Electronics

16 pages, 1803 KiB

Open AccessArticle

Atrial Fibrillation Detection Based on a Residual CNN Using BCG Signals

by Qiushi Su, Yanqi Huang, Xiaomei Wu, Biyong Zhang, Peilin Lu and Tan Lyu

Electronics 2022, 11(18), 2974; https://doi.org/10.3390/electronics11182974 - 19 Sep 2022

Cited by 2 | Viewed by 1912

Atrial fibrillation (AF) is the most common arrhythmia and can seriously threaten patient health. Research on AF detection carries important clinical significance. This manuscript proposes an AF detection method based on ballistocardiogram (BCG) signals collected by a noncontact sensor. We first constructed a [...] Read more.

Atrial fibrillation (AF) is the most common arrhythmia and can seriously threaten patient health. Research on AF detection carries important clinical significance. This manuscript proposes an AF detection method based on ballistocardiogram (BCG) signals collected by a noncontact sensor. We first constructed a BCG signal dataset consisting of 28,214 ten-second nonoverlapping segments collected from 45 inpatients during overnight sleep, including 9438 for AF, 9570 for sinus rhythm (SR), and 9206 for motion artifacts (MA). Then, we designed a residual convolutional neural network (CNN) for AF detection. The network has four modules, namely a downsampling convolutional module, a local feature learning module, a global feature learning module, and a classification module, and it extracts local and global features from BCG signals for AF detection. The model achieved precision, sensitivity, specificity, F1 score, and accuracy of 96.8%, 93.7%, 98.4%, 95.2%, and 96.8%, respectively. The results indicate that the AF detection method proposed in this manuscript could serve as a basis for long-term screening of AF at home based on BCG signal acquisition. Full article

(This article belongs to the Special Issue Deep Learning, Reconfigurable Computing and Machine Learning in Healthcare)

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14 pages, 1199 KiB

Open AccessArticle

Skeleton Action Recognition Based on Temporal Gated Unit and Adaptive Graph Convolution

by Qilin Zhu, Hongmin Deng and Kaixuan Wang

Electronics 2022, 11(18), 2973; https://doi.org/10.3390/electronics11182973 - 19 Sep 2022

Cited by 6 | Viewed by 1552

Abstract

In recent years, great progress has been made in the recognition of skeletal behaviors based on graph convolutional networks (GCNs). In most existing methods, however, the fixed adjacency matrix and fixed graph structure are used for skeleton data feature extraction in the spatial [...] Read more.

In recent years, great progress has been made in the recognition of skeletal behaviors based on graph convolutional networks (GCNs). In most existing methods, however, the fixed adjacency matrix and fixed graph structure are used for skeleton data feature extraction in the spatial dimension, which usually leads to weak spatial modeling ability, unsatisfactory generalization performance, and an excessive number of model parameters. Most of these methods follow the ST-GCN approach in the temporal dimension, which inevitably leads to a number of non-key frames, increasing the cost of feature extraction and causing the model to be slower in terms of feature extraction and the required computational burden. In this paper, a gated temporally and spatially adaptive graph convolutional network is proposed. On the one hand, a learnable parameter matrix which can adaptively learn the key information of the skeleton data in spatial dimension is added to the graph convolution layer, improving the feature extraction and generalizability of the model and reducing the number of parameters. On the other hand, a gated unit is added to the temporal feature extraction module to alleviate interference from non-critical frames and reduce computational complexity. A channel attention mechanism based on an SE module and a frame attention mechanism are used to enhance the model’s feature extraction ability. To prevent model degradation and ensure more stable training, residual links are added to each feature extraction module. The proposed approach was ultimately able to achieve 0.63% higher accuracy on the X-Sub benchmark with 4.46 M fewer parameters than GAT, one of the best SOTA methods. Inference speed of our model reaches as fast as 86.23 sequences/(second × GPU). Extensive experimental results further validate the effectiveness of our proposed approach on three large-scale datasets, namely, NTU RGB+D 60, NTU RGB+D 120, and Kinetics Skeleton. Full article

(This article belongs to the Section Artificial Intelligence)

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26 pages, 3176 KiB

Open AccessArticle

Forensic Analysis of TikTok Alternatives on Android and iOS Devices: Byte, Dubsmash, and Triller

by Yansi Keim, Shinelle Hutchinson, Apoorva Shrivastava and Umit Karabiyik

Electronics 2022, 11(18), 2972; https://doi.org/10.3390/electronics11182972 - 19 Sep 2022

Cited by 7 | Viewed by 4354

Abstract

TikTok has consistently been one of the most used mobile apps worldwide on any mobile operating system. However, despite people’s enjoyment of using the application, there have been growing concerns about the application’s origins and alleged privacy violations. These allegations have become such [...] Read more.

TikTok has consistently been one of the most used mobile apps worldwide on any mobile operating system. However, despite people’s enjoyment of using the application, there have been growing concerns about the application’s origins and alleged privacy violations. These allegations have become such a big problem that the former President of the United States, Donald Trump, expressed a desire to ban the TikTok application from being offered on US application stores like Google’s Play Store and Apple’s App Store. This remark sent TikTok users into a frenzy to find alternatives before the ban took effect. To this end, several alternative applications for TikTok have surfaced and are already garnering millions of users. In this paper, we identified three popular alternatives to the TikTok application (Byte, Dubmash, and Triller) and forensically analyzed each on smartphones of Android version 8 and iOS version 13. We focused on identifying forensically relevant artifacts that may be helpful to investigators in the event of a criminal investigation, should these or similar apps fall under scrutiny. We used Magnet AXIOM Process and Cellebrite UFED 4PC for acquisition, and Magnet AXIOM Examine and DB Browser for SQLite for analysis and reading. The investigation resulted in successful extraction of expected yet unique data points, plain text sensitive data, directories and format. These results lead to a discussion about identifying and comparing these app’s privacy concerns to that of TikTok, as formulated from the literature. Full article

(This article belongs to the Special Issue Digital Security and Privacy Protection: Trends and Applications)

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19 pages, 883 KiB

Open AccessArticle

IoT-Based Access Management Supported by AI and Blockchains

by Eryk Schiller, Elfat Esati and Burkhard Stiller

Electronics 2022, 11(18), 2971; https://doi.org/10.3390/electronics11182971 - 19 Sep 2022

Cited by 2 | Viewed by 1524

Abstract

Internet-of-Things (IoT), Artificial Intelligence (AI), and Blockchains (BCs) are essential techniques that are heavily researched and investigated today. This work here specifies, implements, and evaluates an IoT architecture with integrated BC and AI functionality to manage access control based on facial detection and [...] Read more.

