bluuebunny/crossref_metadata_2025 huggingface dataset:
Knowledge Discovery from Large Amounts of Social Media Data
Authors: Belcastro Loris , Cantini Riccardo , Marozzo Fabrizio
Published: January 2022

In recent years, social media analysis is arousing great interest in various scientific fields, such as sociology, political science, linguistics, and computer science. Large amounts of data gathered from social media are widely analyzed for extracting useful information concerning people’s behaviors and interactions. In particular, they can be exploited to analyze the collective sentiment of people, understand the behavior of user groups during global events, monitor public opinion close to important events, identify the main topics in a public discussion, or detect the most frequent routes followed by social media users. As an example of the countless works in the state-of-the-art on social media analysis, this paper presents three significant applications in the field of opinion and pattern mining from social media data: (i) an automatic application for discovering user mobility patterns, (ii) a novel application for estimating the political polarization of public opinion, and (iii) an application for discovering interesting social media discussion topics through a hashtag recommendation system. Such applications clearly highlight the abundance and wealth of useful information in many application contexts of human life that can be extracted from social media posts.
New Design of a Sample Cell for Neutron Reflectometry in Liquid–Liquid Systems and Its Application for Studying Structures at Air–Liquid and Liquid–Liquid Interfaces
Authors: Akutsu-Suyama Kazuhiro , Yamada Norifumi L. , Ueda Yuki , Motokawa Ryuhei , Narita Hirokazu
Published: January 2022

Knowledge of interfacial structures in liquid–liquid systems is imperative, especially for improving two-phase biological and chemical reactions. Therefore, we developed a new sample cell for neutron reflectometry (NR), which enables us to observe the layer structure around the interface, and investigated the adsorption behavior of a typical surfactant, sodium dodecyl sulfate (SDS), on the toluene-d8-D2O interface under the new experimental conditions. The new cell was characterized by placing the PTFE frame at the bottom to produce a smooth interface and downsized compared to the conventional cell. The obtained NR profiles were readily analyzable and we determined a slight difference in the SDS adsorption layer structure at the interface between the toluene-d8-D2O and air-D2O systems. This could be owing to the difference in the adsorption behavior of the SDS molecules depending on the interfacial conditions.
Performance Analysis of Modular Multilevel Converter with NPC Sub-Modules in Photovoltaic Grid-Integration
Authors: Mikkili Suresh , Krishna Raghu Vamsi , Bonthagorla Praveen Kumar , Senjyu Tomonobu
Published: January 2022

In this article, a three-phase modular multilevel converter (MMC) with three-level neutral point clamped converter (NPC) sub-modules (SMs) along with the placement of transformers in place of arm inductors is proposed for PV grid integration. Compared to the traditional MMCs, the proposed configuration reduces the voltage and power rating for the switches and the requirement of a high capacitor bank. In order to analyze the performance of the proposed converter arrangement, we have implemented four pulse width modulation schemes, such as Sine PWM with phase-level shifted carrier (SPWMLSC), Sine PWM with a phase-shifted carrier (SPWMPSC), Sine with the third harmonic injected level-shifted carrier (STHILSC), and Sine with the third harmonic injected phase-shifted carrier (STHIPSC). The proposed converter was simulated in the MATLAB/Simulink platform. Under normal and faulty operation, the results were presented with their performance indices of voltage and current harmonic distortion and sub-module capacitor voltage ripples at various modulation indices.
Dirichlet Matrix Factorization: A Reliable Classification-Based Recommender System
Authors: Lara-Cabrera Raúl , González Álvaro , Ortega Fernando , González-Prieto Ángel
Published: January 2022

Traditionally, recommender systems have been approached as regression models aiming to predict the score that a user would give to a particular item. In this work, we propose a recommender system that tackles the problem as a classification task instead of as a regression. The new model, Dirichlet Matrix Factorization (DirMF), provides not only a prediction but also its reliability, hence achieving a better balance between the quality and quantity of the predictions (i.e., reducing the prediction error by limiting the model’s coverage). The experimental results conducted show that the proposed model outperforms other models due to its ability to discard unreliable predictions. Compared to our previous model, which uses the same classification approach, DirMF shows a similar efficiency, outperforming the former on some of the datasets included in the experimental setup.
COVID-19′s Pandemic Effects on Bike Sharing Systems: A New Reality for Urban Mobility?
Authors: Bouhouras Efstathios , Basbas Socrates , Ftergioti Stamatia , Paschalidis Evangelos , Siakantaris Harris
Published: January 2022

