bluuebunny/crossref_metadata_2025 huggingface dataset:
Prediction of Thermal Conductivities of Rubbers by MD Simulations—New Insights
Authors: Vasilev Aleksandr , Lorenz Tommy , Breitkopf Cornelia
Published: May 2022

In this article, two main approaches to the prediction of thermal conductivities by molecular dynamics (MD) simulations are discussed, namely non-equilibrium molecular dynamics simulations (NEMD) and the application of the Green–Kubo formula, i.e., EMD. NEMD methods are more affected by size effects than EMD methods. The thermal conductivities of silicone rubbers in special were found as a function of the degree of crosslinking. Moreover, the thermal conductivities of thermoplastic polyurethane as function of the mass fraction of soft segments were obtained by those MD simulations. All results are in good agreement with data from the experimental literature. After the analysis of normalized heat flux autocorrelation functions, it has been revealed that heat in the polymers is mainly transferred by low-frequency phonons. Simulation details as well as advantages and disadvantages of the single methods are discussed in the article.
Durability and Service Life Prediction of Fluorocarbon Elastomer under Thermal Environments
Authors: Lee Pyoung-Chan , Kim Su Young , Ko Youn Ki , Ha Jin Uk , Jeoung Sun Kyoung , Lee Ju-Yub , Kim Minsu
Published: May 2022

This study investigated the service life prediction of fluorocarbon elastomers that are used in automotive vapor fuel hoses under thermal environments. The changes in mechanical properties such as the tensile strength, elongation, compression set (CS), and hardness according to thermal aging were investigated for two types of ternary fluoroelastomers. Destructive tests of the tensile strength and elongation showed large variations in the mechanical properties under the same condition because there is no continuity of samples. In contrast, nondestructive tests of the CS and hardness showed little variations in the mechanical properties under the same condition. The elongation, CS, and hardness were selected as the physical parameters for service life prediction as they showed a tendency according to the aging temperature, which is an accelerating factor. The effective activation energy derived using each physical parameter was 74.91–159.6 kJ mol−1, and the service life was 17.8–140 × 103 h based on B10. In this study, hardness, which has a small deviation between samples, is considered appropriate as mechanical parameter for predicting the service lifetime.
Optimal Design of a Novel Composite Anchorage for Carbon-Fiber-Reinforced Polymer (CFRP) Tendons
Authors: Sun Yamin , Mei Kuihua , Sun Shengjiang , Wang Tao , Ren Xiang
Published: May 2022

In this study, we proposed a novel composite anchorage that considers the anchoring performance and dimension simultaneously. The design concept of this composite anchorage was first introduced, followed by comparison with the traditional inner-cone bond-type anchorage and traditional composite anchorage through theoretical and experimental methods. Then, a parametric study was conducted to determine the influence of different parameters on the anchoring performance, and the optimal design parameters were recommended according to the finite element (FE) and test results. Finally, the practicability of the optimal design parameters were validated through experiments on the anchorage with multiple CFRP tendons. Results showed that the novel composite anchorage could improve the anchoring performance compared with the traditional inner-cone bond-type anchorage by promoting increased anchorage efficiency by 60.4% and, with an ideal failure mode of tendon rupture. Moreover, the novel composite anchorage had smaller dimensions and avoided the presence of a vulnerable position at the junction of the mechanical and bond parts compared with the traditional composite anchorage. In addition, a group of optimal design parameters of this composite anchorage with a pre-tightening force of 130 kN, an inclinational differential angle of 0.1°, an inclination angle of 2.9°, and an embedded length of 30 d~40 d were proposed. The composite anchorage with five CFRP tendons designed with the proposed parameters failed with the rupture of the tendons and exhibited an anchoring efficiency of 1.05. This result showed that the optimal parameters were suitable for this novel composite anchorage to grip multiple tendons. This study can provide an experimental and theoretical basis for designing large-tonnage anchorage for multiple FRP tendons used as hangers or cables in real bridges.
Community Psychiatry in Rural Greece: The Role of the Mobile Mental Health Units
Authors: Peritogiannis Vaios , Papathanasiou Ioanna V. , Giotakos Orestis
Published: May 2022

Almost a decade ago, an article published in the official journal of the Hellenic Psychiatric Association, concerning the state of Greek mental health reform, referred to the significant shortages of mental health staff and services in rural areas of the country [...]
The Puzzle of Revenge
Authors: Powers Bill
Published: May 2022

