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Exploiting channel state information of WiFi signal for human activity detection: an experimental study 利用 WiFi 信号的信道状态信息检测人类活动:一项实验研究
Q2 Mathematics Pub Date : 2024-04-01 DOI: 10.11591/eei.v13i2.6344
Hicham Boudlal, Mohammed Serrhini, Ahmed Tahiri
Ubiquitous computing aims to seamlessly integrate computing into our daily lives, and requires reliable information on human activities and state for various applications. In this paper, we propose a device-free human activity recognition system that leverages the rich information behind WiFi signals to detect human activities in indoor environments, including walking, sitting, and standing. The key idea of our system is to use the dynamic features of activities, which we carefully examine and analyze through the characteristics of channel state information. We evaluate the impact of location changes on WiFi signal distribution for different activities and design an activity detection system that employs signal processing techniques to extract discriminative features from wireless signals in the frequency and temporal domains. We implement our system on a single off-the-shelf WiFi device connecting to a commercial wireless access point and evaluate it in laboratory and conference room environments. Our experiments demonstrate the feasibility of using WiFi signals for device-free human activity recognition, which could provide a practical and non-intrusive solution for indoor monitoring and ubiquitous computing applications.
无所不在的计算旨在将计算无缝集成到我们的日常生活中,各种应用都需要可靠的人类活动和状态信息。在本文中,我们提出了一种无需设备的人类活动识别系统,该系统利用 WiFi 信号背后的丰富信息来检测室内环境中的人类活动,包括行走、坐姿和站姿。我们系统的关键理念是利用活动的动态特征,并通过信道状态信息的特征对其进行仔细研究和分析。我们评估了不同活动的位置变化对 WiFi 信号分布的影响,并设计了一个活动检测系统,该系统采用信号处理技术从无线信号中提取频率域和时间域的判别特征。我们在连接到商用无线接入点的单个现成 WiFi 设备上实现了我们的系统,并在实验室和会议室环境中进行了评估。我们的实验证明了利用 WiFi 信号进行无设备人类活动识别的可行性,这可以为室内监控和泛在计算应用提供实用的非侵入式解决方案。
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引用次数: 0
Feature importance for software development effort estimation using multi level ensemble approaches 利用多级集合方法估算软件开发工作量的特征重要性
Q2 Mathematics Pub Date : 2024-04-01 DOI: 10.11591/eei.v13i2.5531
K. E. Rao, Pandu Ranga, Vital Terlapu, Paidi Annan Naidu, Tammineni Ravi Kumar, Bala Murali Pydi
Feature importance strategy that substantially impacts software development effort estimation (SDEE) can help lower the dimensionality of dataset size. SDEE models developed to estimate effort, time, and wealth required to accomplish a software product on a limited budget are used more frequently by project managers as decision-support tool effort estimation algorithms trained on a dataset containing essential elements to improve their estimation accuracy. Earlier research worked on creating and testing various estimation methods to get accurate. On the other hand, ensemble produces superior prediction accuracy than single approaches. Therefore, this study aims to identify, develop, and deploy an ensemble approach feasible and practical for forecasting software development activities with limited time and minimum effort. This paper proposed a collaborative system containing a multi-level ensemble approach. The first level grabs the optimal features by adopting boosting techniques that impact the decided target; this subset features forward to the second level developed by a stacked ensemble to compute the product development effort concerning lines of code (LOC) and actual. The proposed model yields high accuracy and is more accurate than distinct models.
