Research on encoding and decoding of non-binary polar codes over GF(2m)

Binary Polar Codes (BPCs) have advantages of high-efficiency and capacity-achieving but suffer from large latency due to the Successive-Cancellation List (SCL) decoding. Non-Binary Polar Codes (NBPCs) have been investigated to obtain the performance gains and reduce latency under the implementation of parallel architectures for multi-bit decoding. However, most of the existing works only focus on the Reed-Solomon matrix-based NBPCs and the probability domain-based non-binary polar decoding, which lack flexible structure and have a large computation amount in the decoding process, while little attention has been paid to general non-binary kernel-based NBPCs and Log-Likelihood Ratio (LLR) based decoding methods. In this paper, we consider a scheme of NBPCs with a general structure over GF(2^m). Specifically, we pursue a detailed Monte-Carlo simulation implementation to determine the construction for proposed NBPCs. For non-binary polar decoding, an SCL decoding based on LLRs is proposed for NBPCs, which can be implemented with non-binary kernels of arbitrary size. Moreover, we propose a Perfect Polarization-Based SCL (PPB-SCL) algorithm based on LLRs to reduce decoding complexity by deriving a new update function of path metric for NBPCs and eliminating the path splitting process at perfect polarized (i.e., highly reliable) positions. Simulation results show that the bit error rate of the proposed NBPCs significantly outperforms that of BPCs. In addition, the proposed PPB-SCL decoding obtains about a 40% complexity reduction of SCL decoding for NBPCs.     

采用滑模观测器的机载激光通信视轴精度控制

为了提高机载激光通信系统在机体振动和机械摩擦等扰动下的视轴对准精度,提出了一种基于滑模观测器的反步滑模控制方法。首先建立了机载激光通信系统的数学模型,然后通过设计的滑模观测器对扰动值进行估计,同时针对指令转换模块、激光通信模块和电机模块逐步设计了反步滑模控制律,实现对机载激光通信系统视轴的高精度控制。实验结果表明:提出的方法与分数阶PID控制方法相比突出了更优的快速性和准确性,响应时间仅为0.4 s,最大空间对准误差仅为0.3 m,设计的滑模观测器能够快速、准确地估计出扰动值,响应时间仅为0.3 s,最大估计误差分别仅为0.1 m/s、0.06 (°)/s2 和0.07 A/s,大幅提高了机载激光通信系统中视轴的对准精度。     

Research and Implementation of Parallel Artificial Fish Swarm Algorithm Based on Ternary Optical Computer

Mobile Networks and Applications - Artificial fish swarm algorithm (AFS) is used in the field of function optimization problems widely. The traditional AFS algorithm has some problems such as long...     

Intelligent Firefly Algorithm Deep Transfer Learning Based COVID-19 Monitoring System

With the increasing and rapid growth rate of COVID-19 cases, the healthcare scheme of several developed countries have reached the point of collapse. An important and critical steps in fighting against COVID-19 is powerful screening of diseased patients, in such a way that positive patient can be treated and isolated. A chest radiology image-based diagnosis scheme might have several benefits over traditional approach. The accomplishment of artificial intelligence (AI) based techniques in automated diagnoses in the healthcare sector and rapid increase in COVID-19 cases have demanded the requirement of AI based automated diagnosis and recognition systems. This study develops an Intelligent Firefly Algorithm Deep Transfer Learning Based COVID-19 Monitoring System (IFFA-DTLMS). The proposed IFFA-DTLMS model majorly aims at identifying and categorizing the occurrence of COVID19 on chest radiographs. To attain this, the presented IFFA-DTLMS model primarily applies densely connected networks (DenseNet121) model to generate a collection of feature vectors. In addition, the firefly algorithm (FFA) is applied for the hyper parameter optimization of DenseNet121 model. Moreover, autoencoder-long short term memory (AE-LSTM) model is exploited for the classification and identification of COVID19. For ensuring the enhanced performance of the IFFA-DTLMS model, a wide-ranging experiments were performed and the results are reviewed under distinctive aspects. The experimental value reports the betterment of IFFA-DTLMS model over recent approaches.     