Internet-of-Things (IoT), Artificial Intelligence (AI), and Blockchains (BCs) are essential techniques that are heavily researched and investigated today. This work here specifies, implements, and evaluates an IoT architecture with integrated BC and AI functionality to manage access control based on facial detection and recognition by incorporating the most recent state-of-the-art techniques. The system developed uses IoT devices for video surveillance, AI for face recognition, and BCs for immutable permanent storage to provide excellent properties in terms of image quality, end-to-end delay, and energy efficiency. Full article

(This article belongs to the Special Issue Emerging Technologies for the Next Generation Smart Systems)

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16 pages, 6951 KiB

Open AccessArticle

Design of Radiation-Tolerant High-Speed Signal Processing Circuit for Detecting Prompt Gamma Rays by Nuclear Explosion

by Minwoong Lee, Namho Lee, Huijeong Gwon, Jongyeol Kim, Younggwan Hwang and Seongik Cho

Electronics 2022, 11(18), 2970; https://doi.org/10.3390/electronics11182970 - 19 Sep 2022

Viewed by 1622

Abstract

Electronic equipment in nuclear power plants and nuclear warfare is damaged by transient effects that cause high-energy pulsed radiation. There is a concern that this type of damage can even cause enormous economic losses and human casualties by paralyzing control systems. To solve [...] Read more.

Electronic equipment in nuclear power plants and nuclear warfare is damaged by transient effects that cause high-energy pulsed radiation. There is a concern that this type of damage can even cause enormous economic losses and human casualties by paralyzing control systems. To solve this problem, this study proposes a complementary metal-oxide semiconductor (CMOS) logic-based, switching detection circuit that can detect pulsed radiations at a fast rate. This circuit improved response speed and power consumption by using the switching operation of digital logic compared with conventional circuits. Furthermore, radiation tolerance to total ionizing dose (TID) effects was achieved even in a cumulative radiation environment because of the use of the design using p-metal-oxide semiconductor field effect transistor (p-MOSFET). The proposed detection circuit was manufactured by a 0.18 µm CMOS bulk process for integration. Normal operation in the detection range of 2.0 × 10⁷ rad(si)/s was verified by pulsed radiation test evaluations, and the tolerance properties to a radiation of 2 Mrad was verified based on cumulative radiation test evaluations. Full article

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19 pages, 3051 KiB

Open AccessArticle

Pyramidal Predictive Network: A Model for Visual-Frame Prediction Based on Predictive Coding Theory

by Chaofan Ling, Junpei Zhong and Weihua Li

Electronics 2022, 11(18), 2969; https://doi.org/10.3390/electronics11182969 - 19 Sep 2022

Cited by 1 | Viewed by 1441

Abstract

Visual-frame prediction is a pixel-dense prediction task that infers future frames from past frames. A lack of appearance details, low prediction accuracy and a high computational overhead are still major problems associated with current models or methods. In this paper, we propose a [...] Read more.

Visual-frame prediction is a pixel-dense prediction task that infers future frames from past frames. A lack of appearance details, low prediction accuracy and a high computational overhead are still major problems associated with current models or methods. In this paper, we propose a novel neural network model inspired by the well-known predictive coding theory to deal with these problems. Predictive coding provides an interesting and reliable computational framework. We combined this approach with other theories, such as the theory that the cerebral cortex oscillates at different frequencies at different levels, to design an efficient and reliable predictive network model for visual-frame prediction. Specifically, the model is composed of a series of recurrent and convolutional units forming the top-down and bottom-up streams, respectively. The update frequency of neural units on each of the layers decreases with the increase in the network level, which means that neurons of a higher level can capture information in longer time dimensions. According to the experimental results, this model showed better compactness and comparable predictive performance with those of existing works, implying lower computational cost and higher prediction accuracy. Full article

(This article belongs to the Special Issue Human Robot Interaction and Intelligent System Design)

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16 pages, 1730 KiB

Open AccessArticle

Improving Efficiency of Large RFID Networks Using a Clustered Method: A Comparative Analysis

by M. Thurai Pandian, Kuldeep Chouhan, B. Muthu Kumar, Jatindra Kumar Dash, N. Z. Jhanjhi, Ashraf Osman Ibrahim and Anas W. Abulfaraj

Electronics 2022, 11(18), 2968; https://doi.org/10.3390/electronics11182968 - 19 Sep 2022

Cited by 5 | Viewed by 1434

Abstract

Radio Frequency Identification (RFID) is primarily used to resolve the problems of taking care of the majority of nodes perceived and tracking tags related to the items. Utilizing contactless radio frequency identification data can be communicated distantly using electromagnetic fields. In this paper, [...] Read more.

Radio Frequency Identification (RFID) is primarily used to resolve the problems of taking care of the majority of nodes perceived and tracking tags related to the items. Utilizing contactless radio frequency identification data can be communicated distantly using electromagnetic fields. In this paper, the comparison and analysis made between the Clustered RFID with existing protocols Ad hoc On-demand Multicast Distance Vector Secure Adjacent Position Trust Verification (AOMDV_SAPTV) and Optimal Distance-Based Clustering (ODBC) protocols based on the network attributes of accuracy, vulnerability and success rate, delay and throughput while handling the huge nodes of communication. In the RFID Network, the clustering mechanism was implemented to enhance the performance of the network when scaling nodes. Multicast routing was used to handle the large number of nodes involved in the transmission of particular network communication. While scaling up the network, existing methods may be compromised with their efficiency. However, the Clustered RFID method will give better performance without compromising efficiency. Here, Clustered RFID gives 93% performance, AOMDV_SAPTV can achieve 79%, and ODBC can reach 85% of performance. Clustered RFID gives 14% better performance than AOMDV_SAPTV and 8% better performance than ODBC for handling a huge range of nodes. Full article

(This article belongs to the Collection Smart Sensing RFID Tags)

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22 pages, 14891 KiB

Open AccessReview

Review of the Techniques of the Data Analytics and Islanding Detection of Distribution Systems Using Phasor Measurement Unit Data

by Ahmed Amirul Arefin, Maveeya Baba, Narinderjit Singh Sawaran Singh, Nursyarizal Bin Mohd Nor, Muhammad Aman Sheikh, Ramani Kannan, Ghulam E. Mustafa Abro and Nirbhay Mathur

Electronics 2022, 11(18), 2967; https://doi.org/10.3390/electronics11182967 - 19 Sep 2022

Cited by 7 | Viewed by 2087

Abstract

The application of the Phasor Measurement Unit (PMU) in the power system is expanding day by day since it provides a higher reliability through fast symmetrically monitoring and protection and assists in controlling power systems. For power systems, islanding is a significant event [...] Read more.

