Accordion microwave oven for uniformity and efficiency heating

Conventional microwave oven heating has the problem of poor heating uniformity and low heating efficiency. A novel microwave oven heating model has been proposed for improving heating uniformity by making the electric field in the microwave oven drastically change by changing the geometry of the microwave oven during the heating process. The transformation optics method is used to solve the computational difficulties caused by the continuous change of the mesh during the motion. Finally, the experiment verified the correctness of the simulation. In addition, important factors affecting heating efficiency were discussed.     

A wideband circularly polarized slot antenna with antipodal strips for WLAN and C‐band applications

A single‐fed circularly polarized square shaped wide slot antenna with modified ground plane and microstrip feed has been presented. The field in the slot is perturbed by introducing an antipodal strips section attached with a microstrip line to produce circular polarization in a wide band of frequencies. The antipodal strip section consists of a group of four strips of unequal length and separation. The presence of asymmetric perturbations in the slot is mainly responsible for exciting two orthogonal modes in the slot having equal magnitude and 90° phase difference which results in circular polarization. A wide bandwidth of 3.3 GHz (4.4 GHz‐7.7 GHz) has been achieved for an axial ratio value AR < 3 dB with the minimum axial ratio value being 0.3 dB. The impedance bandwidth for |S₁₁| < ?10 dB ranges from 4.3 GHz to 8 GHz, and therefore covers most of the C‐band communication systems. The antenna exhibits stable radiation patterns throughout the circular polarization bandwidth with a gain around 6 dBi in entire operational bandwidth. A prototype of antenna was fabricated and measured. The antenna has a planar size 0.40λ₀ × 0.40λ₀ and thickness of 0.02λ₀ where λ₀ is the wavelength in free space at the lowest frequency. With its compact size and low profile, the antenna is a favorable choice for WLAN (5.15‐5.85 GHz) and a wide variety of C‐band wireless applications.     

Hybrid feature selection algorithm using symmetrical uncertainty and a harmony search algorithm

Microarray technology can be used as an efficient diagnostic system to recognise diseases such as tumours or to discriminate between different types of cancers in normal tissues. This technology has received increasing attention from the bioinformatics community because of its potential in designing powerful decision-making tools for cancer diagnosis. However, the presence of thousands or tens of thousands of genes affects the predictive accuracy of this technology from the perspective of classification. Thus, a key issue in microarray data is identifying or selecting the smallest possible set of genes from the input data that can achieve good predictive accuracy for classification. In this work, we propose a two-stage selection algorithm for gene selection problems in microarray data-sets called the symmetrical uncertainty filter and harmony search algorithm wrapper (SU-HSA). Experimental results show that the SU-HSA is better than HSA in isolation for all data-sets in terms of the accuracy and achieves a lower number of genes on 6 out of 10 instances. Furthermore, the comparison with state-of-the-art methods shows that our proposed approach is able to obtain 5 (out of 10) new best results in terms of the number of selected genes and competitive results in terms of the classification accuracy.     

A K/Ka‐band dielectric and metallic 3D printed aperture shared multibeam parabolic reflector antenna for satellite communication

A K/Ka‐band (22‐33 GHz) high‐gain aperture shared multibeam parabolic reflector antenna is proposed. It performs a two‐dimensional beam scanning from a shared single parabolic reflector by introducing off‐focal feeds. The feed array is placed on and off the focal of the parabolic reflector. Traditionally, the feed blockage has a great impact on the performance of the antenna, which reduces the gain and increases the sidelobe level. The purpose of this paper is to suppress the negative effects of feed blockage by using hybrid material processing method. Both dielectric and metallic 3D printing technologies are used for antenna fabrication. The parabolic reflector antenna is printed by selective laser melting using aluminum alloy. The feed array and the supporting structures are printed by stereolithography apparatus in resin to control the blockage. The method helps to suppress the sidelobe level from ?10 to ?15 dB and to enhance gain by up to 2.3 dBi. The reflection coefficient is less than ?10 dB, while the coupling coefficient between the ports is less than ?20 dB over the entire designed band. At 31.5 GHz, the simulated maximum gain of the antenna are 30.7, 29.1, and 29.7 dBi, when different port separately excites. Multiple beams at ±15° and 0° are observed on both E‐ and H‐planes. Besides, it also verifies the possibility to use dielectric and metallic 3D printing technologies in hybrid for microwave device fabrication.     

A hybrid approach for learning concept hierarchy from Malay text using artificial immune network

A concept hierarchy is an integral part of an ontology but it is expensive and time consuming to build. Motivated by this, many unsupervised learning methods have been proposed to (semi-) automatically develop a concept hierarchy. A significant work is the Guided Agglomerative Hierarchical Clustering (GAHC) which relies on linguistic patterns (i.e., hypernyms) to guide the clustering process. However, GAHC still relies on contextual features to build the concept hierarchy, thus data sparsity still remains an issue in GAHC. Artificial Immune Systems are known for robustness, noise tolerance and adaptability. Thus, an extension to the GAHC is proposed by hybridizing it with Artificial Immune Network (aiNet) which we call Guided Clustering and aiNet for Learning Concept Hierarchy (GCAINY). In this paper, we have tested GCAINY using two parameter settings. The first parameter setting is obtained from the literature as a baseline parameter setting and second is by automatic parameter tuning using Particle Swarm Optimization (PSO). The effectiveness of the GCAINY is evaluated on three data sets. For further validations, a comparison between GCAINY and GAHC has been conducted and with statistical tests showing that GCAINY increases the quality of the induced concept hierarchy. The results reveal that the parameters value found by using PSO significantly produce better concept hierarchy than the vanilla parameter. Thus it can be concluded that the proposed approach has greater ability to be used in the field of ontology learning.     