对软件开发工作量估算(SDEE)产生重大影响的特征重要性策略有助于降低数据集的维度大小。为估算在有限预算内完成软件产品所需的精力、时间和财富而开发的 SDEE 模型,更多地被项目经理用作决策支持工具,在包含基本要素的数据集上训练的精力估算算法,可提高估算的准确性。早期的研究致力于创建和测试各种估算方法,以获得准确的估算结果。另一方面,与单一方法相比,集合方法能产生更高的预测精度。因此,本研究旨在确定、开发和部署一种切实可行的集合方法,以便在有限的时间和最小的工作量内预测软件开发活动。本文提出了一种包含多层次集合方法的协作系统。第一层通过采用影响已确定目标的提升技术来抓取最佳特征;该子集特征转到由堆叠集合开发的第二层,以计算有关代码行(LOC)和实际的产品开发工作量。所提出的模型具有很高的准确性,而且比不同的模型更加准确。
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引用次数: 0
Golden jackal optimization for economic load dispatch problems with complex constraints 针对具有复杂约束条件的经济负荷调度问题的金豺优化法
Q2 Mathematics Pub Date : 2024-04-01 DOI: 10.11591/eei.v13i2.6572
Ramamoorthi Ragunathan, Balamurugan Ramadoss
This research paper uses the golden jackal optimization (GJO), a novel meta-heuristic algorithm, to address power system economic load dispatch (ELD) problems. The GJO emulates the hunting behavior of golden jackals. GJO algorithm uses the cooperative attacking behavior of golden jackals to tackle complicated optimization problems efficaciously. The objective of ELD problem is to distribute power system load requirement to the different generators with a minimum total fuel cost of generation. ELD problems are highly complex, non-linear, and non-convex optimization problems while considering constraints namely valve point loading effect (VPL) and prohibited operating zones (POZs). The proposed GJO algorithm is applied to solve complex, non-linear, and non-convex ELD problems. Six different test systems having 6, 10, 13, 40, and 140 generators with various constraints are used to validate the usefulness of the suggested GJO method. Simulation outcomes of the test system are compared with various algorithms reported in the algorithms such as particle swarm optimization (PSO), ant colony optimization (ACO), and backtracking search algorithm (BSA). Results show that the proposed GJO algorithm produces minimal fuel cost and has good convergence in solving ELD problems of power system engineering.
本研究论文使用一种新型元启发式算法--金豺优化(GJO)来解决电力系统经济负荷调度(ELD)问题。GJO 模拟了金豺的狩猎行为。GJO 算法利用金豺的合作攻击行为来有效解决复杂的优化问题。ELD 问题的目标是以最小的总发电燃料成本将电力系统的负荷需求分配给不同的发电机。ELD 问题是高度复杂、非线性和非凸性的优化问题,同时还要考虑阀点加载效应(VPL)和禁止运行区(POZ)等约束条件。所提出的 GJO 算法可用于解决复杂、非线性和非凸 ELD 问题。为了验证所建议的 GJO 方法的实用性,我们使用了 6、10、13、40 和 140 台具有不同约束条件的发电机的六个不同测试系统。测试系统的仿真结果与粒子群优化(PSO)、蚁群优化(ACO)和回溯搜索算法(BSA)等各种算法进行了比较。结果表明,在解决电力系统工程的 ELD 问题时,所提出的 GJO 算法能产生最小的燃料成本,并具有良好的收敛性。
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引用次数: 0
Reliability evaluation of non-isolated high gain interleaved DC-DC converter 非隔离式高增益交错直流-直流转换器的可靠性评估
Q2 Mathematics Pub Date : 2024-04-01 DOI: 10.11591/eei.v13i2.6585
Subbulakshmy Ramamurthi, P. Ramasamy
A high gain DC-DC converter is the crucial part in renewable energy systems (RES) and in electric vehicular systems. The reliability of those high-gain converters needs to be assessed for the long-term operation of renewable energy systems. This article presents the reliability analysis of non-isolated high gain interleaved DC-DC converter. The analysis primarily relies on calculating the mean time between failures (MTBF). Based on military handbook (MIL-HDBK-217) criteria, the reliability calculation is performed. Stress factors and predicted failure rate for each component of presented converter is evaluated and tabulated. Reliability evaluation is performed for 1.5 kW hardware prototype. Based on reliability evaluation results, a reliable converter with better operating life time has been introduced.
