bluuebunny/crossref_metadata_2025 huggingface dataset:
Electrospun Sound-Absorbing Nanofibrous Webs from Recycled Poly(vinyl butyral)
Authors: Filip Petr , Sedlacek Tomas , Peer Petra , Juricka Martin
Published: November 2022

The amount of poly(vinyl butyral) (PVB) foils added to car windscreens to suppress glass shattering represents a huge worldwide volume of the material, and once a vehicle is end-of-life it also becomes a significance contributor to landfill. The recycling of PVB materials from windscreens has been expensive and despite improvements in recycling technologies, the landfill burden still increases. However, an increase in oil prices can shift the economic balance and stimulates the possible applicability of recycled PVB. As PVB is a relatively easy electrospinnable material, it is shown that nanofibrous mats produced from recycled PVB blends in ethanol exhibit very good sound-absorbing properties. To achieve an optimal composition between virgin and recycled PVB blends, a series of their ratios was consecutively characterized using various techniques (rheometry, SEM, FTIR, DSC, TGA, DMA, an impedance tube for determining sound absorbance). The best result was obtained with two wt. portions of 8 wt.% solution of virgin PVB in ethanol and one wt. portion of 12 wt.% solution of recycled PVB in ethanol.
Fabrication of a Polybutylene Succinate (PBS)/Polybutylene Adipate-Co-Terephthalate (PBAT)-Based Hybrid System Reinforced with Lignin and Zinc Nanoparticles for Potential Biomedical Applications
Authors: Mtibe Asanda , Hlekelele Lerato , Kleyi Phumelele E. , Muniyasamy Sudhakar , Nomadolo Nomvuyo E. , Ofosu Osei , Ojijo Vincent , John Maya J.
Published: November 2022

Polybutylene adipate-co-terephthalate (PBAT) was used in an effort to improve the properties of polybutylene succinate (PBS). The resultant blend consisting of PBS/PBAT (70/30) was reinforced with lignin at different loadings (5 to 15 wt.%) and zinc (ZnO) nanoparticles (1.5 wt.%). Hot melt extrusion and injection moulding were used to prepare the hybrid composites. The mechanical, thermal, physical, self-cleaning, and antimicrobial properties of the resultant hybrid composites were investigated. The transmission electron microscopy (TEM) results confirmed that ZnO was successfully prepared with average diameters of 80 nm. Fourier transform infrared (FTIR) spectroscopy and X-ray diffraction (XRD) confirmed that there were interactions between the fillers and the blend. The tensile strength and elongation at the break of the resultant materials decreased with increasing the loadings, while the tensile modulus showed the opposite trend. The melting behaviour of the blend was practically unaffected by incorporating lignin and ZnO nanoparticles. In addition, the incorporation of fillers reduced the thermal stability of the materials. Furthermore, the incorporation of ZnO nanoparticles introduced photocatalytic properties into the polymer blend, rendering it to be a functional self-cleaning material and enhancing its antimicrobial activities.
Selection and Optimization Mechanism of the Lower Return Roadway Layout in the near Residual Coal Pillar Area
Authors: Wang Xiao-He , Zhang Hao-Hao , Wu Zheng , Li Xiao-Long , Sui Yi , Gao Ruo-Qi
Published: November 2022

Background: To optimize the layout position of the residual coal pillar return roadway when mining a close coal seam group and to clarify the optimization mechanism, a roadway optimization layout analysis was conducted on the Tashan coal mine. Methods: Surface displacement monitoring was conducted using field tests, and the main stress magnitude, plastic zone morphology, deformation variables, and connectivity between the plastic zone of the roadway and the plastic zone of the residual coal pillar were analyzed at different locations with the help of FLAC3D numerical simulation software. Results: It was found that, in the process of close coal seam group mining, the residual coal pillar of the overlying coal seam seriously affects the stress state and plastic zone distribution of the lower coal seam roadway. The roadway is arranged in a position that is relatively far away from the residual coal pillar, which could reduce the stress influence of the residual coal pillar on the roadway and guarantee the stability of the roadway. Conclusion: Since the Tashan Mine uses the top release method for mining, the stability of the roadway can be better ensured by placing the roadway in the middle and lower regions of the coal seam and using the layout method to retain small coal pillars.
Investigation of Impulse and Continuous Discharge Characteristics of Large-Capacity Lithium-Ion Batteries
Authors: Kuchak Sergey V. , Brovanov Sergey V.
Published: November 2022

Lithium-ion batteries are one of the most popular and efficient energy storage devices. In this paper, the characteristics of high-capacity lithium-iron-phosphate batteries during the impulse and long-term operation modes of batteries with different levels of the discharge current are considered. A modified DP-model is proposed. The novelty of the model is the possibility to calculate the activation polarization parameters for different discharge currents. The state of charge is estimated using a high-order polynomial. Based on the developed model, transient processes with rapid load changes and the dependence of the battery voltage on the state of charge were obtained. Here, the model is intended to be used for the design of energy storage systems. The results showed that the DP-model is reliable under the tested conditions and can be used for the considered application.
Adaptive Pincer Grasping of Soft Pneumatic Grippers Based on Object Stiffness for Modellable and Controllable Grasping Quality
Authors: Sithiwichankit Chaiwuth , Chancharoen Ratchatin
Published: November 2022

