bluuebunny/crossref_metadata_2025 huggingface dataset:
Pyraclostrobin Removal in Pilot-Scale Horizontal Subsurface Flow Constructed Wetlands and in Porous Media Filters
Authors: Gikas Georgios D. , Vryzas Zisis , Karametos Ioannis , Tsihrintzis Vassilios A.
Published: February 2022

Pyraclostrobin is a fungicide extensively used for the control of various fungal diseases and is frequently detected in environmental samples. Natural systems, such as constructed wetlands (CWs) and gravity filters, are effective and environmentally friendly treatment systems, which can reduce or eliminate pesticides from the environment. The aim of this study was to investigate the capacity of two pilot-scale CWs (porous media: cobbles and fine gravel, planted with Phragmites australis) and six gravity filters (filling material: bauxite, carbonate gravel and zeolite) to remove pyraclostrobin from polluted water originating from spraying equipment rinsing sites. For this, experiments were conducted to test the performance of the above natural systems in removing this fungicide. The results showed that the mean percent pyraclostrobin removal efficiencies for cobbles and fine gravel CW units were 56.7% and 75.2%, respectively, and the mean percent removals for HRTs of 6 and 8 days were 68.7% and 62.8%, respectively. The mean removal efficiencies for the bauxite, carbonate gravel and zeolite filter units were 32.5%, 36.7% and 61.2%, respectively, and the mean percent removals for HRTs 2, 4 and 8 days were 39.9%, 43.4% and 44.1%, respectively. Regarding the feeding strategy, the mean removal values of pyraclostrobin in gravity filter units were 43.44% and 40.80% for continuous and batch feeding, respectively. Thus, these systems can be used in rural areas for the treatment of spraying equipment rinsing water.
Thermo-Economic Analysis of Near-Surface Geothermal Energy Considering Heat and Cold Supply within a Low-Temperature District Heating Network
Authors: Kutzner Sebastian , Heberle Florian , Brüggemann Dieter
Published: February 2022

This study evaluates low-temperature district heating (LTDH) networks with different geothermal heat sources under thermo-economic criteria. In particular, the heat and cold supply of modern neighbourhoods are taken into account in a dynamic simulation model built on the modelling language Modelica. Both horizontal and vertical ground heat exchangers (GHE) were investigated in respect to the load profiles of the consumers, depending on dimension as well as location. The selected base case represents a LTDH network near Stuttgart (Germany). The corresponding results of an annual simulation show that a horizontal GHE is suitable for pure heat supply and can reduce costs by up to 12% compared to a vertical system. This economic advantage remains when the cooling demand is considered. Subsequently, a variation of the system location was carried out. It is shown that horizontal GHEs operate more economically in northern regions, whereas vertical ones are more advantageous in regions with increased cooling demand. For both cases, possible savings of between 3.0% and 4.2% resulted from the simulations. The heating-to-cooling demand ratio was used as a first decision criteria to weigh-up between the two systems. Vertical GHEs were more economical than horizontal systems as soon as the ratio dropped below 1.5.
Development of a Novel Reverse Offset Printer Equipped with Double-Layer Blanket (DLB) for Micropattern Printing on 3D Curved Surfaces
Authors: Lee Hyunah , Cho Nam-Joo , Kim Dong-soo
Published: February 2022

The double-layer blanket (DLB) reverse offset is a newly designed printing process for patterning electronic circuits on a 3D curved surface. Unlike the existing reverse offset process, the DLB reverse offset utilizes an offset roll composed of two layers comprising polydimethylsiloxane (PDMS) and a thick, soft cushioned rubber to print microelectrode patterns and transparent electrodes on a curved surface. The optimal printing process was determined by adjusting the printing pressure and printing speed for horizontal and vertical micropatterns, based on which transparent electrodes with metal mesh and honeycomb structures with a line width of 30 μm and pitch of 600 μm with micropatterns ranging from 30 μm to 60 μm were printed on a curved surface. Ag ink was used, and the 3D curved surface indicated a print quality similar to that of the flat surface for both the vertical and horizontal patterns and transparent electrodes. The DLB reverse offset technique demonstrated the possibility of printing on a 3D curved surface and is expected to broaden the range of printed electronics to applications such as smart glasses and 3D shape sensors.
Effect of Solid Volume Concentration on Rheological Properties of Chengdu Clay Slurry
Authors: Ji Xianjun , Liang Ying , Cao Wenhao
Published: February 2022

