bluuebunny/crossref_metadata_2025 huggingface dataset:
Development of Intelligent Gelatin Films Incorporated with Sappan (Caesalpinia sappan L.) Heartwood Extract
Authors: Romruen Orapan , Kaewprachu Pimonpan , Karbowiak Thomas , Rawdkuen Saroat
Published: June 2022

This study aimed to develop intelligent gelatin films incorporated with sappan (Caesalpinia sappan L.) heartwood extracts (SE) and characterize their properties. The intelligent gelatin film was prepared through a casting method from gelatin (3%, w/v), glycerol (25% w/w, based on gelatin weight), and SE at various concentrations (0, 0.25, 0.50, 0.75, and 1.00%, w/v). The thickness of the developed films ranged from 43 to 63 μm. The lightness and transparency of the films decreased with the increasing concentration of SE (p < 0.05). All concentrations of gelatin films incorporated with SE exhibited great pH sensitivity, as indicated by changes in film color at different pH levels (pH 1–12). Significant decreases in tensile strength were observed at 1.00% SE film (p < 0.05). The addition of SE reduced gelatin films’ solubility and water vapor permeability (p < 0.05). The chemical and physical interactions between gelatin and SE affected the absorption peaks in FTIR spectra. SE was affected by increased total phenolic content (TPC) and antioxidant activity of the gelatin film, and the 1.00% SE film showed the highest TPC (15.60 mg GAE/g db.) and antioxidant activity (DPPH: 782.71 μM Trolox/g db. and FRAP: 329.84 mM/g db.). The gelatin films combined with SE could inhibit S. aureus and E. coli, while the inhibition zone was not observed for E. coli; it only affected the film surface area. The result suggested that gelatin films incorporated with SE can be used as an intelligent film for pH indicators and prolong the shelf life of food due to their antioxidant and antimicrobial activities.
Thermomechanical and Fire Properties of Polyethylene-Composite-Filled Ammonium Polyphosphate and Inorganic Fillers: An Evaluation of Their Modification Efficiency
Authors: Barczewski Mateusz , Hejna Aleksander , Sałasińska Kamila , Aniśko Joanna , Piasecki Adam , Skórczewska Katarzyna , Andrzejewski Jacek
Published: June 2022

The development of new polymer compositions characterized by a reduced environmental impact while lowering the price for applications in large-scale production requires the search for solutions based on the reduction in the polymer content in composites’ structure, as well as the use of fillers from sustainable sources. The study aimed to comprehensively evaluate introducing low-cost inorganic fillers, such as copper slag (CS), basalt powder (BP), and expanded vermiculite (VM), into the flame-retarded ammonium polyphosphate polyethylene composition (PE/APP). The addition of fillers (5–20 wt%) increased the stiffness and hardness of PE/APP, both at room and at elevated temperatures, which may increase the applicability range of the flame retardant polyethylene. The deterioration of composites’ tensile strength and impact strength induced by the presence of inorganic fillers compared to the unmodified polymer is described in detail. The addition of BP, CS, and VM with the simultaneous participation of APP with a total share of 40 wt% caused only a 3.1, 4.6, and 3 MPa decrease in the tensile strength compared to the reference value of 23 MPa found for PE. In turn, the cone calorimeter measurements allowed for the observation of a synergistic effect between APP and VM, reducing the peak heat rate release (pHRR) by 60% compared to unmodified PE. Incorporating fillers with a similar thermal stability but differing particle size distribution and shape led to additional information on their effectiveness in changing the properties of polyethylene. Critical examinations of changes in the mechanical and thermomechanical properties related to the structure analysis enabled the definition of the potential application perspectives analyzed in terms of burning behavior in a cone calorimetry test. Adding inorganic fillers derived from waste significantly reduces the flammability of composites with a matrix of thermoplastic polymers while increasing their sustainability and lowering their price without considerably reducing their mechanical properties, which allows for assigning developed materials as a replacement for flame-retarded polyethylene in large-scale non-loaded parts.
Development of an Antibacterial Dentin Adhesive
Authors: Lopes Stephanie R. , Matuda Amanda G. N. , Campos Raquel P. , Mafetano Ana Paula V. P. , Barnabe Ana Helena M. , Chagas Gabriela S. , Barcellos Daphne C. , Niu Li-Na , Tay Franklin R. , Pucci Cesar R.
Published: June 2022

Nisin is a peptide that possesses potent antibacterial properties. This study evaluated the antibacterial activity of a nisin-doped adhesive against Streptococcus mutans, as well as its degree of conversion and microtensile bond strength (μTBS) to dentin. Nisin was added to the adhesive Adper Single Bond 2 (3M ESPE), resulting in four groups: Control Group (Single Bond 2); Group 1% (1 wt% nisin-incorporated), Group 3% (3 wt% nisin-incorporated) and Group 5% (5 wt% nisin-incorporated). Antibacterial activity against S. mutans was evaluated using colony-forming unit counts (CFU). The degree of conversion was tested using FTIR. Forty human teeth were restored for μTBS evaluation. Data were statistically analyzed with ANOVA and Tukey tests at α = 0.05. The nisin-doped adhesives, for all concentrations, exhibited a significant inhibition of the growth of S. mutans (p < 0.05); Incorporation of 5% and 3% nisin decreased the degree of conversion of the adhesive (p < 0.05). The μTBS (in MPa): Control Group—38.3 ± 2.3A, Group 1%—35.6 ± 2.1A, Group 3%—27.1 ± 1.6B and Group 5%—22.3 ± 1.0C. Nisin-doped adhesives exerted a bactericidal effect on S. mutans. The μTBS and degree of conversion of adhesive were not affected after incorporation of 1% nisin.
Exergy Analysis of Reactive Distillation Coupled with High-Pressure Column for the Synthesis of Dimethyl Carbonate
Authors: Alharthi Mathkar A.
Published: June 2022