On 11 March 2020, the World Health Organization made the assessment that a new disease (COVID-19) caused by a novel coronavirus (SARS-CoV-2) could be characterized as a pandemic. From that point, a chain reaction of events and difficult decisions requiring action was launched. National governments all over the world announced partial or total quarantine lockdowns in an effort to control the virus’ spreading in order to save as many lives as possible. The effects of the pandemic were multifaceted and transport was not excluded. The current paper examines data regarding the level of usage (provided by the administrator) of bike-sharing systems in three case studies/medium-sized Greek cities (Igoumenitsa, Chania, and Rhodes) and through a statistical analysis identifies if there is a correlation between the implemented measures and the modal choice of the residents. The main results and conclusions of this analysis reveal that the level of usage of these specific bike-sharing systems was significantly increased during the lockdown period compared to the situation before the lockdown and the pandemic in general.
A Facile Method to Prepare Superhydrophobic Coatings for Various Substrates
Authors: Zhang Yuxuan , Zhou Shuwen , Lv Zaosheng , Fan Lixia , Huang Yanfen , Liu Xuegang
Published: January 2022

In this study, the superhydrophobic composite coatings for self-cleaning were fabricated by mixing fluorine resin and two kinds of nanoparticles of carbon nanotubes (CNTs) and SiO2. When the mass ratio of CNTs to SiO2 is 2:3 and the added amount of nanoparticles is 75 wt. %, the superhydrophobic composite coatings with a water contact angle of 156.8° show the best self-cleaning property and 3.6° of contact angle hysteresis. Furthermore, the superhydrophobic composite coatings demonstrate good properties such as chemical resistance, thermal stability, and mechanical stability. The superhydrophobic composite coatings could be used for oil/water separation and could be applied to various substrate surfaces such as glass plates, cloth, board, steel plate, PVC plate, and so on. The superhydrophobic composite coatings show practical value in many fields because of their low cost and large area preparation.
From Patient to Musician: A Multi-Sensory Virtual Reality Rehabilitation Tool for Spatial Neglect
Authors: Heyse Joris , Carlier Stéphanie , Verhelst Ewoud , Vander Linden Catharine , De Backere Femke , De Turck Filip
Published: January 2022

Unilateral Spatial Neglect (USN) commonly results from a stroke or acquired brain injury. USN affects multiple modalities and results in failure to respond to stimuli on the contralesional side of space. Although USN is a heterogeneous syndrome, present-day therapy methods often fail to consider multiple modalities. Musical Neglect Therapy (MNT) is a therapy method that succeeds in incorporating multiple modalities by asking patients to make music. This research aimed to exploit the immersive and modifiable aspect of VR to translate MNT to a VR therapy tool. The tool was evaluated in a 2-week pilot study with four clinical users. These results are compared to a control group of four non-clinical users. Results indicated that patients responded to triggers in their entire environment and performance results could be clearly differentiated between clinical and non-clinical users. Moreover, patients increasingly corrected their head direction towards their neglected side. Patients stated that the use of VR increased their enjoyment of the therapy. This study contributes to the current research on rehabilitation for USN by proposing the first system to apply MNT in a VR environment. The tool shows promise as an addition to currently used rehabilitation methods. However, results are limited to a small sample size and performance metrics. Future work will focus on validating these results with a larger sample over a longer period. Moreover, future efforts should explore personalisation and gamification to tailor to the heterogeneity of the condition.
A Study on the Teaching Design of a Hybrid Civics Course Based on the Improved Attention Mechanism
Authors: Miao Wenwu
Published: January 2022

As an important vehicle for moral education, the moral indicators of civics and political science textbooks are naturally some of the most important criteria for revising textbooks. However, the textbook text dataset has too much textual information, ambiguous features, unbalanced sample distributions, etc. To address these problems, this paper combines a novel data enhancement method to obtain classification results based on word vectors. Additionally, for the problem of unbalanced sample sizes, this paper proposes a network model based on the attention mechanism, which combines the ideas of SMOTE and EDA, and uses a self-built stop word list and synonym word forest to conduct synonym queries, achieve a few categories of oversampling, and randomly disrupt the sentence order and intra-sentence word order to build a balanced dataset. The experimental results also show that the data augmentation method used in this paper’s model can effectively improve the performance of the model, resulting in a higher boost in the F1-measure of the model. The model incorporating the attention mechanism has better model generalization compared to the one without the attention mechanism, as well as a significant advantage compared to the reference model in other settings. The experimental results show that, compared with the original text classifier, the scheme of this paper effectively improves the evaluation effect and the reliability design for teaching a civics course.
Borehole Geophysical Joint Inversion to Fully Evaluate Shaly Sandstone Formations
Authors: Shahin Alireza , Myers Michael T. , Hathon Lori A.
Published: January 2022

