bluuebunny/crossref_metadata_2025 huggingface dataset:
A Blockchain-Based Efficient, Secure and Anonymous Conditional Privacy-Preserving and Authentication Scheme for the Internet of Vehicles
Authors: Qureshi Kashif Naseer , Shahzad Luqman , Abdelmaboud Abdelzahir , Elfadil Eisa Taiseer Abdalla , Alamri Bandar , Javed Ibrahim Tariq , Al-Dhaqm Arafat , Crespi Noel
Published: January 2022

The rapid advancement in the area of the Internet of Vehicles (IoV) has provided numerous comforts to users due to its capability to support vehicles with wireless data communication. The exchange of information among vehicle nodes is critical due to the rapid and changing topologies, high mobility of nodes, and unpredictable network conditions. Finding a single trusted entity to store and distribute messages among vehicle nodes is also a challenging task. IoV is exposed to various security and privacy threats such as hijacking and unauthorized location tracking of smart vehicles. Traceability is an increasingly important aspect of vehicular communication to detect and penalize malicious nodes. Moreover, achieving both privacy and traceability can also be a challenging task. To address these challenges, this paper presents a blockchain-based efficient, secure, and anonymous conditional privacy-preserving and authentication mechanism for IoV networks. This solution is based on blockchain to allow vehicle nodes with mechanisms to become anonymous and take control of their data during the data communication and voting process. The proposed secure scheme provides conditional privacy to the users and the vehicles. To ensure anonymity, traceability, and unlinkability of data sharing among vehicles, we utilize Hyperledger Fabric to establish the blockchain. The proposed scheme fulfills the requirement to analyze different algorithms and schemes which are adopted for blockchain technology for a decentralized, secure, efficient, private, and traceable system. The proposed scheme examines and evaluates different consensus algorithms used in the blockchain and anonymization techniques to preserve privacy. This study also proposes a reputation-based voting system for Hyperledger Fabric to ensure a secure and reliable leader selection process in its consensus algorithm. The proposed scheme is evaluated with the existing state-of-the-art schemes and achieves better results.
Numerical Simulation and Experimental Investigation of Rotating Blade Centrifugal Jet in Slurry Blast Device Used for Steel Strip Descaling
Authors: Huo Guotao , Ma Zhonghai , Huang Yeqing , Nie Songlin , Zhang Zhenhua
Published: January 2022

Under the requirement of clean production, a new type of slurry blast device for mechanically removing oxide scale on the surface of steel strips is presented, which can avoid the serious problems of rapid wear, low service life, and low efficiency of the traditional abrasive water jet with a nozzle. In this paper, the numerical simulation of the rotating blade centrifugal jet in the slurry blast device is conducted based on CFD, where the DPM and the erosion model are innovatively employed to simulate the movement characteristics of abrasive particles and the erosion rate of mixed slurry on the surface of the steel strip. Simulation results show that the erosion rate and particle motion velocity are proportional to the blade rotation speed and inlet pressure. Reasonable inlet pressure and rotation speed are helpful for improving the rust removal efficiency of slurry blast devices. An experimental system is established to validate the simulation results. The experimental results are consistent with the simulation trend, which exhibits that the developed slurry blast device is feasible for steel strip descaling. This work will play substantial guiding roles in the engineering optimization of slurry blast devices for steel strip descaling.
Context-Aware End-User Development Review
Authors: Ponce Victor , Abdulrazak Bessam
Published: January 2022

Context-aware application development frameworks enable context management and environment adaptation to automatize people’s activities. New technologies such as 5G and the Internet of Things (IoT) increase environment context (from devices/services), making functionalities available to augment context-aware applications. The result is an increased deployment of context-aware applications to support end-users in everyday activities. However, developing applications in context-aware frameworks involve diverse technologies, so that it traditionally involves software experts. In general, context-aware applications are limited in terms of personalization for end-users. They include configurations to personalize applications, but non-software experts can only change some of these configurations. Nowadays, advances in human–computer interaction provide techniques/metaphors to approach non-software experts. One approach is end-user development (EUD)—a set of activities and development tools that considers non-software experts as application builders. In this paper, we present our analysis of existing EUD approaches for building context-aware applications. We present a literature review of 37 screened papers obtained from research databases. This review aims to identify the methods, techniques, and tools proposed to build context-aware applications. Specifically, we reviewed EUD building techniques and implementations. Building techniques include metaphors/interaction styles proposed for application specification, composition, and testing. The implementations include a specification method to integrate and process context on the target application platforms. We also present the adoption trend and challenges of context-aware end-user development.
Deformation Analysis of an Ultra-High Arch Dam under Different Water Level Conditions Based on Optimized Dynamic Panel Clustering
Authors: Liu Yongtao , Zheng Dongjian , Georgakis Christos , Kabel Thomas , Cao Enhua , Wu Xin , Ma Jiajia
Published: January 2022

