bluuebunny/crossref_metadata_2025 huggingface dataset:
Accelerating Effect of Vegetation on the Instability of Rainfall-Induced Shallow Landslides
Authors: Zhang Juanjuan , Qiu Haijun , Tang Bingzhe , Yang Dongdong , Liu Ya , Liu Zijing , Ye Bingfeng , Zhou Wenqi , Zhu Yaru
Published: November 2022

Rainfall-induced shallow landslides are widespread throughout the world, and vegetation is frequently utilized to control them. However, in recent years, shallow landslides have continued to frequently occur during the rainy season on the vegetated slopes of the Loess Plateau in China. To better probe this phenomenon, we considered vegetation cover in the sensitivity analysis of landslide hazards and used the transient rainfall infiltration and grid-based regional slope stability (TRIGRS) model to quantitatively describe the impacts of different types of vegetation cover on slope stability. Based on the rainfall information for landslide events, the spatiotemporal distributions of the pore water pressure and the factor of safety of the vegetated slopes were inverted under the driving changes in the soil properties under different vegetation types, and the average prediction accuracy reached 79.88%. It was found that there was a strong positive correlation between the cumulative precipitation and the proportion of landslide-prone areas in woodland covered by tall trees, grassland covered by shrubs and grasses, and cultivated land. The highest landslide susceptibility, which has the greatest potential to hasten the occurrence of rainfall-induced landslides, is found in woodland with tall trees. Therefore, this paper proposes the promoting relationship between vegetation and landslide erosion, which provides a new scientific perspective on watershed management to prevent shallow landslide disasters and manage and develop watershed vegetation.
An Automatic Approach to Extracting Large-Scale Three-Dimensional Road Networks Using Open-Source Data
Authors: Chen Yang , Yang Xin , Yang Ling , Feng Jiayu
Published: November 2022

3D road networks are amongst the indispensable elements of a smart city, which has been explored in various ways. However, researchers still faces challenges extracting 3D networks on a large scale. The global digital surface models (DSMs) with relatively high spatial resolution make it possible to extract 3D road networks. Nevertheless, the complete and accurate elevation of road networks cannot be obtained directly because of the limitation in sensors on the DSM production platform. Thus, we proposed a novel approach to extract large-scale 3D road networks, integrating terrain correction and road engineering rule constraint, by using the Advanced Land Observing Satellite World 3D-30 m DSM, OpenStreetMap and FABDEM. The simplification and terrain correction algorithm were applied to remove most of the edges with excessive grades and reduced the negative impact of the built-up environment in DSM on the extraction accuracy. Moreover, the tunnel parts of the 3D road networks were refined based on road engineering standards. Nanjing of China, Aalborg of Denmark and Los Angeles of the United States are selected as study areas. Using 3D road networks from unmanned aerial vehicle photogrammetry, light detection and ranging and Google Earth as references, we validated the road elevation accuracy of our method and obtained an overall root-mean-square error of 3.80 m and a mean absolute error of 1.94 m. The 3D topology of interchanges with different radii was reconstructed completely. Overall, our work is an endeavour to utilise multiple open-source data to extract large-scale 3D road networks and benefits future research related to smart city reconstruction and 3D urban analysis.
Rule-Driven Forwarding for Resilient WSN Infrastructures
Authors: Gburzynski Pawel , Nikolaidis Ioanis
Published: November 2022

We present a simple, robust, ad hoc forwarding scheme for small-footprint, low-cost wireless sensor networks (WSNs) and discuss some of its features from the viewpoint of resilience. The class of applications shaping the resilience requirements for our discussion covers temporary, and possibly disposable deployments of potentially massive populations of sensing nodes to assist in the management of emergency missions, including the management of the effects from natural or man-made disasters. Our goal is to make the network resistant to failures of any of its fragments, which may result from the network’s intended modus operandi or from intentional malicious attempts at crippling its function, while keeping the cost and footprint of the devices at the absolute minimum.
The Smart Nervous System for Cracked Concrete Structures: Theory, Design, Research, and Field Proof of Monolithic DFOS-Based Sensors
Authors: Bednarski Łukasz , Sieńko Rafał , Howiacki Tomasz , Zuziak Katarzyna
Published: November 2022

The article presents research on the performance of composite and monolithic sensors for distributed fibre optic sensing (DFOS). The introduction summarises the design of the sensors and the theoretical justification for such an approach. Lessons learned during monitoring cracked concrete are summarised to highlight what features of the DFOS tools are the most favourable from the crack analysis point of view. Later, the results from full-size laboratory concrete specimens working in a cracked state were presented and discussed in reference to conventional layered sensing cables. The research aimed to compare monolithic sensors and layered cables embedded in the same reinforced concrete elements, which is the main novelty. The performance of each DFOS nondestructive tool was investigated in the close vicinity of the cracks—both the new ones, opening within the tension zone, and the existing ones, closing within the compression zone. The qualitative (detection) and quantitative (widths estimation) crack analyses were performed and discussed. Finally, the examples of actual applications within concrete structures, including bridges, are presented with some examples of in situ results.
Performance Comparison of Multiple Convolutional Neural Networks for Concrete Defects Classification
Authors: Arafin Palisa , Issa Anas , Billah A. H. M. Muntasir
Published: November 2022