Simultaneous inversion of sonic, density, and electrical resistivity borehole-derived well logs, has been addressed in literature in recent years. However, this problem is not broadly studied for dual-porosity sandstone formations. In addition, most authors presumed salinity and matrix properties as known parameters in their studies. We integrate the conservation of mass to model density, a differential effective medium theory for elastic modeling, and a laboratory-supported model for electrical resistivity of dual-porosity sandstones. Utilizing this methodology, we simulate electrical resistivity, sonic, and density well-log data. We develop a stochastic global search engine to jointly invert petrophysical properties. We build a dual-porosity formation with associated petrophysical properties and show the proposed workflow accurately replicates true well-log responses in the oil column, water leg, and transition zone. Local petrophysical properties (microporosity, intergranular porosity, total porosity, and water saturation) and global model parameters (salinity, matrix properties, critical porosity, resistivity lithology exponents, and sonic length scales for different pore networks) are all well recovered. The developed multiphysics calibrated rock models will assist petrophysicists and seismic analysts to identify and distinguish sandstone facies characteristics from well-log and prestack seismic data.
Gelatin–Siloxane Hybrid Monoliths as Novel Heavy Metal Adsorbents
Authors: Wojciechowska Patrycja , Cierpiszewski Ryszard , Maciejewski Hieronim
Published: January 2022

Novel gelatin-siloxane hybrid monoliths for heavy metal removal were prepared in the chemical reaction of gelatin with organomodified silicone containing epoxy group. Obtained porous hybrid materials were applied for adsorption of Cu(II), Cd(II) and Pb(II) from aqueous solutions. In this paper, the influence of siloxane amount used for the modification of gelatin on adsorbent stability and heavy metal removal was examined. The effect of pH values of the immersion liquid, as well as the contact time, was studied. Morphology, compressive strength and water absorption of hybrid monoliths were investigated. Desorption tests were also performed. The results showed that the higher the amount of the siloxane, the better stability of the hybrid monoliths in aqueous solutions. The highest values of adsorption capacity were observed for Pb(II) ions. The experimental maximum adsorption capacity determined for hybrid monoliths was 3.75 mg/g for Pb(II), 1.76 mg/g for Cu(II) and 1.5 mg/g for Cd(II). The desorption of metal ions for hybrid monoliths stable in aqueous solutions reached 70%.
Multiple-Valued Logic Modelling for Agents Controlled via Optical Networks
Authors: Bykovsky Alexey Yu.
Published: January 2022

The methods of data verification are discussed, which are intended for the distant control of autonomous mobile robotic agents via networks, combining optical data links. The problem of trust servers is considered for position verification and position-based cryptography tasks. In order to obtain flexible quantum and classical verification procedures, one should use the collective interaction of agents and network nodes, including some elements of the blockchain. Multiple-valued logic functions defined within discrete k-valued Allen–Givone algebra are proposed for the logically linked list of entries and the distributed ledger, which can be used for distant data verification and breakdown restoration in mobile agents with the help of partner network nodes. A distributed ledger scheme involves the assigning by distant partners of random hash values, which further can be used as keys for access to a set of distributed data storages, containing verification and restoration data. Multiple-valued logic procedures are simple and clear enough for high-dimensional logic modelling and for the design of combined quantum and classical protocols.
Understanding the Light Detection in an Integrated Novel Electrophotonic Wavesensor Photodetector
Authors: Hernández-Betanzos Joaquín , Aceves-Mijares Mariano , González-Fernández Alfredo Abelardo
Published: January 2022

This work presents a novel integrable silicon photodetector which can only be conceived as part of a monolithic electrophotonic basic structure formed of a silicon light emitter, waveguide and light detector. That is, it cannot operate as a single electronic or photonic device. The detector presents current gain, and photons reach the depletion region straightforward, allowing the detection of low power light produced by silicon light sources currently in use, which is difficult for existing photodetectors. The waveguide core is made of silicon nitride, and it is simultaneously the insulator in a MOS-like device. The light detection unit is intended for novel seamless electrophotonic platforms, and it is called wavesensor. In spite that the device is a MOS-like structure, it is not a MOSFET neither a lateral bipolar transistor, and one of the main differences with the former is that this is a bulk device working in Punch-Through regime. Being a MOS-like structure, it is fully compatible with standard microelectronics technology. A development of the mathematics involved in its operation is carried out in order to understand the physics of the detector, showing a gain factor in the photocurrent. Computer simulations of the fabrication process and photoelectric response of the device confirmed photocurrent values higher than the expected for a photodiode with efficiency = 1, thus demonstrating a new integrable photodetector with gain, capable of detecting light in the range of nW for electrophotonic applications.
Defect Detection on LED Chips Based on Position Pre-Estimation and Feature Enhancement
Authors: Xu Lu , Hu Xuejuan , He Ting , Hu Kai , Zhang Jaming
Published: January 2022

Light-emitting diode (LED) chips have disordered arrangement and defects with characteristics of low contrast, for which traditional segmentation methods cannot classify surface defects effectively. In this paper, a chip segmentation method based on position pre-estimation and a modified Normalized Correlation Coefficient (NCC) matching algorithm, as well as feature enhancement methods are proposed. The position pre-estimation method is used to avoid the interference introduced by the disordered chip arrangement and the large missing area. By modifying the NCC algorithm, matching speed is improved by eight times compared to traditional NCC while matching result is not affected by brightness change. Furthermore, feature enhancement schemes with higher speed and accuracy were designed to identify low-contrast defects. The experimental results showed that the average accuracy reached 99.54%, improved by 0.66% compared to the state-of-the-art method while the inspection missing rate was 0.03%. In addition, the detection time of a single chip was approximately 1.098 ms, which meets the requirements of online detection, and the smallest defect that could be detected was 2 µm. In summary, the methods proposed in this study meet the requirements of industrial online detection regardless of accuracy, efficiency, or extensibility.
Influence of Circular Saw Blade Design on Reducing Energy Consumption of a Circular Saw in the Cutting Process
Authors: Svoreň Ján , Naščák Ľubomír , Barcík Štefan , Koleda Peter , Stehlík Štefan
Published: January 2022