During the operation period, the deformation of an ultra-high arch dam is affected by the large fluctuation of the reservoir water level. Under the dual coupling of the ultra-high dam and the complex water level conditions, the traditional variational analysis method cannot be sufficiently applied to its deformation analysis. The deformation analysis of the ultra-high arch dam, however, is very important in order to judge the dam safety state. To analyze the deformation law of different parts of an ultra-high arch dam, the panel data clustering theory is used to construct a Spatio-temporal characteristic model of dam deformation. In order to solve the difficult problem of the fluctuating displacement of dam deformation with water level effect, three displacement component indexes (absolute quantity, growing, and fluctuation) are proposed to characterize dam deformation. To further optimize the panel clustering deformation model, the objective weight coefficient of clustering comprehensive distance is calculated based on the CRITIC (CRiteria Importance Through Inter-criteria Correlation) method. The zoning rules of the ultra-high arch dam are established by using the idea of the CSP (Constraint Satisfaction Problem) index, and the complex water level of the reservoir is simulated in the whole process. Finally, the dynamic cluster analysis of dam deformation is realized. Through a case study, three typical working conditions including the rapid rise and fall of water level and the normal operation are calculated, and the deformation laws of different deformation zones are analyzed. The results show that the model can reasonably describe the deformation law of an ultra-high arch dam under different water levels, conveniently and intuitively select representative measuring points and key monitoring parts, effectively reducing the analysis workload of lots of measuring points, and improve the reliability of arch dam deformation analysis.
Hyper-Redundant Manipulator Capable of Adjusting Its Non-Uniform Curvature with Discrete Stiffness Distribution
Authors: Kwon Seongil , Kim Jeongryul , Moon Yonghwan , Kim Keri
Published: January 2022

Hyper-redundant manipulators are widely used in minimally invasive surgery because they can navigate through narrow passages in passive compliance with the human body. Although their stability and dexterity have been significantly improved over the years, we need manipulators that can bend with appropriate curvatures and adapt to complex environments. This paper proposes a design principle for a manipulator capable of adjusting its non-uniform curvature and predicting the bending shape. Rigid segments were serially stacked, and elastic fixtures in the form of flat springs were arranged between hinged-slide joint segments. A manipulator with a diameter of 4.5 mm and a length of 28 mm had been fabricated. A model was established to predict the bending shape through minimum potential energy theory, kinematics, and measured stiffnesses of the flat springs. A comparison of the simulation and experimental results indicated an average position error of 3.82% of the endpoints when compared to the total length. With this modification, the manipulator is expected to be widely used in various fields such as small endoscope systems and single-port robot systems.
Patellar Tendon Force Differs Depending on Jump-Landing Tasks and Estimation Methods
Authors: Garcia Sébastien , Delattre Nicolas , Berton Eric , Rao Guillaume
Published: January 2022

Patellar tendinopathy is a chronic overuse injury of the patellar tendon which is prevalent in jump-landing activities. Sports activities can require jumping not only with a vertical component but also in a forward direction. It is yet unknown how jumping in the forward direction may affect patellar tendon forces. The main purpose of this study was to compare PTF between landings preceded by a vertical jump and a forward jump in volleyball players. The second purpose was to compare two different estimation methods of the patellar tendon force. Fifteen male volleyball players performed vertical and forward jump-landing tasks at a controlled jump height, while kinetics and kinematics were recorded. Patellar tendon forces were calculated through two estimation methods based on inverse dynamic and static optimization procedures, using a musculoskeletal model. Results showed that forward jump-landing generated higher patellar tendon forces compared to vertical jump-landing for both estimation methods. Surprisingly, although the static optimization method considered muscle co-contraction, the inverse kinematic method provided statistically significant higher patellar tendon force values. These findings highlight that limiting the forward velocity component of the aerial phase appears to reduce the load on the patellar tendon during landing and may help to prevent patellar tendinopathy.
Viability of Using High Amounts of Steel Slag Aggregates to Improve the Circularity and Performance of Asphalt Mixtures
Authors: Moura Caroline , Nascimento Lucas , Loureiro Carlos , Rodrigues Mafalda , Oliveira Joel , Silva Hugo
Published: January 2022

Steel slag is a byproduct generated as waste during the steelmaking process and can be considered a cost-effective and environmentally acceptable alternative to replace natural aggregates. Using steel slag aggregates (SSA) to produce asphalt mixtures promotes sustainability and circular economy principles by using an industrial byproduct as a raw material. Thus, this work mainly aims to design more sustainable asphalt mixtures with high amounts of SSA that fit the circular economy expectations. This work developed two asphalt mixtures with SSA for surface (AC 14 surf) and binder/base (AC 20 bin/base) courses. Initially, the excellent wearing and polishing resistance of SSA and their good affinity with bitumen demonstrated the potential of this byproduct to be used in asphalt mixtures. Then, when analyzing the influence of using two different SSA incorporation rates (50% and a percentage close to 100%) in both asphalt mixtures, it was concluded that the use of SSA should be limited to 75% to avoid excessive air void contents and durability problems. The importance of considering the different particle densities of SSA and natural aggregates was highlighted during the mix design by defining a relationship between an effective and equivalent binder content. Finally, the mechanical performance of AC 14 and AC 20 with 75% SSA incorporation was compared to identical conventional mixtures produced with natural granite aggregates. The results obtained showed that the asphalt mixtures with 75% SSA have some workability problems due to the rough and porous surface of SSA. However, they present an excellent water sensitivity and permanent deformation resistance, surpassing the performance of the conventional asphalt mixtures.
A Reflection-Type Dual-Band Phase Shifter with an Independently Tunable Phase
Authors: Kim Suyeon , Jeong Junhyung , Chaudhary Girdhari , Jeong Yongchae
Published: January 2022

