雷达工程专业本科毕业设计指导模式探索

为提高本科毕业设计指导工作效率和毕业论文质量，本文基于雷达工程专业特点建立了“导师主导--研究生辅助--本科生合作”的多层次、模块化、场景化指导模式。该模式以导师为核心、科研小组和学员合作为辅助，全方位全过程保障本科毕设工作。实践表明，该模式可以有效提高指导工作效率和本科毕业设计质量，学生专业素养和实践能力显著提升。本文对电子类专业本科毕设指导具有重要借鉴意义。     

Sizing of multi-stage Op Amps by combining design equations with the gm/ID method

Analog integrated circuit design has as integral parts both analytical reasoning and numerical validation in the process from topology construction to sizing. Given a circuit topology, different circuit sizing results can be obtained from different processes of sizing inference. Sizing methods by simulation-based numerical searching have been a continuously studied subject. However, almost all approaches in this category require an overwhelming number of circuit simulations to arrive at an optimized sizing result. On the other hand, many published manual sizing methods by using the conventional device equations also require repeated SPICE simulations to correct the equation-based sizing results. This paper proposes a systematic gm/ID-based initial sizing method specifically customized for designing multiple-stage operational amplifiers (Op Amps). A main feature of the proposal is to use circuit-level design equations as constraints on the gm/ID table lookup method to substantially reduce the uncertainty in the sizing calculations. As a result, a significant amount of SPICE based correction work can be reduced to complete an initial sizing. The proposed sizing procedure includes a few regular sizing rules customized to the configuration of multi-stage Op Amps. We validate the proposed sizing method by application to several multi-stage Op Amp examples with a capacitive load or Miller compensation. Simulations have justified that the produced initial sizing results can achieve most of the prespecified design targets.     

Jaya Learning-Based Optimization for Optimal Sizing of Stand-Alone Photovoltaic,Wind Turbine,and Battery Systems

Renewable energy sources (RESs) are considered to be reliable and green electric power generation sources. Photovoltaics (PVs) and wind turbines (WTs) are used to provide electricity in remote areas. Optimal sizing of hybrid RESs is a vital challenge in a stand-alone environment. The meta-heuristic algorithms proposed in the past are dependent on algorithm-specific parameters for achieving an optimal solution. This paper proposes a hybrid algorithm of Jaya and a teaching–learning-based optimization (TLBO) named the JLBO algorithm for the optimal unit sizing of a PV–WT–battery hybrid system to satisfy the consumer’s load at minimal total annual cost (TAC). The reliability of the system is considered by a maximum allowable loss of power supply probability (LPSP_max) concept. The results obtained from the JLBO algorithm are compared with the original Jaya, TLBO, and genetic algorithms. The JLBO results show superior performance in terms of TAC, and the PV–WT–battery hybrid system is found to be the most economical scenario. This system provides a cost-effective solution for all proposed LPSP_max values as compared with PV–battery and WT–battery systems.     

面向数据流结构的指令映射优化方法

在高性能计算领域,数据流是一类重要的计算结构,也在很多实际场景表现出很好的性能和适用性。在数据流计算模式中,程序是以数据流图来表示的,数据流计算中一个关键的问题是如何将数据流图映射到多个执行单元上。通过分析现有数据流结构的指令映射方法及其不足,提出了基于数据流结构的新型指令映射优化方法。主要是根据多地址共享数据包的特性对指令映射方法进行优化,延迟多地址共享数据路由包的拆分,减少网络拥堵。     

Modeling,design, and optimization of a cost‐effective and reliable hybrid renewable energy system integrated with desalination using the division algorithm

People in the Middle East are facing the problem of freshwater shortages. This problem is more intense for a remote region, which has no access to the power grid. The use of seawater desalination technology integrated with the generated energy unit by renewable energy sources could help overcome this problem. In this study, we refer a seawater reverse osmosis desalination (SWROD) plant with a capacity of 1.5 m³/h used on Larak Island, Iran. Moreover, for producing fresh water and meet the load demand of the SWROD plant, three different stand‐alone hybrid renewable energy systems (SAHRES), namely wind turbine (WT)/photovoltaic (PV)/battery bank storage (BBS), PV/BBS, and WT/BBS are modeled and investigated. The optimization problem was coded in MATLAB software. Furthermore, the optimized results were obtained by the division algorithm (DA). The DA has been developed to solve the sizing problem of three SAHRES configurations by considering the object function's constraints. These results show that this improved algorithm has been simpler, more precise, faster, and more flexible than a genetic algorithm (GA) in solving problems. Moreover, the minimum total life cycle cost (TLCC = 243 763$), with minimum loss of power supply probability (LPSP = 0%) and maximum reliability, was related to the WT/PV/BBS configuration. WT/PV/BBS is also the best configuration to use less battery as a backup unit (69 units). The batteries in this configuration have a longer life cycle (maximum average of annual battery charge level) than two other configurations (93.86%). Moreover, the optimized results have shown that utilizing the configuration of WT/PV/BBS could lead to attaining a cost‐effective and green (without environmental pollution) SAHRES, with high reliability for remote areas, with appropriate potential of wind and solar irradiance.     