In this article, the Dimethyl Carbonate (DMC) synthesis process was investigated thermodynamically based on a well-optimized DMC system for a developed configuration, according to a real industrial plant, presented by Huang et al. Exergy analysis was performed using ProSimPlus software as an efficient process modeling and simulation environment that is uniquely capable of exergy balance computations. The key operational variables such as the reflux ratio (Rr), feed temperatures, and feed tray location were varied to explore their impact on the total irreversibilities, global intrinsic efficiency, and DMC purity. The influence of the high pressure (HP) column reflux ratio was the most effective parameter on the exergy destruction and DMC purity, which also significantly increased the duties of the HP column reboiler and condenser. The steady state results are reported in comparison with those found in the literature, and an excellent match is shown between them.
EOQ Models for Imperfect Items under Time Varying Demand Rate
Authors: Lok Yi Wen , Supadi Siti Suzlin , Wong Kok Bin
Published: June 2022

In the classical Economic Order Quantity (EOQ) model, the common unrealistic assumptions are that all the purchased items are of perfect quality and the demand is constant. However, in a real-world environment, a portion of the purchased items might be damaged due to mishandling or an accident during the shipment process, and the demand rate may increase or decrease over time. Many companies are torn between repairing or replacing the imperfect items with new ones. The right decision on that options is crucial in order to guarantee that there is no shortage of stocks while at the same time not jeopardising the items’ quality and maximising the company’s profit. This paper investigates two EOQ models for imperfect quality items by assuming the demand rate varies with time. Under Policy 1, imperfect items are sent for repairs at an additional cost to the makeup margin; under Policy 2, imperfect items are replaced with equivalent quality items from a local supplier at a higher price. Two mathematical models are developed, and numerical examples along with sensitivity analyses are provided to illustrate these models. Our results reveal that Policy 1 is preferable to Policy 2 most of the time. However, Policy 2 outperforms Policy 1 if there is no minimum threshold on the purchased stock quantity. This research allows a company to discover solutions to previously identified inventory problems and make the inventory-patching process more controlled.
MHD Williamson Nanofluid Fluid Flow and Heat Transfer Past a Non-Linear Stretching Sheet Implanted in a Porous Medium: Effects of Heat Generation and Viscous Dissipation
Authors: Abbas Amir , Jeelani Mdi Begum , Alnahdi Abeer S. , Ilyas Asifa
Published: June 2022

The present study is carried out to examine the behavior of magnetohydrodynamic Williamson nanofluid flow and heat transfer over a non-linear stretching sheet embedded in a porous medium. In the current work, the influence of heat generation and viscous dissipation has been taken into account. The considered phenomenon in the form of partial differential equations is transformed into ordinary differential equations by utilizing an appropriate similarity transformation. The reduced form is solved by using rigorous MATLAB built-in solver bvp4c. The numerical solutions for the velocity field, temperature field, and mass concentration along with the skin friction coefficient, Nusselt number, and Sherwood number are computed. The obtained solutions are shown in graphs and are discussed with physical reasoning. It is noted that by increasing Williamson fluid parameter W, the velocity decreases and concentration profile increases. It is deduced that increasing Eckert number Ec leads to a rise in temperature and mass concentration. It has been viewed that with the increment in heat generation parameter Q, the temperature field increases and concentration decreases. The results show that an increasing magnetic field parameter M leaves a decreasing trend in the velocity field and an increasing trend in the temperature field and concentration profile. The present results are compared with the existing solution which shows good agreement and endorses the validation of current solutions.
Community Seedbanks in Uganda: Fostering Access to Genetic Diversity and Its Conservation
Authors: Nankya Rose , Jika Abdel Kader Naino , De Santis Paola , Lwandasa Hannington , Jarvis Devra Ivy , Mulumba John Wasswa
Published: June 2022