This paper presents a design for a dual-band tunable phase shifter (PS) with independently controllable phase shifting between each operating frequency band. The proposed PS consists of a 3-dB hybrid coupler, in which the coupled and through ports terminate with the same two reflection loads. Each reflection load consists of a series of quarter-wavelength (λ/4) transmission lines, λ/4 shunt open stubs, and compensation elements at each operating frequency arm. In this design, a wide phase shifting range (PSR) is achievable at each operating frequency band (fL: lower frequency; fH: higher frequency) by compensating for the susceptance occurring at the co-operating frequency band caused by the λ/4 shunt open stub. The load of fL does not affect the load of fH and vice versa. The dual-band tunable PS was fabricated at fL = 1.88 GHz and fH = 2.44 GHz, and testing revealed that achieved a PSR of 114.1° with an in-band phase deviation (PD) of ± 8.43° at fL and a PSR of 114.0° ± 5.409° at fH over a 100 MHz bandwidth. In addition, the maximum insertion losses were smaller than 1.86 dB and 1.89 dB, while return losses were higher than 17.2 dB and 16.7 dB within each respective operating band.
Using the Hurst Exponent and Entropy Measures to Predict Effective Transmissibility in Empirical Series of Malaria Incidence
Authors: Sequeira João , Louçã Jorge , Mendes António M. , Lind Pedro G.
Published: January 2022

We analyze the empirical series of malaria incidence, using the concepts of autocorrelation, Hurst exponent and Shannon entropy with the aim of uncovering hidden variables in those series. From the simulations of an agent model for malaria spreading, we first derive models of the malaria incidence, the Hurst exponent and the entropy as functions of gametocytemia, measuring the infectious power of a mosquito to a human host. Second, upon estimating the values of three observables—incidence, Hurst exponent and entropy—from the data set of different malaria empirical series we predict a value of the gametocytemia for each observable. Finally, we show that the independent predictions show considerable consistency with only a few exceptions which are discussed in further detail.
Stable Isotope and Radiocarbon Analysis for Diet, Climate and Mobility Reconstruction in Agras (Early Iron Age) and Edessa (Roman Age), Northern Greece
Authors: Dotsika Elissavet , Tassi Maria , Karalis Petros , Chrysostomou Anastasia , Michael Dimitra Ermioni , Poutouki Anastasia Elektra , Theodorakopoulou Katerina , Diamantopoulos Georgios
Published: January 2022

In this article we present an isotopic analysis of human bone collagen (δ13Ccol, and δ15Ncol) and bone apatite (δ13C) for diet reconstruction, as well as δ18Oap of human bone apatite for climate reconstruction, using samples from Northern Greece. Radiocarbon dating analysis was conducted on three of the Agras samples and the results (from 1000 to 800 BC) correspond to the Early Iron Age. Isotopic values for δ13Ccol range from −20.5‰ to −16‰ and for δ15Ncol from 6‰ to 11.1‰—a strong indication of a C3-based diet, with contributions by C4 and freshwater fish elements. The results were compared to the ones from Roman Edessa, and Alexandreia (a contemporary city near Edessa), as well as to other Early Iron sites in Greece and wider Europe. In general, the results from Agras are in good agreement with the results from Northern Greece, with the exception of the Makriyalos site, and are quite close to those of Croatia’s and Hungary’s sites. Additionally, from the δ18Oap results we calculated the oxygen isotopic composition of consumed water for Agras (from −9.6‰ to −10.9‰) and for Roman Edessa (from −9.6‰ to −11.2‰) for the palaeoclimate and palaeomobility reconstruction.
Spatiotemporal Deformation of Existing Pipeline Due to New Shield Tunnelling Parallel Beneath Considering Construction Process
Authors: Liu Xiang , Jiang Annan , Fang Qian , Wan Yousheng , Li Jianye , Guo Xinping
Published: January 2022

In this paper, we study the effects of the shield tunnel construction on the deformation of an existing pipeline parallel to and above the new shield tunnel. We propose an analytical solution to predict the spatiotemporal deformation of the existing pipeline and consider different force patterns of the shield tunnelling, i.e., ground volume loss, support pressure, frictional force, and torsional force. The proposed method is validated by the monitoring data of Subway Line 3 of Nanchang and provides a reasonable estimation of the pipeline’s deformation. The parametric analyses are performed to study the influences on the pipeline’s deformation. The main advantage of our paper is that the spatiotemporal characteristics of the existing pipeline’s deformation are analysed, providing longitudinal deformation curve (LDC), deformation development curve (DDC), and grouting reinforcement curve (GRC). Compared with the perpendicular undercrossing project, both LDC and DDC have the same profiles and maximum values and move forward as a whole with the shield tunnel advance. Thus, the spatiotemporal deformation of the overall pipeline can be extrapolated from the deformation of two known points on the pipeline. The spatiotemporal characteristic curves combined with LDC, DDC, and GRC can suggest feasible, effective, and economical construction and grouting schemes to control the pipeline’s deformation after the deformation control standards have been determined.
Design Proposal for Masonry Infill Walls Subject to Seismic Actions
Authors: Leite João , Lourenço Paulo B. , Mendes Nuno
Published: January 2022