The application of the Phasor Measurement Unit (PMU) in the power system is expanding day by day since it provides a higher reliability through fast symmetrically monitoring and protection and assists in controlling power systems. For power systems, islanding is a significant event due to its hazardous consequences. To detect islanding events, several schemes have been previously proposed but inappropriate threshold setting, higher computational time, and false tripping are the main limitations. In addition, differentiating between real island events and transient faults is another limitation. However, appropriate threshold setting plays a considerable part in detecting the island event, which is also important to differentiate between real and non-island events. Phasor Measurement Unit can assist in islanding detection, but it can generate 30 samples/s, so there is always the possibility of making particular period data disappear. The principal contribution of this review article is its detailed discussion of real-time symmetrical PMU data and it further presents different PMU data analytic techniques and the proposed schemes for the islanding detection system. An appropriate methodology tried to understand how to incorporate missing PMU data techniques along with the islanding detection system to ensure the higher reliability of the network. Full article

(This article belongs to the Special Issue Voltage Control and Protection in Power Systems)

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16 pages, 2643 KiB

Open AccessArticle

Multi-Graph Convolutional Network for Fine-Grained and Personalized POI Recommendation

by Suzhi Zhang, Zijian Bai, Pu Li and Yuanyuan Chang

Electronics 2022, 11(18), 2966; https://doi.org/10.3390/electronics11182966 - 19 Sep 2022

Cited by 4 | Viewed by 1570

Abstract

With the advent of the era of rapid information expansion, the massive data backlog that exists on the Internet has led to a serious information overload problem, which makes recommendation systems a crucial part of human life. In particular, the Point-Of-Interest (POI) recommendation [...] Read more.

With the advent of the era of rapid information expansion, the massive data backlog that exists on the Internet has led to a serious information overload problem, which makes recommendation systems a crucial part of human life. In particular, the Point-Of-Interest (POI) recommendation system has been applied to many real-life scenarios, such as life services and autonomous driving. Specifically, the goal of POI recommendation is to recommend locations that match their personalized preferences to users. In existing POI recommendation methods, people tend to pay more attention to the impact of temporal and spatial factors of POI on users, which will alleviate the problems of data sparsity and cold start in POI recommendation. However, this tends to ignore the differences among individual users, and considering only temporal and spatial attributes does not support fine-grained POI recommendations. To solve this problem, we propose a new Fine-grained POI Recommendation With Multi-Graph Convolutional Network (FP-MGCN). This model focuses on the content representation of POIs, captures users’ personalized preferences using semantic information from user comments, and learns fine-grained representations of users and POIs through the relationships between content–content, content–POI, and POI–user. FP-MGCN employs multiple embedded propagation layers and adopts information propagation mechanisms to model the higher-order connections of different POI-related relations for enhanced representation. Fine-grained POI is finally recommended to users through the three types of propagation we designed: content–content information propagation, content–POI information propagation, and POI–user information propagation. We have conducted detailed experiments on two datasets, and the results show that FP-MGCN has advanced performance and can alleviate the data sparsity problem in POI recommendation tasks. Full article

(This article belongs to the Special Issue Recommender Systems: Approaches, Challenges and Applications (Volume II))

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15 pages, 4781 KiB

Open AccessArticle

Methodology for Structured Data-Path Implementation in VLSI Physical Design: A Case Study

by Dhilleswararao Pudi, Samuel Jigme Harrison, Dimitrios Stathis, Srinivas Boppu, Ahmed Hemani and Linga Reddy Cenkeramaddi

Electronics 2022, 11(18), 2965; https://doi.org/10.3390/electronics11182965 - 19 Sep 2022

Cited by 1 | Viewed by 2671

Abstract

State-of-the-art modern microprocessor and domain-specific accelerator designs are dominated by data-paths composed of regular structures, also known as bit-slices. Random logic placement and routing techniques may not result in an optimal layout for these data-path-dominated designs. As a result, implementation tools such as [...] Read more.

State-of-the-art modern microprocessor and domain-specific accelerator designs are dominated by data-paths composed of regular structures, also known as bit-slices. Random logic placement and routing techniques may not result in an optimal layout for these data-path-dominated designs. As a result, implementation tools such as Cadence’s Innovus include a Structured Data-Path (SDP) feature that allows data-path placement to be completely customized by constraining the placement engine. A relative placement file is used to provide these constraints to the tool. However, the tool neither extracts nor automatically places the regular data-path structures. In other words, the relative placement file is not automatically generated. In this paper, we propose a semi-automated method for extracting bit-slices from the Innovus SDP flow. It has been demonstrated that the proposed method results in 17% less density or use for a pixel buffer design. At the same time, the other performance metrics are unchanged when compared to the traditional place and route flow. Full article

(This article belongs to the Collection Advanced Design Techniques and EDA Methodologies for Analog, RF and MM-Wave Circuit Design)

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24 pages, 37206 KiB

Open AccessArticle

A Novel Deep Learning Technique for Detecting Emotional Impact in Online Education

by Shadi AlZu’bi, Raed Abu Zitar, Bilal Hawashin, Samia Abu Shanab, Amjed Zraiqat, Ala Mughaid, Khaled H. Almotairi and Laith Abualigah

Electronics 2022, 11(18), 2964; https://doi.org/10.3390/electronics11182964 - 19 Sep 2022

Cited by 17 | Viewed by 3505

Abstract

Emotional intelligence is the automatic detection of human emotions using various intelligent methods. Several studies have been conducted on emotional intelligence, and only a few have been adopted in education. Detecting student emotions can significantly increase productivity and improve the education process. This [...] Read more.

Emotional intelligence is the automatic detection of human emotions using various intelligent methods. Several studies have been conducted on emotional intelligence, and only a few have been adopted in education. Detecting student emotions can significantly increase productivity and improve the education process. This paper proposes a new deep learning method to detect student emotions. The main aim of this paper is to map the relationship between teaching practices and student learning based on emotional impact. Facial recognition algorithms extract helpful information from online platforms as image classification techniques are applied to detect the emotions of student and/or teacher faces. As part of this work, two deep learning models are compared according to their performance. Promising results are achieved using both techniques, as presented in the Experimental Results Section. For validation of the proposed system, an online course with students is used; the findings suggest that this technique operates well. Based on emotional analysis, several deep learning techniques are applied to train and test the emotion classification process. Transfer learning for a pre-trained deep neural network is used as well to increase the accuracy of the emotion classification stage. The obtained results show that the performance of the proposed method is promising using both techniques, as presented in the Experimental Results Section. Full article

(This article belongs to the Special Issue Big Data Analytics Using Artificial Intelligence)

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11 pages, 4194 KiB

Open AccessArticle

Bipolar Resistive Switching in Hafnium Oxide-Based Nanostructures with and without Nickel Nanoparticles

by Markus Otsus, Joonas Merisalu, Aivar Tarre, Anna-Liisa Peikolainen, Jekaterina Kozlova, Kaupo Kukli and Aile Tamm

Electronics 2022, 11(18), 2963; https://doi.org/10.3390/electronics11182963 - 19 Sep 2022

Cited by 2 | Viewed by 1452

Abstract

As research into additives and intentionally introduced impurities in dielectric thin film for enhancing the resistive switching based random access memories (RRAM) continues to gain momentum, the aim of the study was to evaluate the effects of chemically presynthesised Ni nanoparticles (NPs) embedded [...] Read more.