In this study, adaptive pincer grasping of soft pneumatic grippers (SPGs) is considered, and we propose how the performance of soft pneumatic actuators (SPAs) and the stiffness of grasped objects can be accounted for in modeling and control. The grasping kinetics was analyzed. The connection between grasping quality and SPA performance is discussed. We also devised a subjective definition of grasping quality due to SPA performance. A modeling technique was established, which makes dominant factors of grasping quality due to the SPA performance predictable over the gripper input. Later, a control architecture was developed. This architecture demonstrates how the grasping is implemented. The modeling technique was used to forecast grasping quality due to the SPA performance and its factors. An experiment was conducted to obtain actual results. The predicted and actual results were correspondingly compared. The results show minute deviation, thereby validating the reliability of the grasping. This study clarifies the association between grasping quality and SPA performance and contributes an advancement toward modellable and controllable task-level variables, such as grasping quality, in SPG pincer grasping.
Deep Learning-Based Computer-Aided Diagnosis (CAD): Applications for Medical Image Datasets
Authors: Kadhim Yezi Ali , Khan Muhammad Umer , Mishra Alok
Published: November 2022

Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the best optimal features while reducing the amount of data. Lastly, diagnosis prediction (classification) is achieved using learnable classifiers. The novel framework for the extraction and selection of features is based on deep learning, auto-encoder, and ACO. The performance of the proposed approach is evaluated using two medical image datasets: chest X-ray (CXR) and magnetic resonance imaging (MRI) for the prediction of the existence of COVID-19 and brain tumors. Accuracy is used as the main measure to compare the performance of the proposed approach with existing state-of-the-art methods. The proposed system achieves an average accuracy of 99.61% and 99.18%, outperforming all other methods in diagnosing the presence of COVID-19 and brain tumors, respectively. Based on the achieved results, it can be claimed that physicians or radiologists can confidently utilize the proposed approach for diagnosing COVID-19 patients and patients with specific brain tumors.
Secure Vehicular Platoon Management against Sybil Attacks
Authors: Junaidi Danial Ritzuan , Ma Maode , Su Rong
Published: November 2022

The capacity of highways has been an ever-present constraint in the 21st century, bringing about the issue of safety with greater likelihoods of traffic accidents occurring. Furthermore, recent global oil prices have inflated to record levels. A potential solution lies in vehicular platooning, which has been garnering attention, but its deployment is uncommon due to cyber security concerns. One particular concern is a Sybil attack, by which the admission of fake virtual vehicles into the platoon allows malicious actors to wreak havoc on the platoon itself. In this paper, we propose a secure management scheme for platoons that can protect major events that occur in the platoon operations against Sybil attacks. Both vehicle identity and message exchanged are authenticated by adopting key exchange, digital signature and encryption schemes based on elliptic curve cryptography (ECC). Noteworthy features of the scheme include providing perfect forward secrecy and both group forward and backward secrecy to preserve the privacy of vehicles and platoons. Typical malicious attacks such as replay and man-in-the-middle attacks for example can also be resisted. A formal evaluation of the security functionality of the scheme by the Canetti–Krawczyk (CK) adversary and the random oracle model as well as a brief computational verification by CryptoVerif were conducted. Finally, the performance of the proposed scheme was evaluated to show its time and space efficiency.
A Reference Architecture for Cloud–Edge Meta-Operating Systems Enabling Cross-Domain, Data-Intensive, ML-Assisted Applications: Architectural Overview and Key Concepts
Authors: Trakadas Panagiotis , Masip-Bruin Xavi , Facca Federico M. , Spantideas Sotirios T. , Giannopoulos Anastasios E. , Kapsalis Nikolaos C. , Martins Rui , Bosani Enrica , Ramon Joan , Prats Raül González , Ntroulias George , Lyridis Dimitrios V.
Published: November 2022