Community seedbanks promote conservation and the use of crop genetic diversity, as well as supporting farmer seed systems. This study analyses seed flow and access to crop genetic diversity over time in the Nakaseke, Rubaya, and Kibuga seedbanks of Uganda. The modes of operation of the banks were compared through scrutinizing records of crops and varieties being conserved, quantities of seed distributed, to whom, and quantities returned. The Nakaseke seed bank distributed the highest varietal diversity of common bean (Phaseolus vulgaris) and groundnuts (Arachis hypogaea L.), whereas the Rubaya seedbank distributed the highest quantity of common bean seed, followed by the Kibuga seedbank. There were no significant differences between the type of variety of seed, quantities of seed accessed, and seed returned to the seedbanks by women and men—except for the Nakaseke seedbank, where women returned significantly higher quantities of common bean seed. The Kibuga and Rubaya seedbanks dealt with individual farmers, whereas the Nakaseke seedbank dealt with individual farmers and groups. The extent to which core functions were achieved by a particular seedbank depended on the mode of operation, including actors, management, degree of development, socio-economic setting, among others. Further research is recommended to unpack these factors and come up with the most appropriate combinations for greater seedbank effectiveness.
Ultra-Wide Band Double-Slot Podal and Antipodal Vivaldi Antennas Feed by Compact Out-Of-Phase Power Divider Slot for Fluid Properties Determination
Authors: Ghimire Jiwan , Choi Dong-You
Published: June 2022

In this paper, double slot podal and antipodal ultra-wideband (UWB) microstrip antennas for a fluid property measurement system are proposed. Among different feeding techniques, out of phase uni-planner power divider approach is used. The performance verification of the proposed antenna is explained, along with a performance comparison of the antenna bandwidth, feeding, and the realized gain. The suggested podal antenna has an impedance bandwidth from 2.4 to 15.4 GHz, with a maximum gain of 11.3 dBi in the 12 GHz region while the antipodal antenna has a 2.8 GHz to 16 GHz impedance bandwidth, with a maximum gain of 10.4 dBi in the 10 GHz region. Within the intended band, the radiation pattern had an excellent directivity characteristic. The implementation of the proposed antenna is calibrated by measuring the propagated signals response via various liquid specimens using UWB radar, which might be applied for fluid sensing and prediction purposes. The proposed antenna was connected to an NVA-R661 module of Xethru Inc. for measuring the sample delay and peak-to-peak amplitude of the received signals passing through specimens. The measured parameters at a different radar frequency range of transmission are applied by drawing the fluid viscous analogy based on Poiseuille’s law hypothesis, showing clear differentiation between the test specimens.
A Statistical Approach for A-Posteriori Deployment of Microclimate Sensors in Museums: A Case Study
Authors: Frasca Francesca , Verticchio Elena , Merello Paloma , Zarzo Manuel , Grinde Andreas , Fazio Eugenio , García-Diego Fernando-Juan , Siani Anna Maria
Published: June 2022

The deployment of sensors is the first issue encountered when microclimate monitoring is planned in spaces devoted to the conservation of artworks. Sometimes, the first decision regarding the position of sensors may not be suitable for characterising the microclimate close to climate-sensitive artworks or should be revised in light of new circumstances. This paper fits into this context by proposing a rational approach for a posteriori deployment of microclimate sensors in museums where long-term temperature and relative humidity observations were available (here, the Rosenborg Castle, Copenhagen, Denmark). Different statistical tools such as box-and-whisker plots, principal component analysis (PCA) and cluster analysis (CA) were used to identify microclimate patterns, i.e., similarities of indoor air conditions among rooms. Box-and-whisker plots allowed us to clearly identify one microclimate pattern in two adjoining rooms located in the basement. Multivariate methods (PCA and CA) enabled us to identify further microclimate patterns by grouping not only adjoining rooms but also rooms located on different floors. Based on these outcomes, new configurations about the deployment of sensors were proposed aimed at avoiding redundant sensors and collecting microclimate observations in other sensitive locations of this museum.
Remaining Useful Life Prediction Method for Bearings Based on LSTM with Uncertainty Quantification
Authors: Yang Jinsong , Peng Yizhen , Xie Jingsong , Wang Pengxi
Published: June 2022

To reduce the economic losses caused by bearing failures and prevent safety accidents, it is necessary to develop an effective method to predict the remaining useful life (RUL) of the rolling bearing. However, the degradation inside the bearing is difficult to monitor in real-time. Meanwhile, external uncertainties significantly impact bearing degradation. Therefore, this paper proposes a new bearing RUL prediction method based on long-short term memory (LSTM) with uncertainty quantification. First, a fusion metric related to runtime (or degradation) is proposed to reflect the latent degradation process. Then, an improved dropout method based on nonparametric kernel density is developed to improve estimation accuracy of RUL. The PHM2012 dataset is adopted to verify the proposed method, and comparison results illustrate that the proposed prediction model can accurately obtain the point estimation and probability distribution of the bearing RUL.
Investigation of Temperature Variations and Extreme Temperature Differences for the Corrugated Web Steel Beams under Solar Radiation
Authors: Huang Shiji , Cai Chenzhi , Zou Yunfeng , He Xuhui , Zhou Tieming
Published: June 2022

