling methods was researched. At last, the dose rate caused by ACPs around the blanket cooling loop was calculated using the point kernel code ARShield. The results showed that the dose rate under normal operation for 1.2 years at contact is 1.02 mSv/h and at 1 m away from pipe is 0.45 mSv/h. And after shutting down the reactor, there will be a rapid decrease of dose rate, because of the rapid decay of short-lived ACPs.
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Denier, P., and H. Toivonen. "Evaluation of the International Monitoring System and International Data Centre of the Comprehensive Nuclear-Test-Ban Treaty Organization." Kerntechnik 66, no. 3 (June 1, 2001): 147–51. http://dx.doi.org/10.1515/kern-2001-0068.
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Abstract Evaluation and quality assurance activities of the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO) are reviewed with special emphasis on radionuclide technologies. The CTBTO carries out detailed evaluation in all fields of technical verification of the Treaty. The goal is to provide States Signatories with confidence in the quality of data from the International Monitoring System and data products of the International Data Centre. The largest technical evaluation effort has been the quality assessment of the operational software. About 1.3 million lines of source code and scripts were checked. Software characteristics, such as maintainability, were assessed using automated tool-based techniques and improvements were suggested. Specific to radionuclide technologies, several methods have been developed to cope with the large amounts of spectra produced each day by 80 radionuclide monitoring stations around the world. Some of the key evaluation results, such as the peak detection capability of the operational software are presented in detail.
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Park, Gi Young, C. K. Lee, Jung Taek Kim, K. C. Kwon, and Sang J. Lee. "Design of a Time-Frequency Distribution for Vibration Monitoring under Corrosions in the Pipe." Key Engineering Materials 321-323 (October 2006): 1257–61. http://dx.doi.org/10.4028/www.scientific.net/kem.321-323.1257.
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To monitor the wear and degradation on a pipe by corrosion during a plant operation, the vibration signals were measured by an accelerometer and analyzed by several analysis techniques. From the conventional methods, it was difficult to identify the wear and degradation on the pipe. And hence, the time-frequency distribution (TFD) and the adaptive cone-kernel distribution (ACKD) devised for reducing the interfering cross-terms are applied to the acquired data. They can provide the distinguishing peak patterns between the normal and corrosion signals.
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Khemchandani, Reshma, Jayadeva, and Suresh Chandra. "Learning the optimal kernel for Fisher discriminant analysis via second order cone programming." European Journal of Operational Research 203, no. 3 (June 2010): 692–97. http://dx.doi.org/10.1016/j.ejor.2009.09.020.
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Song, Nan, Dong Qian, Jian Cao, Wing Kam Liu, and Shaofan Li. "Effective Models for Prediction of Springback In Flanging." Journal of Engineering Materials and Technology 123, no. 4 (July 25, 2000): 456–61. http://dx.doi.org/10.1115/1.1395019.
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A study on the prediction of springback angle is presented, with focus on the straight flanging operation. The objective of this work is to evaluate the reliability of different methods of prediction. An experiment of straight flanging operation is conducted. Major prediction approaches such as analytical model, numerical simulation using the Finite Element Method (FEM) and the Meshfree Method using the Reproducing Kernel Particle Methods (RKPM) are discussed. A set of sample problems is computed and comparisons are made with the experiment. The numerical analysis shows that the prediction from the 3D meshfree contact code matches well with the data from the FEM 2D solid model. A material property described by the kinematic hardening law provides a better prediction of springback than the isotropic hardening law.
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Almomany, Abedalmuhdi, and Amin Jarrah. "OpenCL Altera SDK v.14.0 vs. v. 13.1 Benchmarks Study." Oriental journal of computer science and technology 15, no. 010203 (December 31, 2022): 21–26. http://dx.doi.org/10.13005/ojcst15.010203.03.
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Altera SDK for OpenCL allows programmers to write a simple code in OpenCL and abstracts all Field programmable gate array (FPGA) design complexity. The kernels are synthesized to equivalent circuits using the FPGA hardware recourses: Adaptive logic modules (ALMs), DSPs and Memory blocks. In this study, we developed a set of fifteen different benchmarks, each of which has its own characteristics. Benchmarks include with/without loop unrolling, have/have not atomic operations, have one/multiple kernels per single file, and in addition to one/more of these characteristics are combined. Altera OpenCL v14.0 adds more features compared with previous versions. A set of parameters chosen to compare the two OpenCL SDK versions: Logic utilization (in ALMs), total registers, RAM Blocks, total block memory bits, and clock frequency.
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Zaerko, D. V., and V. A. Lipnitski. "Weighted determination algoritm of boundary pixels." «System analysis and applied information science», no. 4 (January 28, 2021): 23–30. http://dx.doi.org/10.21122/2309-4923-2020-4-23-30.