The determination of rheological model about the debris flow is the basis of the simulation of mud flow impact distance and sedimentary fan. By using a mcr301 rheometer, rheological experiments of Chengdu clay slurry with different solid volume concentrations were carried out and the effect of solid volume concentration on shear stress were analyzed. Then the rheological process of Chengdu clay slurry with different solid volume concentration was fitted on the basis of the power law model, the Bingham model and the H–B model. The conclusions are drawn as follows: Chengdu clay mud is a typical shear-thinning non-Newtonian body. The influence of solid concentration on the flow curve is different. When the solid volume concentration is not less than 34% and the shear rate is less than 1.0 s−1, the shear stress increases rapidly as the shear rate increases. Meanwhile, when the shear rate is greater than 1.0 s−1 the shear stress decreases with the increase in the shear rate. When the solid volume concentration is less than 31.6% and the shear rate is less than 1.0 s−1, the shear stress increases with the increase in the shear rate, while when the shear rate is more than 1.0 s−1, the shear stress is less affected by shear rate. In the range of low shear rate (less than 1.0 s−1), the increase amplitude of shear stress (slope of semi logarithmic coordinate flow curve) increases as the solid volume content increases. The flow curve of Chengdu clay mud can be reflected in the whole process by using the Herschel and Bulkley model. It is the best mathematical model to fit the rheological process of Chengdu clay mud. According to the above results, the effect of solid volume concentration on the yield stress of the H–B model is analyzed.
Effect of Mold Electromagnetic Stirring on the Flow and Solidification of Φ 800 mm Round Blooms
Authors: Wang Tao , Zhang Lianwang , Wu Hongjian , Zhang Xiaobing , Jin Yukai , Yang Peiqi , Xu Changjun
Published: February 2022

Knowing the effect of electromagnetic force on fluid flow and solidification within the molds of large-size round blooms is of paramount importance to minimize internal and external defects. In this regard, a three-dimensional coupling model is established, containing magnetohydrodynamics, fluid flow, and heat transfer within the mold, and a new approach for the uniformity of the initial shell is presented. Meanwhile, the effect of stirring parameters on fluid flow and solidification is discussed. The results show that M-EMS can significantly change the temperature and velocity distribution within the mold. These changes can stabilize the level fluctuations and make the initial shell uniform. The maximum industrial height fluctuation was reduced from 1.9 mm to 1.3 mm when the stirring intensity was 375 A/3 Hz. The stirring intensity of M-EMS is relatively ideal.
Application of Ultrasound-Assisted Extraction and Non-Thermal Plasma for Fucus virsoides and Cystoseira barbata Polysaccharides Pre-Treatment and Extraction
Authors: Dobrinčić Ana , Zorić Zoran , Pedisić Sandra , Repajić Maja , Roje Marin , Herceg Zoran , Čož-Rakovac Rozelindra , Dragović-Uzelac Verica
Published: February 2022

Brown algae Fucus virsoides and Cystoseira barbata are an abundant source of sulfated polysaccharide fucoidan, which has shown a wide range of biological activities. These activities are significantly dependent on the fucoidan chemical composition, which is closely linked with the applied extraction technique and process parameters. In order to overcome the drawbacks of lengthy conventional extraction (CE), advanced extraction techniques, such as ultrasound-assisted extraction (UAE) and non-thermal plasma (NTP), were applied. Furthermore, this study also investigated the efficiency of different solvents as well as UAE and NTP as 5 min pre-treatments prior to CE as a more effective course of cell wall breakage and, consequently, a higher polysaccharide yield (%PS). Apart from %PS, the effect of this procedure on the chemical composition and antioxidant capacity of the extracted polysaccharides was also monitored. When comparing the extraction solvent, the application of 0.1 M H2SO4, instead of H2O, resulted in a three-fold higher %PS, a higher sulfate group, and a lower fucose content. Application of CE resulted in higher %PS, uronic acids, and fucose content as well as oxygen radical absorbance capacity (ORAC) and DPPH values, while the average molecular weight (Mw), sulfate group, and glucose content were lower during CE when compared to 30 min of UAE and NTP treatment. Application of UAE and NTP as 5 min pre-treatments decreased fucose content, while %PS and sulfate content were similar to values obtained when using CE.
Positivism and Reasonableness: Authoritarian Leanings in New Atheism’s Thinking
Authors: Roseneck Michael
Published: February 2022

Various contemporary phenomena of social regression and authoritarianism are related to religious actors, movements, and beliefs. This text, however, seeks to follow this up with the political–theoretical argumentation that New Atheism has to be understood as a way of thinking which carries illiberal and authoritarian tendencies with it as well. In defence of this position, this article will first reconstruct, with reference to Habermas’s and Rawls’s theory of democracy, elements that must include personal beliefs in order to be considered congruent with democratic values. Subsequently, New Atheism’s conception of rational politics will be presented in order to show in which aspects it contradicts the demands of reasonable convictions. This concerns, in particular, the rejection of reasonable pluralism on the one hand and a non-positivistic view of human beings on the other. As a conclusion, this text supports the proposition that, when speaking of the connection between certain worldviews and today’s illiberalism, New Atheism must also be considered as an unreasonable comprehensive doctrine.
In Situ Measuring Stem Diameters of Maize Crops with a High-Throughput Phenotyping Robot
Authors: Fan Zhengqiang , Sun Na , Qiu Quan , Li Tao , Feng Qingchun , Zhao Chunjiang
Published: February 2022

