bluuebunny/crossref_metadata_2025 huggingface dataset:
Semantic Data Mining in Ubiquitous Sensing: A Survey
Authors: Nalepa Grzegorz J. , Bobek Szymon , Kutt Krzysztof , Atzmueller Martin
Published: June 2021

Mining ubiquitous sensing data is important but also challenging, due to many factors, such as heterogeneous large-scale data that is often at various levels of abstraction. This also relates particularly to the important aspects of the explainability and interpretability of the applied models and their results, and thus ultimately to the outcome of the data mining process. With this, in general, the inclusion of domain knowledge leading towards semantic data mining approaches is an emerging and important research direction. This article aims to survey relevant works in these areas, focusing on semantic data mining approaches and methods, but also on selected applications of ubiquitous sensing in some of the most prominent current application areas. Here, we consider in particular: (1) environmental sensing; (2) ubiquitous sensing in industrial applications of artificial intelligence; and (3) social sensing relating to human interactions and the respective individual and collective behaviors. We discuss these in detail and conclude with a summary of this emerging field of research. In addition, we provide an outlook on future directions for semantic data mining in ubiquitous sensing contexts.
Hierarchical Tactile Sensation Integration from Prosthetic Fingertips Enables Multi-Texture Surface Recognition
Authors: Abd Moaed A. , Paul Rudy , Aravelli Aparna , Bai Ou , Lagos Leonel , Lin Maohua , Engeberg Erik D.
Published: June 2021

Multifunctional flexible tactile sensors could be useful to improve the control of prosthetic hands. To that end, highly stretchable liquid metal tactile sensors (LMS) were designed, manufactured via photolithography, and incorporated into the fingertips of a prosthetic hand. Three novel contributions were made with the LMS. First, individual fingertips were used to distinguish between different speeds of sliding contact with different surfaces. Second, differences in surface textures were reliably detected during sliding contact. Third, the capacity for hierarchical tactile sensor integration was demonstrated by using four LMS signals simultaneously to distinguish between ten complex multi-textured surfaces. Four different machine learning algorithms were compared for their successful classification capabilities: K-nearest neighbor (KNN), support vector machine (SVM), random forest (RF), and neural network (NN). The time-frequency features of the LMSs were extracted to train and test the machine learning algorithms. The NN generally performed the best at the speed and texture detection with a single finger and had a 99.2 ± 0.8% accuracy to distinguish between ten different multi-textured surfaces using four LMSs from four fingers simultaneously. The capability for hierarchical multi-finger tactile sensation integration could be useful to provide a higher level of intelligence for artificial hands.
Design of a Single-Layer ±45° Dual-Polarized Directional Array Antenna for Millimeter Wave Applications
Authors: Lv Qinyi , Yang Yu-Hang , Zhou Shi-Gang , Shao Chan , Zhou Deyun , Sim Chow-Yen-Desmond
Published: June 2021

A single-layer ±45° dual-polarized directional array antenna for millimeter wave (mm-wave) applications is designed in this communication. Based on the theory of orthogonal circularly polarized (CP) wave multiplexing, two ports of a series-fed dual CP array are fed with equal amplitudes, and the array can radiate a linearly polarized wave with ±45° polarization orientations through the adjustment of the feeding phase difference. As the two ports of the series-fed array are simultaneously excited, the antenna can achieve directional radiation. In addition, the cross-polarization level of the array can be effectively suppressed by placing two series-fed arrays side by side. A prototype of the designed array antenna operating at 30 GHz is fabricated and measured; the working bandwidth of the proposed antenna is approximately 3.5%. Owing to its simple structure and directional radiation, the proposed antenna array is a competitive candidate for mm-wave applications.
Concurrent Validity and Reliability of Manual Versus Specific Device Transcostal Measurements for Breathing Diaphragm Thickness by Ultrasonography in Lumbopelvic Pain Athletes
Authors: Marugán-Rubio Daniel , Chicharro Jose L. , Becerro-de-Bengoa-Vallejo Ricardo , Losa-Iglesias Marta Elena , Rodríguez-Sanz David , Vicente-Campos Davinia , Dávila-Sánchez Gabriel J. , Calvo-Lobo César
Published: June 2021