Optimal cutting conditions, which lead to a high quality of the machined surface and low energy consumption, are crucial for wood processing. This paper describes the effect of feed speed, cutting speed and mean chip thickness on energy consumption and saw blade surface temperature during the spruce (Picea excelsa) cutting process. In the experiment, the energy consumption and the surface temperature of the saw blades were measured to find the optimal cutting conditions for the energy-efficient cutting process. The surface temperature of the circular saw blade was monitored online using a non-contact infrared sensor connected directly to a PC via a USB connector. The results show that the cutting power and the surface temperature of the circular saw blade increased with increasing feed speed. The lowest values of cutting power were shown by the saw blade CSB3. Compared to the classic CSB1 circular saw blade, the values were lower by 8%. The surface temperature of the circular saw blade is highest at the outer edge (area of the heel of the teeth), and decreases towards the center of the circular saw blade. For an identical mean chip thickness, energy-efficient cutting was achieved at a feed speed of 21 m/min. There must be a trade-off between machine productivity and energy consumption. Monitoring the cutting process of circular saws using intelligent sensors is the way to adaptive control systems that ensure higher quality of the machined surface and cost-effective machining.
SAR Target Incremental Recognition Based on Hybrid Loss Function and Class-Bias Correction
Authors: Zhou Yongsheng , Zhang Shuo , Sun Xiaokun , Ma Fei , Zhang Fan
Published: January 2022

The Synthetic Aperture Radar (SAR) target recognition model usually needs to be retrained with all the samples when there are new-coming samples of new targets. Incremental learning emerges to continuously obtain new knowledge from new data while preserving most previously learned knowledge, saving both time and storage. There are still three problems in the existing incremental learning methods: (1) the recognition performance of old target classes degrades significantly during the incremental process; (2) the target classes are easily confused when similar target classes increase; (3) the model is inclined to new target classes due to class imbalance. Regarding the three problems, firstly, the old sample preservation and knowledge distillation were introduced to preserve both old representative knowledge and knowledge structure. Secondly, a class separation loss function was designed to reduce the intra-class distance and increase the inter-class distance, effectively avoiding the confusion between old and new classes. Thirdly, a bias correction layer and a linear model was designed, which enabled the model to treat the old and new target classes more fairly and eliminate the bias. The experimental results on the MSTAR dataset verified the superior performance compared with the other incremental learning methods.
Active Disturbance Rejection Control Based Sinusoidal Trajectory Tracking for an Upper Limb Robotic Rehabilitation Exoskeleton
Authors: Aole Sumit , Elamvazuthi Irraivan , Waghmare Laxman , Patre Balasaheb , Bhaskarwar Tushar , Meriaudeau Fabrice , Su Steven
Published: January 2022

In this paper, a combined control strategy with extended state observer (ESO) and finite time stable tracking differentiator (FTSTD) has been proposed to perform flexion and extension motion repetitively and accurately in the sagittal plane for shoulder and elbow joints. The proposed controller improves the tracking accuracy, performs state estimation, and actively rejects disturbance. A sinusoidal trajectory as an input has been given to a two-link multiple-input multiple-output (MIMO) upper limb robotic rehabilitation exoskeleton (ULRRE) for a passive rehabilitation purpose. The efficacy of the controller has been tested with the help of performance indices such as integral time square error (ITSE), integral square error (ISE), integral time absolute error (ITAE), and integral of the absolute magnitude of error (IAE). The system model is obtained through the Euler–Lagrangian method, and the controller’s stability is also given. The proposed controller has been simulated for ±20% parameter variation with constant external disturbances to test the disturbance rejection ability and robustness against parametric uncertainties. The proposed controller has been compared with already developed ESO-based methods such as active disturbance rejection control (ADRC), nonlinear active disturbance rejection control (NLADRC), and improved active disturbance rejection control (I-ADRC). It has been found that the proposed method increases tracking performance, as evidenced by the above performance indices.
Reconditioning of Diamond Coated Tools and Its Impact on Cutting Performance for CFRP Laminates
Authors: Soldatov Alexander , Remnev Alexey , Okada Akira
Published: January 2022