高增益直流-直流转换器是可再生能源系统(RES)和电动汽车系统的关键部分。为了保证可再生能源系统的长期运行,需要对这些高增益转换器的可靠性进行评估。本文介绍了非隔离式高增益交错直流-直流转换器的可靠性分析。分析主要依靠计算平均故障间隔时间(MTBF)。根据军用手册 (MIL-HDBK-217) 标准,进行了可靠性计算。对转换器各组件的应力系数和预测故障率进行了评估并制成表格。对 1.5 kW 硬件原型进行了可靠性评估。根据可靠性评估结果,推出了具有更长工作寿命的可靠转换器。
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引用次数: 0
A novel modified mountain gazelle optimizer for tuning parameter proportional integral derivative of DC motor 用于调整直流电机参数比例积分导数的新型改良瞪羚优化器
Q2 Mathematics Pub Date : 2024-04-01 DOI: 10.11591/eei.v13i2.5575
Widi Aribowo, L. Abualigah, Diego Oliva, Aditya Prapanca
This article presents a modified method of mountain gazelle optimizer (MMGO) as a direct current (DC) motor control. Mountain gazelle optimizer (MGO) is an algorithm inspired by the life of the mountain gazelle animal in nature. This animal concept has five essential steps that are duplicated in mathematical modeling. This article uses two tests to get the performance of the MMGO method. The first test uses a benchmark function test with a comparison method, namely the sine tree seed algorithm (STSA) and the original MGO. The second test is the application of MMGO as a DC motor control. The simulation results show that MMGO can reduce the overshoot of conventional proportional integral derivative (PID) control by 0.447% and has a better integral time square error (ITSE) value of 5.345 than conventional PID control. Thus, the MMGO method shows promising performance.
本文介绍了一种改进的山羚优化器(MMGO)方法,作为直流(DC)电机控制。山羚优化器(MGO)是一种算法,其灵感来源于大自然中山羚动物的生活。这种动物的概念有五个基本步骤,在数学建模中也有重复。本文通过两个测试来了解 MMGO 方法的性能。第一个测试使用基准函数测试与一种比较方法,即正弦树种子算法(STSA)和原始 MGO。第二个测试是将 MMGO 应用于直流电机控制。仿真结果表明,MMGO 可以将传统比例积分导数(PID)控制的过冲降低 0.447%,积分时间平方误差(ITSE)值为 5.345,优于传统 PID 控制。因此,MMGO 方法显示出良好的性能。
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引用次数: 0
Image quality evaluation: evaluation of the image quality of actual images by using machine learning models 图像质量评估:利用机器学习模型评估实际图像的图像质量
Q2 Mathematics Pub Date : 2024-04-01 DOI: 10.11591/eei.v13i2.5947
Shiva Shankar Reddy, V. R. Maheswara Rao, Kalidindi Sravani, Silpa Nrusimhadri
Evaluating image features is a significant step in image processing in applications like number plate detection, vehicle tracking and many image processing-based applications. Image processing-based applications need accurate parts to get the best outcomes. Feature detection is done based on various feature detection techniques. The proposed system aims to get the best feature detector based on the input images by evaluating the image features. For assessing the image features, the proposed system worked on various descriptors like oriented FAST and rotated brief (ORB), learned arrangements of three patch codes (LATCH), binary robust independent elementary features (BRIEF), and binary robust invariant scalable keypoints (BRISK) to extract and evaluate the features using K-nearest neighbor (KNN)-matching and retrieve the inliers of the matching. Each descriptor produces different matching features and inliers; with the matchings and inliers, the inlier ratio calculates to show the analysis. To increase performance, we also examine adding depth information to descriptors.
在车牌检测、车辆跟踪和许多基于图像处理的应用中,评估图像特征是图像处理的一个重要步骤。基于图像处理的应用需要精确的部件才能获得最佳结果。特征检测是基于各种特征检测技术完成的。所提出的系统旨在通过评估图像特征,根据输入图像获得最佳特征检测器。为了评估图像特征,所提出的系统使用了各种描述符,如定向 FAST 和旋转简图(ORB)、三个补丁代码的学习排列(LATCH)、二进制鲁棒独立基本特征(BRIEF)和二进制鲁棒不变可扩展关键点(BRISK),使用 K 近邻(KNN)匹配来提取和评估特征,并检索匹配的离群值。每个描述符都会产生不同的匹配特征和离群值;利用匹配和离群值计算离群值比率,以显示分析结果。为了提高性能,我们还研究了在描述符中添加深度信息。
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引用次数: 0
Energy efficiency in activated sludge process using adaptive iterative learning control with PI ABAC 利用自适应迭代学习控制与 PI ABAC 提高活性污泥法的能效
Q2 Mathematics Pub Date : 2024-04-01 DOI: 10.11591/eei.v13i2.5095
Maimun Huja Husin, Mohamad Faizrizwan Mohd Sabri, Kismet Anak Hong Ping, Norazlina Bateni, S. Suhaili
This paper proposed an iterative learning control (ILC) with a feedback regulator based on proportional integral ammonium-based aeration control (PI ABAC) to improve dissolved oxygen control through data learning of iteration data. The proposed controller's performance is evaluated using benchmark simulation model no. 1. (BSM1). The assessments focused on four main areas: effluent violation, effluent quality, aeration energy, and overall cost index. The proposed ILC PI ABAC controller's effectiveness is evaluated by comparing the performance of the activated sludge process to the BSM1 PI and feedback PI ABAC under three different weather conditions: dry, rain, and storm. The improvement of the proposed method over BSM1 PI is demonstrated by a reduction in aeration energy of up to 24%. In conclusion, if the proposed ILC PI ABAC controller is given enough information, it can be quite successful in achieving energy efficiency.