The use of rehabilitative ultrasound imaging (RUSI) to evaluate diaphragm thickness during breathing in athletes who suffer from non-specific lumbopelvic pain presents some measurement errors. The purpose of this study was to evaluate intra- and inter-sessions, intra- and inter-rater reliabilities, and concurrent validity of diaphragm thickness measurements during breathing using transcostal RUSI with a novel thoracic orthotic device that was used to fix the US probe versus those measurements obtained using manual fixation. A total of 37 athletes with non-specific lumbopelvic pain were recruited. Intra- (same examiner) and inter-rater (two examiners) and intra- (same day) and inter-session (alternate days) reliabilities were analyzed. All measurements were obtained after manual probe fixation and after positioning the thoracic orthotic device to fix the US probe in order to correctly correlate both measurement methods. Both left and right hemi-diaphragm thickness measurements were performed by transcostal RUSI at maximum inspiration, expiration, and the difference between the two parameters during relaxed breathing. Intra-class correlation coefficients (ICC), standard errors of measurement (SEM), minimum detectable changes (MCD), systematic errors, and correlations (r) were assessed. Orthotic device probe fixation showed excellent reliability (ICC = 0.852–0.996, SEM = 0.0002–0.054, and MDC = 0.002–0.072), and most measurements did not show significant systematic errors (p > 0.05). Despite manual probe fixation with a reliability ranging from good to excellent (ICC = 0.714–0.997, SEM = 0.003–0.023, and MDC = 0.008–0.064 cm), several significant systematic measurement errors (p < 0.05) were found. Most significant correlations between both orthotic device and manual probe fixation methods were moderate (r = 0.486–0.718; p < 0.05). Bland–Altman plots indicated adequate agreement between both measurement methods according to the agreement limits. The proposed novel thoracic orthotic device may allow ultrasound probe fixation to provide valid and reliable transcostal RUSI measurements of diaphragmatic thickness during relaxed breathing thus reducing some measurement errors and avoiding systematic measurement errors. It may be advisable to measure diaphragm thickness and facilitate visual biofeedback with respect to diaphragm re-education during normal breathing in athletes with non-specific lumbopelvic pain.
Reliability and Validity of the Polhemus Liberty System for Upper Body Segment and Joint Angular Kinematics of Elite Golfers
Authors: Wheare Matilda Jane , Nelson Maximillian J. , Lumsden Ryan , Buttfield Alec , Crowther Robert George
Published: June 2021

Golf swing analysis is common in both recreational and professional levels where players are searching for improvements in shot accuracy and distance. The use of motion analysis systems such as the portable Polhemus Liberty system is gaining interest by coaches and players; however, to date, no research has examined the usefulness of the Polhemus Liberty system for golf swing analysis. Therefore, the purpose of this study was to determine the reliability of the Polhemus Liberty system and validity compared to the VICON Nexus motion analysis system when assessing segment (pelvis and thorax) and joint (shoulder, elbow and wrist) angular kinematics during a golf swing at key events (address, top of backswing and impact). Fifteen elite amateur/professional golfers performed ten golf swing trials within specified bounds using their 5-iron club. Reliability was assessed using interclass coefficient, effect size and t-test statistics by all participants completing two separate testing sessions on separate days following the same experimental protocol. Validity was assessed using effect size, Pearson correlation and t-test statistics by comparing swings captured using both Polhemus Liberty and VICON Nexus concurrently. Results demonstrated no difference in ball outcome results using the Trackman launch monitor (P > 0.05) and that the Polhemus Liberty system was reliable across the two sessions for all segment (pelvis and thorax) and joint (lead shoulder (gleno-humeral joint), elbow and wrist) angular kinematics (P > 0.05). Validity analysis showed that the Polhemus Liberty system for the segments (pelvis and thorax) and joints (lead shoulder and wrist) were different compared to the VICON Nexus data at key events during the golf swing. Although validity could not be confirmed against VICON Nexus modeling, the Polhemus Liberty system may still be useful for golf swing analysis across training sessions. However, caution should be applied when comparing data from the system to published research data using different motion analysis methods.
An Autonomous Robot-Aided Auditing Scheme for Floor Cleaning
Authors: Pathmakumar Thejus , Kalimuthu Manivannan , Elara Mohan Rajesh , Ramalingam Balakrishnan
Published: June 2021

Cleaning is an important factor in most aspects of our day-to-day life. This research work brings a solution to the fundamental question of “How clean is clean” by introducing a novel framework for auditing the cleanliness of built infrastructure using mobile robots. The proposed system presents a strategy for assessing the quality of cleaning in a given area and a novel exploration strategy that facilitates the auditing in a given location by a mobile robot. An audit sensor that works by the “touch and inspect” analogy that assigns an audit score corresponds to its area of inspection has been developed. A vision-based dirt-probability-driven exploration is proposed to empower a mobile robot with an audit sensor on-board to perform auditing tasks effectively. The quality of cleaning is quantified using a dirt density map representing location-wise audit scores, dirt distribution pattern obtained by kernel density estimation, and cleaning benchmark score representing the extent of cleanliness. The framework is realized in an in-house developed audit robot to perform the cleaning audit in indoor and semi-outdoor environments. The proposed method is validated by experiment trials to estimate the cleanliness in five different locations using the developed audit sensor and dirt-probability-driven exploration.
Multi-Aspect SAR Target Recognition Based on Prototypical Network with a Small Number of Training Samples
Authors: Zhao Pengfei , Huang Lijia , Xin Yu , Guo Jiayi , Pan Zongxu
Published: June 2021