In recent years, CVD diamond-coated tungsten carbide (WC-Co) tools have been widely utilized due to their benefits in the machining of non-ferrous alloys and polymer composite materials, especially carbon-fiber-reinforced plastics (CFRPs). The reconditioning of such coated tools is economically attractive due to their high cost and short tool life. The decoating of the remaining diamond film from the used tools and the subsequent surface preparation by wet chemical pretreatment are essential steps for new CVD diamond film formation. Previously, it was shown that reactive ion beam etching (RIBE) could effectively remove CVD diamond films. However, some degree of WC-Co tool substrate damage is expected due to the high ion energy in RIBE and the chemical activity in wet etching. This study addresses the effects of RIBE decoating and surface pretreatment steps on WC-Co tools with a complex shape in terms of the ion-induced surface damage, geometry alteration, and adhesion of a subsequently re-applied CVD diamond film. Moreover, the cutting performance of the tools subjected to the RIBE decoating and repeated film deposition was studied via CFRP cutting tests. It has been shown that the RIBE decoated and recoated tools had a high level of cutting performance comparable to the new tools.
Aircraft Rotation Detection in Remote Sensing Image Based on Multi-Feature Fusion and Rotation-Aware Anchor
Authors: Tang Feifan , Wang Wei , Li Jian , Cao Jiang , Chen Deli , Jiang Xin , Xu Huifang , Du Yanling
Published: January 2022

Due to the variations of aircraft types, sizes, orientations, and complexity of remote sensing images, it is still difficult to effectively obtain accurate position and type by aircraft detection, which plays an important role in intelligent air transportation and digital battlefield. Current aircraft detection methods often use horizontal detectors, which produce significant redundancy, nesting, and overlap of detection areas and negatively affect the detection performance. To address these difficulties, a framework based on RetinaNet that combines a multi-feature fusion module and a rotating anchors generation mechanism is proposed. Firstly, the multi-feature fusion module mainly realizes feature fusion in two ways. One is to extract multi-scale features by the feature pyramid, and the other is to obtain corner features for each layer of feature map, thereby enriching the feature expression of aircraft. Then, we add a rotating anchor generation mechanism in the middle of the framework to realize the arbitrary orientation detection of aircraft. In the last, the framework connects two sub-networks, one for classifying anchor boxes and the other for regressing anchor boxes to ground-truth aircraft boxes. Compared with state-of-the-art methods by conducting comprehensive experiments on a publicly available dataset to validate the proposed method performance of aircraft detection. The detection precision (P) of proposed method achieves 97.06% on the public dataset, which demonstrates the effectiveness of the proposed method.
Amharic Adhoc Information Retrieval System Based on Morphological Features
Authors: Yeshambel Tilahun , Mothe Josiane , Assabie Yaregal
Published: January 2022

Information retrieval (IR) is one of the most important research and development areas due to the explosion of digital data and the need of accessing relevant information from huge corpora. Although IR systems function well for technologically advanced languages such as English, this is not the case for morphologically complex, under-resourced and less-studied languages such as Amharic. Amharic is a Semitic language characterized by a complex morphology where thousands of words are generated from a single root form through inflection and derivation. This has made the development of Amharic natural language processing (NLP) tools a challenging task. Amharic adhoc retrieval also faces challenges due to scarcity of linguistic resources, tools and standard evaluation corpora. In this research work, we investigate the impact of morphological features on the representation of Amharic documents and queries for adhoc retrieval. We also analyze the effects of stem-based and root-based text representation, and proposed new Amharic IR system architecture. Moreover, we present the resources and corpora we constructed for evaluation of Amharic IR systems and other NLP tools. We conduct various experiments with a TREC-like approach for Amharic IR test collection using a standard evaluation framework and measures. Our findings show that root-based text representation outperforms the conventional stem-based representation on Amharic IR.
A Survey on Artificial Intelligence (AI) and eXplainable AI in Air Traffic Management: Current Trends and Development with Future Research Trajectory
Authors: Degas Augustin , Islam Mir Riyanul , Hurter Christophe , Barua Shaibal , Rahman Hamidur , Poudel Minesh , Ruscio Daniele , Ahmed Mobyen Uddin , Begum Shahina , Rahman Md Aquif , Bonelli Stefano , Cartocci Giulia , Di Flumeri Gianluca , Borghini Gianluca , Babiloni Fabio , Aricó Pietro
Published: January 2022

Air Traffic Management (ATM) will be more complex in the coming decades due to the growth and increased complexity of aviation and has to be improved in order to maintain aviation safety. It is agreed that without significant improvement in this domain, the safety objectives defined by international organisations cannot be achieved and a risk of more incidents/accidents is envisaged. Nowadays, computer science plays a major role in data management and decisions made in ATM. Nonetheless, despite this, Artificial Intelligence (AI), which is one of the most researched topics in computer science, has not quite reached end users in ATM domain. In this paper, we analyse the state of the art with regards to usefulness of AI within aviation/ATM domain. It includes research work of the last decade of AI in ATM, the extraction of relevant trends and features, and the extraction of representative dimensions. We analysed how the general and ATM eXplainable Artificial Intelligence (XAI) works, analysing where and why XAI is needed, how it is currently provided, and the limitations, then synthesise the findings into a conceptual framework, named the DPP (Descriptive, Predictive, Prescriptive) model, and provide an example of its application in a scenario in 2030. It concludes that AI systems within ATM need further research for their acceptance by end-users. The development of appropriate XAI methods including the validation by appropriate authorities and end-users are key issues that needs to be addressed.
Hardware Platform-Aware Binarized Neural Network Model Optimization
Authors: Vo Quang Hieu , Asim Faaiz , Alimkhanuly Batyrbek , Lee Seunghyun , Kim Lokwon
Published: January 2022