Due to the coupling impacts of solar radiation, wind, air temperature and other environmental parameters, the temperature field of steel structures is significantly non-uniform during their construction and service stages. Corrugated web steel beams have gained popularity in structural engineering during the last few decades, while their thermal actions are barely investigated. In this paper, both experimental and numerical investigations were conducted to reveal the non-uniform features and time variation of the corrugated web steel beams under various environmental conditions. The heat-transfer simulation model was established and verified using the experimental temperature data. Both the experiment and simulation results demonstrate that the steel beam has a complicated and non-uniform temperature field. Moreover, 2-year continuous numerical simulations of steel beams’ thermal actions regarding eight different cities were carried out to investigate the long-term temperature variations. Finally, based on the long-term simulation results and extreme value analysis (EVA), the representative values of steel beams’ daily temperature difference with a 50-year return period were determined. The extreme temperature difference of the steel beam in Harbin reached up to 46.9 °C, while the extreme temperature difference in Haikou was 28.8 °C. The extreme temperature difference is highly associated with the steel beam’s location and surrounding climate. Ideally, the outcomes will provide some contributions for the structural design regarding the corrugated web steel beam.
Integration of Inertial Sensors in a Lower Limb Robotic Exoskeleton
Authors: Calle-Siguencia John , Callejas-Cuervo Mauro , García-Reino Sebastián
Published: June 2022

Motion assistance exoskeletons are designed to support the joint movement of people who perform repetitive tasks that cause damage to their health. To guarantee motion accompaniment, the integration between sensors and actuators should ensure a near-zero delay between the signal acquisition and the actuator response. This study presents the integration of a platform based on Imocap-GIS inertial sensors, with a motion assistance exoskeleton that generates joint movement by means of Maxon motors and Harmonic drive reducers, where a near zero-lag is required for the gait accompaniment to be correct. The Imocap-GIS sensors acquire positional data from the user’s lower limbs and send the information through the UDP protocol to the CompactRio system, which constitutes a high-performance controller. These data are processed by the card and subsequently a control signal is sent to the motors that move the exoskeleton joints. Simulations of the proposed controller performance were conducted. The experimental results show that the motion accompaniment exhibits a delay of between 20 and 30 ms, and consequently, it may be stated that the integration between the exoskeleton and the sensors achieves a high efficiency. In this work, the integration between inertial sensors and an exoskeleton prototype has been proposed, where it is evident that the integration met the initial objective. In addition, the integration between the exoskeleton and IMOCAP is among the highest efficiency ranges of similar systems that are currently being developed, and the response lag that was obtained could be improved by means of the incorporation of complementary systems.
A New Frequency Analysis Operator for Population Improvement in Genetic Algorithms to Solve the Job Shop Scheduling Problem
Authors: Viana Monique Simplicio , Contreras Rodrigo Colnago , Morandin Junior Orides
Published: June 2022

Job Shop Scheduling is currently one of the most addressed planning and scheduling optimization problems in the field. Due to its complexity, as it belongs to the NP-Hard class of problems, meta-heuristics are one of the most commonly used approaches in its resolution, with Genetic Algorithms being one of the most effective methods in this category. However, it is well known that this meta-heuristic is affected by phenomena that worsen the quality of its population, such as premature convergence and population concentration in regions of local optima. To circumvent these difficulties, we propose, in this work, the use of a guidance operator responsible for modifying ill-adapted individuals using genetic material from well-adapted individuals. We also propose, in this paper, a new method of determining the genetic quality of individuals using genetic frequency analysis. Our method is evaluated over a wide range of modern GAs and considers two case studies defined by well-established JSSP benchmarks in the literature. The results show that the use of the proposed operator assists in managing individuals with poor fitness values, which improves the population quality of the algorithms and, consequently, leads to obtaining better results in the solution of JSSP instances. Finally, the use of the proposed operator in the most elaborate GA-like method in the literature was able to reduce its mean relative error from 1.395% to 0.755%, representing an improvement of 45.88%.
Target Detection Based on Improved Hausdorff Distance Matching Algorithm for Millimeter-Wave Radar and Video Fusion
Authors: Xu Dongpo , Liu Yunqing , Wang Qian , Wang Liang , Liu Renjun
Published: June 2022

The intelligent transportation system (ITS) is inseparable from people’s lives, and the development of artificial intelligence has made intelligent video surveillance systems more widely used. In practical traffic scenarios, the detection and tracking of vehicle targets is an important core aspect of intelligent surveillance systems and has become a hot topic of research today. However, in practical applications, there is a wide variety of targets and often interference factors such as occlusion, while a single sensor is unable to collect a wealth of information. In this paper, we propose an improved data matching method to fuse the video information obtained from the camera with the millimetre-wave radar information for the alignment and correlation of multi-target data in the spatial dimension, in order to address the problem of poor recognition alignment caused by mutual occlusion between vehicles and external environmental disturbances in intelligent transportation systems. The spatio-temporal alignment of the two sensors is first performed to determine the conversion relationship between the radar and pixel coordinate systems, and the calibration on the timeline is performed by Lagrangian interpolation. An improved Hausdorff distance matching algorithm is proposed for the data dimension to calculate the similarity between the data collected by the two sensors, to determine whether they are state descriptions of the same target, and to match the data with high similarity to delineate the region of interest (ROI) for target vehicle detection.
Optimal Rotational Angular Velocity Determination Method Based on Compound Rotary Semi-Strapdown Inertial Navigation System
Authors: Zhang Chenming , Li Jie , Yuan Xiaoqiao , Zhang Xi , Wei Xiaokai , Feng Kaiqiang , Hu Chenjun , Zhang Debiao , Jiao Yubing
Published: June 2022