Future data-intensive intelligent applications are required to traverse across the cloud-to-edge-to-IoT continuum, where cloud and edge resources elegantly coordinate, alongside sensor networks and data. However, current technical solutions can only partially handle the data outburst associated with the IoT proliferation experienced in recent years, mainly due to their hierarchical architectures. In this context, this paper presents a reference architecture of a meta-operating system (RAMOS), targeted to enable a dynamic, distributed and trusted continuum which will be capable of facilitating the next-generation smart applications at the edge. RAMOS is domain-agnostic, capable of supporting heterogeneous devices in various network environments. Furthermore, the proposed architecture possesses the ability to place the data at the origin in a secure and trusted manner. Based on a layered structure, the building blocks of RAMOS are thoroughly described, and the interconnection and coordination between them is fully presented. Furthermore, illustration of how the proposed reference architecture and its characteristics could fit in potential key industrial and societal applications, which in the future will require more power at the edge, is provided in five practical scenarios, focusing on the distributed intelligence and privacy preservation principles promoted by RAMOS, as well as the concept of environmental footprint minimization. Finally, the business potential of an open edge ecosystem and the societal impacts of climate net neutrality are also illustrated.
Ion-Imprinted Chitosan-Based Localized Surface Plasmon Resonance Sensor for Ni2+ Detection
Authors: Zhong Xiujuan , Ma Li , Yin Guolu
Published: November 2022

Heavy metals are important sources of environmental pollution and cause disease in organisms throughout the food chain. A localized surface plasmon resonance sensor was proposed and demonstrated to realize Ni2+ detection by using ion-imprinted chitosan. Au nanoparticles were coated on the multimode fiber to excite the local surface plasmon resonance, and Ni2+-imprinted chitosan was then functionalized by using the dip coating technique. Ethylene diamine tetra-acetic acid was used to release the Ni2+ ions and hence form countless voids. Ni2+ was refilled into the voids to increase the refractive index of the sensing material, thus realizing the measurement of Ni2+ by monitoring the wavelength shift in the localized surface plasmon resonant peak. The coating thickness of the Ni2+–chitosan gel was optimized to obtain greater sensitivity. Experimental results show that the proposed Ni2+ sensor has a sensitivity of 185 pm/μM, and the limit of detection is 0.512 μM. The comparison experiments indicated that the ion-imprinted chitosan has better selectivity than pure chitosan.
A Novel Joint Adversarial Domain Adaptation Method for Rotary Machine Fault Diagnosis under Different Working Conditions
Authors: Zhao Xiaoping , Shao Fan , Zhang Yonghong
Published: November 2022

In real-world applications of detecting faults, many factors—such as changes in working conditions, equipment wear, and environmental causes—can cause a significant mismatch between the source domain on which classifiers are trained and the target domain to which those classifiers are applied. As such, existing deep network algorithms perform poorly under different working conditions. To solve this problem, we propose a novel fault diagnosis method named Joint Adversarial Domain Adaptation (JADA) for fault detection under different working conditions. Our approach simultaneously aligns marginal distribution and conditional distribution across the source and target through a unified adversarial learning process. JADA aims to construct domain-invariant and category-discriminative feature representation that is effective and robust for substantial distribution difference caused by working conditions. We also introduce a supervision signal, namely center loss, that penalizes the distances between the deep features and their corresponding class centers. This makes the learned features better equipped with more discriminative structures and effectively prevents mode collapse. Twenty-four transfer fault diagnosis tasks based on two experimental platforms were conducted to evaluate the effectiveness of the proposed methods. Extensive experiments verified that the JADA can significantly outperform several popular methods under different transfer diagnosis tasks.
Dynamic Phase and Polarization Modulation Using Two-Beam Parallel Coding for Optical Storage in Transparent Materials
Authors: Hong Jintao , Li Jin , Chu Daping
Published: November 2022

In this paper, we propose and experimentally demonstrate a parallel coding and two-beam combining approach for the simultaneous implementation of dynamically generating holographic patterns at their arbitrary linear polarization states. Two orthogonal input beams are parallelly and independently encoded with the same target image information but there is different amplitude information by using two-phase computer-generated holograms (CGH) on two Liquid-Crystal-on-Silicon-Spatial-Light Modulators (LCOS SLMs). Two modulated beams are then considered as two polarization components and are spatially superposed to form the target polarization state. The final linear vector beam is created by the spatial superposition of the two base beams, capable of controlling the vector angle through the phase depth of the phase-only CGHs. Meanwhile, the combined holographic patterns can be freely encoded by the holograms of two vector components. Thus, this allows us to tailor the optical fields endowed with arbitrary holographic patterns and the linear polarization states at the same time. This method provides a more promising approach for laser data writing generation systems in the next-generation optical data storage technology in transparent materials.
Low-Cost Nitric Oxide Sensors: Assessment of Temperature and Humidity Effects
Authors: Owen Steven , Yee Lachlan H. , Maher Damien T.
Published: November 2022