Periodical vision-based inspection is a principal form of structural health monitoring (SHM) technique. Over the last decades, vision-based artificial intelligence (AI) has successfully facilitated an effortless inspection system owing to its exceptional ability of accuracy of defects’ pattern recognition. However, most deep learning (DL)-based methods detect one specific type of defect, whereas DL has a high proficiency in multiple object detection. This study developed a dataset of two types of defects, i.e., concrete crack and spalling, and applied various pre-built convolutional neural network (CNN) models, i.e., VGG-19, ResNet-50, InceptionV3, Xception, and MobileNetV2 to classify these concrete defects. The dataset developed for this study has one of the largest collections of original images of concrete crack and spalling and avoided the augmentation process to replicate a more real-world condition, which makes the dataset one of a kind. Moreover, a detailed sensitivity analysis of hyper-parameters (i.e., optimizers, learning rate) was conducted to compare the classification models’ performance and identify the optimal image classification condition for the best-performed CNN model. After analyzing all the models, InceptionV3 outperformed all the other models with an accuracy of 91%, precision of 83%, and recall of 100%. The InceptionV3 model performed best with optimizer stochastic gradient descent (SGD) and a learning rate of 0.001.
Finger-Gesture Controlled Wheelchair with Enabling IoT
Authors: Sadi Muhammad Sheikh , Alotaibi Mohammed , Islam Md. Repon , Islam Md. Saiful , Alhmiedat Tareq , Bassfar Zaid
Published: November 2022

Modern wheelchairs, with advanced and robotic technologies, could not reach the life of millions of disabled people due to their high costs, technical limitations, and safety issues. This paper proposes a gesture-controlled smart wheelchair system with an IoT-enabled fall detection mechanism to overcome these problems. It can recognize gestures using Convolutional Neural Network (CNN) model along with computer vision algorithms and can control the wheelchair automatically by utilizing these gestures. It maintains the safety of the users by performing fall detection with IoT-based emergency messaging systems. The development cost of the overall system is cheap and is lesser than USD 300. Hence, it is expected that the proposed smart wheelchair should be affordable, safe, and helpful to physically disordered people in their independent mobility.
Microsatellite Uncertainty Control Using Deterministic Artificial Intelligence
Authors: Wilt Evan , Sands Timothy
Published: November 2022

This manuscript explores the applications of deterministic artificial intelligence (DAI) in a space environment in response to unknown sensor noise and sudden changes in craft physical parameters. The current state of the art literature has proposed the method, but only ideal environments, and accordingly this article addresses the literature gaps by critically evaluating efficacy in the face of unaddressed parametric uncertainties. We compare an idealized combined non-linear feedforward (FFD) and linearized feedback (FB) control scheme with an altered feedforward, feedback, and deterministic artificial intelligence scheme in the presence of simulated craft damage and environmental disturbances. Mean trajectory tracking error was improved over 91%, while the standard deviation was improved over 97% whilst improving (reducing) control effort by 13%.
The Atmospheric Vertical Detection of Large Area Regions Based on Interference Signal Denoising of Weighted Adaptive Kalman Filter
Authors: Shen Qiying , Liu Yongsheng , Chen Ren , Xu Zhijing , Zhang Yuan , Chen Yaxuan , Huang Jingyu
Published: November 2022

In comparison with traditional space infrared spectroscopy technology, the interference signals of a large focal plane array (FPA) can be used to obtain spectra over a larger area range and rapidly achieve large-scale coverage of hyperspectral remote sensing. However, the low signal-to-noise ratio of the interference signals limits the application of spectral data, especially when atmospheric detection occurs in the long-wavelength infrared (LWIR) band. In this paper, we construct an LWIR hyperspectral system of a Fourier transform spectrometer composed of a HgCdTe photovoltaic IR FPA and a Michelson interferometer. The LWIR interference signals are obtained by a high-frequency oversampling technique. We use the Kalman filter (KF) and its improved weighted adaptive Kalman filter (WAKF) to reduce the noise of multiple measured data of each pixel. The effect of overshoot and ringing artifacts on the objective signals is reduced by the WAKF. The applicability is studied by the interference signals from the different sampling frequencies and different pixels. The effectiveness is also verified by comparing the spectra of denoised interferograms with the reference spectrum. The experimental results show that the WAKF algorithm has excellent noise suppression, and the standard deviation of the interferogram can be reduced by 39.50% compared with that of KF. The WAKF is more advantageous in improving the signal-to-noise ratio of the interferogram and spectra. The results indicate that our system can be applied to atmospheric vertical detection and hyperspectral remote sensing over large area ranges because our denoised technique is suitable for large LWIR FPA.
Energy-Efficient Trajectory Planning for Smart Sensing in IoT Networks Using Quadrotor UAVs
Authors: Jia Guoku , Li Chengming , Li Mengtang
Published: November 2022