Single-axis rotation modulation (SRM) still accumulates errors in the roll axis direction, which leads to the navigation accuracy not meeting the requirements of guided missiles. Compound rotation modulation (CRM) superimposes one-dimensional rotation on the basis of SRM, so that the error of the projectile in the direction of the roll axis is also modulated. However, the error suppression effect of CRM is not only affected by the error of the IMU itself, but also related to the modulation angular velocity. In order to improve the accuracy of rotary semi-strapdown inertial navigation system (RSSINS), this paper proposes an optimal rotation angular velocity determination method. Firstly, the residual error in CRM scheme is analyzed; then, the relationship between the incomplete modulation error and the modulation angular velocity in CRM is discussed; finally, a method for determining the optimal modulation angular velocity is proposed (K-value method). The analysis of the results shows that the navigation accuracy of the guided projectile is effectively improved with the rotation scheme set at the modulation angular velocity determined by the K-value method.
Scan Time Reduction of PLCs by Dedicated Parallel-Execution Multiple PID Controllers Using an FPGA
Authors: Dhanabalan Gnanasekaran , Tamil Selvi Sankar , Mahdal Miroslav
Published: June 2022

A programmable logic controller (PLC) executes a ladder diagram (LD) using input and output modules. An LD also has PID controller function blocks. It contains as many PID function blocks as the number of process parameters to be controlled. Adding more process parameters slows down PLC scan time. Process parameters are measured as analog signals. The analog input module in the PLC converts these analog signals into digital signals and forwards them to the PID controller as inputs. In this research work, a field-programmable gate array (FPGA)-based multiple PID controller is proposed to retain PLC scan time at a lower value. Concurrent execution of multiple PID controllers was assured by assigning separate FPGA hardware resources for every PID controller. Digital input to the PID controller is routed by the novel idea of analog to digital conversion (ADC), performed using a digital to analog converter (DAC), comparator, and FPGA. ADC combined with dedicated PID controller logic in an FPGA for every closed-loop control system confirms concurrent execution of multiple PID controllers. The time required to execute two closed-loop controls was identified as 18.96000004 ms. This design can be used either with or without a PLC.
Blockchain Privacy and Scalability in a Decentralized Validated Energy Trading Context with Hyperledger Fabric
Authors: Westphall Johann , Martina Jean Everson
Published: June 2022

Lower renewable energy generator prices are leading people to install solar panels to reduce their electricity bills or, in some cases, even sell the surplus generated energy to the grid and earn credits from the grid operator. Generally, they are limited to trading the energy they generate with the grid company, which has a dominant role in price determination. Decentralized energy markets might increase both market competitiveness and incentive to further people’s adoption of renewable energy, reducing security vulnerabilities and improving resiliency. Blockchain is a widely studied technology to provide decentralization for energy markets in this context. Scalability, privacy, market design, and user security are some of the open research topics. This work analyzes the literature related to blockchain and energy markets, proposes a model, implements it, performs experiments, and analyzes network scalability and data generation. The model, implemented with Hyperledger Fabric, enables validated clean energy trading with anonymized buyers to prevent consumption pattern exposure. The maximum transaction throughput was achieved with 5000 sensors, 5000 buyers, and 5000 sellers. The data generation rate by network and the baseline deployment costs were also analyzed to judge the network viability. Furthermore, this work provides empirical results on a topic that the literature lacks.
A Novel Image Inpainting Method Used for Veneer Defects Based on Region Normalization
Authors: Ge Yilin , Chen Jiahao , Lou Yunyi , Cui Mingdi , Zhou Hongju , Zhou Hongwei , Sun Liping
Published: June 2022

The quality of the veneer directly affects the quality and grade of a blockboard made of veneer. To improve the quality and utilization of a defective veneer, a novel deep generative model-based method is proposed, which can generate higher-quality inpainting results. A two-phase network is proposed to stabilize the network training process. Then, region normalization is introduced to solve the inconsistency problem between the mean and standard deviation, improve the convergence speed of the model, and prevent the model gradient from exploding. Finally, a hybrid dilated convolution module is proposed to reconstruct the missing areas of the panels, which alleviates the gridding problem by changing the dilation rate. Experiments on our dataset prove the effectiveness of the improved approach in image inpainting tasks. The results show that the PSNR of the improved method reaches 33.11 and the SSIM reaches 0.93, which are superior to other methods.
The State-of-the-Art Sensing Techniques in Human Activity Recognition: A Survey
Authors: Bian Sizhen , Liu Mengxi , Zhou Bo , Lukowicz Paul
Published: June 2022