High equipment cost is a significant entry barrier to research for small organizations in developing solutions to air pollution problems. Low-cost electrochemical sensors show sensitivity at parts-per-billion by volume mixing ratios but are subject to variation due to changing environmental conditions, in particular temperature. In this study, we demonstrate a low-cost Internet of Things (IoT)-based sensor system for nitric oxide analysis. The sensor system used a four-electrode electrochemical sensor exposed to a series of isothermal/isohume conditions. When deployed under these conditions, stable baseline responses were achieved, in contrast to ambient air conditions where temperature and humidity conditions may be variable. The interrelationship between working and auxiliary electrodes was linear within an environmental envelope of 20–40 °C and 30–80% relative humidity, with correlation coefficients from 0.9980 to 0.9999 when measured under isothermal/isohume conditions. These data enabled the determination of surface functions that describe the working to auxiliary electrode offsets and calibration curve gradients and intercepts. The linear and reproducible nature of individual calibration curves for stepwise nitric oxide (NO) additions under isothermal/isohume environments suggests the suitability of these sensors for applications aside from their role in air quality monitoring. Such applications would include nitric oxide kinetic studies for atmospheric applications or measurement of the potential biocatalytic activity of nitric oxide consuming enzymes in biocatalytic coatings, both of which currently employ high-capital-cost chemiluminescence detectors.
Removing False Targets for Cyclic Prefixed OFDM Sensing with Extended Ranging
Authors: Wu Kai , Zhang J. Andrew , Huang Xiaojing , Guo Y. Jay
Published: November 2022

Employing a cyclic prefixed OFDM (CP-OFDM) communication waveform for sensing has attracted extensive attention in vehicular integrated sensing and communications (ISAC). A unified sensing framework was developed recently, enabling CP-OFDM sensing to surpass the conventional limits imposed by underlying communications. However, a false target issue still remains unsolved. In this paper, we investigate and solve this issue. Specifically, we unveil that false targets are caused by periodic cyclic prefixes (CPs) in CP-OFDM waveforms. We also derive the relation between the locations of false and true targets, and other features, e.g., strength, of false targets. Moreover, we develop an effective solution to remove false targets. Simulations are provided to confirm the validity of our analysis and the effectiveness of the proposed solution. In particular, our design can reduce the false alarm rate caused by false targets by over 50% compared with the prior art.
Joint Optimization of Energy Consumption and Data Transmission in Smart Body Area Networks
Authors: Li Limiao , Long Junyao , Zhou Wei , Jolfaei Alireza , Haghighi Mohammad Sayad
Published: November 2022

In Wireless Body Area Networks (BAN), energy consumption, energy harvesting, and data communication are the three most important issues. In this paper, we develop an optimal allocation algorithm (OAA) for sensor devices, which are carried by or implanted in human body, harvest energy from their surroundings, and are powered by batteries. Based on the optimal allocation algorithm that uses a two-timescale Lyapunov optimization approach, we design a framework for joint optimization of network service cost and network utility to study energy, communication, and allocation management at the network edge. Then, we formulate the utility maximization problem of network service cost management based on the framework. Specifically, we use OAA, which does not require prior knowledge of energy harvesting to decompose the problem into three subproblems: battery management, data collection amount control and transmission energy consumption control. We solve these through OAA to achieve three main goals: (1) balancing the cost of energy consumption and the cost of data transmission on the premise of minimizing the service cost of the devices; (2) keeping the balance of energy consumption and energy collection under the condition of stable queue; and (3) maximizing network utility of the device. The simulation results show that the proposed algorithm can actually optimize the network performance.
An Experimental Assessment of People’s Location Efficiency Using Low-Energy Communications-Based Movement Tracking
Authors: Minea Marius
Published: November 2022

(1) Background: public transport demand dynamics represents important information for fleet managers and is also a key factor in making public transport attractive to reduce the environmental footprint of urban traffic. This research presents some experimental results on the assessment of low-energy communication technologies, such as Wi-Fi and Bluetooth, as support for people density and/or movement tracking sensing technologies. (2) Methods: the research is based on field measurements to determine the percentage of discoverable devices carried by people, in relation to the total number of physical persons in interest, different scenarios of mobile devices usage and evaluation of influences on radio signals’ propagation, RSSI / RX read values, and efficiency of indoor localization, or in similar GPS-denied environments. Different situations are investigated, especially public transport-related ones, such as subway stations, indoors of commuting hubs, railway stations and trains. (3) Results: diagrams and experiments are presented, and models of signal behavior are also proposed. (4) Conclusions: recommendations on the efficiency of these non-conventional traveler and passenger flow tracking solutions and models are presented at the end of the paper.
A Study on Object Detection Performance of YOLOv4 for Autonomous Driving of Tram
Authors: Woo Joo , Baek Ji-Hyeon , Jo So-Hyeon , Kim Sun Young , Jeong Jae-Hoon
Published: November 2022