As research into additives and intentionally introduced impurities in dielectric thin film for enhancing the resistive switching based random access memories (RRAM) continues to gain momentum, the aim of the study was to evaluate the effects of chemically presynthesised Ni nanoparticles (NPs) embedded in a dielectric layer to the overall structure and resistive switching properties. HfO₂-based thin films embedded with Ni NPs were produced by atomic layer deposition (ALD) from tetrakis(ethylmethylamino)hafnium (TEMAH) and the O₂ plasma ALD process onto a TiN/Si substrate. The Ni NPs were separately synthesised through a continuous flow chemistry process and dispersed on the dielectric layer between the two stages of preparing the HfO₂ layer. The nanodevices’ morphology and composition were analysed with physical characterisation methods and were found to be uniformly dispersed across the sample, within an amorphous HfO₂ layer deposited around them. When comparing the resistive switching properties of otherwise identical samples with and without Ni NPs, the ILRS/IHRS ratio rose from around a 4 to 9 at 0.2 V reading voltage, the switching voltage dropped from ~2 V to ~1.5 V, and a distinct increase in the endurance characteristics could be seen with the addition of the nanoparticles. Full article

(This article belongs to the Section Circuit and Signal Processing)

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20 pages, 11276 KiB

Open AccessArticle

Eight-Element Antenna Array with Improved Radiation Performances for 5G Hand-Portable Devices

by Atta Ullah, Naser Ojaroudi Parchin, Ahmed S. I. Amar and Raed A. Abd-Alhameed

Electronics 2022, 11(18), 2962; https://doi.org/10.3390/electronics11182962 - 19 Sep 2022

Cited by 3 | Viewed by 1707

Abstract

This study aims to introduce a new phased array design with improved radiation properties for future cellular networks. The procedure of the array design is simple and has been accomplished on a low-cost substrate material while offering several interesting features with high performance. [...] Read more.

This study aims to introduce a new phased array design with improved radiation properties for future cellular networks. The procedure of the array design is simple and has been accomplished on a low-cost substrate material while offering several interesting features with high performance. Its schematic involves eight air-filled slot-loop metal-ring elements with a 1 × 8 linear arrangement at the top edge of the 5G smartphone mainboard. Considering the entire board area, the proposed antenna elements occupy an extremely small area. The antenna elements cover the range of 21–23.5 GHz sub-mm-wave 5G bands. Due to the air-filled function in the configurations of the elements, low-loss and high-performance radiation properties are observed. In addition, the fundamental characteristics of the introduced array are insensitive to various types of substrates. Moreover, its radiation properties have been compared with conventional arrays and better results have been observed. The proposed array appears with a simple design, a low complexity profile, and its attractive broad impedance bandwidth, end-fire radiation mode, wide beam steering, high radiation coverage, and stable characteristics meet the needs of 5G applications in future cellular communications. Additionally, the smartphone array design offers sufficient efficiency when it comes to the appearance and integration of the user’s components. Thus, it could be used in 5G hand-portable devices. Full article

(This article belongs to the Special Issue Antenna Designs for 5G/IoT and Space Applications, Volume II)

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16 pages, 3847 KiB

Open AccessArticle

A Voronoi Diagram-Based Grouping Test Localization Scheme in Wireless Sensor Networks

by Guangming Li, Menghui Xu, Gaofei Teng, Wei Yang, Shu-Lun Mak, Chun-Yin Li and Chi-Chung Lee

Electronics 2022, 11(18), 2961; https://doi.org/10.3390/electronics11182961 - 18 Sep 2022

Cited by 1 | Viewed by 1462

Abstract

The wireless sensor network (WSN) provides us with a cost-effective way to remotely monitor a large number of objects, locations, and environmental parameters. Taking advantage of WSNs to applications can add new capabilities to existing products and bring out new services. We propose [...] Read more.

The wireless sensor network (WSN) provides us with a cost-effective way to remotely monitor a large number of objects, locations, and environmental parameters. Taking advantage of WSNs to applications can add new capabilities to existing products and bring out new services. We propose a novel range-free localization scheme, the Voronoi diagram-based grouping test localization (VTL) scheme, to estimate the location efficiently for WSNs. VTL divides the anchor nodes into multiple groups and uses the corresponding closest Voronoi cells to compute the estimated location. Apart from improving the accuracy of location estimation, it also largely simplifies the implementation. Simulation results show that the VTL scheme has better performance compared with other range-free localization schemes. When reaching a certain anchor node density, the VTL scheme will have higher localization accuracy and a larger percentage of localizable nodes. Hence, VTL is likely more appropriate for upcoming WSN scenarios with large ratios of anchor nodes being available. Full article

(This article belongs to the Special Issue Feature Papers in "Networks" Section)

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20 pages, 4569 KiB

Open AccessArticle

Classification of Roads and Types of Public Roads Using EOG Smart Glasses and an Algorithm Based on Machine Learning While Driving a Car

by Rafał Doniec, Natalia Piaseczna, Frédéric Li, Konrad Duraj, Hawzhin Hozhabr Pour, Marcin Grzegorzek, Katarzyna Mocny-Pachońska and Ewaryst Tkacz

Electronics 2022, 11(18), 2960; https://doi.org/10.3390/electronics11182960 - 18 Sep 2022

Cited by 7 | Viewed by 1804

Abstract

Driving a car is an activity that became necessary for exploration, even when living in the present world. Research exploring the topic of safety on the roads has therefore become increasingly relevant. In this paper, we propose a recognition algorithm based on physiological [...] Read more.