At present, synthetic aperture radar (SAR) automatic target recognition (ATR) has been deeply researched and widely used in military and civilian fields. SAR images are very sensitive to the azimuth aspect of the imaging geomety; the same target at different aspects differs greatly. Thus, the multi-aspect SAR image sequence contains more information for classification and recognition, which requires the reliable and robust multi-aspect target recognition method. Nowadays, SAR target recognition methods are mostly based on deep learning. However, the SAR dataset is usually expensive to obtain, especially for a certain target. It is difficult to obtain enough samples for deep learning model training. This paper proposes a multi-aspect SAR target recognition method based on a prototypical network. Furthermore, methods such as multi-task learning and multi-level feature fusion are also introduced to enhance the recognition accuracy under the case of a small number of training samples. The experiments by using the MSTAR dataset have proven that the recognition accuracy of our method can be close to the accruacy level by all samples and our method can be applied to other feather extraction models to deal with small sample learning problems.
A Pilot Study to Validate a Wearable Inertial Sensor for Gait Assessment in Older Adults with Falls
Authors: García-Villamil Guillermo , Neira-Álvarez Marta , Huertas-Hoyas Elisabet , Ramón-Jiménez Antonio , Rodríguez-Sánchez Cristina
Published: June 2021

The high prevalence of falls and the enormous impact they have on the elderly population is a cause for concern. We aimed to develop a walking-monitor gait pattern (G-STRIDE) for older adults based on a 6-axis inertial measurement (IMU) with the application of pedestrian dead reckoning algorithms and tested its structural and clinical validity. A cross-sectional case–control study was conducted with 21 participants (11 fallers and 10 non-fallers). We measured gait using an IMU attached to the foot while participants walked around different grounds (indoor flooring, outdoor floor, asphalt, etc.). The G-STRIDE consisted of a portable inertial device that monitored the gait pattern and a mobile app for telematic clinical analysis. G-STRIDE made it possible to measure gait parameters under normal living conditions when walking without assessing the patient in the outpatient clinic. Moreover, we verified concurrent validity with convectional outcome measures using intraclass correlation coefficients (ICCs) and analyzed the differences between participants. G-STRIDE showed high estimation accuracy for the walking speed of the elderly and good concurrent validity compared to conventional measures (ICC = 0.69; p < 0.000). In conclusion, the developed inertial-based G-STRIDE can accurately classify older people with risk to fall with a significance as high as using traditional but more subjective clinical methods (gait speed, Timed Up and Go Test).
Event-Centered Data Segmentation in Accelerometer-Based Fall Detection Algorithms
Authors: Šeketa Goran , Pavlaković Lovro , Džaja Dominik , Lacković Igor , Magjarević Ratko
Published: June 2021

Automatic fall detection systems ensure that elderly people get prompt assistance after experiencing a fall. Fall detection systems based on accelerometer measurements are widely used because of their portability and low cost. However, the ability of these systems to differentiate falls from Activities of Daily Living (ADL) is still not acceptable for everyday usage at a large scale. More work is still needed to raise the performance of these systems. In our research, we explored an essential but often neglected part of accelerometer-based fall detection systems—data segmentation. The aim of our work was to explore how different configurations of windows for data segmentation affect detection accuracy of a fall detection system and to find the best-performing configuration. For this purpose, we designed a testing environment for fall detection based on a Support Vector Machine (SVM) classifier and evaluated the influence of the number and duration of segmentation windows on the overall detection accuracy. Thereby, an event-centered approach for data segmentation was used, where windows are set relative to a potential fall event detected in the input data. Fall and ADL data records from three publicly available datasets were utilized for the test. We found that a configuration of three sequential windows (pre-impact, impact, and post-impact) provided the highest detection accuracy on all three datasets. The best results were obtained when either a 0.5 s or a 1 s long impact window was used, combined with pre- and post-impact windows of 3.5 s or 3.75 s.
Indoor Positioning System Based on Global Positioning System Signals with Down- and Up-Converters in 433 MHz ISM Band
Authors: Uzun Abdulkadir , Ghani Firas Abdul , Ahmadi Najafabadi Amir Mohsen , Yenigün Hüsnü , Tekin İbrahim
Published: June 2021

In this paper, an indoor positioning system using Global Positioning System (GPS) signals in the 433 MHz Industrial Scientific Medical (ISM) band is proposed, and an experimental demonstration of how the proposed system operates under both line-of-sight and non-line-of-sight conditions on a building floor is presented. The proposed method is based on down-converting (DC) repeaters and an up-converting (UC) receiver. The down-conversion is deployed to avoid the restrictions on the use of Global Navigation Satellite Systems (GNSS) repeaters, to achieve higher output power, and to expose the GPS signals to lower path loss. The repeaters receive outdoor GPS signals at 1575.42 MHz (L1 band), down-convert them to the 433 MHz ISM band, then amplify and retransmit them to the indoor environment. The front end up-converter is combined with an off-the-shelf GPS receiver. When GPS signals at 433 MHz are received by the up-converting receiver, it then amplifies and up-converts these signals back to the L1 frequency. Subsequently, the off-the-shelf GPS receiver calculates the pseudo-ranges. The raw data are then sent from the receiver over a 2.4 GHz Wi-Fi link to a remote computer for data processing and indoor position estimation. Each repeater also has an attenuator to adjust its amplification level so that each repeater transmits almost equal signal levels in order to prevent jamming of the off-the-shelf GPS receiver. Experimental results demonstrate that the indoor position of a receiver can be found with sub-meter accuracy under both line-of-sight and non-line-of-sight conditions. The estimated position was found to be 54 and 98 cm away from the real position, while the 50% circular error probable (CEP) of the collected samples showed a radius of 3.3 and 4 m, respectively, for line-of-sight and non-line-of-sight cases.
Portable Interactive Pulse Tactile Recorder and Player System
Authors: Hsieh Tzu-Chieh , Wu Chien-Min , Tsai Cheng-Chung , Lo Wen-Chien , Wang Yu-Min , Smith Shana
Published: June 2021