Recently, autonomous driving technology has been in the spotlight. However, autonomous driving is still in its infancy in the railway industry. In the case of railways, there are fewer control elements than autonomous driving of cars due to the characteristics of running on railways, but there is a disadvantage in that evasive maneuvers cannot be made in the event of a dangerous situation. In addition, when braking, it cannot be decelerated quickly for the weight of the body and the safety of the passengers. In the case of a tram, one of the railway systems, research has already been conducted on how to generate a profile that plans braking and acceleration as a base technology for autonomous driving, and to find the location coordinates of surrounding objects through object recognition. In pilot research about the tram’s automated driving, YOLOv3 was used for object detection to find object coordinates. YOLOv3 is an artificial intelligence model that finds coordinates, sizes, and classes of objects in an image. YOLOv3 is the third upgrade of YOLO, which is one of the most famous object detection technologies based on CNN. YOLO’s object detection performance is characterized by ordinary accuracy and fast speed. For this paper, we conducted a study to find out whether the object detection performance required for autonomous trams can be sufficiently implemented with the already developed object detection model. For this experiment, we used the YOLOv4 which is the fourth upgrade of YOLO.
Heuristic Resource Reservation Policies for Public Clouds in the IoT Era
Authors: Gul Omer Melih
Published: November 2022

With the advances in the IoT era, the number of wireless sensor devices has been growing rapidly. This increasing number gives rise to more complex networks where more complex tasks can be executed by utilizing more computational resources from the public clouds. Cloud service providers use various pricing models for their offered services. Some models are appropriate for the cloud service user’s short-term requirements whereas the other models are appropriate for the long-term requirements of cloud service users. Reservation-based price models are suitable for long-term requirements of cloud service users. We used the pricing schemes with spot and reserved instances. Reserved instances support a hybrid cost model with fixed reservation costs that vary with contract duration and an hourly usage charge which is lower than the charge of the spot instances. Optimizing resources to be reserved requires sufficient research effort. Recent algorithms proposed for this problem are generally based on integer programming problems, so they do not have polynomial time complexity. In this work, heuristic-based polynomial time policies are proposed for this problem. It is exhibited that the cost for the cloud service user which uses our approach is comparable to optimal solutions, i.e., it is near-optimal.
Intraoperative Needle Tip Tracking with an Integrated Fibre-Optic Ultrasound Sensor
Authors: Baker Christian , Xochicale Miguel , Lin Fang-Yu , Mathews Sunish , Joubert Francois , Shakir Dzhoshkun I. , Miles Richard , Mosse Charles A. , Zhao Tianrui , Liang Weidong , Kunpalin Yada , Dromey Brian , Mistry Talisa , Sebire Neil J. , Zhang Edward , Ourselin Sebastien , Beard Paul C. , David Anna L. , Desjardins Adrien E. , Vercauteren Tom , Xia Wenfeng
Published: November 2022

Ultrasound is an essential tool for guidance of many minimally-invasive surgical and interventional procedures, where accurate placement of the interventional device is critical to avoid adverse events. Needle insertion procedures for anaesthesia, fetal medicine and tumour biopsy are commonly ultrasound-guided, and misplacement of the needle may lead to complications such as nerve damage, organ injury or pregnancy loss. Clear visibility of the needle tip is therefore critical, but visibility is often precluded by tissue heterogeneities or specular reflections from the needle shaft. This paper presents the in vitro and ex vivo accuracy of a new, real-time, ultrasound needle tip tracking system for guidance of fetal interventions. A fibre-optic, Fabry-Pérot interferometer hydrophone is integrated into an intraoperative needle and used to localise the needle tip within a handheld ultrasound field. While previous, related work has been based on research ultrasound systems with bespoke transmission sequences, the new system—developed under the ISO 13485 Medical Devices quality standard—operates as an adjunct to a commercial ultrasound imaging system and therefore provides the image quality expected in the clinic, superimposing a cross-hair onto the ultrasound image at the needle tip position. Tracking accuracy was determined by translating the needle tip to 356 known positions in the ultrasound field of view in a tank of water, and by comparison to manual labelling of the the position of the needle in B-mode US images during an insertion into an ex vivo phantom. In water, the mean distance between tracked and true positions was 0.7 ± 0.4 mm with a mean repeatability of 0.3 ± 0.2 mm. In the tissue phantom, the mean distance between tracked and labelled positions was 1.1 ± 0.7 mm. Tracking performance was found to be independent of needle angle. The study demonstrates the performance and clinical compatibility of ultrasound needle tracking, an essential step towards a first-in-human study.
Towards the Digital Twin (DT) of Narrow-Band Internet of Things (NBIoT) Wireless Communication in Industrial Indoor Environment
Authors: Dangana Muhammad , Ansari Shuja , Asad Syed Muhammad , Hussain Sajjad , Imran Muhammad Ali
Published: November 2022

A study of the behavior of NB-IoT wireless communication in an industrial indoor environment was conducted in this paper. With Wireless Insite software, a scenario in the industrial sector was simulated and modeled. Our research examined how this scenario or environment affected the communication parameters of NB-IoT’s physical layer. In this context, throughput levels among terminals as well as between terminals and transceiver towers, the power received at signal destination points, signal-to-noise ratios (SNRs) in the environment, and distances between terminals and transceivers are considered. These simulated results are also compared with the calculated or theoretical values of these parameters. The results show the effect of the industrial setting on wireless communication. The differences between the theoretical and simulated values are also established.
OHetTLAL: An Online Transfer Learning Method for Fingerprint-Based Indoor Positioning
Authors: Gidey Hailu Tesfay , Guo Xiansheng , Zhong Ke , Li Lin , Zhang Yukun
Published: November 2022