Driving a car is an activity that became necessary for exploration, even when living in the present world. Research exploring the topic of safety on the roads has therefore become increasingly relevant. In this paper, we propose a recognition algorithm based on physiological signals acquired from JINS MEME ES_R smart glasses (electrooculography, acceleration and angular velocity) to classify four commonly encountered road types: city road, highway, housing estate and undeveloped area. Data from 30 drivers were acquired in real driving conditions. Hand-crafted statistical features were extracted from the physiological signals to train and evaluate a random forest classifier. We achieved an overall accuracy, precision, recall and F1 score of 87.64%, 86.30%, 88.12% and 87.08% on the test dataset, respectively. Full article

(This article belongs to the Special Issue 10th Anniversary of Electronics: Recent Advances in Computer Science & Engineering)

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16 pages, 2341 KiB

Open AccessArticle

Motion Video Recognition in Speeded-Up Robust Features Tracking

by Jianguang Zhang, Yongxia Li, An Tai, Xianbin Wen and Jianmin Jiang

Electronics 2022, 11(18), 2959; https://doi.org/10.3390/electronics11182959 - 18 Sep 2022

Cited by 4 | Viewed by 1292

Abstract

Motion video recognition has been well explored in applications of computer vision. In this paper, we propose a novel video representation, which enhances motion recognition in videos based on SURF (Speeded-Up Robust Features) and two filters. Firstly, the detector scheme of SURF is [...] Read more.

Motion video recognition has been well explored in applications of computer vision. In this paper, we propose a novel video representation, which enhances motion recognition in videos based on SURF (Speeded-Up Robust Features) and two filters. Firstly, the detector scheme of SURF is used to detect the candidate points of the video because it is an efficient faster local feature detector. Secondly, by using the optical flow field and trajectory, the feature points can be filtered from the candidate points, which enables a robust and efficient extraction of motion feature points. Additionally, we introduce a descriptor, called MoSURF (Motion Speeded-Up Robust Features), based on SURF (Speeded-Up Robust Features), HOG (Histogram of Oriented Gradient), HOF (Histograms of Optical Flow), MBH(Motion Boundary Histograms), and trajectory information, which can effectively describe motion information and are complementary to each other. We evaluate our video representation under action classification on three motion video datasets namely KTH, YouTube, and UCF50. Compared with state-of-the-art methods, the proposed method shows advanced results on all datasets. Full article

(This article belongs to the Special Issue Multimedia Information Retrieval: From Theory to Applications)

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19 pages, 12058 KiB

Open AccessArticle

System for Non-Contact and Multispectral Examination of Blood Supply to Cutaneous Tissue

by Michal Labuda, Maros Smondrk, Branko Babusiak and Stefan Borik

Electronics 2022, 11(18), 2958; https://doi.org/10.3390/electronics11182958 - 18 Sep 2022

Cited by 1 | Viewed by 1290

Abstract

The presented system for non-contact examination of tissue perfusion is one of the tools for complex examination of human body tissues (skin, subcutaneous) and their mutual interactions, including blood flow and activity under various external stimuli. In our system, optical radiation, with wavelengths [...] Read more.

The presented system for non-contact examination of tissue perfusion is one of the tools for complex examination of human body tissues (skin, subcutaneous) and their mutual interactions, including blood flow and activity under various external stimuli. In our system, optical radiation, with wavelengths of 525 nm, 625 nm, and 940 nm, was used to investigate the perfusion and properties of skin tissue. Our work presents that it is possible to obtain comprehensive information about the cardiovascular system and skin tissue perfusion by a suitable combination of wavelengths, light intensity, and homogeneous illumination distribution with a properly chosen sensing device—a camera. The proposed system consists of an illumination device that emits light of the three wavelengths mentioned above and thus makes it possible to investigate the skin tissue structures and their interrelationships in terms of their blood supply and interactions with each other. Full article

(This article belongs to the Special Issue Electronic Devices and Systems for Biomedical Applications)

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13 pages, 2893 KiB

Open AccessArticle

A Measurement Compensation Method for Electrical Capacitance Tomography Sensors with Inhomogeneous Electrode Parameters

by Yaohong Tang, Weiqing Lin, Shungen Xiao, Kaihao Tang and Xiufang Lin

Electronics 2022, 11(18), 2957; https://doi.org/10.3390/electronics11182957 - 18 Sep 2022

Cited by 2 | Viewed by 1303

Abstract

An electrical capacitance tomography (ECT) sensor is an array capacitive sensor that is sensitive to the medium of the measured object and can be widely used in oil, natural gas, machinery and other industrial fields to solve the problem of multiphase fluid object [...] Read more.

An electrical capacitance tomography (ECT) sensor is an array capacitive sensor that is sensitive to the medium of the measured object and can be widely used in oil, natural gas, machinery and other industrial fields to solve the problem of multiphase fluid object parameter detection in industrial processes. However, ECT sensor uniformity defects need to be addressed. Aiming at the problem that the non-uniform electrode spacing angle affects the characteristics of the measured value of the actual ECT sensor, a method for compensating the measured value of the ECT sensor based on the assumption that the geometric factor is invariant is proposed. The simulated measurement value in the case of the tube and the measurement value of the actual sensor in the case of an empty tube and a full tube are to compensate the measurement value of the actual ECT. Experiments show that, without compensation, non-ideal sensor monitoring has large error, and, after compensation, it has a good effect and can be expected to perform satisfactorily in practical use. Full article

(This article belongs to the Special Issue Product Design and Development Using Computational and Numerical Modeling)

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7 pages, 1435 KiB

Open AccessCommunication

A New Approach to Power Distribution by a Dual-Gate MOSFET for Controlling a Smart Actuator Array

by Seok-Hyun Lee and Jaehwan Kim

Electronics 2022, 11(18), 2956; https://doi.org/10.3390/electronics11182956 - 18 Sep 2022

Viewed by 1261

Abstract

Remotely driven smart actuator technology by microwave is attractive since it simplifies and reduces the complexity and weight of the remote system. A rectifying antenna (rectenna) array receives and converts microwave power into DC power for actuators, and the power collected from the [...] Read more.

Remotely driven smart actuator technology by microwave is attractive since it simplifies and reduces the complexity and weight of the remote system. A rectifying antenna (rectenna) array receives and converts microwave power into DC power for actuators, and the power collected from the rectenna array should be accurately allocated and distributed to each actuator. In this research, a new power distribution (PD) logic circuit is studied to control an actuator array effectively. The PD logic circuit was designed and tested to validate it. The preliminary design was tested for a 4 × 4 piezoelectric actuator array with a 16 dual-gate MOSFET array and a computer-controlled 16-channel DAC board. Additionally, power compensation as a remedial approach for a partial power failure of the array was integrated. This PD scheme with a new logic device simplifies the thousands of control cables required for connecting each array element. The performance and limitations of the designed PD circuit are discussed. Full article

(This article belongs to the Special Issue Power Electronics Converter Topologies and Control Techniques)

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18 pages, 5453 KiB

Open AccessArticle

Queue-Buffer Optimization Based on Aggressive Random Early Detection in Massive NB-IoT MANET for 5G Applications

by Syed Talib Abbas Jafri, Irfan Ahmed and Sundus Ali

Electronics 2022, 11(18), 2955; https://doi.org/10.3390/electronics11182955 - 18 Sep 2022

Cited by 8 | Viewed by 1810

Abstract

Elements in massive narrowband Internet of Things (NB-IoT) for 5G networks suffer severely from packet drops due to queue overflow. Active Queue Management (AQM) techniques help in maintaining queue length by dropping packets early, based on certain defined parameters. In this paper, we [...] Read more.