Quadrotor unmanned aerial vehicles (UAVs) are widely used as flexible and mobile access points and information carriers for the future Internet of Things (IoT). This work studies a quadrotor UAV-assisted IoT network, where the UAV helps to collect sensing data from a group of IoT users. Our goal is to optimize the UAV’s overall energy consumption required to complete the sensing task. Firstly, we propose a more accurate and mathematically tractable model to characterize the UAV’s real-time energy consumption, which accounts for the UAV’s dynamics, brushless direct current (BLDC) motor dynamics and aerodynamics. Then, we can show that the UAV’s circular flight based on the proposed energy-consumption model consumes less energy than that of hover flight. Therefore, a fly–circle–communicate (FCC) trajectory design algorithm, adopting Dubins curves for circular flight, is proposed and derived to save energy and increase flight duration. Employing the FCC strategy, the UAV moves to each IoT user and implements a circular flight in the sequence solved by the travelling-salesman-problem (TSP) algorithm. Finally, we evaluate the efficiency of the proposed algorithm in a mobile sensing network by comparing the proposed algorithm with the conventional hover-communicate (HC) algorithm in terms of energy consumption. Numerical results show that the FCC algorithm reduces energy consumption by 1–10% compared to the HC algorithm, and also improves the UAV’s flight duration and the sensing network’s service range.
Research on a Bearing Fault Enhancement Diagnosis Method with Convolutional Neural Network Based on Adaptive Stochastic Resonance
Authors: Wang Chen , Qiao Zijian , Huang Zhangjun , Xu Junchen , Fang Shitong , Zhang Cailiang , Liu Jinjun , Zhu Ronghua , Lai Zhihui
Published: November 2022

As a powerful feature extraction tool, a convolutional neural network (CNN) has strong adaptability for big data applications such as bearing fault diagnosis, whereas the classification performance is limited when the quality of raw signals is poor. In this paper, stochastic resonance (SR), which provides an advanced feature enhancement approach for weak signals with strong background noise, is introduced as a data pre-processing method for the CNN to improve its classification performance. First, a multiparameter adjusting bistable Duffing system that can achieve SR under large-parameter weak signals is introduced. A hybrid optimization algorithm (HOA) combining the genetic algorithm (GA) and the simulated annealing (SA) is proposed to adaptively obtain the optimized parameters and output signal-to-noise ratio (SNR) of the Duffing system. Therefore, the data optimization based on the multiparameter-adjusting SR of Duffing system can be realized. An SR-based mapping method is further proposed to convert the outputs of the Duffing system into grey images, which can be further processed by a normal CNN with batch normalization (BN) layers and dropout layers. After verifying the feasibility of the HOA in multiparameter optimization of the Duffing system, the bearing fault data set from the CWRU bearing data center was processed by the proposed fault enhancement classification and identification method. The research showed that the weak features of the bearing signals could be enhanced significantly through the adaptive multiparameter optimization of SR, and classification accuracies for 10 categories of bearing signals could achieve 100% and those for 20 categories could achieve more than 96.9%, which is better than other methods. The influences of the population number on the classification accuracies and calculation time were further studied, and the feature map and network visualization are presented. It was demonstrated that the proposed method can realize high-performance fault enhancement classification and identification.
Continuous Monitoring of Suspended Particulate Matter in Tropical Inland Waters by High-Frequency, Above-Water Radiometry
Authors: Borges Henrique Dantas , Martinez Jean-Michel , Harmel Tristan , Cicerelli Rejane Ennes , Olivetti Diogo , Roig Henrique Llacer
Published: November 2022

Water and sediment discharges can change rapidly, and low-frequency measurement devices might not be sufficient to elucidate existing dynamics. As such, above-water radiometry might enhance monitoring of suspended particulate matter (SPM) dynamics in inland waters. However, it has been barely applied for continuous monitoring, especially under partially cloudy sky conditions. In this study, an in situ, high-frequency (30 s timestep), above-water radiometric dataset, collected over 18 days in a tropical reservoir, is analyzed for the purpose of continuous monitoring of SPM concentration. Different modalities to retrieve reflectance spectra, as well as SPM inversion algorithms, were applied and evaluated. We propose a sequence of processing that achieved an average unsigned percent difference (UPD) of 10.4% during cloudy conditions and 4.6% during clear-sky conditions for Rrs (665 nm), compared to the respective UPD values of 88.23% and 13.17% when using a simple calculation approach. SPM retrieval methods were also evaluated and, depending on the methods used, we show that the coefficient of variation (CV) of the SPM concentration varied from 69.5% down to 2.7% when using a semi-analytical approach. As such, the proposed processing approach is effective at reducing unwanted variability in the resulting SPM concentration assessed from above-water radiometry, and our work paves the way towards the use of this noninvasive technique for high-frequency monitoring of SPM concentrations in streams and lakes.
Study of the Influence of the Backplate Position on EMAT Thickness-Measurement Signals
Authors: Wang Junjie , Wu Xinjun , Song Yun , Sun Lingsi
Published: November 2022