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While working with digital noise reduction techniques, which are based on theory of convolution matrix and used convolution operation, it necessary to use algorithms to bypass boundary pixels in the image pixel matrix. The problem exists because convolution itself algorithm have peculiarity, it mean that peculiarity convolution kernel used to each element of pixel matrix. That feature characterize a lot of classes of methods which used idea of convolution matrix. There are a lot of primitive ways to solve it, but none of these ways made a consensus between economical use of resources and filling border pixels with colour coding, which is not so far from colours of corresponding pixels. The object of research is pixel matrix of image. The subject of study is algorithms for filling boundary pixels when superimposing a convolution matrix on a pixel matrix of an image. The main target is creating of effective filled algorithm for border pixels which are close to code colour to relation pixels for used in convolution matrix. Filled border pixels will use to operation convolution for each pixels original image. Algorithm of filled border pixels by step of applied convolution kernel anchors to the pixel, when pixel accessing in convolution algorithm goes beyond the pixel matrix of the original image. Algorithm takes into account the «special» cases of overstepping and allows to do fast calculation to determine the colour code of the missing pixel. The algorithm is simple to program and easily integrates with the basic convolution matrix algorithm in digital image defects.
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Zhao, Mengling, Xinyu Yin, and Huiping Yue. "Genetic Simulated Annealing-Based Kernel Vector Quantization Algorithm." International Journal of Pattern Recognition and Artificial Intelligence 31, no. 05 (February 27, 2017): 1758002. http://dx.doi.org/10.1142/s0218001417580022.
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Genetic Algorithm (GA) has been successfully applied to codebook design for vector quantization and its candidate solutions are normally turned by LBG algorithm. In this paper, to solve premature phenomenon and falling into local optimum of GA, a new Genetic Simulated Annealing-based Kernel Vector Quantization (GSAKVQ) is proposed from a different point of view. The simulated annealing (SA) method proposed in this paper can approach the optimal solution faster than the other candidate approaches. In the frame of GA, firstly, a new special crossover operator and a mutation operator are designed for the partition-based code scheme, and then a SA operation is introduced to enlarge the exploration of the proposed algorithm, finally, the Kernel function-based fitness is introduced into GA in order to cluster those datasets with complex distribution. The proposed method has been extensively compared with other algorithms on 17 datasets clustering and four image compression problems. The experimental results show that the algorithm can achieve its superiority in terms of clustering correct rate and peak signal-to-noise ratio (PSNR), and the robustness of algorithm is also very good. In addition, we took “Lena” as an example and added Gaussian noise into the original image then adopted the proposed algorithm to compress the image with noise. Compared to the original image with noise, the reconstructed image is more distinct, and with the parameter value increasing, the value of PSNR decreases.
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Petrich, Mario. "On certain lattices of varieties of completely regular semigroups." Studia Scientiarum Mathematicarum Hungarica 55, no. 1 (March 2018): 1–22. http://dx.doi.org/10.1556/012.2018.55.1.1366.
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The class CR of completely regular semigroups considered as algebras with binary multiplication and unary operation of inversion forms a variety. Kernel, trace, local and core relations, denoted by K, T, L and C, respectively, are quite useful in studying the structure of the lattice L(CR) of subvarieties of CR. They are equivalence relations whose classes are intervals. Their ends are used for defining operators on L(CR). Starting with a few band varieties, we repeatedly apply operators induced by upper ends of classes of these relations and characterize corresponding classes up to certain variety low in the lattice L(CR). We consider only varieties whose origin are “central” band varieties, that is those in the middle column of the lattice L(B) of band varieties. Several diagrams represent the (semi)lattices studied.
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Liu, Shengyang, Lei Dong, Xiaozhong Liao, Xiaodong Cao, and Xiaoxiao Wang. "Photovoltaic Array Fault Diagnosis Based on Gaussian Kernel Fuzzy C-Means Clustering Algorithm." Sensors 19, no. 7 (March 28, 2019): 1520. http://dx.doi.org/10.3390/s19071520.
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In the fault diagnosis process of a photovoltaic (PV) array, it is difficult to discriminate single faults and compound faults with similar signatures. Furthermore, the data collected in the actual field experiment also contains strong noise, which leads to the decline of diagnostic accuracy. In order to solve these problems, a new eigenvector composed of the normalized PV voltage, the normalized PV current and the fill factor is constructed and proposed to characterize the common faults, such as open circuit, short circuit and compound faults in the PV array. The combination of these three feature characteristics can reduce the interference of external meteorological conditions in the fault identification. In order to obtain the new eigenvectors, a multi-sensory system for fault diagnosis in a PV array, combined with a data-mining solution for the classification of the operational state of the PV array, is needed. The selected sensors are temperature sensors, irradiance sensors, voltage sensors and current sensors. Taking account of the complexity of the fault data in the PV array, the Kernel Fuzzy C-means clustering method is adopted to identify these fault types. Gaussian Kernel Fuzzy C-means clustering method (GKFCM) shows good clustering performance for classifying the complex datasets, thus the classification accuracy can be effectively improved in the recognition process. This algorithm is divided into the training and testing phases. In the training phase, the feature vectors of 8 different fault types are clustered to obtain the training core points. According to the minimum Euclidean Distances between the training core points and new fault data, the new fault datasets can be identified into the corresponding classes in the fault classification stage. This strategy can not only diagnose single faults, but also identify compound fault conditions. Finally, the simulation and field experiment demonstrated that the algorithm can effectively diagnose the 8 common faults in photovoltaic arrays.