Human activity recognition (HAR) has become an intensive research topic in the past decade because of the pervasive user scenarios and the overwhelming development of advanced algorithms and novel sensing approaches. Previous HAR-related sensing surveys were primarily focused on either a specific branch such as wearable sensing and video-based sensing or a full-stack presentation of both sensing and data processing techniques, resulting in weak focus on HAR-related sensing techniques. This work tries to present a thorough, in-depth survey on the state-of-the-art sensing modalities in HAR tasks to supply a solid understanding of the variant sensing principles for younger researchers of the community. First, we categorized the HAR-related sensing modalities into five classes: mechanical kinematic sensing, field-based sensing, wave-based sensing, physiological sensing, and hybrid/others. Specific sensing modalities are then presented in each category, and a thorough description of the sensing tricks and the latest related works were given. We also discussed the strengths and weaknesses of each modality across the categorization so that newcomers could have a better overview of the characteristics of each sensing modality for HAR tasks and choose the proper approaches for their specific application. Finally, we summarized the presented sensing techniques with a comparison concerning selected performance metrics and proposed a few outlooks on the future sensing techniques used for HAR tasks.
LPG–PCFG: An Improved Probabilistic Context- Free Grammar to Hit Low-Probability Passwords
Authors: Guo Xiaozhou , Tan Kaijun , Liu Yi , Jin Min , Lu Huaxiang
Published: June 2022

With the development of the Internet, information security has attracted more attention. Identity authentication based on password authentication is the first line of defense; however, the password-generation model is widely used in offline password attacks and password strength evaluation. In real attack scenarios, high-probability passwords are easy to enumerate; extremely low-probability passwords usually lack semantic structure and, so, are tough to crack by applying statistical laws in machine learning models, but these passwords with lower probability have a large search space and certain semantic information. Improving the low-probability password hit rate in this interval is of great significance for improving the efficiency of offline attacks. However, obtaining a low-probability password is difficult under the current password-generation model. To solve this problem, we propose a low-probability generator–probabilistic context-free grammar (LPG–PCFG) based on PCFG. LPG–PCFG directionally increases the probability of low-probability passwords in the models’ distribution, which is designed to obtain a degeneration distribution that is friendly for generating low-probability passwords. By using the control variable method to fine-tune the degeneration of LPG–PCFG, we obtained the optimal combination of degeneration parameters. Compared with the non-degeneration PCFG model, LPG–PCFG generates a larger number of hits. When generating 107 and 108 times, the number of hits to low-probability passwords increases by 50.4% and 42.0%, respectively.
DPSSD: Dual-Path Single-Shot Detector
Authors: Shan Dongri , Xu Yalu , Zhang Peng , Wang Xiaofang , He Dongmei , Zhang Chenglong , Zhou Maohui , Yu Guoqi
Published: June 2022

Object detection is one of the most important and challenging branches of computer vision. It has been widely used in people’s lives, such as for surveillance security and autonomous driving. We propose a novel dual-path multi-scale object detection paradigm in order to extract more abundant feature information for the object detection task and optimize the multi-scale object detection problem, and based on this, we design a single-stage general object detection algorithm called Dual-Path Single-Shot Detector (DPSSD). The dual path ensures that shallow features, i.e., residual path and concatenation path, can be more easily utilized to improve detection accuracy. Our improved dual-path network is more adaptable to multi-scale object detection tasks, and we combine it with the feature fusion module to generate a multi-scale feature learning paradigm called the “Dual-Path Feature Pyramid”. We trained the models on PASCAL VOC datasets and COCO datasets with 320 pixels and 512 pixels input, respectively, and performed inference experiments to validate the structures in the neural network. The experimental results show that our algorithm has an advantage over anchor-based single-stage object detection algorithms and achieves an advanced level in average accuracy. Researchers can replicate the reported results of this paper.
A Global Fundamental Matrix Estimation Method of Planar Motion Based on Inlier Updating
Authors: Wei Liang , Huo Ju
Published: June 2022

A fundamental matrix estimation based on matching points is a critical problem in epipolar geometry. In this paper, a global fundamental matrix estimation method based on inlier updating is proposed. Firstly, the coplanar constraint was incorporated into the solution of the fundamental matrix to reduce the number of parameters to be solved. Subsequently, an inlier updating matrix was introduced according to the threshold of the epipolar geometry distance to eliminate the potential outliers and obtain a reliable initial value of the fundamental matrix. On this basis, we employed a four-point iterative method to estimate the fundamental matrix and make it satisfy the rank constraint at the same time. Finally, the epipolar geometry in binocular vision was extended to triple-view, and the fundamental matrix obtained in the previous step was globally optimized by minimizing the coordinate deviation between the intersection point and feature point in each group of images. The experiments show that the proposed fundamental matrix estimation method is robust to noise and outliers. In the attitude measurement, the maximum static error was 0.104° and dynamic measurement error was superior to 0.273°, which improved the reconstruction accuracy of feature points. Indoor images were further used to test the method, and the mean rotation angle error was 0.362°. The results demonstrate that the estimation method proposed in this paper has a good practical application prospect in multi-view 3D reconstruction and visual localization.
Joint Estimation Method of DOD and DOA of Bistatic Coprime Array MIMO Radar for Coherent Targets Based on Low-Rank Matrix Reconstruction
Authors: You Zhiyuan , Hu Guoping , Zhou Hao , Zheng Guimei
Published: June 2022