Nondestructive testing (NDT) is an essential method for assessing structural integrity in the oil and gas industry. Electromagnetic acoustic transducers (EMATs) have been extensively used to detect the wall-thickness reduction of plate-like structures, because they do not require direct contact. The pulse intervals of echoes are used to calculate the remnant thickness of structures. If the width of a single pulse is too large, multiple pulses will be superimposed, making it more difficult to extract the pulse interval. Thus, the width of a single pulse affects the resolution of measurements. This paper investigates the impacts of the backplate position on the pulse width and amplitude of thickness-measurement signals, using EMATs. By means of impedance modeling and measurement, it can be shown that the output impedance of the receiving coil is strongly influenced by the coil-backplate gap. With the increment in the coil-backplate gap, the signal amplitude and damping coefficient increase, while the self-resonant frequency decreases. By means of signal measurements on the specimen, it is shown that the pulse width and the signal amplitude can be significantly influenced by the backplate position. By reducing the coil–backplate gap, the pulse width can be reduced by over 80%, and by increasing the gap, the signal amplitude can be increased by over 300%. These research results can be used to optimize EMAT design, thereby suppressing the superposition of pulse echoes.
Equivalent Circuit to Analyze the Transmitting Characteristics of a Cymbal Array
Authors: Shim Hayeong , Kim Kyungseop , Seo Heeseon , Roh Yongrae
Published: November 2022

A cymbal transducer has a simple structure consisting of a piezoceramic disk and metallic caps and has broadband characteristics when built as an array. The finite element method (FEM) is generally used to analyze the characteristics of acoustic transducers. However, the FEM requires a longer analysis time as the model becomes larger, which makes it limited and less efficient for analyzing the cymbal array. In this study, a new equivalent circuit with higher efficiency and accuracy, comparable to that of the FEM, was proposed to analyze the performance of cymbal arrays. The equivalent circuit for the array was constructed by connecting the equivalent circuits of individual cymbal transducers in parallel with a radiation impedance matrix that included both the self- and mutual radiation characteristics of the array. The validity of the new equivalent circuit was verified by measuring the transmitting voltage response of a cymbal array specimen and comparing it with that calculated using the circuit. The comparison confirmed the efficiency of the equivalent circuit in analyzing the characteristics of the cymbal array. The proposed equivalent circuit can facilitate the design of a large array of cymbal transducers.
Telepresence Robot System for People with Speech or Mobility Disabilities
Authors: ElGibreen Hebah , Al Ali Ghada , AlMegren Rawan , AlEid Reema , AlQahtani Samar
Published: November 2022

Due to an increase in the number of disabled people around the world, inclusive solutions are becoming a priority. People with disabilities may encounter many problems and may not be able to easily participate in various activities due to physical barriers, which may sometimes cause them to be frustrated and embarrassed. Recently, the emerging telepresence robot technology has been proposed to enable people with disabilities to increase their presence by incorporating information and communications technology (ICT) into robotics platforms. Therefore, in this paper we conduct a comprehensive analysis using comparative and elicitation studies to understand the current state of mobile telepresence robot systems and to identify the gaps that must be filled. This paper further contributes to the literature by proposing a novel telepresence robot system that adapts text-to-speech (TTS) and ICT technologies with robotics for its use as an assistant. To the authors’ knowledge, the proposed system is the first MRP system that supports speech impairment and introduces emotion components into its communication function. It includes an operator site (mobile) and a remote site (robot) to allow users to control the robot from a distance and communicate with others in remote locations. It allows the user to physically interact with people and show certain emotions through the robot in remote locations, or it can accompany them to speak on their behalf. It can provide agency for both remote and in-class users through emoji-based communication and audio–video streaming with recording functionality. As shown at the end of this paper, the system was tested with 30 people, some of whom had mobility or speech disabilities, showing that the user acceptance score was above 95% and that people with disabilities liked to interact with other people using the proposed system. The users appreciated having the ability to control the robot from a distance and praised the capability to show their emotions through the robot emoji motions and to control the audio–video streaming. From this study, we conclude that the proposed telepresence system could be an asset to people with speech and mobility disabilities and could help them feel physically present in various places.
Robust 6-DoF Pose Estimation under Hybrid Constraints
Authors: Ren Hong , Lin Lin , Wang Yanjie , Dong Xin
Published: November 2022