本文提出了一种带反馈调节器的迭代学习控制(ILC),该反馈调节器基于比例积分氨曝气控制(PI ABAC),通过对迭代数据的学习来改进溶解氧控制。利用基准模拟模型 No.1. (BSM1)进行了性能评估。评估主要集中在四个方面:出水违规、出水质量、曝气能耗和总体成本指数。通过比较活性污泥工艺与 BSM1 PI 和反馈 PI ABAC 在三种不同天气条件下(干燥、下雨和暴风雨)的性能,评估了所提出的 ILC PI ABAC 控制器的有效性。与 BSM1 PI 相比,拟议方法的改进体现在曝气能耗降低了 24%。总之,如果给拟议的 ILC PI ABAC 控制器提供足够的信息,它就能成功地提高能效。
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引用次数: 0
Elitism-crossover barnacle mating optimization and its application to PID controller design for a buck converter 精选-交叉藤壶配对优化及其在降压转换器 PID 控制器设计中的应用
Q2 Mathematics Pub Date : 2024-04-01 DOI: 10.11591/eei.v13i2.5481
Ahmad Nor Kasruddin Nasir, Mohd Redzuan Ahmad, Muhammad Almaa Anwari Roslan
This paper presents an elitism-crossover barnacle mating optimization (ECBMO). It is an improvement of barnacle mating optimization (BMO). The original BMO suffers from local optima problem leading to a low accurate solution. A new method of offspring generation is adopted into the original BMO structure. Some features of the best-so-far solution are incorporated into the generated offspring. The accuracy performance of the proposed algorithm is tested on several IEEE functions. A statistical analysis is conducted to compare its performance over the original BMO. It is also applied to optimize proportional integral derivative (PID) parameters for controlling output voltage of a buck converter. Result of benchmark functions test shows the proposed algorithm has attained higher accuracy for all functions compared to BMO algorithm. Application on the real problem shows both algorithms control the converter voltage satisfactorily. However, the ECBMO has achieved more optimal PID parameters and leading to a better output voltage response.
本文提出了一种精英交叉藤壶交配优化(ECBMO)。它是对藤壶交配优化(BMO)的改进。原始 BMO 存在局部最优问题,导致解的精确度较低。在原有的 BMO 结构中采用了一种新的子代生成方法。在生成的子代中加入了迄今为止最佳解的一些特征。在多个 IEEE 函数上测试了所提算法的准确性。通过统计分析,比较了该算法与原始 BMO 的性能。该算法还被用于优化比例积分导数(PID)参数,以控制降压转换器的输出电压。基准函数测试结果表明,与 BMO 算法相比,所提出的算法在所有函数上都达到了更高的精度。在实际问题上的应用表明,两种算法都能令人满意地控制转换器电压。不过,ECBMO 实现了更优化的 PID 参数,从而获得了更好的输出电压响应。
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引用次数: 0
Palmprint recognition system using VR-LBP and KAZE features for better recognition accuracy 利用 VR-LBP 和 KAZE 特征提高识别准确率的掌纹识别系统
Q2 Mathematics Pub Date : 2024-04-01 DOI: 10.11591/eei.v13i2.4739
Noor Aldeen A. Khalid, Muhammad Imran Ahmad, Tan Shie Chow, Thulfiqar H. Mandeel, Ibrahim Majid Mohammed, Mokhalad Abdulameer Kadhim Alsaeedi
The palmprint recognition system has gained significant attention in security and law enforcement due to its unique features, such as principle lines, ridges, and wrinkles. However, many existing methods for extracting these features have limited accuracy, especially when the image illumination varies or the size of the processed pixels increases. Previous studies have shown that the local binary patterns (LBP) algorithm is effective for palmprint recognition due to the rich texture characteristics of a palmprint. In this paper, we propose a new technique for a robust contact-based palmprint identification system using vertical-LBP and KAZE feature detection. Our technique aims to improve recognition accuracy by using KAZE, which is a nonlinear diffusion approach that extracts nonlinear features from the evolution of the illuminance of an image. We also utilize principal component analysis (PCA) to reduce the dimensionality of the generated descriptor vector elements. The proposed method was tested on the PolyU database and achieved recognition accuracy of 99.7%.