Several factors influence the behaviour of masonry infilled frames, which have been the subject of previous research with moderate success. The new generation of European design standards imposes the need to prevent the brittle collapse of infills and makes the structural engineer accountable for this requirement, yet it fails to provide sufficient information for masonry infill design. The present study aimed to compare experimental results with the provisions of the standard for the computation of the demand and capacity of infilled frames. Three reinforced concrete buildings with different infill solutions were constructed at a 1:1.5 scale. The infill walls were tested until collapse, or severe damage, using the shake table of the National Laboratory for Civil Engineering, Portugal, and their response was measured using accelerometers attached to the walls. The European normative standard provides results close to the experimental ones as far as demand and capacity are concerned. Based on the experiments, two design proposals for infill walls are presented here, one for the definition of the natural frequency of the infills, and another for a reduction factor to account for the presence of openings in the out-of-plane capacity of infills.
Boundary-Aware Hashing for Hamming Space Retrieval
Authors: Hu Wenjin , Chen Yukun , Wu Lifang , Shi Ge , Jian Meng
Published: January 2022

Hamming space retrieval is a hot area of research in deep hashing because it is effective for large-scale image retrieval. Existing hashing algorithms have not fully used the absolute boundary to discriminate the data inside and outside the Hamming ball, and the performance is not satisfying. In this paper, a boundary-aware contrastive loss is designed. It involves an exponential function with absolute boundary (i.e., Hamming radius) information for dissimilar pairs and a logarithmic function to encourage small distance for similar pairs. It achieves a push that is bigger than the pull inside the Hamming ball, and the pull is bigger than the push outside the ball. Furthermore, a novel Boundary-Aware Hashing (BAH) architecture is proposed. It discriminatively penalizes the dissimilar data inside and outside the Hamming ball. BAH enables the influence of extremely imbalanced data to be reduced without up-weight to similar pairs or other optimization strategies because its exponential function rapidly converges outside the absolute boundary, making a huge contrast difference between the gradients of the logarithmic and exponential functions. Extensive experiments conducted on four benchmark datasets show that the proposed BAH obtains higher performance for different code lengths, and it has the advantage of handling extremely imbalanced data.
Experimental Evaluation of the Blackbody Radiation Shift in the Cesium Atomic Fountain Clock
Authors: Yang Fan , Wang Xinliang , Ruan Jun , Shi Junru , Fan Sichen , Bai Yang , Guan Yong , Hao Qiang , Zhang Hui , Liu Dandan , Zhang Shougang
Published: January 2022

The cesium atomic fountain clock is the world’s most accurate microwave atomic clock. The uncertainty of blackbody radiation (BBR) shift accounts for an increasingly large percentage of the uncertainty associated with fountain clocks and has become a key factor in the performance of fountain clocks. The uncertainty of BBR shift can be reduced by improving the system environment temperature. This study examined the mechanism by which the BBR shift of the transition frequency between the two hyperfine energy levels of the 133Cs ground state is generated and the calculation method for the BBR shift in the atomic fountain. Methods used to reduce the uncertainty of BBR shift were also examined. A fountain system structure with uniform temperature and good heat preservation was designed, and related technologies, such as that for measuring the temperature of the cesium fountain system, were studied. The results of 20 days of measurements, in combination with computer simulation results, showed that the temperature uncertainty of the atomic action zone is 0.12 °C and that the resulting uncertainty of BBR shift is 2.4 × 10−17.
3D Stress Analysis of Multilayered Functionally Graded Plates and Shells under Moisture Conditions
Authors: Brischetto Salvatore , Torre Roberto
Published: January 2022

This paper presents the steady-state stress analysis of single-layered and multilayered plates and shells embedding Functionally Graded Material (FGM) layers under moisture conditions. This solution relies on an exact layer-wise approach; the formulation is unique despite the geometry. It studies spherical and cylindrical shells, cylinders, and plates in an orthogonal mixed curvilinear coordinate system (α, β, z). The moisture conditions are defined at the external surfaces and evaluated in the thickness direction under steady-state conditions following three procedures. This solution handles the 3D Fick diffusion equation, the 1D Fick diffusion equation, and the a priori assumed linear profile. The paper discusses their assumptions and the different results they deliver. Once defined, the moisture content acts as an external load; this leads to a system of three non-homogeneous second-order differential equilibrium equations. The 3D problem is reduced to a system of partial differential equations in the thickness coordinate, solved via the exponential matrix method. It returns the displacements and their z-derivatives as a direct result. The paper validates the model by comparing the results with 3D analytical models proposed in the literature and numerical models. Then, new results are presented for one-layered and multilayered FGM plates, cylinders, and cylindrical and spherical shells, considering different moisture contents, thickness ratios, and material laws.
Resilience Assessment of a Twin-Tube Motorway Tunnel in the Event of a Traffic Accident or Fire in a Tube
Authors: Caliendo Ciro , Russo Isidoro , Genovese Gianluca
Published: January 2022