To solve the problem of the insufficient accuracy and stability of the two-stage pose estimation algorithm using heatmap in the problem of occluded object pose estimation, a new robust 6-DoF pose estimation algorithm under hybrid constraints is proposed in this paper. First, a new loss function suitable for heatmap regression is formulated to improve the quality of the predicted heatmaps and increase keypoint accuracy in complex scenes. Second, the heatmap regression network is expanded and a translation regression branch is added to constrain the pose further. Finally, a robust pose optimization module is used to fuse the heatmap and translation estimates and improve the pose estimation accuracy. The proposed algorithm achieves ADD(-S) accuracy rates of 93.5% and 46.2% on the LINEMOD dataset and the Occlusion LINEMOD dataset, which are better than other state-of-the-art algorithms. Compared with the conventional two-stage heatmap-based pose estimation algorithms, the mean estimation error is greatly reduced, and the stability of pose estimation is improved. The proposed algorithm can run at a maximum speed of 22 FPS, thus constituting both a performant and efficient method.
Using Inertial and Physiological Sensors to Investigate the Effects of a High-Intensity Interval Training and Plyometric Program on the Performance of Young Judokas
Authors: Mañas-Paris Adrián , Muyor José M. , Oliva-Lozano José M.
Published: November 2022

The use of inertial and physiological sensors in a sport such as judo is scarce to date. The information provided by these sensors would allow practitioners to have a better understanding of sports performance, which is necessary for an accurate training prescription. The purpose of this study was to use inertial and physiological sensors in order to investigate the effect of a plyometric and high-intensity interval training (HIIT) training program on Special Judo Fitness Test (SJFT) performance and speed of execution of throws in young judokas. A total of 32 participants were divided into two groups: experimental and control. The intervention consisted of six sessions with a duration of 60 min for 3 weeks. Physiological sensors collected heart rate data to assess the Special Judo Fitness Test, and inertial sensors collected angular velocity. The results show a significant decrease in the SJFT index (Score pre: 22.27 ± 2.73; Score post: 19.65 ± 1.70; p ≤ 0.05; d = 0.61) and a significant increase in the angular velocity of the X-axis (Pre: 320.87 ± 51.15°/s; Post: 356.50 ± 40.47°/s; p ≤ 0.05; d = 0.45) and Y-axis (Pre: 259.40 ± 41.99°/s; Post: 288.02 ± 65.12°/s; p ≤ 0.05; d = 0.31) in the experimental group. In conclusion, this study demonstrates that using inertial and physiological sensors allowed us to analyze the effect that a high-intensity interval training program and plyometrics had on the performance of young judokas. Strength and conditioning coaches should consider these results because including plyometric training and HIIT in judokas’ workout programming can be especially positive for eliciting increases in performance. However, future training interventions should investigate the training adaptations to longer interventions.
Filtering Strategies for Deformation-Rate Distributed Acoustic Sensing
Authors: Yang Jihyun , Shragge Jeffrey , Jin Ge
Published: November 2022

Deformation-rate distributed acoustic sensing (DAS), made available by the unique designs of certain interrogator units, acquires seismic data that are theoretically equivalent to the along-fiber particle velocity motion recorded by geophones for scenarios involving elastic ground-fiber coupling. While near-elastic coupling can be achieved in cemented downhole installations, it is less obvious how to do so in lower-cost horizontal deployments. This investigation addresses this challenge by installing and freezing fiber in shallow backfilled trenches (to 0.1 m depth) to achieve improved coupling. This acquisition allows for a reinterpretation of processed deformation-rate DAS waveforms as a “filtered particle velocity” rather than the conventional strain-rate quantity. We present 1D and 2D filtering experiments that suggest 2D velocity-dip filtering can recover improved DAS data panels that exhibit clear surface and refracted arrivals. Data acquired on DAS fibers deployed in backfilled, frozen trenches were more repeatable over a day of acquisition compared to those acquired on a surface-deployed DAS fiber, which exhibited more significant amplitude variations and lower signal-to-noise ratios. These observations suggest that deploying fiber in backfilled, frozen trenches can help limit the impact of environmental factors that would adversely affect interpretations of time-lapse DAS observations.
Synthesis and Structural Characterization of an Amorphous and Photoluminescent Mixed Eu/Zr Coordination Compound, a Potential Marker for Gunshot Residues
Authors: Serra Ayla Roberta Borges , Casagrande Thiago Rui , de Lima Juliana Fonseca , de Oliveira Marcelo Firmino , Júnior Severino Alves , de Oliveira Junior Marcos , Serra Osvaldo Antonio
Published: November 2022

Hydrogels based on mixed zirconium/europium ions and benzene tricarboxylic acid were synthesized by hydrothermal reaction. A solid glass-like material is formed upon drying, showing strong reddish luminescence. The system was characterized by solid-state nuclear magnetic resonance, thermal analyses, and infrared spectroscopy. The results reveal the amorphous character of the structure and the presence of at least four types of binding modes between the metal oxide clusters and benzene tricarboxylic acid. On the other hand, thermogravimetric analysis (TGA) showed high thermal stability, with the material decomposing at temperatures higher than 500 °C. The combination of intense Eu3+ luminescence with large thermal stability makes this material a strong candidate for application as a luminescent red marker for gunshot residue (GSR). As proof of concept, we show the feasibility of this application by performing shooting tests using our compound as a GSR marker. After the shots, the residual luminescent particles could be visualized in the triggered cartridge, inner the muzzle of the firearm, and a lower amount on the hands of the shooter, using a UV lamp (λ = 254 nm). Remarkably, our results also show that the Eu3+ emission for the GSR is very similar to that observed for the original solid material. These characteristics are of huge importance since they provide a chance to use smaller amounts of the marker in the ammunition, lowering the costs of potential industrial manufacturing processes.
Analysis of Faults in Software Systems Using Tsallis Distribution: A Unified Approach
Authors: Sharma Shachi
Published: November 2022