Pulse palpation is an effective method for diagnosing arterial diseases. However, most pulse measurement devices use preconfigured pressures to collect pulse signals, and most pulse tactile simulators can only display standard or predefined pulse waveforms. Here, a portable interactive human pulse measurement and reproduction system was developed that allows users to take arbitrary pulses and experience realistic simulated pulse tactile feedback in real time by using their natural pulse-taking behaviors. The system includes a pulse tactile recorder and a pulse tactile player. Pulse palpation forces and vibrations can be recorded and realistically replayed for later tactile exploration and examination. To retain subtle but vital pulse information, empirical mode decomposition was used to decompose pulse waveforms into several intrinsic mode functions. Artificial neural networks were then trained based on intrinsic mode functions to determine the relationship between the driving signals of the pulse tactile player and the resulting vibration waveforms. Experimental results indicate that the average normalized root mean square error and the average R-squared values between the reproduced and original pulses were 0.0654 and 0.958 respectively, which indicate that the system can reproduce high-fidelity pulse tactile vibrations.
The Impact of Coil Position and Number on Wireless System Performance for Electric Vehicle Recharging
Authors: Mohamed Naoui , Aymen Flah , Issam Zaafouri , Bajaj Mohit , Ghoneim Sherif S. M. , Ahmed Mahrous
Published: June 2021

Recently, most transportation systems have used an integrated electrical machine in their traction scheme, resulting in a hybrid electrified vehicle. As a result, an energy source is required to provide the necessary electric power to this traction portion. However, this cannot be efficient without a reliable recharging method and a practical solution. This study discusses the wireless recharge solutions and tests the system’s effectiveness under various external and internal conditions. Moreover, the Maxwell tool is used in this research to provide a complete examination of the coils’ position, size, number, and magnetic flux evolution when the coils are translated. In addition, the mutual inductance for each of these positions is computed to determine the ideal conditions for employing the wireless recharge tool for every charging application. A thorough mathematical analysis is also presented, and the findings clearly demonstrate the relationship between the magnet flux and the various external conditions employed in this investigation.
Design and Implementation of a Position, Speed and Orientation Fuzzy Controller Using a Motion Capture System to Operate a Wheelchair Prototype
Authors: Callejas-Cuervo Mauro , González-Cely Aura Ximena , Bastos-Filho Teodiano
Published: June 2021

The design and implementation of an electronic system that involves head movements to operate a prototype that can simulate future movements of a wheelchair was developed here. The controller design collects head-movements data through a MEMS sensor-based motion capture system. The research was divided into four stages: First, the instrumentation of the system using hardware and software; second, the mathematical modeling using the theory of dynamic systems; third, the automatic control of position, speed, and orientation with constant and variable speed; finally, system verification using both an electronic controller test protocol and user experience. The system involved a graphical interface for the user to interact with it by executing all the controllers in real time. Through the System Usability Scale (SUS), a score of 78 out of 100 points was obtained from the qualification of 10 users who validated the system, giving a connotation of “very good”. Users accepted the system with the recommendation to improve safety by using laser sensors instead of ultrasonic range modules to enhance obstacle detection.
Numerical Analysis of 2-D Positioned, Indoor, Fuzzy-Logic, Autonomous Navigation System Based on Chromaticity and Frequency-Component Analysis of LED Light
Authors: Jeong Jae-Hoon , Park Kiwon
Published: June 2021

Topics concerning autonomous navigation, especially those related to positioning systems, have recently attracted increased research attention. The commonly available global positioning system (GPS) is unable to determine the positions of vehicles in GPS-shaded regions. To address this concern, this paper presents a fuzzy-logic system capable of determining the position of a moving robot in a GPS-shaded indoor environment by analyzing the chromaticity and frequency-component ratio of LED lights installed under the ceiling. The proposed system’s performance was analyzed by performing a MATLAB simulation of an indoor environment with obstacles. During the simulation, the mobile robot utilized a fuzzy autonomous navigation system with behavioral rules to approach targets successfully in a variety of indoor environments without colliding with obstacles. The robot utilized the x and y coordinates of the fuzzy positioning system. The results obtained in this study confirm the suitability of the proposed method for use in applications involving autonomous navigation of vehicles in areas with poor GPS-signal reception, such as in tunnels.
Ethanol Sensing Properties and First Principles Study of Au Supported on Mesoporous ZnO Derived from Metal Organic Framework ZIF-8
Authors: Kang Yanli , Zhang Lu , Wang Wenhao , Yu Feng
Published: June 2021