Level of match between facial dimensions of Chilean workers and respirator fit test panels proposed by LANL and NIOSH

The facial fit of respirators is crucial for determining how effectively respirators may protect users from exposure to airborne contaminants, when their use is required in the workplace. In the Chilean market, all the respirators available have been designed and manufactured using foreign regulations. The aim of this research was to determine the facial dimensions in a sample of Chilean workers (users or potential users of respiratory protective equipment) and the possible mismatch between their anthropometric characteristics and the respirator fit test panels proposed by Los Alamos National Laboratory (LANL) and National Institute for Occupational Safety and Health (NIOSH). An anthropometric survey that included 11 measurements was conducted, based on ISO/TS 16976–2 and ISO 15535 to ensure the highest standards possible, and a total of 474 workers (female: 229, male: 245), aged 18–66 years old participated in the survey. The anthropometric measurements were then contrasted with the fit test panels used in LANL (for half and full facepieces) and NIOSH (Bivariate and Principal component analysis (PCA)), to verify the level of mismatch. The results showed that LANL panels presented a level of mismatch of 11.8% and 21% for the half-facepiece and the full-facepiece, respectively. Considering the NIOSH bivariate and PCA panels, 4.6% and 4.4% of the sample remains without an assigned cell, respectively. It can be concluded that the LANL panels for half and full facepieces do not match the facial dimensions of the Chilean working population. The panels developed by NIOSH and considered by the ISO/TS 16976–2 (bivariate and PCA), are applicable to the Chilean working population.Relevance for the IndustryThis research provides anthropometric measurements of Chilean workers, to determine the dimensions for half- and full-facepiece respirators, which are currently not available. The NIOSH or ISO fit test panels, as opposed to LANL panels, should be used when manufacturing respirators for Chilean workers.     

Formulations and solution algorithms for dynamic assembly routing problem

We study a dynamic version of the assembly routing problem. The assembly lot sizing section deals with decisions concerning the production phase, whereas the routing section organises the collection of raw materials necessary for the production. Traditionally, these two problems are treated separately, and more specifically, in a hierarchical way. We propose three linear programming models: a non-vehicle index model, a two-commodity flow formulation and a logic-based benders decomposition. We develop aggregated rounded capacity constraints for non-vehicle index model and separated them dynamically during the Branch & Cut procedure. Logic-based benders decomposition algorithm solves the Dynamic Assembly Routing Problem iteratively and obtains a feasible solution at each iteration. The numerical tests show that, the two first models are particularly effective at finding the optimal solutions in a reasonable amount of time on instances with up to 50 components and 3 periods.     

Effects of multiple-try feedback and question type during mathematics problem solving on performance in similar problems

In a study of mathematics problem solving, the effect of providing multiple-try feedback on later success in solving similar problems was examined. Participants solved mathematics problems that were presented as either multiple-choice or open-ended questions, and were provided with one of four types of feedback: no feedback (NF), immediate knowledge of the correct response (KCR), multiple-try feedback with knowledge of the correct response (MTC), or multiple-try feedback with hints after an initial incorrect response (MTH). Results showed that gains in performance were larger in the open-ended than multiple-choice condition. Furthermore, gains under NF and KCR were similar, gains were larger under MTC than KCR, and gains were larger under MTH than MTC. The implications of these results for the design of assessments for learning are discussed.     

Allocation and sizing of battery energy storage system for primary frequency control based on bio-inspired methods: A case study

This paper presents a new procedure for optimal allocation and optimal sizing of a battery energy storage system (BESS) for primary frequency support in an isolated power system. For the BESS allocation, a transmission bus system with larger frequency decline is recognized and the BESS sizing is performed by a constrained optimization strategy based on a new modified metaheuristic, called Developed Harris Hawks Optimization (DHHO). The simulation results of the suggested DHHO are compared with Bat Optimization Algorithm (BOA) and Genetic Algorithm (GA) from the literature to show the method efficiency. The final results showed higher precision with lower required iterations for the suggested DHHO method. Also, the proposed DHHO gives lower investment costs for BESS with lower power and energy requirement toward the other compared methods.