In an indoor positioning system (IPS), transfer learning (TL) methods are commonly used to predict the location of mobile devices under the assumption that all training instances of the target domain are given in advance. However, this assumption has been criticized for its shortcomings in dealing with the problem of signal distribution variations, especially in a dynamic indoor environment. The reasons are: collecting a sufficient number of training instances is costly, the training instances may arrive online, the feature spaces of the target and source domains may be different, and negative knowledge may be transferred in the case of a redundant source domain. In this work, we proposed an online heterogeneous transfer learning (OHetTLAL) algorithm for IPS-based RSS fingerprinting to improve the positioning performance in the target domain by fusing both source and target domain knowledge. The source domain was refined based on the target domain to avoid negative knowledge transfer. The co-occurrence measure of the feature spaces (Cmip) was used to derive the homogeneous new feature spaces, and the features with higher weight values were selected for training the classifier because they could positively affect the location prediction of the target. Thus, the objective function was minimized over the new feature spaces. Extensive experiments were conducted on two real-world scenarios of datasets, and the predictive power of the different modeling techniques were evaluated for predicting the location of a mobile device. The results have revealed that the proposed algorithm outperforms the state-of-the-art methods for fingerprint-based indoor positioning and is found robust to changing environments. Moreover, the proposed algorithm is not only resilient to fluctuating environments but also mitigates the model’s overfitting problem.
Toward an Intelligent Campus: IoT Platform for Remote Monitoring and Control of Smart Buildings
Authors: Ahmed Mohamed A. , Chavez Sebastian A. , Eltamaly Ali M. , Garces Hugo O. , Rojas Alejandro J. , Kim Young-Chon
Published: November 2022

With the growing need to obtain information about power consumption in buildings, it is necessary to investigate how to collect, store, and visualize such information using low-cost solutions. Currently, the available building management solutions are expensive and challenging to support small and medium-sized buildings. Unfortunately, not all buildings are intelligent, making it difficult to obtain such data from energy measurement devices and appliances or access such information. The internet of things (IoT) opens new opportunities to support real-time monitoring and control to achieve future smart buildings. This work proposes an IoT platform for remote monitoring and control of smart buildings, which consists of four-layer architecture: power layer, data acquisition layer, communication network layer, and application layer. The proposed platform allows data collection for energy consumption, data storage, and visualization. Various sensor nodes and measurement devices are considered to collect information on energy use from different building spaces. The proposed solution has been designed, implemented, and tested on a university campus considering three scenarios: an office, a classroom, and a laboratory. This work provides a guideline for future implementation of intelligent buildings using low-cost open-source solutions to enable building automation, minimize power consumption costs, and guarantee end-user comfort.
Real-Time Video Synopsis via Dynamic and Adaptive Online Tube Resizing
Authors: Liao Xiaoxin , Liu Song , Cai Zemin
Published: November 2022

Nowadays, with the increased numbers of video cameras, the amount of recorded video is growing. Efficient video browsing and retrieval are critical issues when considering the amount of raw video data to be condensed. Activity-based video synopsis is a popular approach to solving the video condensation problem. However, conventional synopsis methods always consists of complicated and pairwise energy terms that involve a time-consuming optimization problem. In this paper, we propose a simple online video synopsis framework in which the number of collisions of objects is classified first. Different optimization strategies are applied according to different collision situations to maintain a balance among the computational cost, condensation ratio, and collision cost. Secondly, tube-resizing coefficients that are dynamic in different frames are adaptively assigned to a newly generated tube. Therefore, a suitable mapping result can be obtained in order to represent the proper size of the activity in each frame of the synopsis video. The maximum number of activities can be displayed in one frame with minimal collisions. Finally, in order to remove motion anti-facts and improve the visual quality of the condensed video, a smooth term is introduced to constrain the resizing coefficients. Experimental results on extensive videos validate the efficiency of the proposed method.
Stereo Image Matching Using Adaptive Morphological Correlation
Authors: Diaz-Ramirez Victor H. , Gonzalez-Ruiz Martin , Kober Vitaly , Juarez-Salazar Rigoberto
Published: November 2022

A stereo matching method based on adaptive morphological correlation is presented. The point correspondences of an input pair of stereo images are determined by matching locally adaptive image windows using the suggested morphological correlation that is optimal with respect to an introduced binary dissimilarity-to-matching ratio criterion. The proposed method is capable of determining the point correspondences in homogeneous image regions and at the edges of scene objects of input stereo images with high accuracy. Furthermore, unknown correspondences of occluded and not matched points in the scene can be successfully recovered using a simple proposed post-processing. The performance of the proposed method is exhaustively tested for stereo matching in terms of objective measures using known database images. In addition, the obtained results are discussed and compared with those of two similar state-of-the-art methods.
3D Point Cloud Acquisition and Correction in Radioactive and Underwater Environments Using Industrial 3D Scanners
Authors: Hyun Dongjun , Joo Sungmoon , Kim Ikjune , Lee Jonghwan
Published: November 2022