Recent advancement in VM task allocation system for cloud computing: review from 2015 to2021

Cloud computing is new technology that has considerably changed human life at different aspect over the last decade. Especially after the COVID-19 pandemic, almost all life activity shifted into cloud base. Cloud computing is a utility where different hardware and software resources are accessed on pay per user ground base. Most of these resources are available in virtualized form and virtual machine (VM) is one of the main elements of visualization.VM used in data center for distribution of resource and application according to benefactor demand. Cloud data center faces different issue in respect of performance and efficiency for improvement of these issues different approaches are used. Virtual machine play important role for improvement of data center performance therefore different approach are used for improvement of virtual machine efficiency (i-e) load balancing of resource and task. For the improvement of this section different parameter of VM improve like makespan, quality of service, energy, data accuracy and network utilization. Improvement of different parameter in VM directly improve the performance of cloud computing. Therefore, we conducting this review paper that we can discuss about various improvements that took place in VM from 2015 to 20,201. This review paper also contain information about various parameter of cloud computing and final section of paper present the role of machine learning algorithm in VM as well load balancing approach along with the future direction of VM in cloud data center.

     

平面接收阵列天线的反射测量

在微波无线能量传输(MWPT)中,接收阵列天线通常采用分布式整流将接收到的微波能量转换为直流能量,其天线单元的最大入射功率决定了整流电路的设计.然而,接收阵列天线边缘单元所能接收到的功率小,使所接整流电路阻抗发生变化,与阵列天线单元失配造成较大的反射.首先从理论上论证了随着接收天线单元输入功率的变化,接收阵列天线边缘单元的反射大于中间单元.然后设计了一个低剖面(0.05λ2)、高定向性(12.5 dBi)、高前后比(27 dB)的微带准八木天线作为探头.最后测量了10×10平面接收阵列天线连接整流电路时的反射和入射功率分布图,并计算得到反射因子(反射因子定义为到达接收阵列天线单元表面上的反射功率和入射功率的比值)分布图.实验结果与理论分析一致,该实验为提高MWPT中接收端的效率起到指导作用.     

Software effort estimation accuracy prediction of machine learning techniques: A systematic performance evaluation

Software effort estimation accuracy is a key factor in effective planning, controlling, and delivering a successful software project within budget and schedule. The overestimation and underestimation both are the key challenges for future software development, henceforth there is a continuous need for accuracy in software effort estimation. The researchers and practitioners are striving to identify which machine learning estimation technique gives more accurate results based on evaluation measures, datasets and other relevant attributes. The authors of related research are generally not aware of previously published results of machine learning effort estimation techniques. The main aim of this study is to assist the researchers to know which machine learning technique yields the promising effort estimation accuracy prediction in software development. In this article, the performance of the machine learning ensemble and solo techniques are investigated on publicly and non-publicly domain datasets based on the two most commonly used accuracy evaluation metrics. We used the systematic literature review methodology proposed by Kitchenham and Charters. This includes searching for the most relevant papers, applying quality assessment (QA) criteria, extracting data, and drawing results. We have evaluated a state-of-the-art accuracy performance of 35 selected studies (17 ensemble, 18 solo) using mean magnitude of relative error and PRED (25) as a set of reliable accuracy metrics for performance evaluation of accuracy among two techniques to report the research questions stated in this study. We found that machine learning techniques are the most frequently implemented in the construction of ensemble effort estimation (EEE) techniques. The results of this study revealed that the EEE techniques usually yield a promising estimation accuracy than the solo techniques.     

A metallic 3D printed K‐band quasi‐pyramidal‐horn antenna array

A K‐band (18‐27 GHz) antenna array is presented in this article. By deposing the quasi‐pyramidal‐horn upon a print circuit board (PCB), a traveling‐wave quasi‐pyramidal‐horn antenna is formed. Parasitic rings are introduced to decrease the quality factor for an extended bandwidth. The antenna element demonstrates impedance bandwidth 18.6 to 23.3 GHz. The gain is 10.3 dBi at 20.4 GHz with a stable radiation pattern. The impedance bandwidth of a 2 × 2 array is 18.3 to 22.7 GHz, with a maximum gain of 15.2 dBi at 20.4 GHz. The simulated and measured radiation patterns on E‐ and H‐planes at 20.4 GHz agree well. Taking advantage of the 3D printing technology, the quasi‐pyramidal horn is fabricated by selective laser melting using aluminum alloy for time‐saving and process simplicity. The proposed design highlights the hybrid usage of PCB and metallic 3D printing technology in fabricating microwave devices. It is a capable candidate for wireless communication.     

构建基于Windows和MPI的Beowulf并行计算系统

利用普通微机构建并行计算集群(常称为Beowulf系统),能够以低廉的价格获得强大的计算能力。文章介绍了利用16台微机构建一套Beowulf并行计算系统,节点微机上运行Windows2000操作系统,采用MPI(Message-Passing-Interface)的MPICH最新版本:MPICH.NT1.2.3作为并行计算的支撑环境,并以100Mbps高速交换式以太网作为互连网络。通过编制的并行计算程序对该Beowulf系统进行了并行效率的实际测试,测试结果表明该Beowulf系统能够达到非常高的并行加速比和并行效率。