Deep Neural Networks (DNNs) have shown superior accuracy at the expense of high memory and computation requirements. Optimizing DNN models regarding energy and hardware resource requirements is extremely important for applications with resource-constrained embedded environments. Although using binary neural networks (BNNs), one of the recent promising approaches, significantly reduces the design’s complexity, accuracy degradation is inevitable when reducing the precision of parameters and output activations. To balance between implementation cost and accuracy, in addition to proposing specialized hardware accelerators for corresponding specific network models, most recent software binary neural networks have been optimized based on generalized metrics, such as FLOPs or MAC operation requirements. However, with the wide range of hardware available today, independently evaluating software network structures is not good enough to determine the final network model for typical devices. In this paper, an architecture search algorithm based on estimating the hardware performance at the design time is proposed to achieve the best binary neural network models for hardware implementation on target platforms. With the XNOR-net used as a base architecture and target platforms, including Field Programmable Gate Array (FPGA), Graphic Processing Unit (GPU), and Resistive Random Access Memory (RRAM), the proposed algorithm shows its efficiency by giving more accurate estimation for the hardware performance at the design time than FLOPs or MAC operations.
Experimental Investigation and Exergy Analysis of Dehumidification Performances for a Cascaded Phase Change Heat Storage Dehumidifier
Authors: Zhang Lixi , Jia Yi , Fan Zhida , Wang Kangbo
Published: January 2022

In the humidification and dehumidification solar desalination system, the recovery of vapor condensation latent heat is the key problem. Using a cascaded phase change heat storage method to recover vapor condensation latent heat can improve the phase change heat storage rate and the water production performance of dehumidifier. The exergy analysis and experimental methods are used to study the cascaded phase change storage dehumidifier. The results show that the more stages of phase change materials in the cascaded phase change heat storage device, the greater the exergy efficiency will be. The heat transfer performance of phase change materials increases with the increase of hot and wet air temperature and flow at the inlet of the dehumidifier. The exergy efficiency and gain output ratio of three-stage phase change heat storage are higher than that of the single-stage. The three-stage one is recommended. If the heat recovered by the cascaded phase change heat storage device is supplied to the passive humidification dehumidification desalinator for secondary water output, the water output and gain output ratio will increase by 25% and the water production cost will be reduced by 20%. The results can provide a basis for the design and application of a cascaded phase change heat storage dehumidifier.
The Effects of Display Parameters and Devices on Spatial Ability Test Times
Authors: Guzsvinecz Tibor , Orbán-Mihálykó Éva , Sik-Lányi Cecília , Perge Erika
Published: January 2022

The effects of display parameters and devices are examined on spatial ability test times in virtual environments. Before the investigation, completion times of 240 and 61 students were measured, using an LG desktop display and the Gear VR, respectively. The virtual environment also logged the following randomized display parameters: virtual camera type, field of view, rotation, contrast ratio, whether shadows are turned on, and the used display device. The completion times were analyzed using regression analysis methods. Except for the virtual camera type, every factor has a significant influence on the test completion times. After grouping the remaining factors into pairs, triplets, quartets, and quintets, the following can be concluded: the combination of 75° field of view, 45° camera rotation, and 3:1 contrast ratio has the largest increase in completion times with an estimate of 420.88 s—even when this combination is in-side a quartet or a quintet. Consequently, significant decreases in completion times exist up to variable quartets (the largest being −106.29 s on average), however, the significance disappears among variable quintets. The occurrences of factors were also investigated: an undefined field of view, a 0° camera rotation, the Gear VR, a 7:1 contrast ratio, and turned-on shadows are the factors that occur in most significant combinations. These are the factors that often and significantly influence completion times.
Path Planning Based on NURBS for Hyper-Redundant Manipulator Used in Narrow Space
Authors: Duan Jinjun , Wang Bingcheng , Cui Kunkun , Dai Zhendong
Published: January 2022