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Venkanna, Mood, and Rameshwar Rao. "Static Worst-Case Execution Time Optimization using DPSO for ASIP Architecture." Ingeniería Solidaria 14, no. 25 (May 1, 2018): 1–11. http://dx.doi.org/10.16925/.v14i0.2230.
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Introduction: The application of specific instructions significantly improves energy, performance, and code size of configurable processors. The design of these instructions is performed by the conversion of patterns related to application-specific operations into effective complex instructions. This research was presented at the icitkm Conference, University of Delhi, India in 2017.Methods: Static analysis was a prominent research method during late the 1980’s. However, end-to-end measurements consist of a standard approach in industrial settings. Both static analysis tools perform at a high-level in order to determine the program structure, which works on source code, or is executable in a disassembled binary. It is possible to work at a low-level if the real hardware timing information for the executable task has the desired features.Results: We experimented, tested and evaluated using a H.264 encoder application that uses nine cis, covering most of the computation intensive kernels. Multimedia applications are frequently subject to hard real time constraints in the field of computer vision. The H.264 encoder consists of complicated control flow with more number of decisions and nested loops. The parameters evaluated were different numbers of A partitions (300 slices on a Xilinx Virtex 7each), reconfiguration bandwidths, as well as relations of cpu frequency and fabric frequency fCPU/ffabric. ffabric remains constant at 100MHz, and we selected a multiplicity of its values for fCPU that resemble realistic units. Note that while we anticipate the wcet in seconds (wcetcycles/ f CPU) to be lower (better) with higher fCPU, the wcet cycles increase (at a constant ffabric) because hardware cis perform less computations on the reconfigurable fabric within one cpu cycle.Conclusions: The method is similar to tree hybridization and path-based methods which are less precise, and to the global ipet method, which is more precise. Optimization is evaluated with the Discrete Particle Swarm Optimization (dpso) algorithm for wcet. For several real-world applications involving embedded processors, the proposed technique develops improved instruction sets in comparison to native instruction sets.Originality: For wcet estimation, flow analysis, low-level analysis and calculation phases of the program need to be considered. Flow analysis phase or the high-level of analysis helps to extract the program’s dynamic behavior that gives information on functions being called, number of loop iteration, dependencies among if-statements, etc. This is due to the fact that the analysis is unaware of the execution path corresponding to the longest execution time.Limitations: This path is executed within a kernel iteration that relies upon the nature of mb, either i-mb or p-mb, determined by the motion estimation kernel, that is, its’ input depends on the i-mb and p-mb paths ,which also contain separate cis leading to the instability of the worst-case path, that is, adding more partitions to the current worst-case path can result in the other path becoming the worst case. The pipeline stalls for the reconfiguration delay and continues when entering the kernel once the reconfiguration process finishes.
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Sambath Kumar, K., and A. Rajendran. "An automatic brain tumor segmentation using modified inception module based U-Net model." Journal of Intelligent & Fuzzy Systems 42, no. 3 (February 2, 2022): 2743–54. http://dx.doi.org/10.3233/jifs-211879.
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Manual segmentation of brain tumor is not only a tedious task that may bring human mistakes. An automatic segmentation gives results faster, and it extends the survival rate with an earlier treatment plan. So, an automatic brain tumor segmentation model, modified inception module based U-Net (IMU-Net) proposed. It takes Magnetic resonance (MR) images from the BRATS 2017 training dataset with four modalities (FLAIR, T1, T1ce, and T2). The concatenation of two series 3×3 kernels, one 5×5, and one 1×1 convolution kernels are utilized to extract the whole tumor (WT), core tumor (CT), and enhance tumor (ET). The modified inception module (IM) collects all the relevant features and provides better segmentation results. The proposed deep learning model contains 40 convolution layers and utilizes intensity normalization and data augmentation operation for further improvement. It achieved the mean dice similarity coefficient (DSC) of 0.90, 0.77, 0.74, and the mean Intersection over Union (IOU) of 0.79, 0.70, 0.70 for WT, CT, and ET during the evaluation.