Elements in massive narrowband Internet of Things (NB-IoT) for 5G networks suffer severely from packet drops due to queue overflow. Active Queue Management (AQM) techniques help in maintaining queue length by dropping packets early, based on certain defined parameters. In this paper, we have proposed an AQM technique, called Aggressive Random Early Detection (AgRED) which, in comparison to previously used Random Early Detection (RED) and exponential RED technique, improves the overall end-to-end delay, throughput, and packet delivery ratio of the massive NB-IoT 5G network while using UDP. This improvement has been achieved due to a sigmoid function used by the AgRED technique, which aggressively and randomly drops the incoming packets preventing them from filling the queue. Because of the incorporation of the AgRED technique, the queue at different nodes will remain available throughout the operation of the network and the probability of delivering the packets will increase. We have analyzed and compared the performance of our proposed AgRED technique and have found that the performance gain for the proposed technique is higher than other techniques (RED and exponential RED) and passive queue management techniques (drop-tail and drop-head). The improvement in results is most significant in congested network deployment scenarios and provides improvements in massive Machine Type Communication, while also supporting ultra-low latency and reliable communication for 5G applications. Full article

(This article belongs to the Special Issue Smart Applications of 5G Network)

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8 pages, 2722 KiB

Open AccessArticle

Evaluation of Pulsed Spark Discharge for Triggering GaAs Photoconductive Semiconductor Switches

by Qin Zhang, Wei Shi, Cheng Ma and Lei Yang

Electronics 2022, 11(18), 2954; https://doi.org/10.3390/electronics11182954 - 18 Sep 2022

Viewed by 1396

Abstract

In this study, a 3 mm gap GaAs photoconductive semiconductor switch (GaAs PCSS) was triggered by pulsed spark discharge. The typical linear mode of GaAs PCSS was fulfilled at a low bias voltage. The on-state current waveform was similar to that of an [...] Read more.

In this study, a 3 mm gap GaAs photoconductive semiconductor switch (GaAs PCSS) was triggered by pulsed spark discharge. The typical linear mode of GaAs PCSS was fulfilled at a low bias voltage. The on-state current waveform was similar to that of an optical pulse. The “nonlinear mode” was demonstrated at a bias voltage of 4 kV; concurrently, the peak current and the carriers’ multiplication rate were 33 A and 179, respectively. This study indicates that pulsed spark discharge is a promising candidate light source for the direct triggering of GaAs PCSSs. Full article

(This article belongs to the Section Semiconductor Devices)

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26 pages, 3543 KiB

Open AccessReview

Current Source Topologies for Photovoltaic Applications: An Overview

by Oscar Miguel Rodríguez-Benítez, Juan Antonio Aqui-Tapia, Isaac Ortega-Velázquez and Gerardo Espinosa-Pérez

Electronics 2022, 11(18), 2953; https://doi.org/10.3390/electronics11182953 - 17 Sep 2022

Cited by 4 | Viewed by 1593

Abstract

Current source topologies have several advantages compared to conventional voltage systems. Their inherent voltage-boosting function, intrinsic short-circuit protection, no electrolytic capacitor, direct-current control, continuous input current, and high reliability make them exceptional candidates for power generation systems, particularly for photovoltaic applications. This study [...] Read more.

Current source topologies have several advantages compared to conventional voltage systems. Their inherent voltage-boosting function, intrinsic short-circuit protection, no electrolytic capacitor, direct-current control, continuous input current, and high reliability make them exceptional candidates for power generation systems, particularly for photovoltaic applications. This study provides an overview of the current source topologies for multi-stage photovoltaic grid-connected systems by comparing the number of components, performance, power-decoupling techniques, efficiency, and frequency operation. The overview reveals gain, performance, energy quality and lifetime improvements, thereby providing current source systems as an attractive alternative for renewable applications. Full article

(This article belongs to the Special Issue Recent Developments and Emerging Trends in Power Electronics Converters)

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17 pages, 19699 KiB

Open AccessArticle

Research on Generalized Intelligent Routing Technology Based on Graph Neural Network

by Xiangyu Zheng, Wanwei Huang, Hui Li and Guangyuan Li

Electronics 2022, 11(18), 2952; https://doi.org/10.3390/electronics11182952 - 17 Sep 2022

Cited by 4 | Viewed by 2439

Abstract

Aiming at the problems of poor load balancing ability and weak generalization of the existing routing algorithms, this paper proposes an intelligent routing algorithm, GNN-DRL, in the Software Defined Networking (SDN) environment. The GNN-DRL algorithm uses a graph neural network (GNN) to perceive [...] Read more.

Aiming at the problems of poor load balancing ability and weak generalization of the existing routing algorithms, this paper proposes an intelligent routing algorithm, GNN-DRL, in the Software Defined Networking (SDN) environment. The GNN-DRL algorithm uses a graph neural network (GNN) to perceive the dynamically changing network topology, generalizes the state of nodes and edges, and combines the self-learning ability of Deep Reinforcement Learning (DRL) to find the optimal routing strategy, which makes GNN-DRL minimize the maximum link utilization and reduces average end-to-end delay under high network load. In this paper, the GNN-DRL intelligent routing algorithm is compared with the Open Shortest Path First (OSPF), Equal-Cost Multi-Path (ECMP), and intelligence-driven experiential network architecture for automatic routing (EARS). The experimental results show that GNN-DRL reduces the maximum link utilization by 13.92% and end-to-end delay by 9.48% compared with the superior intelligent routing algorithm EARS under high traffic load, and can be effectively extended to different network topologies, making possible better load balancing capability and generalizability. Full article

(This article belongs to the Special Issue Artificial Intelligence Driven Software-Defined Networking (SDN) Technologies for Next Generation Networks)

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17 pages, 5912 KiB

Open AccessArticle

Inverted Microstrip Gap Waveguide Coplanar EBG Filter for Antenna Applications

by Luis Inclán-Sánchez

Electronics 2022, 11(18), 2951; https://doi.org/10.3390/electronics11182951 - 17 Sep 2022

Cited by 2 | Viewed by 1843

Abstract

The possibility of making compact stopband filters using coplanar-coupled EBG resonators in inverted microstrip gap waveguide technology is studied in this work. To do this, the filtering characteristics of different configurations of mushroom-type elements are shown in which the short-circuit element is placed [...] Read more.