Hyper-redundant manipulators with multiple degrees of freedom have special application prospects in narrow spaces, such as detection in small spaces in aerospace, rescue on-site disaster relief, etc. In order to solve the problems of complex obstacle avoidance planning and inverse solution selection of a hyper-redundant robot in a narrow space, a cubic B-spline curve based on collision-free trajectory using environmental edge information is planned. Firstly, a hyper-redundant robot composed of four pairs of double UCR (Universal-Cylindrical-Revolute) parallel mechanisms (2R1T, 2 Rotational DOFs and 1 Translation DOF) in series to realize flexible obstacle avoidance motion in narrow space is designed. The trajectory point envelope of a single UCR and the workspace of a single pair of UCR in Cartesian space based on the motion constraint boundaries of each joint are obtained. Then, the constraint control points according to the edge information of the obstacle are obtained, and the obstacle avoidance trajectory in the constrained space is planned by combining the A* algorithm and cubic B-spline algorithm. Finally, a variety of test scenarios are built to verify the obstacle avoidance planning algorithm. The results show that the proposed algorithm reduces the computational complexity of the obstacle avoidance process and enables the robot to complete flexible obstacle avoidance movement in the complex narrow space.
Study on the Influence of a Soft Soil Interlayer on Spatially Varying Ground Motions
Authors: Yao Erlei , Li Weichao , Miao Yu , Ye Lin , Yang Zhaowei
Published: January 2022

The existence of local soft interlayer can significantly amplify or attenuate the ground motion and thus might influence the lagged spatial coherency between spatially varying earthquake ground motions. A target site with a local soft interlayer was assumed first, and then two numerical examples were set. In example 1, linear soil behavior was considered and a large amount of quasi-stationary spatially varying earthquake ground motions were generated by combining the one-dimensional wave propagation theory and the classical spectral representation method. The influence regularity of varying shear wave velocity, buried depth, and thickness of the soft interlayer on the characteristics of lagged spatial coherency was investigated. In example 2, non-linear soil behavior was taken into account and fully non-stationary spatially varying earthquake ground motions were thus generated by using time-varying transfer function and spectral representation method. An overall evaluation was carried out to shed light on the differences of characteristics of spatial coherency between non-linear soil and linear soil cases. It showed that: (i) As the shear wave velocity of interlayer declines and as the buried depth and thickness increase, remarkable reduction of spatial coherency showed up; (ii) the reduction of lagged spatial coherency caused by varying buried depth may be more inclined to concentrate in the lower frequency range; (iii) the non-linear soil behavior can cause greater further reduction of lagged spatial coherency in comparison with linear soil behavior, especially in the higher frequency range; (iv) the troughs of lagged spatial coherency curve tend to be located in the variation range of vibration frequency of time-varying spectral ratio.
Influence of Acoustic Black Hole Array Embedded in a Plate on Its Energy Propagation and Sound Radiation
Authors: Liang Haoming , Liu Xiandong , Yuan Jiakai , Bao Yue , Shan Yingchun , He Tian
Published: January 2022

The plate embedded with acoustic black hole (ABH) indentations is potential for structural vibration and noise control. This work focuses on the mid- and low-frequency performance of plates embedded with the array of ABH for energy focalization and vibration and noise suppression. Plates embedded with two-dimensional ABHs are modelled with detailed Finite Element models, and the power flow method is introduced to analyze the energy propagation characteristics arising from the ABH effect. Then, the distribution of average vibration power density along the ABH radius is studied. Next, the energy dissipation effects of the plate model embedded with the ABH array with two types of damping layers are investigated. Finally, the sound pressure levels of the ABH structure are calculated and discussed. This work is helpful to understand the characteristics of plates embedded with the ABH array in reducing vibration and noise radiation. Results show that the ABH array can realize more than 100 times energy focalization effect at some frequencies, which indicates a potential in vibration and noise control when coupled with damping materials.
Optically Pumped Magnetometer Measuring Fatigue-Induced Damage in Steel
Authors: Koss Peter A. , Durmaz Ali Riza , Blug Andreas , Laskin Gennadii , Pawar Omkar Satish , Thiemann Kerstin , Bertz Alexander , Straub Thomas , Elsässer Christian
Published: January 2022

Uniaxial fatigue testing of micro-mechanical metallic specimens can provide valuable insight into damage formation. Magnetic and piezomagnetic testing are commonly used for qualitative characterization of damage in ferromagnetic specimens. Sensitive and accurate measurements with magnetic sensors is a key part of such a characterization. This work presents an experimental setup to induce structural defects in a micro-mechanical fatigue test. Simultaneously, the resulting piezomagnetic signals are measured during the complete lifetime of the tested specimen. The key component is a highly sensitive optically pumped magnetometer (OPM) used to measure the piezomagnetic hysteresis of a small specimen whose structural defects can be analyzed on a small scale by other metallographic characterization methods as well. This setup aims to quantify the magnetic signatures of damage during the fatigue process, which could enable non-destructive mechanical testing of materials. This paper reports the initial results obtained from this novel micro-magneto-mechanical test setup for a ferritic steel specimen.
Implementing a GIS-Based Digital Atlas of Agricultural Plastics to Reduce Their Environmental Footprint; Part I: A Deductive Approach
Authors: Cillis Giuseppe , Statuto Dina , Schettini Evelia , Vox Giuliano , Picuno Pietro
Published: January 2022