We have developed a traffic simulation model to quantitatively assess the resilience of a twin-tube motorway tunnel in the event of traffic accident or fire occurring within a tube. The motorway section containing the tunnel was investigated for different possible scenarios including its partial or complete closure. The functionality of the road infrastructure, in the case of an accident in one of the two tubes (each tube presents two lanes with unidirectional traffic under ordinary conditions), was assumed to be recovered both by using the remaining undisrupted lane of the tube interested by the disruptive event (only one lane is closed) and reorganizing the traffic flow by utilizing the adjacent tube for bi-directional traffic (both lanes are closed). The effects of an alternative itinerary individualized in the corresponding open road network were also examined. The level of functionality of the system during the period in which the tube is partially or completely closed was computed as the ratio between the average travel time required to reach a given destination from a specific origin before and after the occurrence of the disruptive event. The resilience metrics were assumed to be resilience loss, recovery speed, and resilience index. The best scenario was found to be the partial closure of the tube in contrast to the complete one. However, in order to contain the negative effects on the functionality of the motorway section due to the complete closure of the tube, it is worth highlighting how the traffic by-pass before the entrance portal of the closed tube should be open in a very short time by the tunnel management team to allow for the quick use of the adjacent tube for bi-directional traffic. An additional improvement, with reference exclusively to passenger cars traveling through the adjacent unblocked tube, might be obtained by activating the variable message signs, located at a sufficient distance from the motorway junction before the entrance portal of the closed tube, in order to suggest an alternative route to heavy good vehicles (HGVs) only. Whereas, when the alternative itinerary is used by all vehicles traveling towards the blocked tube (i.e., both passenger cars and HGVs), this redirectioning of the motorway traffic flow was found to be characterized by an excessive travel time, with it therefore not being advisable. The results obtained might be useful as a decision-making support tool aimed at improving the resilience of twin-tube tunnels.
Analytical Model Formulation of Steel Plate Reinforced Concrete Walls against Hard Projectile Impact
Authors: Pu Bo , Wang Xiaoming , Li Weibing , Feng Jun
Published: January 2022

Steel plate reinforced concrete (SC) walls can effectively resist projectile impact by preventing the rear concrete fragments flying away, thus attracting much attention in defence technology. This work numerically and analytically investigated the hard projectile perforation of steel plate reinforced concrete walls. Impact resistance theories, including cavity expansion analysis as well as the petaling theory of thin steel plates were used to describe the cratering, tunneling and plugging phases of SC walls perforation. Numerical modeling of SC walls perforation was performed to estimate projectile residual velocity and target destructive form, which were validated against the test results. An analytical model for SC wall perforation was established to describe the penetration resistance featuring five stages, i.e., cratering, tunneling and plugging, petaling with plugging and solely petaling. Analytical model predictions matched numerical results well with respect to projectile deceleration evolution as well as residual velocity. From a structural absorbed energy perspective, the effect of front concrete panel and rear steel plate thickness combinations was also studied and analyzed. Finally, equivalent concrete slab thickness was derived with respect to the ballistic limit of SC walls, which may be helpful in the design of a protective strategy.
Embedded AI-Based Digi-Healthcare
Authors: Ashfaq Zarlish , Mumtaz Rafia , Rafay Abdur , Zaidi Syed Mohammad Hassan , Saleem Hadia , Mumtaz Sadaf , Shahid Adnan , Poorter Eli De , Moerman Ingrid
Published: January 2022

Healthcare is an indispensable part of human life and chronic illnesses like cardiovascular diseases (CVD) have a deeply negative impact on the healthcare sector. Since the ever-growing population of chronic patients cannot be managed at hospitals, therefore, there is an urgent need for periodic monitoring of vital parameters and apposite treatment of these patients. In this paper, an Internet of Medical Things (IoMT) -based remote patient monitoring system is proposed which is based on Artificial Intelligence (AI) and edge computing. The primary focus of this paper is to develop an embedded prototype that can be used for remote monitoring of cardiovascular patients. The system will continuously monitor physiological parameters like body temperature, heart rate, and blood oxygen saturation, and then report the health status to the authenticated users. The system employs edge computing to perform multiple functionalities including health status inference using a Machine Learning (ML) model which makes predictions on real-time data, alert notifications in case of an emergency, and transferring data between the sensor network and the cloud. A web-based application is developed for the depiction of raw data and ML results and to provide a direct communication channel between the patient and the doctor. The ML module achieved an accuracy of 96.26% on the test set using the K-Nearest Neighbors (KNNs) algorithm. This solution aims to address the sense of emergency due to the alarming statistics that highlight the mortality rate of cardiovascular patients. The project will enable a smart option based on IoT and ML to improve standards of living and prove crucial in saving human lives.
Indoor-Guided Navigation for People Who Are Blind: Crowdsourcing for Route Mapping and Assistance
Authors: Plikynas Darius , Indriulionis Audrius , Laukaitis Algirdas , Sakalauskas Leonidas
Published: January 2022