Robotic High-Throughput Phenotyping (HTP) technology has been a powerful tool for selecting high-quality crop varieties among large quantities of traits. Due to the advantages of multi-view observation and high accuracy, ground HTP robots have been widely studied in recent years. In this paper, we study an ultra-narrow wheeled robot equipped with RGB-D cameras for inter-row maize HTP. The challenges of the narrow operating space, intensive light changes, and messy cross-leaf interference in rows of maize crops are considered. An in situ and inter-row stem diameter measurement method for HTP robots is proposed. To this end, we first introduce the stem diameter measurement pipeline, in which a convolutional neural network is employed to detect stems, and the point cloud is analyzed to estimate the stem diameters. Second, we present a clustering strategy based on DBSCAN for extracting stem point clouds under the condition that the stem is shaded by dense leaves. Third, we present a point cloud filling strategy to fill the stem region with missing depth values due to the occlusion by other organs. Finally, we employ convex hull and plane projection of the point cloud to estimate the stem diameters. The results show that the R2 and RMSE of stem diameter measurement are up to 0.72 and 2.95 mm, demonstrating its effectiveness.
Integrating Multi-Source Remote Sensing to Assess Forest Aboveground Biomass in the Khingan Mountains of North-Eastern China Using Machine-Learning Algorithms
Authors: Wang Xiaoyi , Liu Caixia , Lv Guanting , Xu Jinfeng , Cui Guishan
Published: February 2022

Forest aboveground biomass (AGB) is of great significance since it represents large carbon storage and may reduce global climate change. However, there are still considerable uncertainties in forest AGB estimates, especially in rugged regions, due to the lack of effective algorithms to remove the effects of topography and the lack of comprehensive comparisons of methods used for estimation. Here, we systematically compare the performance of three sources of remote sensing data used in forest AGB estimation, along with three machine-learning algorithms using extensive field measurements (N = 1058) made in the Khingan Mountains of north-eastern China in 2008. The datasets used were obtained from the LiDAR-based Geoscience Laser Altimeter System onboard the Ice, Cloud, and land Elevation satellite (ICESat/GLAS), the optical-based Moderate Resolution Imaging Spectroradiometer (MODIS), and the SAR-based Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR). We show that terrain correction is effective for this mountainous study region and that the combination of terrain-corrected GLAS and PALSAR features with Random Forest regression produces the best results at the plot scale. Including further MODIS-based features added little power for prediction. Based upon the parsimonious data source combination, we created a map of AGB circa 2008 and its uncertainty, which yields a coefficient of determination (R2) of 0.82 and a root mean squared error of 16.84 Mg ha−1 when validated with field data. Forest AGB values in our study area were within the range 79.81 ± 16.00 Mg ha−1, ~25% larger than a previous, SAR-based, analysis. Our result provides a historic benchmark for regional carbon budget estimation.
A Novel Method for Hyperspectral Mineral Mapping Based on Clustering-Matching and Nonnegative Matrix Factorization
Authors: Ren Zhongliang , Zhai Qiuping , Sun Lin
Published: February 2022

The emergence of hyperspectral imagery paved a new way for rapid mineral mapping. As a classical hyperspectral classification method, spectral matching (SM) can automatically map the spatial distribution of minerals without the need for selecting training samples. However, due to the influence of noise, the mapping accuracy of SM is usually poor, and its per-pixel matching method is inefficient to some extent. To solve these problems, we propose an unsupervised clustering-matching mapping method, using a combination of k-means and SM (KSM). First, nonnegative matrix factorization (NMF) is used and combined with a simple and effective NMF initialization method (SMNMF) for feature extraction. Then, k-means is implemented to get the cluster centers of the extracted features and band depth, which are used for clustering and matching, respectively. Finally, dimensionless matching methods, including spectral angle mapper (SAM), spectral correlation angle (SCA), spectral gradient angle (SGA), and a combined matching method (SCGA) are used to match the cluster centers of band depth with a spectral library to obtain the mineral mapping results. A case study on the airborne hyperspectral image of Cuprite, Nevada, USA, demonstrated that the average overall accuracies of KSM based on SAM, SCA, SGA, and SCGA are approximately 22%, 22%, 35%, and 33% higher than those of SM, respectively, and KSM can save more than 95% of the mapping time. Moreover, the mapping accuracy and efficiency of SMNMF are about 15% and 38% higher than those of the widely used NMF initialization method. In addition, the proposed SCGA could achieve promising mapping results at both high and low signal-to-noise ratios compared with other matching methods. The mapping method proposed in this study provides a new solution for the rapid and autonomous identification of minerals and other fine objects.
Target Detection and DOA Estimation for Passive Bistatic Radar in the Presence of Residual Interference
Authors: Wang Haitao , Wang Jun , Jiang Junzheng , Liao Kefei , Xie Ningbo
Published: February 2022