It is of great significance to develop ethanol sensors with high sensitivity and low detection temperature. Hence, we prepared Au-supported material on mesoporous ZnO composites derived from a metal-organic framework ZIF-8 for the detection of ethanol gas. The obtained Au/ZnO materials were characterized by X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), field emission scanning electron microscopy (SEM), field emission transmission electron microscopy (TEM) and nitrogen adsorption and desorption isotherms. The results showed that the Au/ZnO-1.0 sample maintains a three-dimensional (3D) dodecahedron structure with a larger specific surface area (22.79 m2 g−1) and has more oxygen vacancies. Because of the unique ZIF structure, abundant surface defects and the formation of Au-ZnO Schottky junctions, an Au/ZnO-1.0 sensor has a response factor of 37.74 for 100 ppm ethanol at 250 °C, which is about 6 times that of pure ZnO material. In addition, the Au/ZnO-1.0 sensor has good selectivity for ethanol. According to density functional theory (DFT) calculations, the adsorption energy of Au/ZnO for ethanol (−1.813 eV) is significantly greater than that of pure ZnO (−0.217 eV). Furthermore, the adsorption energy for ethanol is greater than that of other gases.
Whole-Body Movements Increase Arm Use Outcomes of Wrist-Worn Accelerometers in Stroke Patients
Authors: Regterschot Gerrit Ruben Hendrik , Selles Ruud W. , Ribbers Gerard M. , Bussmann Johannes B. J.
Published: June 2021

Wrist-worn accelerometers are often applied to measure arm use after stroke. They measure arm movements during all activities, including whole-body movements, such as walking. Whole-body movements may influence clinimetric properties of arm use measurements—however, this has not yet been examined. This study investigates to what extent arm use measurements with wrist-worn accelerometers are affected by whole-body movements. Assuming that arm movements during whole-body movements are non-functional, we quantify the effect of whole-body movements by comparing two methods: Arm use measured with wrist-worn accelerometers during all whole-body postures and movements (P&M method), and during sitting/standing only (sit/stand method). We have performed a longitudinal observational cohort study with measurements in 33 stroke patients during weeks 3, 12, and 26 poststroke. The P&M method shows higher daily paretic arm use outcomes than the sit/stand method (p < 0.001), the mean difference increased from 31% at week three to 41% at week 26 (p < 0.001). Differences in daily paretic arm use between methods are strongly related to daily walking time (r = 0.83–0.92). Changes in the difference between methods are strongly related to changes in daily walking time (r = 0.89). We show that not correcting arm use measurements for whole-body movements substantially increases arm use outcomes, thereby threatening the validity of arm use outcomes and measured arm use changes.
Electrospun Nickel Manganite (NiMn2O4) Nanocrystalline Fibers for Humidity and Temperature Sensing
Authors: Dojcinovic Milena P. , Vasiljevic Zorka Z. , Krstic Jugoslav B. , Vujancevic Jelena D. , Markovic Smilja , Tadic Nenad B. , Nikolic Maria Vesna
Published: June 2021

Nickel manganite nanocrystalline fibers were obtained by electrospinning and subsequent calcination at 400 °C. As-spun fibers were characterized by TG/DTA, Scanning Electron Microscopy and FT-IR spectroscopy analysis. X-ray diffraction and FT-IR spectroscopy analysis confirmed the formation of nickel manganite with a cubic spinel structure, while N2 physisorption at 77 K enabled determination of the BET specific surface area as 25.3 m2/g and (BJH) mesopore volume as 21.5 m2/g. The material constant (B) of the nanocrystalline nickel manganite fibers applied by drop-casting on test interdigitated electrodes on alumina substrate, dried at room temperature, was determined as 4379 K in the 20–50 °C temperature range and a temperature sensitivity of −4.95%/K at room temperature (25 °C). The change of impedance with relative humidity was monitored at 25 and 50 °C for a relative humidity (RH) change of 40 to 90% in the 42 Hzπ1 MHz frequency range. At 100 Hz and 25 °C, the sensitivity of 327.36 ± 80.12 kΩ/%RH was determined, showing that nickel manganite obtained by electrospinning has potential as a multifunctional material for combined humidity and temperature sensing.
An Online Data-Driven Fault Diagnosis Method for Air Handling Units by Rule and Convolutional Neural Networks
Authors: Liao Huanyue , Cai Wenjian , Cheng Fanyong , Dubey Swapnil , Rajesh Pudupadi Balachander
Published: June 2021

The stable operation of air handling units (AHU) is critical to ensure high efficiency and to extend the lifetime of the heating, ventilation, and air conditioning (HVAC) systems of buildings. In this paper, an online data-driven diagnosis method for AHU in an HVAC system is proposed and elaborated. The rule-based method can roughly detect the sensor condition by setting threshold values according to prior experience. Then, an efficient feature selection method using 1D convolutional neural networks (CNNs) is proposed for fault diagnosis of AHU in HVAC systems according to the system’s historical data obtained from the building management system. The new framework combines the rule-based method and CNNs-based method (RACNN) for sensor fault and complicated fault. The fault type of AHU can be accurately identified via the offline test results with an accuracy of 99.15% and fast online detection within 2 min. In the lab, the proposed RACNN method was validated on a real AHU system. The experimental results show that the proposed RACNN improves the performance of fault diagnosis.
Automatic Actionable Information Processing and Trust Management towards Safer Internet of Things
Authors: Janiszewski Marek , Felkner Anna , Lewandowski Piotr , Rytel Marcin , Romanowski Hubert
Published: June 2021