This paper presents an approach to enhance electronic traveling aids (ETAs) for people who are blind and severely visually impaired (BSVI) using indoor orientation and guided navigation by employing social outsourcing of indoor route mapping and assistance processes. This type of approach is necessary because GPS does not work well, and infrastructural investments are absent or too costly to install for indoor navigation. Our approach proposes the prior outsourcing of vision-based recordings of indoor routes from an online network of seeing volunteers, who gather and constantly update a web cloud database of indoor routes using specialized sensory equipment and web services. Computational intelligence-based algorithms process sensory data and prepare them for BSVI usage. In this way, people who are BSVI can obtain ready-to-use access to the indoor routes database. This type of service has not previously been offered in such a setting. Specialized wearable sensory ETA equipment, depth cameras, smartphones, computer vision algorithms, tactile and audio interfaces, and computational intelligence algorithms are employed for that matter. The integration of semantic data of points of interest (such as stairs, doors, WC, entrances/exits) and evacuation schemes could make the proposed approach even more attractive to BVSI users. Presented approach crowdsources volunteers’ real-time online help for complex navigational situations using a mobile app, a live video stream from BSVI wearable cameras, and digitalized maps of buildings’ evacuation schemes.
Negotiating Uneven Terrain by a Simple Teleoperated Tracked Vehicle with Internally Movable Center of Gravity
Authors: Fukuoka Yasuhiro , Oshino Kazuyuki , Ibrahim Ahmad Najmuddin
Published: January 2022

We propose a mechanical design for a simple teleoperated unmanned ground vehicle (UGV) to negotiate uneven terrain. UGVs are typically classified into legged, legged-wheeled, wheeled, and tanked forms. Legged vehicles can significantly shift their center of gravity (COG) by positioning their multi-articulated legs at appropriate trajectories, stepping over a high obstacle. To realize a COG movable mechanism with a small number of joints, a number of UGVs have been developed that can shift their COG by moving a mass at a high position above the body. However, these tend to pose a risk of overturning, and the mass must be moved quite far to climb a high step. To address these issues, we design a novel COG shift mechanism, in which the COG can be shifted forward and backward inside the body by moving most of its internal devices. Since this movable mass includes DC motors for driving both tracks, we can extend the range of the COG movement. We demonstrate that a conventional tracked vehicle prototype can traverse a step and a gap between two steps, as well as climb stairs and a steep slope, with a human operating the vehicle movement and the movable mass position.
Data Augmentation for Audio-Visual Emotion Recognition with an Efficient Multimodal Conditional GAN
Authors: Ma Fei , Li Yang , Ni Shiguang , Huang Shao-Lun , Zhang Lin
Published: January 2022

Audio-visual emotion recognition is the research of identifying human emotional states by combining the audio modality and the visual modality simultaneously, which plays an important role in intelligent human-machine interactions. With the help of deep learning, previous works have made great progress for audio-visual emotion recognition. However, these deep learning methods often require a large amount of data for training. In reality, data acquisition is difficult and expensive, especially for the multimodal data with different modalities. As a result, the training data may be in the low-data regime, which cannot be effectively used for deep learning. In addition, class imbalance may occur in the emotional data, which can further degrade the performance of audio-visual emotion recognition. To address these problems, we propose an efficient data augmentation framework by designing a multimodal conditional generative adversarial network (GAN) for audio-visual emotion recognition. Specifically, we design generators and discriminators for audio and visual modalities. The category information is used as their shared input to make sure our GAN can generate fake data of different categories. In addition, the high dependence between the audio modality and the visual modality in the generated multimodal data is modeled based on Hirschfeld-Gebelein-Rényi (HGR) maximal correlation. In this way, we relate different modalities in the generated data to approximate the real data. Then, the generated data are used to augment our data manifold. We further apply our approach to deal with the problem of class imbalance. To the best of our knowledge, this is the first work to propose a data augmentation strategy with a multimodal conditional GAN for audio-visual emotion recognition. We conduct a series of experiments on three public multimodal datasets, including eNTERFACE’05, RAVDESS, and CMEW. The results indicate that our multimodal conditional GAN has high effectiveness for data augmentation of audio-visual emotion recognition.
An Ultra-Wideband Vivaldi Antenna System for Long-Distance Electromagnetic Detection
Authors: Ren Jinjing , Fan Hezhihan , Tang Qi , Yu Zhongyuan , Xiao Yang , Zhou Xiang
Published: January 2022