The possibility of making compact stopband filters using coplanar-coupled EBG resonators in inverted microstrip gap waveguide technology is studied in this work. To do this, the filtering characteristics of different configurations of mushroom-type elements are shown in which the short-circuit element is placed on the edge of the resonator’s patch. The behavior of the structure as well as its main advantages such as: low losses, self-packaging, low level of complexity, flexibility and easy design are illustrated in the paper. To evaluate the possibility of integrating these structures in gap waveguide planar antennas feeding networks, a 5-cell EBG filter was designed and built at the X band. The proposed filter reached a maximum rejection level of −35.4 dB, had a stopband centered at 9 GHz and a relative fractional bandwidth below −20 dB of 10.6%. The new compact filter presented a flat passband in which it was well matched and had low insertion losses that, including the connectors, were close to 1.5 dB in most of the band. These results are enough to improve low-complexity future antenna designs with filter functionalities in this technology. Full article

(This article belongs to the Special Issue Metastructures and Antennas with Enhanced Properties for Modern Microwave and Millimeter-Wave Applications)

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18 pages, 9823 KiB

Open AccessArticle

A Novel Airspace Planning Algorithm for Cooperative Target Localization

by Yi Mao, Yongwen Zhu, Zhili Tang and Zhijie Chen

Electronics 2022, 11(18), 2950; https://doi.org/10.3390/electronics11182950 - 17 Sep 2022

Cited by 52 | Viewed by 1723

Abstract

With the development of modern electromagnetic stealth technology and ARM, traditional active radar detection cannot accomplish its detection mission, limited by its ability. Relying on such superior advantages such as imperceptibility, anti-electromagnetic interference and electromagnetic stealth, passive transducers are playing an indispensable and [...] Read more.

With the development of modern electromagnetic stealth technology and ARM, traditional active radar detection cannot accomplish its detection mission, limited by its ability. Relying on such superior advantages such as imperceptibility, anti-electromagnetic interference and electromagnetic stealth, passive transducers are playing an indispensable and significant role in situation awareness. While, in addition to different passive transducer localization modes and solutions of target’s location, the reasonable planning and optimal layout of passive transducers’ location are other major factors affecting the precision of localization. Planning an optimal airspace for passive transducers is the key problem to improve the monitoring efficiency. This paper proposes the optimal layout algorithm for the cooperative platform in the space based on the geometrical relationship of cooperative localization. For example, the principle of direction location in traditional methods is simple: only two passive sensors can work, but the location accuracy of long-distance targets is low. At the same time, TDOA (Time Difference Of Arrival) location has high accuracy and good stability, but it needs at least three passive sensors to work together, which requires the most resources. In this paper, a platform optimization layout algorithm based on direction and TDOA hybrid positioning is proposed. Compared with direction positioning, it improves the long-distance positioning accuracy, reduces the number of sensors required for TDOA positioning, and reduces the resource occupancy rate. However, the TDOA positioning data mixed with direction positioning data inevitably leads to the decline of overall accuracy. In order to solve these difficulties, the weighted least square method is used to optimize the accuracy. The simulation shows that, within the designated target airspace, the optimal action airspace can be generated automatically based on the platforms’ cooperation mode. If there is no resource limitation, the airspace planning based on TDOA positioning has the highest accuracy for the target. However, in practical application, considering the resource limitation, the hybrid positioning of direction and TDOA can also meet the requirements of high accuracy and high stability. The average error is reduced by more than 45% compared with direction positioning, and the airspace occupancy is reduced by more than 30% compared with TDOA positioning. The goal of minimizing the scope of platform airspace planning is realized. Full article

(This article belongs to the Special Issue Modelling, Control and Emerging Application for Unmanned Vehicles)

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13 pages, 2773 KiB

Open AccessArticle

Deterministic Brownian-like Motion: Electronic Approach

by José Luis Echenausía-Monroy, Eric Campos, Rider Jaimes-Reátegui, Juan Hugo García-López and Guillermo Huerta-Cuellar

Electronics 2022, 11(18), 2949; https://doi.org/10.3390/electronics11182949 - 17 Sep 2022

Cited by 6 | Viewed by 1407

Abstract

Brownian motion is a dynamic behavior with random changes over time (stochastic) that occurs in many vital functions related to fluid environments, stock behavior, or even renewable energy generation. In this paper, we present a circuit implementation that reproduces Brownian motion based on [...] Read more.

Brownian motion is a dynamic behavior with random changes over time (stochastic) that occurs in many vital functions related to fluid environments, stock behavior, or even renewable energy generation. In this paper, we present a circuit implementation that reproduces Brownian motion based on a fully deterministic set of differential equations. The dynamics of the electronic circuit are characterized using four well-known metrics of Brownian motion, namely: (i) Detrended Fluctuation Analysis (DFA), (ii) power law in the power spectrum, (iii) normal probability distribution, and (iv) Mean Square Displacement (MSD); where traditional Brownian motion exhibits linear time growth of the MSD, a Gaussian distribution, a

- 2

power law of the frequency spectrum, and DFA values close to

1.5

. The obtained results show that for a certain combination of values in the deterministic model, the dynamics in the electronic circuit are consistent with the expectations for a stochastic Brownian behavior. The presented electronic circuit improves the study of Brownian behavior by eliminating the stochastic component, allowing reproducibility of the results through fully deterministic equations, and enabling the generation of physical signals (analog electronic signals) with Brownian-like properties with potential applications in fields such as medicine, economics, genetics, and communications, to name a few. Full article

(This article belongs to the Special Issue Embedded and Integrated Circuits and Systems in Real Engineering Applications)

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19 pages, 5666 KiB

Open AccessFeature PaperArticle

An Efficient Slotted Waveguide Antenna System Integrated with Inside-Grooves and Modified Gaussian Slot Distribution

by Asif Mehmood Khan, Muhammad Mansoor Ahmed, Umair Rafique, Arslan Kiyani and Syed Muzahir Abbas

Electronics 2022, 11(18), 2948; https://doi.org/10.3390/electronics11182948 - 17 Sep 2022

Cited by 1 | Viewed by 1950

Abstract

In this work, an efficient slotted waveguide antenna (SWA) system is designed for S-band high power microwave (HPM) applications. The designed SWA comprises of 10-slot elements placed on the broad wall of SWA with a modified Gaussian distribution (MGD), integrated with two inside-grooves [...] Read more.