This study proposes a method to acquire an accurate 3D point cloud in radioactive and underwater environments using industrial 3D scanners. Applications of robotic systems at nuclear facility dismantling require 3D imaging equipment for localization of target structures in radioactive and underwater environments. The use of industrial 3D scanners may be a better option than developing prototypes for researchers with basic knowledge. However, such industrial 3D scanners are designed to operate in normal environments and cannot be used in radioactive and underwater environments. Modifications to environmental obstacles also suffer from hidden technical details of industrial 3D scanners. This study shows how 3D imaging equipment based on the industrial 3D scanner satisfies the requirements of the remote dismantling system, using a robotic system despite insufficient environmental resistance and hidden technical details of industrial 3D scanners. A housing unit is designed for waterproofing and radiation protection using windows, mirrors and shielding. Shielding protects the industrial 3D scanner from radiation damage. Mirrors reflect the light required for 3D scanning because shielding blocks the light. Windows in the waterproof housing also transmit the light required for 3D scanning with the industrial 3D scanner. The basic shielding thickness calculation method through the experimental method is described, including the analysis of the experimental results. The method for refraction correction through refraction modeling, measurement experiments and parameter studies are described. The developed 3D imaging equipment successfully satisfies the requirements of the remote dismantling system: waterproof, radiation resistance of 1 kGy and positional accuracy within 1 mm. The proposed method is expected to provide researchers with an easy approach to 3D scanning in radioactive and underwater environments.
An Integrated Conceptual Model to Understand Suicidality among Queer Youth to Inform Suicide Prevention
Authors: Williams Denise Yookong , Hall William J. , Dawes Hayden C. , Rizo Cynthia Fraga , Goldbach Jeremy T.
Published: November 2022

In this article, we apply and combine elements from four theoretical frameworks (i.e., Minority Stress Theory, Person-in-Environment and Risk and Resilience Framework, Interpersonal-Psychological Theory of Suicide, and Intersectionality) to explain the problem of queer youth suicide through our integrated conceptual model, Queer Prevention of Youth Suicidality Model (Queer-PRYSM). The need for this conceptual model is based on the current state of the literature, including mixed empirical findings on factors related to queer youth suicidality, no scholarly consensus on specific contributing factors regarding high rates of suicidality among queer youth (including queer youth subgroups), and the absence of a unifying theory to explain the queer youth suicide risk. To address these limitations in theory, evidence, and scholarship explaining suicidality among queer youth we present our integrated model with growing, current, relevant research with queer youth. Queer-PRYSM includes minority stressors specific to queer youth, mental health problems, interpersonal-psychological factors, socioecological factors (i.e., family, school, peers, and community), and intersectionality concepts. Queer-PRYSM is essential to understanding the relationship of distal and proximal risk and protective factors in queer youth suicide and developing evidence-informed suicide preventive interventions that can be incorporated into practice, policy, and system structures.
Reliability and Effectiveness of a Lateral Countermovement Jump for Stratifying Shuffling Performance Amongst Elite Basketball Players
Authors: Leidersdorf Eric , Rauch Jacob , Reeves Trent , Borkan Leah , Francis Javan , Storey Luke , Souza Eduardo Oliveira De , Elliott Marcus , Ugrinowitsch Carlos
Published: November 2022

Though research suggests that basketball players spend approximately 31% of game actions shuffling laterally, limited data are available on the kinetic factors that separate fast and slow shufflers. The purpose of this study was twofold: (1.) Examine the reliability of kinetic metrics from a single-leg Lateral Countermovement Jump (LCMJ) (2.) Determine if kinetic metrics from the LCMJ can stratify above (i.e., “fast”) or below (i.e., “slow”) median shuffling performance. Twenty professional basketball players participated in the reliability study (21.7 ± 3.5 years, 1.98 ± 0.1 m; 89.9 ± 10.9 kg). One hundred seven professional and thirty-three collegiate basketball players (N = 140) (22.7 ± 3.5 years, 2.0 ± 0.1 m; 98.4 ± 11.9 kg) participated in the experimental study examining the ability of LCMJ kinetics to stratify shuffling performance. Reliability was assessed using Bland–Altman plots, coefficients of variation (CVs), typical errors (TEs), and intraclass correlation coefficients (ICCs). Anthropometric and LCMJ kinetic differences between fast and slow shufflers were assessed with an independent t-test. Four kinetic metrics (peak vertical force, peak lateral force, relative lateral force, and lateral impulse) met within- and between-session reliability thresholds (CV < 10% and ICC > 0.70). Faster shufflers generated significantly more relative lateral force than their slower counterparts (9.51 ± 0.8 Nx/kg vs. 8.9 ± 0.9 Nx/kg, %Diff 6.3, p < 0.00007, ES = 0.70). Basketball practitioners who have access to triaxial force plates may consider adding the LCMJ into their testing battery, as relative lateral force is a reliable metric that can stratify fast and slow shufflers.
Evolutionary Game Analysis on Sharing Bicycles and Metro Strategies: Impact of Phasing out Subsidies for Bicycle–Metro Integration Model
Authors: Jia Cai , Chen Yanyan , Chen Tingzhao , Li Yanan , Lin Luzhou
Published: November 2022