With the development of radio technology, passive bistatic radar (PBR) will suffer from interferences not only from the base station that is used as the illuminator of opportunity (BS-IoO), but also from the base station with co-frequency or adjacent frequency (BS-CF/AF). It is difficult for clutter cancellation algorithm to suppress all the interferences, especially the interferences from BS-CF/AF. The residual interferences will seriously affect target detection and DOA estimation. To solve this problem, a novel target detection and DOA estimation method for PBR based on compressed sensing sparse reconstruction is proposed. Firstly, clutter cancellation algorithm is used to suppress the interferences from BS-IoO. Secondly, the residual interferences and target echo are separated in spatial domain based on the azimuth sparse reconstruction. Finally, target detection and DOA estimation method are given. The proposed method can achieve not only target detection and DOA estimation in the presence of residual interferences, but also better anti-mainlobe interferences and high-resolution DOA estimation performance. Numerical simulation and experimental results verify the effectiveness of the proposed algorithm.
Using LiDAR System as a Data Source for Agricultural Land Boundaries
Authors: Borowiec Natalia , Marmol Urszula
Published: February 2022

In this study, LiDAR sensor data were used to identify agricultural land boundaries. This is a remote sensing method using a pulsating laser directed toward the ground. This study focuses on accurately determining the edges of parcels using only the point cloud, which is an original approach because the point cloud is a scattered set, which may complicate finding those points that define the course of a straight line defining the parcel boundary. The innovation of the approach is the fact that no data from other sources are supported. At the same time, a unique contribution of the research is the attempt to automate the complex process of detecting the edges of parcels. The first step was to classify the data, using intensity, and define land use boundaries. Two approaches were decided, for two test fields. The first test field was a rectangular shaped parcel of land. In this approach, pixels describing each edge of the plot separately were automatically grouped into four parts. The edge description was determined using principal component analysis. The second test area was the inner subdivision plot. Here, the Hough Transform was used to emerge the edges. Obtained boundaries, both for the first and the second test area, were compared with the boundaries from the Polish land registry database. Performed analyses show that proposed algorithms can define the correct course of land use boundaries. Analyses were conducted for the purpose of control in the system of direct payments for agriculture (Integrated Administration Control System—IACS). The aim of the control is to establish the borders and areas of croplands and to verify the declared group of crops on a given cadastral parcel. The proposed algorithm—based solely on free LiDAR data—allowed the detection of inconsistencies in farmers’ declarations. These mainly concerned areas of field roads that were misclassified by farmers as subsidized land, when in fact they should be excluded from subsidies. This is visible in both test areas with areas belonging to field roads with an average width of 1.26 and 3.01 m for test area no. 1 and 1.31, 1.15, 1.88, and 2.36 m for test area no. 2 were wrongly classified as subsidized by farmers.
A Remote Sensing Perspective on Mass Wasting in Contrasting Planetary Environments: Cases of the Moon and Ceres
Authors: Sam Lydia , Bhardwaj Anshuman
Published: February 2022

Mass wasting, as one of the most significant geomorphological processes, contributes immensely to planetary landscape evolution. The frequency and diversity of mass wasting features on any planetary body also put engineering constraints on its robotic exploration. Mass wasting on other Solar System bodies shares similar, although not identical, morphological characteristics with its terrestrial counterpart, indicating a possible common nature for their formation. Thus, planetary bodies with contrasting environmental conditions might help reveal the effects of the atmosphere, subsurface fluids, mass accumulation/precipitation, and seismicity on mass wasting, and vice versa. Their relative positions within our Solar System and the environmental and geophysical conditions on the Moon and the dwarf planet Ceres are not only extremely different from Earth’s but from each other too. Their smaller sizes coupled with the availability of global-scale remote sensing datasets make them ideal candidates to understand mass wasting processes in widely contrasting planetary environments. Through this concept article, we highlight several recent advances in and prospects of using remote sensing datasets to reveal unprecedented details on lunar and Cerean mass wasting processes. We start with briefly discussing several recent studies on mass wasting using Lunar Reconnaissance Orbiter Camera (LROC) data for the Moon and Dawn spacecraft data for Ceres. We further identify the prospects of available remote sensing data in advancing our understanding of mass wasting processes under reduced gravity and in a scant (or absent) atmosphere, and we conclude the article by suggesting future research directions.
Area-Efficient Integrated Current-Reuse Feedback Amplifier for Wake-Up Receivers in Wireless Sensor Network Applications
Authors: Galante-Sempere David , Ramos-Valido Dailos , Khemchandani Sunil Lalchand , del Pino Javier
Published: February 2022