The security of the Internet of Things (IoT) is a very important aspect of everyday life for people and industries, as well as hospitals, military, households and cities. Unfortunately, this topic is still too little researched and developed, which results in exposing users of Internet of Things to possible threats. One of the areas which should be addressed is the creation of a database of information about vulnerabilities and exploits in the Internet of Things; therefore, the goal of our activities under the VARIoT (Vulnerability and Attack Repository for IoT) project is to develop such a database and make it publicly available. The article presents the results of our research aimed at building this database, i.e., how the information about vulnerabilities is obtained, standardized, aggregated and correlated as well as the way of enhancing and selecting IoT related data. We have obtained and proved that existing databases provide various scopes of information and because of that a single and most comprehensive source of information does not exist. In addition, various sources present information about a vulnerability at different times—some of them are faster than others, and the differences in publication dates are significant. The results of our research show that aggregation of information from various sources can be very beneficial and has potential to enhance actionable value of information. We have also shown that introducing more sophisticated concepts, such as trust management and metainformation extraction based on artificial intelligence, could ensure a higher level of completeness of information as well as evaluate the usefulness and reliability of data.
Psychophysiological Response According to the Greenness Index of Subway Station Space
Authors: Kim Won-Ji , Lee Tae-Kyung
Published: June 2021

This study proposed a plan for implementing a pleasant and healthy indoor landscape in subway station space. To this end, it established a 3D landscape model of the subway interior by reviewing previous studies on indoor landscape and the greenness index of indoor spaces. Moreover, it investigated and analyzed psychophysiological responses of users to environmental indoor landscape design in subway station space. Subway stations were classified as underground subway stations and ground subway stations according to the presence of natural light inflow. The greenness index of indoor spaces was also divided into four types of 0%, 10%, 15%, and 20%. Through this process, eight 3D landscape models of the subway interior were implemented. In addition, this study investigated psychophysiological responses of 60 male and female adults in their 20 s and 30 s using the models implemented. The investigation result was analyzed based on a frequency analysis, the χ2 test, T-test, one-way analysis of variance, and multidimensional scaling, which were performed in SPSS Statistics 25. The results of this study can be summarized as follows. First, physiological responses of research subjects were analyzed based on their prefrontal α wave asymmetric values. The analytic result showed that the environment where interior landscape was adopted produced more positive effects than the environment where interior landscape was not adopted. Second, psychological responses of research subjects were examined based on their greenness index preference, awareness of interior landscape area, attention restoration effect, and space images. The analytic result indicated that, among eight 3D landscape models of the subway interior, they preferred the model with the greenness index of 15% for underground subway stations. In addition, they preferred the model with the greenness index of 10% the most for ground subway stations.
A CMOS Optoelectronic Receiver IC with an On-Chip Avalanche Photodiode for Home-Monitoring LiDAR Sensors
Authors: Joo Ji-Eun , Lee Myung-Jae , Park Sung Min
Published: June 2021

This paper presents an optoelectronic receiver (Rx) IC with an on-chip avalanche photodiode (APD) realized in a 0.18-μm CMOS process for the applications of home-monitoring light detection and ranging (LiDAR) sensors, where the on-chip CMOS P+/N-well APD was implemented to avoid the unwanted signal distortion from bondwires and electro-static discharge (ESD) protection diodes. Various circuit techniques are exploited in this work, such as the feedforward transimpedance amplifier for high gain, and a limiting amplifier with negative impedance compensation for wide bandwidth. Measured results demonstrate 93.4-dBΩ transimpedance gain, 790-MHz bandwidth, 12-pA/√Hz noise current spectral density, 6.74-μApp minimum detectable signal that corresponds to the maximum detection range of 10 m, and 56.5-mW power dissipation from a 1.8-V supply. This optoelectronic Rx IC provides a potential for a low-cost low-power solution in the applications of home-monitoring LiDAR sensors.
Classification of Space Objects by Using Deep Learning with Micro-Doppler Signature Images
Authors: Jung Kwangyong , Lee Jae-In , Kim Nammoon , Oh Sunjin , Seo Dong-Wook
Published: June 2021