Enlarging or reducing the antenna beam width of antennas can improve the positioning capability of detection systems. A miniaturized and easily fabricated ultra-wideband (UWB) antenna system for long-distance electromagnetic detection is proposed in this article. Two ultra-wideband Vivaldi antennae were designed. One was the transmitting antenna with a beam width of 90° or above, the other was a narrow beam antenna array with beam width less than 10°, as a receiving antenna. Both proposed antennae feature broadside gain diagrams with stable radiation patterns and wideband impedance matching in the frequency range between 2.5 GHz and 4 GHz. After detecting their frequency and time-domain behaviors, the detection system can achieve measurements covering a radius of 30 m.
Electronic Voting System Using an Enterprise Blockchain
Authors: Denis González Camilo , Frias Mena Daniel , Massó Muñoz Alexi , Rojas Omar , Sosa-Gómez Guillermo
Published: January 2022

Conventional electronic voting systems use a centralized scheme. A central administration of these systems manages the entire voting process and has partial or total control over the database and the system itself. This creates some problems, accidental or intentional, such as possible manipulation of the database and double voting. Many of these problems have been solved thanks to permissionless blockchain technologies in new voting systems; however, the classic consensus method of such blockchains requires specific computing power during each voting operation. This has a significant impact on power consumption, compromises the efficiency and increases the system latency. However, using a permissioned blockchain improves efficiency and reduces system energy consumption, mainly due to the elimination of the typical consensus protocols used by public blockchains. The use of smart contracts provides a secure mechanism to guarantee the accuracy of the voting result and make the counting procedure public and protected against fraudulent actions, and contributes to preserving the anonymity of the votes. Its adoption in electronic voting systems can help mitigate part of these problems. Therefore, this paper proposes a system that ensures high reliability by applying enterprise blockchain technology to electronic voting, securing the secret ballot. In addition, a flexible network configuration is presented, discussing how the solution addresses some of the security and reliability issues commonly faced by electronic voting system solutions.
Using Deep Learning for Collecting Data about Museum Visitor Behavior
Authors: Ferrato Alessio , Limongelli Carla , Mezzini Mauro , Sansonetti Giuseppe
Published: January 2022

Nowadays, technology makes it possible to admire objects and artworks exhibited all over the world remotely. We have been able to appreciate this convenience even more in the last period, in which the pandemic has forced us into our homes for a long time. However, visiting art sites in person remains a truly unique experience. Even during on-site visits, technology can help make them much more satisfactory, by assisting visitors during the fruition of cultural and artistic resources. To this aim, it is necessary to monitor the active user for acquiring information about their behavior. We, therefore, need systems able to monitor and analyze visitor behavior. The literature proposes several techniques for the timing and tracking of museum visitors. In this article, we propose a novel approach to indoor tracking that can represent a promising and non-expensive solution for some of the critical issues that remain. In particular, the system we propose relies on low-cost equipment (i.e., simple badges and off-the-shelf RGB cameras) and harnesses one of the most recent deep neural networks (i.e., Faster R-CNN) for detecting specific objects in an image or a video sequence with high accuracy. An experimental evaluation performed in a real scenario, namely, the “Exhibition of Fake Art” at Roma Tre University, allowed us to test our system on site. The collected data has proven to be accurate and helpful for gathering insightful information on visitor behavior.
An Inductively Coupled Plasma Optical Emission Spectrometric Method for the Determination of Toxic and Nutrient Metals in Spices after Pressure-Assisted Digestion
Authors: Manousi Natalia , Isaakidou Eleni , Zachariadis George A.
Published: January 2022

The aim of this study was to develop a simple and rapid inductively coupled plasma optical emission spectrometric (ICP-OES) method for the determination of 17 metals (Ag, Al, B, Ba, Bi, Ca, Cd, Co, Cr, Cu, Fe, Mg, Mn, Ni, Pb, Tl and Zn) in packaged spices. For this purpose, the spice samples (200 mg) in the form of powder were submitted to pressure-assisted wet-acid digestion with a mixture of 6 mL concentrated HNO3 and 1 mL H2O2. The proposed method was validated in terms of linearity, trueness, precision, limits of detection (LODs) and limits of quantification (LOQs). Good method trueness, precision and linearity were observed for the examined elements. The LODs of the examined analytes ranged between 0.08 and 5.95 mg kg−1. The present method was employed for the analysis of twenty-two packaged commercially available spices including asteroid anise, clove, cardamon, cinnamon, curry, coriander, turmeric, cumin, white pepper, black pepper, nutmeg, allspice, red pepper, paprika, ginger, green pepper and pink pepper from the Greek market that are widely consumed. A wide variety of metal of different concentration ranges were determined in the samples.
A Large Area Pixelated Silicon Array Detector for Independent Transit In Vivo Dosimetry
Authors: Brace Owen J. , Fuduli Iolanda , Alnaghy Saree , Le Albert T. , Davis Jeremy A. , Causer Trent , Wilkinson Dean , Perevertaylo Aleksandr , Rosenfeld Anatoly B. , Petasecca Marco
Published: January 2022