Wireless sensor network (WSN) applications are under extensive research and development due to the need to interconnect devices with each other. To reduce latency while keeping very low power consumption, the implementation of a wake-up receiver (WuR) is of particular interest. In WuR implementations, meeting high performance metrics is a design challenge, and the obtention of high-sensitivity, high data rate, low-power-consumption WuRs is not a straightforward procedure. The focus of our proposals is centered on power consumption and area reduction to provide high integrability and maintain a low cost-per-node, while we simultaneously improve circuit sensitivity. Firstly, we present a two-stage design based on a feedback technique and improve the area use, power consumption and sensitivity of the circuit by adding a current-reuse approach. The first solution is composed of a feedback amplifier, two op-amps plus a low-pass filter. The circuit achieves a sensitivity of –63.2 dBm with a power consumption of 6.77 µA and an area as low as 398 × 266 µm2. With the current-reuse feedback amplifier, the power consumption is halved in the second circuit (resulting in 3.63 µA), and the resulting circuit area is as low as 262 × 262 µm2. Thanks to the nature of the circuit, the sensitivity is improved to –75 dBm. This latter proposal is particularly suitable in applications where a fully integrated WuR is desired, providing a reasonable sensitivity with a low power consumption and a very low die footprint, therefore facilitating integration with other components of the WSN node. A thorough discussion of the most relevant state-of-the-art solutions is presented, too, and the two developed solutions are compared to the most relevant contributions available in the literature.
Evaluation of 3D Vulnerable Objects’ Detection Using a Multi-Sensors System for Autonomous Vehicles
Authors: Khatab Esraa , Onsy Ahmed , Abouelfarag Ahmed
Published: February 2022

One of the primary tasks undertaken by autonomous vehicles (AVs) is object detection, which comes ahead of object tracking, trajectory estimation, and collision avoidance. Vulnerable road objects (e.g., pedestrians, cyclists, etc.) pose a greater challenge to the reliability of object detection operations due to their continuously changing behavior. The majority of commercially available AVs, and research into them, depends on employing expensive sensors. However, this hinders the development of further research on the operations of AVs. In this paper, therefore, we focus on the use of a lower-cost single-beam LiDAR in addition to a monocular camera to achieve multiple 3D vulnerable object detection in real driving scenarios, all the while maintaining real-time performance. This research also addresses the problems faced during object detection, such as the complex interaction between objects where occlusion and truncation occur, and the dynamic changes in the perspective and scale of bounding boxes. The video-processing module works upon a deep-learning detector (YOLOv3), while the LiDAR measurements are pre-processed and grouped into clusters. The output of the proposed system is objects classification and localization by having bounding boxes accompanied by a third depth dimension acquired by the LiDAR. Real-time tests show that the system can efficiently detect the 3D location of vulnerable objects in real-time scenarios.
Selectivity of Relative Humidity Using a CP Based on S-Block Metal Ions
Authors: García-García Amalia , Toral Víctor , Quílez del Moral José F. , Galisteo Pretel Alberto , Morales Diego P. , Salinas-Castillo Alfonso , Cepeda Javier , Choquesillo-Lazarte Duane , Bobinger Marco , Salmerón José F. , Rivadeneyra Almudena , Rodríguez-Diéguez Antonio
Published: February 2022

Herein, we present the syntheses of a novel coordination polymer (CP) based on the perylene-3,4,9,10-tetracarboxylate (pery) linkers and sodium metal ions. We have chosen sodium metal center with the aim of surmising the effect that the modification of the metal ion may have on the relative humidity (RH) experimental measurements of the material. We confirm the role of the ions in the functionalization of the deposited layer by modifying their selectivity towards moisture content, paving the way to the generation of sensitive and selective chemical sensors.
Recent Progress of Switching Power Management for Triboelectric Nanogenerators
Authors: Zhou Han , Liu Guoxu , Zeng Jianhua , Dai Yiming , Zhou Weilin , Xiao Chongyong , Dang Tianrui , Yu Wenbo , Chen Yuanfen , Zhang Chi
Published: February 2022

Based on the coupling effect of contact electrification and electrostatic induction, the triboelectric nanogenerator (TENG) as an emerging energy technology can effectively harvest mechanical energy from the ambient environment. However, due to its inherent property of large impedance, the TENG shows high voltage, low current and limited output power, which cannot satisfy the stable power supply requirements of conventional electronics. As the interface unit between the TENG and load devices, the power management circuit can perform significant functions of voltage and impedance conversion for efficient energy supply and storage. Here, a review of the recent progress of switching power management for TENGs is introduced. Firstly, the fundamentals of the TENG are briefly introduced. Secondly, according to the switch types, the existing power management methods are summarized and divided into four categories: travel switch, voltage trigger switch, transistor switch of discrete components and integrated circuit switch. The switch structure and power management principle of each type are reviewed in detail. Finally, the advantages and drawbacks of various switching power management circuits for TENGs are systematically summarized, and the challenges and development of further research are prospected.
Novel Scoring for Energy-Efficient Routing in Multi-Sensored Networks
Authors: Kim Wooseong , Umar Muhammad Muneer , Khan Shafiullah , Khan Muhammad Altaf
Published: February 2022