基于网络远程数据采集的虚拟仪器实验系统构建

与传统的实验系统相比,基于网络远程数据采集的虚拟实验系统,能降低实验室建设成本,它使课堂教学更形象、生动,能更好地实现理论教学与实践相结合。该文提出基于DataSocket远程数据采集技术,构建了多层分布式网络远程数据采集体系结构模式。通过虚拟议器设计,在电子线路实验中得以应用,有较好的效果。     

A blog emotion corpus for emotional expression analysis in Chinese

Weblogs are increasingly popular modes of communication and they are frequently used as mediums for emotional expression in the ever changing online world. This work uses blogs as object and data source for Chinese emotional expression analysis. First, a textual emotional expression space model is described, and based on this model, a relatively fine-grained annotation scheme is proposed for manual annotation of an emotion corpus. In document and paragraph levels, emotion category, emotion intensity, topic word and topic sentence are annotated. In sentence level, emotion category, emotion intensity, emotional keyword and phrase, degree word, negative word, conjunction, rhetoric, punctuation, objective or subjective, and emotion polarity are annotated. Then, using this corpus, we explore these linguistic expressions that indicate emotion in Chinese, and present a detailed data analysis on them, involving mixed emotions, independent emotion, emotion transfer, and analysis on words and rhetorics for emotional expression.     

An improved differential evolution algorithm for vehicle routing problem with simultaneous pickups and deliveries and time windows

The vehicle routing problem with simultaneous pickups and deliveries and time windows (VRP-SPDTW) is the problem of optimally integrating forward (good distribution) and reverse logistics (returning materials) for cost saving and environmental protection. We constructed a general mixed integer programming model of VRP-SPDTW. The model contained some classical vehicle routing problems as special cases. We proposed an improved differential evolution algorithm (IDE) for solving this problem. In the algorithm, we firstly adopted the novel decimal coding to construct an initial population, then used some improved differential evolution operators unlike the existing algorithm, and in mutation operation, we used an integer order criterion based on natural number coding method. We introduced a penalty technical to publish the infeasible solution. In addition, in the crossover operation, we designed a self-adapting crossover probability that varied with iteration. We did some numerical experiments, and the results showed that the proposed method is effective for solving VRP-SPDTW.     

Blind maximum likelihood estimation of traffic matrices under long-range dependent traffic

A new method, based on the maximum likelihood principle, through the numerical Expectation–Maximization algorithm, is proposed to estimate traffic matrices when traffic exhibits long-range dependence. The methods proposed so far in the literature do not account for long-range dependence. The method proposed in the present paper also provides an estimate of the Hurst parameter. Simulation results show that: (i) the estimate of the traffic matrix is more efficient than those obtained via existing techniques; (ii) the estimation error of the traffic matrix is lower for larger values of the true traffic intensity; (iii) the estimate of the Hurst parameter is slightly negatively biased.     

Intelligent adaptive process control using dynamic deadband for semiconductor manufacturing

This paper proposes an efficient control method to minimize process error and to reduce process variance in semiconductor manufacturing. The photolithography (photo) process forms a complex semiconductor circuit and is important for quality. Obstacles to the process include the facility itself, vibration, wear and tear, product/process changes and environmental influences. Control methodologies being currently used to address these issues often amplify the variation of the process by failing to perform adequate process control. Therefore, this paper proposes an effective process control method to reduce process variance by quickly detecting and identifying process disturbances and accurately reflecting the degree of change to process control. This study proposes dynamic deadband control that uses a region (band) to detect the status of a process change. It adjusts the process control based on the changes detected. In this research, the semiconductor manufacturing company is supported to perform control that is more precise and reduces fluctuations by producing products of uniform quality. In addition, it can contribute to yield due to the quality incentive and increased process control of semiconductor manufacturing.     

Partner selection in a virtual enterprise under uncertain information about candidates

Partner selection is a major issue in the formation of a virtual enterprise. In practice, in the partner selection process, the information about the candidates and their performances are incomplete and uncertain. Vague sets theory is one of the methods used to deal with uncertain information. In this paper, a new method based on vague sets is proposed to deal with the partner selection problem in the formation of a virtual enterprise while the factors of satisfaction degree, due date, cost and the precedence of tasks are taken into account. On the basis of the agreement index of satisfaction degree, the formulated partner selection problems are interpreted so as to maximize the minimum agreement index. To solve the problem, an improved particle swarm optimization (PSO) algorithm is proposed. Finally, the simulation of a numerical example demonstrates that the method is effective.