The identification of the appropriate distribution of faults is important for ensuring the reliability of a software system and its maintenance. It has been observed that different distributions explain faults in different types of software. Faults in large and complex software systems are best represented by Pareto distribution, whereas Weibull distribution fits enterprise software well. An analysis of faults in open-source software endorses generalized Pareto distribution. This paper presents a model, called the Tsallis distribution, derived using the maximum-entropy principle, which explains faults in many diverse software systems. The effectiveness of Tsallis distribution is ascertained by carrying out experiments on many real data sets from enterprise and open-source software systems. It is found that Tsallis distribution describes software faults better and more precisely than Weibull and generalized Pareto distributions, in both cases. The applications of the Tsallis distribution in (i) software fault-prediction using the Bayesian inference method, and (ii) the Goal and Okumoto software-reliability model, are discussed.
Perceptions on Sack Gardening in Rural Areas: The Case of Vegetable Stakeholders in Koutiala and Bougouni, Mali
Authors: Govoeyi Benoit , Tignégré Jean-Baptiste De La Salle , Badolo Felix , Zaato Paul Alhassan , Sanogo Karamoko , Birhanu Birhanu Zemadim
Published: November 2022

Understanding the perception of sack gardening technology is important in order to better support the adoption of sack gardening in households, given the nutritional role vegetables play. This notwithstanding, research has not yet been carried out to understand the stakeholders’ perception of sack gardening technology in the zones of Bougouni and Koutiala, where sack gardening technology was introduced under the Africa Research in Sustainable Intensification for the Next Generation (Africa-RISING) project. This study assessed the perception of farm households on sack gardening technology and specifically to understand to what extent this innovation responds to household needs. Q-methodology was used to identify rural household’s viewpoints and principal component analysis (PCA) was performed to compare stakeholders’ opinion typologies to discourses retained by Q-method results. Focus group discussions were used to identify the statements used for the q-set in the individual surveys. Our findings showed three factors or discourses which reflected the stakeholders’ viewpoints. A nutritional role, the role of making vegetables available for household consumption and the role of environment protection, specifically soil protection, were indicated in the stakeholders’ opinions. The understanding of the different discourses retained provides insights that can be used to design public and private interventions to support the usage of the technology in households or the adoption of this technology.
ICT Adoption Scale Development for SMEs
Authors: Özşahin Mehtap , Çallı Büşra Alma , Coşkun Erman
Published: November 2022

Information systems research lacks a validated scale for assessing and measuring the adoption of information and communication technologies (ICTs) by small- and medium-sized enterprises (SMEs). The relevant literature is limited in studies mainly concentrating on developing country settings. Furthermore, the emergence of new technological elements and increasing digitalization and digital transformation efforts in the last two years have changed how an organization utilizes and adopts ICTs. Therefore, it is inevitable that the conceptual dimensions proposed in the previous literature and the definitions of these dimensions will also alter. Hence, it is essential to revisit and validate the prior work and enhance it based on current vitality and developments. This study developed and validated a scale for measuring ICT adoption and digitalization for SMEs in a developing country context. The researchers followed an eight-step scale development procedure: (1) comprehensive literature review on ICT adoption and digitalization; (2) identification of dimensions of the level of ICT adoption and digitalization; (3) generation of items; (4) item refinement through focus group; (5) pretest of the measurement; (6) scale purification; (7) data collection; and (8) measurement evaluation. Within the Turkish setting, the ICT adoption scale was determined to have sufficient reliability and validity. Data for this study were gathered from 421 respondents of 219 Turkish SMEs. Supporting the multidimensionality of ICT adoption, 14 items and five dimensions (communication, internal integration, integration with customers, interorganizational integration, and strategic integration) constituted the ICT adoption construct. Considering the dominance of conceptual frameworks that were proposed based on developed countries and the prevalence of unidimensional constructs in the field, the developed multidimensional scale is expected to contribute significantly. Practitioners and policymakers can utilize the suggested scale to discover areas where specific changes are required for the digital transformation in SME utilization efforts that need attention. The outcomes can be applied to industrial sectors and different geographic contexts. By considering stage-based integration, the developed scale can also be used in future studies to investigate the effects of different variables on the extent of ICT adoption and the impact of ICTs on several organizational outcomes.
Catalytic Pyrolysis Process to Produce Styrene from Waste Expanded Polystyrene Using a Semi-Batch Rotary Reactor
Authors: Pérez-Bravo Gerardo , Contreras-Larios José Luis , Rodríguez Jorge Francisco , Zeifert-Soares Beatriz , Angeles-Beltrán Deyanira , López-Medina Ricardo , Vázquez-Rodríguez Tamara , Salmones-Blasquez José
Published: November 2022