The seamless operation of inter-connected smart devices in Internet of Things (IoT) wireless sensor networks (WSNs) requires consistently available end-to-end routes. However, the sensor nodes that rely on a very limited power source tend to cause disconnection in multi-hop routes due to power shortages in the WSNs, which eventually results in the inefficiency of the overall IoT network. In addition, the density of the available sensor nodes affects the existence of feasible routes and the level of path multiplicity in the WSNs. Therefore, an efficient routing mechanism is expected to extend the lifetime of the WSNs by adaptively selecting the best routes for the data transfer between interconnected IoT devices. In this work, we propose a novel routing mechanism to balance the energy consumption among all the nodes and elongate the WSN lifetime, which introduces a score value assigned to each node along a path as the combination of evaluation metrics. Specifically, the scoring scheme considers the information of the node density at a certain area and the node energy levels in order to represent the importance of individual nodes in the routes. Furthermore, our routing mechanism allows for incorporating non-cooperative nodes. The simulation results show that the proposed work gives comparatively better results than some other experimented protocols.
A Cloud Computing-Based Modified Symbiotic Organisms Search Algorithm (AI) for Optimal Task Scheduling
Authors: Zubair Ajoze Abdulraheem , Razak Shukor Abd , Ngadi Md. Asri , Al-Dhaqm Arafat , Yafooz Wael M. S. , Emara Abdel-Hamid M. , Saad Aldosary , Al-Aqrabi Hussain
Published: February 2022

The search algorithm based on symbiotic organisms’ interactions is a relatively recent bio-inspired algorithm of the swarm intelligence field for solving numerical optimization problems. It is meant to optimize applications based on the simulation of the symbiotic relationship among the distinct species in the ecosystem. The task scheduling problem is NP complete, which makes it hard to obtain a correct solution, especially for large-scale tasks. This paper proposes a modified symbiotic organisms search-based scheduling algorithm for the efficient mapping of heterogeneous tasks to access cloud resources of different capacities. The significant contribution of this technique is the simplified representation of the algorithm’s mutualism process, which uses equity as a measure of relationship characteristics or efficiency of species in the current ecosystem to move to the next generation. These relational characteristics are achieved by replacing the original mutual vector, which uses an arithmetic mean to measure the mutual characteristics with a geometric mean that enhances the survival advantage of two distinct species. The modified symbiotic organisms search algorithm (G_SOS) aims to minimize the task execution time (makespan), cost, response time, and degree of imbalance, and improve the convergence speed for an optimal solution in an IaaS cloud. The performance of the proposed technique was evaluated using a CloudSim toolkit simulator, and the percentage of improvement of the proposed G_SOS over classical SOS and PSO-SA in terms of makespan minimization ranges between 0.61–20.08% and 1.92–25.68% over a large-scale task that spans between 100 to 1000 Million Instructions (MI). The solutions are found to be better than the existing standard (SOS) technique and PSO.
Single-Trial Classification of Error-Related Potentials in People with Motor Disabilities: A Study in Cerebral Palsy, Stroke, and Amputees
Authors: Usama Nayab , Niazi Imran Khan , Dremstrup Kim , Jochumsen Mads
Published: February 2022

Brain-computer interface performance may be reduced over time, but adapting the classifier could reduce this problem. Error-related potentials (ErrPs) could label data for continuous adaptation. However, this has scarcely been investigated in populations with severe motor impairments. The aim of this study was to detect ErrPs from single-trial EEG in offline analysis in participants with cerebral palsy, an amputation, or stroke, and determine how much discriminative information different brain regions hold. Ten participants with cerebral palsy, eight with an amputation, and 25 with a stroke attempted to perform 300–400 wrist and ankle movements while a sham BCI provided feedback on their performance for eliciting ErrPs. Pre-processed EEG epochs were inputted in a multi-layer perceptron artificial neural network. Each brain region was used as input individually (Frontal, Central, Temporal Right, Temporal Left, Parietal, and Occipital), the combination of the Central region with each of the adjacent regions, and all regions combined. The Frontal and Central regions were most important, and adding additional regions only improved performance slightly. The average classification accuracies were 84 ± 4%, 87± 4%, and 85 ± 3% for cerebral palsy, amputation, and stroke participants. In conclusion, ErrPs can be detected in participants with motor impairments; this may have implications for developing adaptive BCIs or automatic error correction.
Application of Filters to Improve Flight Stability of Rotary Unmanned Aerial Objects
Authors: Salwa Maciej , Krzysztofik Izabela
Published: February 2022

The most common filters used to determine the angular position of quadrotors are the Kalman filter and the complementary filter. The problem of angular position estimation consist is a result of the absence of direct data. The most common sensors on board UAVs are micro electro mechanical system (MEMS) type sensors. The data acquired from the sensors are processed using digital filters. In the literature, the results of research conducted on the effectiveness of Kalman and complementary filters are known. A significant problem in evaluating the performance of the studied filters was the lack of an arbitrarily determined UAV position. The authors of this paper undertook the task of determining the best filter for a real object. The main objective of this research was to improve the stability of the physical quadrotor. For this purpose, we developed a research method using a laboratory station for testing quadrotor drones. Moreover, using the MATLAB environment, they determined the optimal parameters for the real filter applied using the PX4 software, which is new and has not been considered before in the available scientific literature. It should be mentioned that the authors of this work focused on the analysis of filters most commonly used for flight stabilization, without modifying the structure of these filters. By not modifying the filter structure, it is possible to optimize the existing flight controllers. The main contribution of this study lies in finding the most optimal filter, among those available in flight controllers, for angular position estimation. The special emphasis of our work was to develop a procedure for selecting the filter coefficients for a real object. The algorithm was designed so that other researchers could use it, provided they collected arbitrary data for their objects. Selected results of the research are presented in graphical form. The proposed procedure for improving the embedded filter can be used by other researchers on their subjects.
An Image Registration Method Based on Correlation Matching of Dominant Scatters for Distributed Array ISAR
Authors: Zhang Liqi , Li Yanlei
Published: February 2022