The rapid development of sharing bicycles has facilitated the last mile of travel and provided new opportunities for the sustainable development of metro transportation. However, there is still insufficient literature on how to promote the bicycle–metro integration mode. This paper designs a bicycle–metro integrated model based on evolutionary game theory and explores the evolutionary mechanism of the sharing of bicycles connection system and metro system under the subsidy phasing out. The conditions for achieving different equilibrium states were discussed based on the replication dynamics equation. In order to prove the evolutionary game analysis, the system dynamics simulation model was used to reveal the effects of the cost factor, subsidy factor, reward, and penalty factors on the equilibrium of the integrated model. Moreover, the values of the influence factors that make the system reach the optimal equilibrium were obtained through sensitivity analysis. The results show that by reasonably adjusting the values of the parameters, sharing bicycles connection systems, metro systems and connection travelers can reach an equilibrium state where they are willing to cooperate. Subsidy phasing-out policies for travelers were key to promoting the equilibrium of the model. The unit price of shared bicycles has a greater impact on users, and the irregular parking ratio changes have a greater impact on the benefits of travelers compared to the benefits of the metro system. In order to promote bicycle–metro integration and enhance the attractiveness of metro transportation, policies designed for participants should be integrated with dynamic evolution.
Innovative Internet Solutions for Suburban Community Farm Practices: A Study in Lowland Communities of Hangzhou, China
Authors: Shi Jianren , Guo Qiaoyun , Zhao Xiumin
Published: November 2022

The development of permaculture follows the principle of respecting nature and protecting ecology, which is of great significance to the development of modern urban agriculture. Community planning combines urban life with traditional agricultural production, so that agricultural development and suburban urban life have symbiosis and complement each other. On the one hand, it alleviates the contradiction between the city and ecological environment protection and guides ecological and green development in the suburbs of the city. On the other hand, it creates a better living environment for the city and promotes the sustainable development of urban–rural integration. This paper combines the sustainable design concept of permaculture with the resource conditions and advantages of the comprehensive project base and applies the concept of permaculture to the development of the “air vegetable plot” urban farm. At the same time, we use the integration strategy of agriculture and tourism, through the “Internet + Agriculture” path, to build a multi-functional industry of life, production and ecology; to promote the sustainable development of rural industries with the digitization of agricultural industries; to promote the common prosperity of rural areas; and to open a new model of “Internet + Future Agriculture”.
Efficient Water Use and Greenhouse Gas Emission Reduction in Agricultural Land Use—The Aspect of Land Consolidation
Authors: Kuburić Miroslav , Trifković Milan , Nestorović Žarko
Published: November 2022

Efficient water utilization and greenhouse gas emissions have become the topic of wide scientific interest in the last few decades. In this research, we considered the reduction in the road length and the increase in the irrigation channel length after land consolidation. The efficiency of water use is considered as the function of the distance between the water source and crops. The reduction of greenhouse gases is considered as the function of the reduction in the length of the agricultural mechanized transport. A simple mathematical model was developed for calculating the reduction of the road network transport length. The results showed that land consolidation (LC) reduces the road network length, by itself, and provides conditions for an increase in the irrigation channel length. In the case study area, the road network length was reduced by more than one-third (36.8%) and the irrigation channel length was more than doubled (125.9%).
Emotional Intelligence as a Personality Trait That Predicts Consumption Behavior: The Role of Consumer Emotional Intelligence in Persuasive Communication
Authors: Ahn Hongmin
Published: November 2022

While a significant number of studies have examined the effect of cognitive ability on social behaviors, researchers have devoted insufficient attention to emotional ability as a distinguishing individual characteristic that influences social behaviors. This study aims to address this critical gap by examining the specific role that consumer emotional intelligence (CEI) plays in the susceptibility to persuasive messages. Based on emotional intelligence and regulatory focus theories, an experiment was conducted to test CEI effect and its boundary conditions. The results demonstrate that people with high CEI are more likely to be persuaded by positive emotion-evoking ads than people with low CEI. Furthermore, the study found that this effect is more pronounced for promotion-focused (vs. prevention-focused) ad messages. These findings indicate that emotional intelligence is a meaningful individual trait to consider when predicting how people will respond to persuasive messages.