Radar target classification is an important task in the missile defense system. State-of-the-art studies using micro-doppler frequency have been conducted to classify the space object targets. However, existing studies rely highly on feature extraction methods. Therefore, the generalization performance of the classifier is limited and there is room for improvement. Recently, to improve the classification performance, the popular approaches are to build a convolutional neural network (CNN) architecture with the help of transfer learning and use the generative adversarial network (GAN) to increase the training datasets. However, these methods still have drawbacks. First, they use only one feature to train the network. Therefore, the existing methods cannot guarantee that the classifier learns more robust target characteristics. Second, it is difficult to obtain large amounts of data that accurately mimic real-world target features by performing data augmentation via GAN instead of simulation. To mitigate the above problem, we propose a transfer learning-based parallel network with the spectrogram and the cadence velocity diagram (CVD) as the inputs. In addition, we obtain an EM simulation-based dataset. The radar-received signal is simulated according to a variety of dynamics using the concept of shooting and bouncing rays with relative aspect angles rather than the scattering center reconstruction method. Our proposed model is evaluated on our generated dataset. The proposed method achieved about 0.01 to 0.39% higher accuracy than the pre-trained networks with a single input feature.
Graphene Oxide Nanoparticles Modified Paper Electrode as a Biosensing Platform for Detection of the htrA Gene of O. tsutsugamushi
Authors: Kala Deepak , Sharma Tarun Kumar , Gupta Shagun , Verma Vivek , Thakur Atul , Kaushal Ankur , Trukhanov Alex V. , Trukhanov Sergei V.
Published: June 2021

The unique structural and electrochemical properties of graphene oxide (GO) make it an ideal material for the fabrication of biosensing devices. Therefore, in the present study, graphene oxide nanoparticles modified paper electrodes were used as a low-cost matrix for the development of an amperometric DNA sensor. The graphene oxide was synthesized using the modified hummers method and drop cast on a screen-printed paper electrode (SPPE) to enhance its electrochemical properties. Further, the GO/SPPE electrode was modified with a 5′NH2 labeled ssDNA probe specific to the htrA gene of Orientia tsutsugamushi using carbodiimide cross-linking chemistry. The synthesized GO was characterized using UV-Vis, FTIR, and XRD. The layer-by-layer modification of the paper electrode was monitored via FE-SEM, cyclic voltammetry, and electrochemical impedance spectroscopy (EIS). The sensor response after hybridization with single-stranded genomic DNA (ssGDNA) of O. tsutsugamushi was recorded using differential pulse voltammetry (DPV). Methylene blue (1 mM in PBS buffer, pH 7.2) was used as a hybridization indicator and [Fe(CN)6]−3/−4 (2.5 mM in PBS buffer, pH 7.2) as a redox probe during electrochemical measurements. The developed DNA sensor shows excellent sensitivity (1228.4 µA/cm2/ng) and LOD (20 pg/µL) for detection of O. tsutsugamushi GDNA using differential pulse voltammetry (DPV).
Energy-Efficient Packet Forwarding Scheme Based on Fuzzy Decision-Making in Underwater Sensor Networks
Authors: Pabani Jitander Kumar , Luque-Nieto Miguel-Ángel , Hyder Waheeduddin , Otero Pablo
Published: June 2021

Underwater Wireless Sensor Networks (UWSNs) are subjected to a multitude of real-life challenges. Maintaining adequate power consumption is one of the critical ones, for obvious reasons. This includes proper energy consumption due to nodes close to and far from the sink node (gateway), which affect the overall energy efficiency of the system. These wireless sensors gather and route the data to the onshore base station through the gateway at the sea surface. However, finding an optimum and efficient path from the source node to the gateway is a challenging task. The common reasons for the loss of energy in existing routing protocols for underwater are (1) a node shut down due to battery drainage, (2) packet loss or packet collision which causes re-transmission and hence affects the performance of the system, and (3) inappropriate selection of sensor node for forwarding data. To address these issues, an energy efficient packet forwarding scheme using fuzzy logic is proposed in this work. The proposed protocol uses three metrics: number of hops to reach the gateway node, number of neighbors (in the transmission range of a node) and the distance (or its equivalent received signal strength indicator, RSSI) in a 3D UWSN architecture. In addition, the performance of the system is also tested with adaptive and non-adaptive transmission ranges and scalable number of nodes to see the impact on energy consumption and number of hops. Simulation results show that the proposed protocol performs better than other existing techniques or in terms of parameters used in this scheme.
Advances in Electrical Source Imaging: A Review of the Current Approaches, Applications and Challenges
Authors: Zorzos Ioannis , Kakkos Ioannis , Ventouras Errikos M. , Matsopoulos George K.
Published: June 2021

Brain source localization has been consistently implemented over the recent years to elucidate complex brain operations, pairing the high temporal resolution of the EEG with the high spatial estimation of the estimated sources. This review paper aims to present the basic principles of Electrical source imaging (ESI) in the context of the recent progress for solving the forward and the inverse problems, and highlight the advantages and limitations of the different approaches. As such, a synthesis of the current state-of-the-art methodological aspects is provided, offering a complete overview of the present advances with regard to the ESI solutions. Moreover, the new dimensions for the analysis of the brain processes are indicated in terms of clinical and cognitive ESI applications, while the prevailing challenges and limitations are thoroughly discussed, providing insights for future approaches that could help to alleviate methodological and technical shortcomings.
Vital Conjunctures in Compound Crises: Conceptualising Young People’s Education Trajectories in Protracted Displacement in Jordan and Lebanon
Authors: Jordan Zoë , Brun Cathrine
Published: June 2021