Distributed array radar provides new prospects for three-dimensional (3D) inverse synthetic aperture radar (ISAR) imaging. The accuracy of image registration, as an essential part of 3D ISAR imaging, affects the performance of 3D reconstruction. In this paper, the imaging process of distributed array ISAR is proposed according to the imaging model. The ISAR images of distributed array radar at different APCs have different distribution of scatters. When the local distribution of scatters for the same target are quite different, the performance of the existing ISAR image registration methods may not be optimal. Therefore, an image registration method is proposed by integrating the feature-based method and the area-based method. The proposed method consists of two stages: coarse registration and fine registration. In the first stage, a dominant scatters model is established based on scale-invariant feature transform (SIFT). In the second stage, sub-pixel precision registration is achieved using the local correlation matching method. The effectiveness of the proposed method is verified by comparison with other image registration methods. The 3D reconstruction of the registered experimental data is carried out to assess the practicability of the proposed method.
A Multi-Frequency Tomographic Inverse Scattering Using Beam Basis Functions
Authors: Tuvi Ram
Published: February 2022

We present an overview of a beam-based approach to ultra-wide band (UWB) tomographic inverse scattering, where beam-waves are used for local data-processing and local imaging, as an alternative to the conventional plane-wave and Green’s function approaches. Specifically, the method utilizes a phase–space set of iso-diffracting beam-waves that emerge from a discrete set of points and directions in the source domain. It is shown that with a proper choice of parameters, this set constitutes a frame (an overcomplete generalization of a basis), termed “beam frame”, over the entire propagation domain. An important feature of these beam frames is that they need to be calculated once and then used for all frequencies, hence the method can be implemented either in the multi-frequency domain (FD), or directly in the time domain (TD). The algorithm consists of two phases: in the processing phase, the scattering data is transformed to the beam domain using windowed phase–space transformations, while in the imaging phase, the beams are backpropagated to the target domain to form the image. The beam-domain data is not only localized and compressed, but it is also physically related to the local Radon transform (RT) of the scatterer via a local Snell’s reflection of the beam-waves. This expresses the imaging as an inverse local RT that can be applied to any local domain of interest (DoI). In previous publications, the emphasis has been set on TD data processing using a special class of localized space–time beam-waves (wave-packets). The goal of the present paper is to present the imaging scheme in the UWB FD, utilizing simpler Fourier-based data-processing tools in the space and time domains.
Experimental Investigation of Vibration Analysis on Implant Stability for a Novel Implant Design
Authors: Lu Shouxun , Vien Benjamin Steven , Russ Matthias , Fitzgerald Mark , Chiu Wing Kong
Published: February 2022

Osseointegrated prostheses are widely used following transfemoral amputation. However, this technique requires sufficient implant stability before and during the rehabilitation period to mitigate the risk of implant breakage and loosening. Hence, reliable assessment methods for the osseointegration process are essential to ensure initial and long–term implant stability. This paper researches the feasibility of a vibration analysis technique for the osseointegration (OI) process by investigating the change in the dynamic response of the residual femur with a novel implant design during a simulated OI process. The paper also proposes a concept of an energy index (the E–index), which is formulated based on the normalized magnitude. To illustrate the potential of the E–index, this paper reports on changes in the vibrational behaviors of a 133 mm long amputated artificial femur model and implant system, with epoxy adhesives applied at the interface to simulate the OI process. The results show a significant variation in the magnitude of the colormap against curing time. The study also shows that the E–index was sensitive to the interface stiffness change, especially during the early curing process. These findings highlight the feasibility of using the vibration analysis technique and the E–index to quantitatively monitor the osseointegration process for future improvement on the efficiency of human health monitoring and patient rehabilitation.
Determination of Binary Gas Mixtures by Measuring the Resonance Frequency in a Piezoelectric Tube
Authors: Keeratirawee Kanchalar , Hauser Peter C.
Published: February 2022

The composition of gas mixtures may be determined via changes of the speed of sound. As this affects the resonance frequency of the gas inside a tube, indirect measurements through a frequency analysis are also possible. It is demonstrated that this may be carried out with unprecedented simplicity by the novel employment of a piezoelectric tube which serves at the same time as a resonance tube and as transducer into the electronic domain. Experiments were run using a simple diecast aluminum box as the measuring cell, inside which the piezoelectric tube made from lead zirconium titanate with 30-mm length and 5.35-mm inner diameter was suspended. A small loudspeaker placed into the cell served for excitation of the resonance. Peak frequencies between 3910 and 14,590 Hz (for pure CO2 and He, respectively) were obtained. Two component mixtures of O2/N2, CO2/N2, and He/N2 at various composition were tested. A linear frequency change from 4790 to 5100 Hz was observed when going from pure O2 to pure N2.
Power Flow Analysis in Urban Distribution Networks with Implementation of Grid-Connected Photovoltaic Systems
Authors: Uruel-Sanz Julia , Perpiñán-Lamigueiro Oscar
Published: February 2022