In this work, an efficient slotted waveguide antenna (SWA) system is designed for S-band high power microwave (HPM) applications. The designed SWA comprises of 10-slot elements placed on the broad wall of SWA with a modified Gaussian distribution (MGD), integrated with two inside-grooves and a Gaussian dielectric radome of high-density polyethylene (HDPE) material. The inside-grooves are introduced to suppress the surface current on the waveguide, which results in high gain as well as sidelobe level (SLL) reduction in the E-plane. The MGD controls the SLLs, and the unique Gaussian profile shape radome offers constant radiation characteristics. The proposed antenna system, within existing size constraints, offers a high gain of 20.1 dBi in conjunction with a high-power handling capability of greater than 100 MW. The designed SWA system has compact dimensions of 8.46λ₀ × 1.38λ₀ × 1.50λ₀, with SLLs of −20 dB and −22 dB in the H- and E-plane, respectively. The HPM antenna system, radiating at 3 GHz, is fabricated on aluminium material using the milling process. The simulated SWA system has good agreement with measured results. Moreover, the proposed SWA system offers clear advantages in terms of its robustness, design simplicity, high power handling capability, and high gain. Full article

(This article belongs to the Special Issue Microwave and Millimeter-Wave Antennas: Latest Advances and Prospects)

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13 pages, 2535 KiB

Open AccessArticle

eXplainable AI (XAI)-Based Input Variable Selection Methodology for Forecasting Energy Consumption

by Taeyong Sim, Seonbin Choi, Yunjae Kim, Su Hyun Youn, Dong-Jin Jang, Sujin Lee and Chang-Jae Chun

Electronics 2022, 11(18), 2947; https://doi.org/10.3390/electronics11182947 - 17 Sep 2022

Cited by 9 | Viewed by 2110

Abstract

This research proposes a methodology for the selection of input variables based on eXplainable AI (XAI) for energy consumption prediction. For this purpose, the energy consumption prediction model (R² = 0.871; MAE = 2.176; MSE = 9.870) was selected by collecting the [...] Read more.

This research proposes a methodology for the selection of input variables based on eXplainable AI (XAI) for energy consumption prediction. For this purpose, the energy consumption prediction model (R² = 0.871; MAE = 2.176; MSE = 9.870) was selected by collecting the energy data used in the building of a university in Seoul, Republic of Korea. Applying XAI to the results from the prediction model, input variables were divided into three groups by the expectation of the ranking-score (

F q^{v a r}

) (10 ≤ Strong, 5 ≤ Ambiguous < 10, and Weak < 5), according to their influence. As a result, the models considering the input variables of the Strong + Ambiguous group (R² = 0.917; MAE = 1.859; MSE = 6.639) or the Strong group (R² = 0.916; MAE = 1.816; MSE = 6.663) showed higher prediction results than other cases (p < 0.05 or 0.01). There were no statistically significant results between the Strong group and the Strong + Ambiguous group (R²: p = 0.408; MAE: p = 0.488; MSE: p = 0.478). This means that when considering the input variables of the Strong group (

F q^{v a r}

: Year = 14.8; E-Diff = 12.8; Hour = 11.0; Temp = 11.0; Surface-Temp = 10.4) determined by the XAI-based methodology, the energy consumption prediction model showed excellent performance. Therefore, the methodology proposed in this study is expected to determine a model that can accurately and efficiently predict energy consumption. Full article

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24 pages, 1279 KiB

Open AccessArticle

A Framework for the Classification and Evaluation of Game Mechanics for Virtual Reality Games

by Sara Vlahovic, Mirko Suznjevic and Lea Skorin-Kapov

Electronics 2022, 11(18), 2946; https://doi.org/10.3390/electronics11182946 - 17 Sep 2022

Cited by 2 | Viewed by 2586

Abstract

In broad terms, UX design is concerned with minimizing the workload neccessary for the user to interact with the system. In gaming, however, the system is supposed to provide a level of challenge to keep the player entertained, along with offering specific tools [...] Read more.

In broad terms, UX design is concerned with minimizing the workload neccessary for the user to interact with the system. In gaming, however, the system is supposed to provide a level of challenge to keep the player entertained, along with offering specific tools and mechanisms of interaction that are not commonly found across other use-cases. When talking about virtual reality (VR), numerous sources have discussed the optimization of interaction techniques, but there is a gap in research on the subject of gaming-specific VR interaction design, which we aimed to address in this paper. Focusing on the diversity of VR gaming, we introduced the term “interaction mechanics” and provided a taxonomy of interaction mechanics based on several criteria. Based on this taxonomy, we highlighted multiple target-related, task-related, and tool-related parameters that may influence the quality of interaction mechanics. Lastly, we presented the INTERACT framework, which was created to serve as a conceptual foundation for creating applications to be used as tools for user research, and used it to design an application aimed at facilitating the evaluation of interaction mechanics quality. Full article

(This article belongs to the Special Issue Immersive Quality of Experience Management and Evaluation)

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22 pages, 2802 KiB

Open AccessArticle

A Knowledge Base Technique for Detecting Multiple High-Speed Serial Interface Synchronization Errors in Multiprocessor-Based Real-Time Embedded Systems

by Sabeen Masood, Shoab Ahmed Khan, Ali Hassan and Fatima Khalique

Electronics 2022, 11(18), 2945; https://doi.org/10.3390/electronics11182945 - 17 Sep 2022

Viewed by 1361

Abstract

The heterogeneity of the multiple processing elements (PEs) is a feature of real-time embedded systems. General-purpose processors and several embedded processors, as well as dedicated high-speed interfaces, are among these elements. Communication between the processors is among the most significant characteristics of developing [...] Read more.

The heterogeneity of the multiple processing elements (PEs) is a feature of real-time embedded systems. General-purpose processors and several embedded processors, as well as dedicated high-speed interfaces, are among these elements. Communication between the processors is among the most significant characteristics of developing such complex systems. Furthermore, synchronization is a common issue during interprocessor communication in embedded systems. Debugging and testing such systems is time-consuming, difficult, and laborious, with the majority of the complexities centered on debugging real-time interprocessor communication, such as synchronization in terms of timing and accuracy. While the hardware design features of heterogeneous multiprocessor real-time embedded systems have received a lot of attention, the design and development of software-based solutions still have the potential to be addressed. In particular, software-based testing becomes challenging due to interprocessor communication and the synchronization of real-time applications. A knowledge-based technique that aids in testing high-speed serial interfaces in multiprocessor-based real-time embedded systems is proposed that needs debugging in real time while an application is running. It is becoming much more important to test and validate these interfaces in real time as the demand for high data transmission rates increases. The presented work uses a technique to simulate, create and enhance the knowledge base used as correlation-based error detection that reduces the development time. The proposed technique helps in detecting synchronization-related errors that occur during communication among multiple high-speed serial interfaces. The presented work also lists a series of experiments to validate the effectiveness of the proposed technique. The results show that the presented techniques are effective for error identification in real-time embedded systems. Full article

(This article belongs to the Special Issue Embedded Systems: Fundamentals, Design and Practical Applications)

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