Thermal and catalytic pyrolysis of waste expanded polystyrene (WEPS) was studied to obtain mainly styrene monomer, which can be recycled in the polystyrene industry. Initially, preliminary experiments were carried out in a static semi-batch glass reactor with basic catalysts and without catalysts, using toluene as solvent at 250 °C, determining their styrene yields to select the best catalyst. MgO turned out to be the best catalyst due to its stability and cost. This catalyst was characterized by XRD, BET area, SEM-EDS, Raman spectroscopy, UV–VIS, and TGA. The kinetic equation for WEPS pyrolysis in the glass reactor was determined as a first-order reaction. The heat of reaction, the Gibbs free energy change, and the entropy change were calculated. Finally, WEPS pyrolysis experiments were carried out using a rotating semi-batch steel reactor, at higher temperatures and without using solvents, evaluating the styrene yield and its performance for its possible industrial application. In this reaction, the activity remained almost constant after four catalyst regenerations. The best styrene yield was 94 wt%, which could be one of the highest reported in the literature. This result may be associated with the back-mixing obtained in the rotary reactor, in contrast to the performance observed in the static glass reactor.
An Experimental Study on Performance Evaluation of Shading Matrix to Select Optimal Parking Space for Solar-Powered Electric Vehicles
Authors: Baek Jieun , Choi Yosoon
Published: November 2022

This study evaluated the applicability of a shading matrix generated using hemispherical fisheye images to select the optimal parking space to maximize the photovoltaic (PV) power generation of solar electric vehicles. The study aims to identify the maximum power point (MPP) of a PV module in a parking space using current–voltage measuring equipment to determine whether the shading matrix reflects any shadow phenomenon. The experiment was conducted on a parking lot at Daeyeon Campus. The fisheye images were taken in seven parking spaces. The shading matrices were generated by tracking the position of the sun over 12 months and 24 h periods. A 50 W PV module was installed on the roof of the vehicle and the MPP was measured in five experiments (9 a.m., 11 a.m., 13 p.m., 15 p.m., and 17 p.m.) in seven parking spaces. In parking spaces with a shading factor of 0, the PV modules were not shaded at all during the experiment, and the average MPPs were 34, 43, 37, and 21 W at 9 a.m., 11 a.m., 13 p.m., and 15 p.m., respectively. The shading matrix calculated using the fisheye images accurately reflected the shadow phenomenon that decreases PV power generation.
Bioeconomy: The Innovative Twin of Sustainability
Authors: Vogt Markus , Frankenreiter Ivo
Published: November 2022

With its far-reaching promise of a new synthesis of ecology and economy, the concept of the bioeconomy is a shimmering, ambiguous term in need of ethical and conceptual interpretation. The paper identifies potentials and strategies of the bioeconomy for a knowledge-based energy and raw material turnaround, which, by turning away from fossil resources, can at the same time contribute significantly to waste prevention. The focus is on ethical criteria for a responsible bioeconomy. In terms of environmental ethics, this approach has exemplary significance because it currently represents the most prominent concept for unfolding and operationalizing the innovative side of sustainability. The paper therefore argues for an expanded concept of the bioeconomy that includes the reproductive capacity of nature, for which soil conservation is a strong example. This will be unfolded with the proposal of an ethics of innovation.
Identification of Territorial Spatial Pattern Conflicts in Aksu River Basin, China, from 1990 to 2020
Authors: Cao Yuee , Jiang Yunlu , Feng Lin , Shi Ge , He Haotian , Yang Jianjun
Published: November 2022

The change in land use leads to territorial spatial conflict. Territorial spatial conflicts mainly show that the boundaries of agricultural space, urban space, and ecological space overlap each other and interfere with each other’s functions, which will have a negative impact on regional high-quality development. The Aksu River, the most principal source of the Tarim River, the largest instream river in China, is a key area for maintaining ecological security in Northwestern China. It is highly significant to identify the spatial conflict characteristics of land use in this region to promote the sustainable use of regional land resources, optimization of spatial patterns, and the balance between economic construction and ecological environmental protection in mountainous areas. This paper takes the Aksu River Basin as the research area. Using Arcgis 10.8 software, Yaahp software, and SPSSAU software, it builds a land use spatial conflict measurement model based on a quantitative analysis of land use changes from 1990 to 2020 and explores the spatial and temporal evolution characteristics of land use conflicts in the Aksu River Basin. The results show that: (1) From 1990 to 2020, the spatial conflict pattern of the study area was dominated by ecological spatial conflicts. The spatial conflict area shows dynamic changes, but the overall trend is decreasing. (2) The spatial conflict pattern of territorial space in the Aksu River Basin has basically formed, and the three types of spatial conflicts are closely related to the level of local economic development. (3) Ecological spatial conflicts are mainly distributed in high-altitude mountains, river valleys, and oasis-to-desert transition areas. Urban spatial conflicts are mainly distributed in the middle and lower reaches of the Aksu River plain oasis. Agricultural spatial conflicts are scattered but large in scale, with small differences in the proportion of conflict distribution among the counties.
Students’ Mobile Phone Practices for Academic Purposes: Strengthening Post-Pandemic University Digitalization
Authors: Nikolopoulou Kleopatra
Published: November 2022