In the last few years, renewable energies became more socially and economically relevant, and among them, photovoltaic systems stand out. Residential self-consumption of electricity is a field with great potential, and implementation of grid-connected photovoltaic systems (GCPS) is in full rise. The installation of distributed generation systems in residential environments could alter the performance of low-voltage distribution networks, since these are designed for unidirectional power flow and adding these generators means fluctuations in power-flows. For these reasons, a study of the fundamental magnitudes of three low-voltage distribution networks located in Madrid was made for various photovoltaic penetration rates, making use of simulations via the software OpenDSS and subsequent analysis of results. The research concludes that, among other aspects, GCPS produce load flow variations that are dependent on: the penetration rates; the distance from the point of interest and the distribution transformer, increasing the voltage variation between the most productive hours and the night hours with that distance; and on the rate between consumption and generation, so that when it diminishes, the self-sufficiency of the system increases, and with it the voltage of all the buses that tend to the rated voltage. Moreover, there are wide seasonal fluctuations: specifically, in summer months, generation profiles override consumption fluctuations, while in winter months consumption guides voltage and power profiles. Both the code implemented and the results of the analysis were published in an open source website using a free software license.
DNA as a Next-Generation Biomonitoring Tool of Hospital Effluent Contamination
Authors: Bekir Karima , Beltifa Asma , Maatouk Ferdaws , Khdary Nezar H. , Barhoumi Houcine , Mansour Hedi Ben
Published: February 2022

A DNA biosensor based on a modified gold electrode with a Au/cysteine/DNA matrix was developed for ultratrace determination of genotoxicity antibiotics. The modified Au/cysteine/DNA electrode was characterized by cyclic voltammetry and impedance spectroscopy methods. The interaction between immobilized DNA and genotoxicity antibiotics in hospital wastewater was investigated using differential pulse voltammetry (DPV) technology. Using this technique, ciprofloxacin and ofloxacin were detected in real time in the hospital wastewater (HW) of the Tunisian cities of Gabes, Tozeur, Sfax, and Gbeli. In addition, physicochemical parameters such as the chemical oxygen demand (COD), biological oxygen demand (BOD), and total organic carbon (TOC) of HW samples that may affect the nature of the samples were studied. Comet assay (single-cell gel electrophoresis) was performed to measure the capacity of xenobiotics to induce DNA damage. In our conditions, this test indicated that all tested wastewater was able to alter cell integrity and cause DNA molecular damage, and the most genotoxic effect was found in the wastewater of Gabes hospital. Results show that the concentrations of the two antibiotics reached 33 and 40 ng/mL in the hospital wastewater of Gabes and Tozeur, respectively. The DNA biosensor based on the modified gold electrode exhibited superb performance and offers a probable application for the detection of genotoxicity antibiotics in hospital wastewater. The level of genotoxicity is proportional to the concentration of antibiotics detected in hospital wastewater. We will explore the application of this model for continuous monitoring downstream of hospital discharge and wastewater treatment plants for effective control of the presence of genotoxic products.
A Novel Method of BP Neural Network Based Green Building Design—The Case of Hotel Buildings in Hot Summer and Cold Winter Region of China
Authors: Xu Bin , Yuan Xiang
Published: February 2022

With the advent of the big data era, architectural design gradually tends to become more quantified and intelligent. This study proposes a novel green design method for energy-saving buildings based on a BP neural network. This study changed the traditional trial–error mode by evaluating energy consumption based on design performance parameters such as building shape, space, and interface. Instead, energy consumption quota values obtained from statistical data, as well as thermal parameters and energy system parameters in energy-saving standards, were taken as input parameters, and then the design scheme of building shape can be obtained through BP neural network technology. Based on data of 61 hotel buildings in a representative city among a hot summer and cold winter climate zone, the BP neural network model is established to control the building design variables, with 41 kgce/m2·a as its energy-saving design target. Through the energy consumption quota, the trained BP network is applied to predict the optimal architectural design parameters, including the building orientation angle, shape coefficient, window–wall ratio, etc., for twelve building typologies in an area range of 5000~60,000 m2. With recommended control thresholds of quantifiable architectural design elements obtained, this research can provide effective design decision-making suggestions for architects.
Challenges in the Long-Term Behaviour of Highly Radioactive Materials
Authors: Ojovan Michael I.
Published: February 2022

Highly radioactive materials are at the core in many useful applications ranging from operating nuclear reactors (including fast breeder reactors) to vitrified high-level radioactive waste, which is currently stored and awaiting final disposal into dedicated facilities within deep geological formations [...]