The agricultural sector has benefitted over the last century from several factors that have led to an exponential increase in its productive efficiency. The increasing use of new materials, such as plastics, has been one of the most important factors, as they have allowed for increased production in a simpler and more economical way. Various polymer types are used in different phases of the agricultural production cycle, but when their use is incorrectly managed, it can lead to different environmental impacts. In this study, an applied and simplified methodology to manage agricultural plastics monitoring and planning is proposed. The techniques used are based on quantification through the use of different datasets (orthophotos and satellite images) of the areas covered by plastics used for crop protection. The study area chosen is a part of the Ionian Coast of Southern Italy, which includes the most important municipalities of the Basilicata Region for fruit and vegetable production. The use of geographical techniques and observation methodologies, developed in an open-source GIS environment, enabled accurate location of about 2000 hectares of agricultural land covered by plastics, as well as identification of the areas most susceptible to the accumulation of plastic waste. The techniques and the model implemented, due to its simplicity of use and reliability, can be applied by different local authorities in order to realize an Atlas of agricultural plastics, which would be applied for continuous monitoring, thereby enabling the upscaling of future social and ecological impact assessments, identification of new policy impacts, market searches, etc.
Cellulose through the Lens of Microfluidics: A Review
Authors: Abbasi Moud Aref
Published: January 2022

Cellulose, a linear polysaccharide, is the most common and renewable biopolymer in nature. Because this natural polymer cannot be melted (heated) or dissolved (in typical organic solvents), making complicated structures from it necessitates specialized material processing design. In this review, we looked at the literature to see how cellulose in various shapes and forms has been utilized in conjunction with microfluidic chips, whether as a component of the chips, being processed by a chip, or providing characterization via chips. We utilized more than approximately 250 sources to compile this publication, and we sought to portray cellulose manufacturing utilizing a microfluidic system. The findings reveal that a variety of products, including elongated fibres, microcapsules, core–shell structures and particles, and 3D or 2D structured microfluidics-based devices, may be easily built utilizing the coupled topics of microfluidics and cellulose. This review is intended to provide a concise, visual, yet comprehensive depiction of current research on the topic of cellulose product design and understanding using microfluidics, including, but not limited to, paper-based microfluidics design and implications, and the emulsification/shape formation of cellulose inside the chips.
How Much Green Is Really “Cool”? Target Setting for Thermal Comfort Enhancement in a Warm, Humid City (Jakarta, Indonesia)
Authors: Stepani Hanna Meiria Naomi , Emmanuel Rohinton
Published: January 2022

Green infrastructure is well recognized as a key urban climate mitigation strategy. In line with this, and following a central government decree, Jakarta Municipal Government has created a green infrastructure target of 30% underpinned by a green space weighting factor. This study questions the efficacy of such a “universal” target setting from the point of view of outdoor thermal comfort and demonstrates the basis for an alternative approach. Based on a “new’ green factor developed from a systematic analysis of the literature, thermal comfort simulations of representative local climate zones (LCZ) show that improvements in current green space policy are possible. We enumerate a rational basis for specifying green space targets per local area based on contextual realities as captured by the LCZ approach. Such a nuanced approach to mitigate the human comfort consequences of inadvertent urban growth is not only more contextually appropriate but also enhances the feasibility of achieving the intended goal of urban greening in Jakarta.
Interfacial Dark Aging Is an Overlooked Source of Aqueous Secondary Organic Aerosol
Authors: Zhang Fei , Nguyen Manh Thuong , Fu Yao , Yu Xiao-Ying
Published: January 2022

In this work, the relative yields of aqueous secondary organic aerosols (aqSOAs) at the air–liquid (a–l) interface are investigated between photochemical and dark aging using in situ time-of-flight secondary ion mass spectrometry (ToF-SIMS). Our results show that dark aging is an important source of aqSOAs despite a lack of photochemical drivers. Photochemical reactions of glyoxal and hydroxyl radicals (•OH) produce oligomers and cluster ions at the aqueous surface. Interestingly, different oligomers and cluster ions form intensely in the dark at the a–l interface, contrary to the notion that oligomer formation mainly depends on light irradiation. Furthermore, cluster ions form readily during dark aging and have a higher water molecule adsorption ability. This finding is supported by the observation of more frequent organic water cluster ion formation. The relative yields of water clusters in the form of protonated and hydroxide ions are presented using van Krevelen diagrams to explore the underlying formation mechanisms of aqSOAs. Large protonated and hydroxide water clusters (e.g., (H2O)nH+, 17 < n ≤ 44) have reasonable yields during UV aging. In contrast, small protonated and hydroxide water clusters (e.g., (H2O)nH+, 1 ≤ n ≤ 17) form after several hours of dark aging. Moreover, cluster ions have higher yields in dark aging, indicating the overlooked influence of dark aging interfacial products on aerosol optical properties. Molecular dynamic simulation shows that cluster ions form stably in UV and dark aging. AqSOAs molecules produced from dark and photochemical aging can enhance UV absorption of the aqueous surface, promote cloud condensation nuclei (CCN) activities, and affect radiative forcing.