A large area pixelated silicon array detector named “MP987” has been developed for in vivo dosimetry. The detector was developed to overcome the non-water equivalent response of EPID (Electronic Portal Imaging Device) dosimetry systems, due to the shortfalls of the extensive corrections required. The detector, readout system and software have all been custom designed to be operated independently from the linac with the array secured directly above the EPID, to be used in combination with the 6 MV imaging system. Dosimetry characterisation measurements of percentage depth dose (PDD), dose rate dependence, radiation damage, output factors (OF), profile measurements, linearity and uniformity were performed. Additionally, the first pre-clinical tests with this novel detector of a transit dosimetry characterization and a collapsed IMRT (intensity-modulated radiation therapy) study are presented. Both PDD and OF measurements had a percentage difference of less than 2.5% to the reference detector. A maximum change in sensitivity of 4.3 ± 0.3% was observed after 30 kGy of gamma accumulated dose. Transit dosimetry measurements through a homogeneous Solid Water phantom had a measured dose within error of the TPS calculations, for field sizes between 3 × 3 cm2 and 10 × 10 cm2. A four-fraction collapsed IMRT plan on a lung phantom had absolute dose pass fractions between the MP987 and TPS (treatment planning system) from 94.2% to 97.4%, with a 5%/5 mm criteria. The ability to accurately measure dose at a transit level, without the need for correction factors derived from extensive commissioning data collection procedures, makes the MP987 a viable alternative to the EPID for in vivo dosimetry. This MP987 is this first of its kind to be successfully developed specifically for a dual detector application.
A New Integrated Multi-Criteria Decision-Making Model for Resilient Supplier Selection
Authors: Leong Wan Yee , Wong Kuan Yew , Wong Wai Peng
Published: January 2022

Unexpected worldwide disruptions brought various challenges to supply chain management thus manipulating the research direction towards resilience. Since the supplier is one of the important supply chain elements, the challenges can be overcome through resilient supplier selection. Supplier selection is a multi-criteria decision-making problem where several criteria are involved. In this study, GRA-BWM-TOPSIS was proposed to evaluate resilient suppliers. Seven resilience criteria which were Quality, Lead Time, Cost, Flexibility, Visibility, Responsiveness and Financial Stability have been proposed and five experts were selected to provide judgments for the selection process. By using the proposed method, the criteria importance levels were obtained using GRA and the criteria weights were computed using BWM, together with a consistency test. TOPSIS was applied to evaluate the suppliers’ performances. Through a case study in a food manufacturing company, 10 suppliers were evaluated and ranked. A validation process was carried out and the managerial implications were provided to ensure the effectiveness of the proposed model. GRA-BWM-TOPSIS is suitable for resilient supplier selection when there are uncertainties and incomplete data.
Evaluating the Utility of High-Resolution Spatiotemporal Air Pollution Data in Estimating Local PM2.5 Exposures in California from 2015–2018
Authors: Gladson Laura , Garcia Nicolas , Bi Jianzhao , Liu Yang , Lee Hyung Joo , Cromar Kevin
Published: January 2022

Air quality management is increasingly focused not only on across-the-board reductions in ambient pollution concentrations but also on identifying and remediating elevated exposures that often occur in traditionally disadvantaged communities. Remote sensing of ambient air pollution using data derived from satellites has the potential to better inform management decisions that address environmental disparities by providing increased spatial coverage, at high-spatial resolutions, compared to air pollution exposure estimates based on ground-based monitors alone. Daily PM2.5 estimates for 2015–2018 were estimated at a 1 km2 resolution, derived from NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) satellite instrument and the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm in order to assess the utility of highly refined spatiotemporal air pollution data in 92 California cities and in the 13 communities included in the California Community Air Protection Program. The identification of pollution hot-spots within a city is typically not possible relying solely on the regulatory monitoring networks; however, day-to-day temporal variability was shown to be generally well represented by nearby ground-based monitoring data even in communities with strong spatial gradients in pollutant concentrations. An assessment of within-ZIP Code variability in pollution estimates indicates that high-resolution pollution estimates (i.e., 1 km2) are not always needed to identify spatial differences in exposure but become increasingly important for larger geographic areas (approximately 50 km2). Taken together, these findings can help inform strategies for use of remote sensing data for air quality management including the screening of locations with air pollution exposures that are not well represented by existing ground-based air pollution monitors.
Lithium Silicates in Anode Materials for Li-Ion and Li Metal Batteries
Authors: Su Yu-Sheng , Hsiao Kuang-Che , Sireesha Pedaballi , Huang Jen-Yen
Published: January 2022

The structural and interfacial stability of silicon-based and lithium metal anode materials is essential to their battery performance. Scientists are looking for a better inactive material to buffer strong volume change and suppress unwanted surface reactions of these anodes during cycling. Lithium silicates formed in situ during the formation cycle of silicon monoxide anode not only manage anode swelling but also avoid undesired interfacial interactions, contributing to the successful commercialization of silicon monoxide anode materials. Additionally, lithium silicates have been further utilized in the design of advanced silicon and lithium metal anodes, and the results have shown significant promise in the past few years. In this review article, we summarize the structures, electrochemical properties, and formation conditions of lithium silicates. Their applications in advanced silicon and lithium metal anode materials are also introduced.