掌纹识别系统因其独特的特征,如原理线、纹脊和皱纹等,在安全和执法领域备受关注。然而,现有的许多提取这些特征的方法准确性有限,尤其是当图像光照变化或处理像素尺寸增大时。以往的研究表明,由于掌纹具有丰富的纹理特征,局部二值模式(LBP)算法对掌纹识别非常有效。在本文中,我们提出了一种使用垂直 LBP 和 KAZE 特征检测的新技术,用于基于接触的鲁棒性掌纹识别系统。KAZE 是一种非线性扩散方法,可从图像照度的变化中提取非线性特征。我们还利用主成分分析(PCA)来降低生成的描述符向量元素的维度。所提出的方法在理大数据库中进行了测试,识别准确率达到 99.7%。
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引用次数: 0
Real-time monitoring tool for heart rate and oxygen saturation in young adults 青壮年心率和血氧饱和度实时监测工具
Q2 Mathematics Pub Date : 2024-04-01 DOI: 10.11591/eei.v13i2.6371
Siti Fatimah Abdul Razak, Yap Jia Wee, S. Yogarayan, Sharifah Noor Masidayu Sayed Ismail, Mohd Fikri Azli Abdullah
Health monitoring is crucial to maintain optimal well-being, especially for young adults. Wearable sensors have become popular for collecting healthcare data, but there are concerns regarding their reliability and safety, particularly with wireless sensors that use radio-frequency (RF) based devices. Researchers have proposed real-time monitoring systems for measuring heart rate beats per minute (BPM) and blood oxygen saturation (SpO2) saturation levels, but more studies are needed to determine the accuracy and user acceptance of these tools among young adults. To address these concerns, this study proposes a real-time monitoring tool that incorporates MAX 30100 sensors to collect heart rate BPM and SpO2 data. The collected data is then connected to a visualization platform, i.e., InfluxDB and Grafana, to provide valuable insights of the body’s physiological state. By testing the feasibility and usability of the tool, we found motivating differences in resting heart rates and changes in heart rate after activity between male and female participants. By developing this real-time monitoring tool and investigating gender-specific differences in heart rate and activity-induced changes, our study contributes to the advancement of health monitoring technologies for young adults, ultimately promoting personalized healthcare and well-being.
健康监测对于保持最佳健康状态至关重要,尤其是对年轻人而言。可穿戴传感器已成为收集健康数据的常用工具,但人们对其可靠性和安全性表示担忧,尤其是使用射频(RF)设备的无线传感器。研究人员提出了测量心率每分钟次数(BPM)和血氧饱和度(SpO2)的实时监测系统,但还需要更多的研究来确定这些工具在年轻人中的准确性和用户接受度。为了解决这些问题,本研究提出了一种实时监测工具,该工具采用 MAX 30100 传感器来收集心率 BPM 和血氧饱和度 SpO2 数据。然后将收集到的数据连接到一个可视化平台,即 InfluxDB 和 Grafana,以提供有关人体生理状态的有价值的见解。通过测试该工具的可行性和可用性,我们发现男性和女性参与者在静息心率和活动后心率变化方面存在激励性差异。通过开发这种实时监测工具并调查心率和活动引起的心率变化的性别差异,我们的研究有助于推动面向年轻人的健康监测技术的发展,最终促进个性化医疗保健和福祉。
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引用次数: 0
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Bulletin of Electrical Engineering and Informatics
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