Based on low-rank matrix reconstruction theory, this paper proposes a joint DOD and DOA estimation method for coherent targets with bistatic coprime array MIMO radar. Unlike the conventional vectorization, the proposed method processed the coprime array with virtual sensor interpolation, which obtained a uniform linear array to generate the covariance matrix. Then, we reconstructed the Toeplitz matrix and established a matrix optimization recovery model according to the kernel norm minimization theory. Finally, the reduced dimension multiple signal classification algorithm was applied to estimate the angle of the coherent targets, with which the automatic pairing of DOD and DOA could be realized. With the same number of physical sensors, the proposed method expanded the array aperture effectively, so that the degree of freedom and angular resolution could be improved significantly for coherent signals. However, the effectiveness of the method was largely limited by the signal-to-noise ratio. The superiority and effectiveness of the method were proved using simulation experiments.
HARNU-Net: Hierarchical Attention Residual Nested U-Net for Change Detection in Remote Sensing Images
Authors: Li Haojin , Wang Liejun , Cheng Shuli
Published: June 2022

Change detection (CD) is a particularly important task in the field of remote sensing image processing. It is of practical importance for people when making decisions about transitional situations on the Earth’s surface. The existing CD methods focus on the design of feature extraction network, ignoring the strategy fusion and attention enhancement of the extracted features, which will lead to the problems of incomplete boundary of changed area and missing detection of small targets in the final output change map. To overcome the above problems, we proposed a hierarchical attention residual nested U-Net (HARNU-Net) for remote sensing image CD. First, the backbone network is composed of a Siamese network and nested U-Net. We remold the convolution block in nested U-Net and proposed ACON-Relu residual convolution block (A-R), which reduces the missed detection rate of the backbone network in small change areas. Second, this paper proposed the adjacent feature fusion module (AFFM). Based on the adjacency fusion strategy, the module effectively integrates the details and semantic information of multi-level features, so as to realize the feature complementarity and spatial mutual enhancement between adjacent features. Finally, the hierarchical attention residual module (HARM) is proposed, which locally filters and enhances the features in a more fine-grained space to output a much better change map. Adequate experiments on three challenging benchmark public datasets, CDD, LEVIR-CD and BCDD, show that our method outperforms several other state-of-the-art methods and performs excellent in F1, IOU and visual image quality.
Health, Functional Ability, and Environmental Quality as Predictors of Life Satisfaction in Physically Active Older Adults
Authors: Zapata-Lamana Rafael , Poblete-Valderrama Felipe , Ledezma-Dames Andres , Pavón-León Patricia , Leiva Ana María , Fuentes-Alvarez María Trinidad , Cigarroa Igor , Parra-Rizo María Antonia
Published: June 2022

The factors that make physically active older people feel more satisfied in adulthood have not been extensively studied. For this reason, the aim of this work has been to evaluate, among physically active older adults, whether the level of physical activity they perform and the factors that foster their quality of life can be predictors of their satisfaction with life. For this, the IPAQ, CUBRECAVI and LSI-A scales were applied to a sample of 397 people between 61 and 93 years old (M = 69.65, SD = 4.71). The results show that health (β = 0.373), functional abilities (β = 0.159) and environmental quality (β = 0.105) are predictors of satisfaction in the most active adults. In conclusion, neither physical activity (to a greater or lesser extent) nor income are predictive variables of satisfaction with life but, rather, predict some of the components that cement their quality of life (health, fending for themselves and the home environment).
Soil Type Rather Than Freezing Determines the Size of Soil-Root Plate of Silver Birch (Betula pendula Roth.) in the Eastern Baltic Region
Authors: Krišāns Oskars , Matisons Roberts , Vuguls Jānis , Seipulis Andris , Elferts Didzis , Samariks Valters , Saleniece Renāte , Jansons Āris
Published: June 2022

In the Eastern Baltic region, severe windstorms increase both in frequency and magnitude, particularly during the dormancy period, increasing wind damage risks even more for silver birch (Betula pendula Roth.), which is considered to be less vulnerable forest tree species. Tree anchorage, particularly the properties of soil–root plate, determines the type of fatal failures trees experience under extreme wind loads and, subsequently, the potential for timber recovery during salvage logging. The link between soil–root plate properties and fatal failure types was assessed by conducting destructive static pulling tests; trees on freely draining minerals and drained deep peat soils under frozen and non-frozen soil conditions were tested. The size of the root plate did not differ between trees experiencing uprooting or stem breakage but was largely affected by soil type. Frozen soil conditions increased soil–root anchorage (via binding between soil particles) and, hence, the frequency of stem breakage without changing the size of soil–root plate. However, the lack of frozen soil conditions is among the main climatic risks for forestry within the region. The differences in the properties of soil–root plate implies plasticity in adaptation to wind loadings relative to birch, suggesting a potential for managing different types of fatal failure of trees and, subsequently, the share of retrievable timber in cases of salvage logging.
Which Fabric/Scale Is Better for Transit-Oriented Urban Design: Case Studies in a Developing Country
Authors: Abdi Mohammad Hamed , Soltani Ali
Published: June 2022