This paper emerges out of a study with 293 young people (Syrians, Palestinians and nationals) living in contexts of compound crises and protracted displacement in Jordan and Lebanon. In the paper, we discuss how young people’s education trajectories can be conceptualised, operationalised and studied. We synthesise different approaches to understanding and analysing such trajectories into a framework that captures the intricate and multi-directional ways that young people navigate towards uncertain futures. The framework on multi-directional trajectories takes its starting point from an understanding of Victoria Browne’s ‘lived time’, captured through how different temporalities come together in one person’s story. After presenting our framework and the context in the first part of the paper, the second part applies the framework to analyse the ‘vital conjuncture’ of leaving education. By analysing leaving education as lived time, we create nuanced insights into how this vital conjuncture can be understood to shape young peoples’ trajectories. In conclusion, we discuss the value of understanding trajectories as lived time by illuminating how young people experience and navigate their education trajectories.
Intersectional Gaps in Self-Efficacy among Post-Graduate Students in International Renewable-Energy Programs: The Role of Maternal Employment
Authors: Corsi Marcella , Zacchia Giulia , Zuazu Izaskun
Published: June 2021

Relatively little empirical research has analyzed the sources of students’ self-perceptions outside the US and Europe, and in new fields of study like renewable energy. This paper aims at filling this gap by identifying differences in self-efficacy levels of post-graduate students in Erasmus+ capacity-building programs on renewable energy in Argentinian and Guatemalan universities. We analyzed a sample of 43 students to test intersectional differences in self-efficacy, looking at students’ gender, country of origin, and maternal employment. Using the New General Self-Efficacy scale, we performed the t-test to compare mean differences in self-efficacy, and one-way and two-way ANOVA tests to check the consistency of the results. Our estimates did not show significant gender gaps in self-efficacy among renewable-energy post-graduate students, but they did uncover relevant country differences in mean self-efficacy levels, mainly due to differences in socio-economic indicators and gender norms between the two countries analyzed. Moreover, we found a mediating role of maternal employment in cross-country self-efficacy differences, whereas the characteristics of fathers appeared uninfluential. We conclude by stressing the importance of intersectional analysis in terms of country of origin, family backgrounds, and gender norms to increase knowledge about differences in self-efficacy of students.
Effects of Moderate- versus Mixed-Intensity Training on VO2peak in Young Well-Trained Rowers
Authors: Kirchenberger Timo , Ketelhut Sascha , Ketelhut Reinhard G.
Published: June 2021

The effects of moderate-intensity continuous training (MICT) and a combination of MICT and high-intensity interval training (HIIT) on rowing performance and VO2peak were investigated in young athletes. Seventeen well-trained rowers (aged 15 ± 1.3 years) were randomly allocated to an intervention (IG) (n = 10) and control group (CG) (n = 7). During 8 weeks, both groups took part in the regular rowing training (3×/week MICT, 70–90 min, 65–70% of HRpeak + 2×/week resistance training). The IG completed an additional high-intensity interval training twice weekly (2 × 4 × 2 min at ≈95% of HRpeak, 60 s rest). Instead of the HIIT, the CG completed two more MICT sessions (70–90 min, 65–70% of HRpeak). Before and after the intervention, a 2000 m time trial and an exercise test were performed. The IG showed a significant improvement (p = 0.001) regarding the absolute rowing time in the graded exercise test. Furthermore, the intervention group showed a significant increase in relative VO2peak (p = 0.023), a significant increase in absolute VO2peak (p = 0.036), and a significant improvement in the 2000 m time trail (p = 0.003). No significant changes could be detected in the CG. The interaction effects were not significant. A mixed-intensity training, including HIIT, was beneficial on rowing performance and VO2peak in highly trained athletes.
Sprint and Jump Mechanical Profiles in Academy Rugby League Players: Positional Differences and the Associations between Profiles and Sprint Performance
Authors: Nicholson Ben , Dinsdale Alex , Jones Ben , Till Kevin
Published: June 2021

This cross-sectional study evaluated the sprint and jump mechanical profiles of male academy rugby league players, the differences between positions, and the associations between mechanical profiles and sprint performance. Twenty academy rugby league players performed 40-m sprints and squat jumps at increasing loads (0–80 kg) to determine individual mechanical (force-velocity-power) and performance variables. The mechanical variables (absolute and relative theoretical maximal force-velocity-power, force-velocity linear relationship, and mechanical efficiency) were determined from the mechanical profiles. Forwards had significantly (p < 0.05) greater vertical and horizontal force, momentum but jumped lower (unloaded) and were slower than backs. No athlete presented an optimal jump profile. No associations were found between jump and sprint mechanical variables. Absolute theoretical maximal vertical force significantly (p < 0.05) correlated (r = 0.71–0.77) with sprint momentum. Moderate (r = −0.47) to near-perfect (r = 1.00) significant associations (p < 0.05) were found between sprint mechanical and performance variables. The largest associations shifted from maximum relative horizontal force-power generation and application to maximum velocity capabilities and force application at high velocities as distance increased. The jump and sprint mechanical profiles appear to provide distinctive and highly variable information about academy rugby league players’ sprint and jump capacities. Associations between mechanical variables and sprint performance suggest horizontal and vertical profiles differ and should be trained accordingly.