The COVID-19 pandemic is considered as a turning point that has impacted the digital transformation of higher education. However, the link between students’ mobile phone practices and university digitalization is not sufficiently or explicitly discussed. The purpose of this study is to provide evidence about university students’ mobile phone practices for academic purposes, and to contribute to the debate regarding post-pandemic university digitalization. The participants were 60 students studying in a Greek university, data were collected via an open-ended questionnaire, and descriptive content analysis was used to examine the qualitative data. Students mainly use their mobile phones for information searches (e.g., for assignments, videos, photos, graphs, simulations, online dictionaries, and scientific papers), easy and quick access to e-classes (e.g., course material/slides) and the faculty’s site, and for communication with peers (e.g., queries, sharing educational resources) and tutors. During mobile practices, students experience advantages (easy-quick searches, flexibility, familiarization with digital technology) and disadvantages (internet connectivity, unreliable information sources, distractions). Implications for students, educators, and university policy-organization (policymakers have a role in reshaping digitalization) are discussed. It is argued that mobile learning has the potential to strengthen university digitalization, thus affecting the sustainability of education in the post-pandemic era.
How Extraction and Purification Affect MALDI-TOF MS Characterization of Mangrove Condensed Tannins, An Ecologically Important Secondary Metabolites in Coastal Wetland Ecosystem
Authors: Lang Tao , Xiang Ping , Li Mingdang , Chen Zhiteng , Li Fenglan , Jiang Mingguo , Zhou Haichao
Published: November 2022

Mangrove plants are rich in tannins, especially condensed tannins (CTs), which play an important role in biogeochemistry in coastal wetland ecosystem due to their functions of binding nutrients and heavy metal chelation. This study aims to obtain authentic chemical structures of mangrove CTs by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). Four organic solvents (n-hexane, ether, chloroform, and EtOAc (ethyl acetate)) were used for extraction tests and three purification methods (Method 1, Sephadex LH-20 absorbed tannins, and nontannins fraction were washed by 50% methanol (mp) solution; Method 2, Sephadex LH-20 absorbed tannins and nontannins fraction were washed by 100% ethanol (ep), and released in 70% acetone solution; and Method 3, Yb3+ selectivity precipitated tannins) were conducted to investigate their influences on the characterization of CTs from two mangrove species, Bruguiera gymnorhiza and Kandelia obovata. The results showed that (1) EtOAc was used as an extraction solvent, leading to unauthentic structural properties of CTs; (2) the distribution patterns of the polymers in mangrove CTs purified with 50% methanol elicited the least different trends with those of CTs in the two mangrove crude extracts, and the lower oligomers (dimmer-hexamer) and higher polymers were lost during purification of CTs by 100% ep. Therefore, based on the toxicity and price of solvents, the crude CTs from mangrove plants can be extracted with n-hexane or ether to remove lipid and pigment impurities and then purified with 50% methanol, which is a complete set of methods to obtain completely authentic structural information of mangrove CTs. This study can offer more accurate structural information of mangrove CTs and new insights for the conservation of mangrove living environments for follow-up research.
Outage Survivability Investigation of a PV/Battery/CHP System in a Hospital Building in Texas
Authors: Islam Kazi Sifatul , Hasan Samiul , Chowdhury Tamal , Chowdhury Hemal , Sait Sadiq M.
Published: November 2022

Climate change and the associated global warming raise the possibility of weather-related natural disasters. Power outages due to natural catastrophes cause substantial financial loss. Moreover, an uninterrupted power supply is essential in disaster-prone areas to continue rescue and other humanitarian activities. Therefore, energy systems must be resilient to withstand power outages due to natural events. Resilience and enhancement techniques, and schemes of integrated electricity and microgrids’ heat demand during power outages, were mainly overlooked in the earlier analysis. Therefore, this analysis aims to analyze a grid-tied microgrid’s survivability during a power outage due to a natural disaster in Texas, USA. Mixed-integer linear programming (MILP) is used to optimize various energy resources, such as PV, battery, grid, and combined heat and power (CHP) for Texas, USA. These technologies were run in an outage condition to observe their resiliency benefits. To determine the resilience performance of the CHP/PV/battery system for the hospital building, a new probabilistic approach was applied. A 24-h outage was simulated in REopt lite software, and this study found that the PV/battery/CHP system could easily withstand the outage. The optimum system consists of 3933 kW of PV, 4441 kWh of storage, and a CHP unit having a capacity of 208 kW. The proposed microgrid emits 79.81% less CO2 than the only grid system. The microgrid has a net benefit of $1,007,204 over the project duration. The introduction of the proposed microgrid will bring about life-cycle savings (LCS) of 37.02 million USD over the project’s lifespan.