The goal of this study was to find out how suitable the existing design of urban forms is for adopting transit-oriented development (TOD) basic ideas. Within a major metropolis and a medium-sized city, three varieties of Iranian urban fabric (historic, transitional, and modern) around transit stations were selected using the case study research technique. Then, for two sizes of station areas (macro) and street scales (micro), several TOD design dimensions were evaluated. The results of the comparative research indicated that Iranian cities offer greater chances for TOD design in inner urban areas (including historical and transitional urban forms), whereas microscale characteristics are less reliant on the kind of urban form.
What Grounds Our Loyalty towards “Authentic Brand Activism” of a Sustainable Food Brand?
Authors: Rivaroli Sergio , Spadoni Roberta , Bregoli Ilenia
Published: June 2022

“Authentic brand activism” is an under-researched area of study, and it suffers from a clear lack of understanding concerning the effectiveness of its practices. This study aims to assess how consumers’ evaluations of a brand regarding brand reputation, competence, credibility, and benevolence affect consumers’ brand trust and brand loyalty. This research focuses on the Italian brand “Libera Terra” (“Free Land”), an organisation that uses assets confiscated from the mafias for the production of environmentally and socially sustainable agri-food products. Based on a sample of 366 randomly chosen consumers in a supermarket in the urban district of Bologna (Italy), the results show that consumers’ perceptions of brand performance contribute to their perceived levels of brand trust. The brand trust subsequently impacts consumers’ brand loyalty. This research confirms that alignment between an organisation’s values, business practices, and marketing strategies ensures that authentic brand activism is effective, highlighting the need for businesses to consciously adopt brand activism and avoid “woke washing” practices. The theoretical and managerial implications arising from this research are also presented.
Approach to the Imaginaries of Agroecology in Paraguay
Authors: Soto Carmiña , Insfrán Ortiz Amado , Aparicio Meza María José
Published: June 2022

This paper explores the imaginary of different actors in Paraguay regarding agroecology and whether they contain any similarities. This study used an exploratory, hermeneutic phenomenological approach as its interpretative framework and focused on six key actors: the central government, subgovernmental entities, the private sector, non-governmental organizations (NGOs), farmers’ associations, and academia. The analysis revealed that there are some similarities of imaginaries regarding agroecology’s role as a holistic, integral paradigm that contributes to the sustainability and resilience of the ecosystem, with it being perceived as a practice aimed at small producers with defined niches. The lack of political or state support for small production systems was also evident. Production costs (high for some, low for others) and market niches were mentioned as controversial issues. The results show that the different actors’ imaginaries are not so divergent as to disrupt agroecological practice and indicate the need to conduct more in-depth research to determine what factors affect Paraguayans’ practices or habitus regarding production and their link with nature.
Exploring the Influence of the Visual Attributes of Kaplan’s Preference Matrix in the Assessment of Urban Parks: A Discrete Choice Analysis
Authors: Shayestefar Marjan , Pazhouhanfar Mahdieh , van Oel Clarine , Grahn Patrik
Published: June 2022

A significant majority of the literature on natural environments and urban green spaces justifies the preferences that people have for natural environments using four predictors defined by Kaplan’s preference matrix theory, namely coherence, legibility, complexity, and mystery. However, there are no studies implicitly focusing on the visual attributes assigned to each of these four predictors. Thus, the aim of this study was to explore the influence of nine visual attributes derived from the four predictors of Kaplan’s matrix on people’s preferences in the context of urban parks. A discrete choice experiment was used to obtain responses from a sample of 396 students of Golestan University. Students randomly evaluated their preferences towards a set of potential scenarios with urban park images. The results of a random parameter logit analysis showed that all of the attributes of complexity (variety of elements, number of colors, and organization of elements) and one attribute each of coherence (uniformity), mystery (visual access), and legibility (distinctive elements) affect students’ choices for urban parks, while one attribute each of mystery (physical access) and legibility (wayfinding) did not affect the choices. Furthermore, the results indicated a preference for heterogeneity of the attributes. The findings of this study can provide instructions for designing parks.
Data-Driven Behavioural Biometrics for Continuous and Adaptive User Verification Using Smartphone and Smartwatch
Authors: Verma Akriti , Moghaddam Valeh , Anwar Adnan
Published: June 2022

Recent studies have shown how motion-based biometrics can be used as a form of user authentication and identification without requiring any human cooperation. This category of behavioural biometrics deals with the features we learn in our life as a result of our interaction with the environment and nature. This modality is related to changes in human behaviour over time. The developments in these methods aim to amplify continuous authentication such as biometrics to protect their privacy on user devices. Various Continuous Authentication (CA) systems have been proposed in the literature. They represent a new generation of security mechanisms that continuously monitor user behaviour and use this as the basis to re-authenticate them periodically throughout a login session. However, these methods usually constitute a single classification model which is used to identify or verify a user. This work proposes an algorithm to blend behavioural biometrics with multi-factor authentication (MFA) by introducing a two-step user verification algorithm that verifies the user’s identity using motion-based biometrics and complements the multi-factor authentication, thus making it more secure and flexible. This two-step user verification algorithm is also immune to adversarial attacks, based on our experimental results that show how the rate of misclassification drops while using this model with adversarial data.