We pursue a multi-leveled phenomenological exploration of revenge. Revenge’s puzzle is to give an account of what exactly revenge accomplishes when it apparently cannot alter the past or remedy the initiating harm. The structure of revenge consists of one harmed, the perception of harm and suffering, and one perceived as responsible for the harm. The situation is apperceived as a negatively saturated experience; as such, it binds and has a hold on the one harmed, constituting her as enthralled. Revenge seeks to remedy the situation by the intentional act of objectifying, constituting, and finitizing the infinite situation. This is accomplished by constituting the guilty one as guilty, thereby mastering, in some measure, the saturated situation. We suggest that the realm and machinery required for this process is found in the realm of the imagination, where similarity and association of ideas and concepts are at play. Saturation plays at the edge of this realm as alien. It is by way of the familiar and constituted that the alien is tamed, and revenge puts the situation to “rest”.
On the Exploitation of Remote Sensing Technologies for the Monitoring of Coastal and River Delta Regions
Authors: Zhao Qing , Pan Jiayi , Devlin Adam Thomas , Tang Maochuan , Yao Chengfang , Zamparelli Virginia , Falabella Francesco , Pepe Antonio
Published: May 2022

Remote sensing technologies are extensively applied to prevent, monitor, and forecast hazardous risk conditions in the present-day global climate change era. This paper presents an overview of the current stage of remote sensing approaches employed to study coastal and delta river regions. The advantages and limitations of Earth Observation technology in characterizing the effects of climate variations on coastal environments are also presented. The role of the constellations of satellite sensors for Earth Observation, collecting helpful information on the Earth’s system and its temporal changes, is emphasized. For some key technologies, the principal characteristics of the processing chains adopted to obtain from the collected raw data added-value products are summarized. Emphasis is put on studying various disaster risks that affect coastal and megacity areas, where heterogeneous and interlinked hazard conditions can severely affect the population.
Multi-Level Alignment Network for Cross-Domain Ship Detection
Authors: Xu Chujie , Zheng Xiangtao , Lu Xiaoqiang
Published: May 2022

Ship detection is an important research topic in the field of remote sensing. Compared with optical detection methods, Synthetic Aperture Radar (SAR) ship detection can penetrate clouds to detect hidden ships in all-day and all-weather. Currently, the state-of-the-art methods exploit convolutional neural networks to train ship detectors, which require a considerable labeled dataset. However, it is difficult to label the SAR images because of expensive labor and well-trained experts. To address the above limitations, this paper explores a cross-domain ship detection task, which adapts the detector from labeled optical images to unlabeled SAR images. There is a significant visual difference between SAR images and optical images. To achieve cross-domain detection, the multi-level alignment network, which includes image-level, convolution-level, and instance-level, is proposed to reduce the large domain shift. First, image-level alignment exploits generative adversarial networks to generate SAR images from the optical images. Then, the generated SAR images and the real SAR images are used to train the detector. To further minimize domain distribution shift, the detector integrates convolution-level alignment and instance-level alignment. Convolution-level alignment trains the domain classifier on each activation of the convolutional features, which minimizes the domain distance to learn domain-invariant features. Instance-level alignment reduces domain distribution shift on the features extracted from the region proposals. The entire multi-level alignment network is trained end-to-end and its effectiveness is proved on multiple cross-domain ship detection datasets.
Comparison between Automated and Manual Detection of Lava Fountains from Fixed Monitoring Thermal Cameras at Etna Volcano, Italy
Authors: Calvari Sonia , Nunnari Giuseppe
Published: May 2022

The Etna volcano is renowned worldwide for its extraordinary lava fountains that rise several kilometers above the vent and feed eruptive columns, then drift hundreds of kilometers away from the source. The Italian Istituto Nazionale di Geofisica e Vulcanologia-Osservatorio Etneo (INGV-OE) is responsible for the monitoring of Mt. Etna, and for this reason, has deployed a network of visible and thermal cameras around the volcano. From these cameras, INGV-OE keeps a keen eye, and is able to observe the eruptive activity, promptly advising the civil protection and aviation authorities of any changes, as well as quantifying the spread of lava flows and the extent of pyroclastic and ash plumes by using a careful analysis of the videos recorded by the monitoring cameras. However, most of the work involves analysis carried out by hand, which is necessarily approximate and time-consuming, thus limiting the usefulness of these results for a prompt hazard assessment. In addition, the start of lava fountains is often a gradual process, increasing in strength from Strombolian activity, to intermediate explosive activity, and eventually leading to sustained lava fountains. The thresholds between these different fields (Strombolian, Intermediate, and lava fountains) are not clear cut, and are often very difficult to distinguish by a manual analysis of the images. In this paper, we presented an automated routine that, when applied to thermal images and with good weather conditions, allowed us to detect (1) the starting and ending time of each lava fountain, (2) the area occupied by hot pyroclasts, (3) the elevation reached by the lava fountains over time, and (4) eventually, to calculate in real-time the erupted volume of pyroclasts, giving results close to the manual analysis but more focused on the sustained portion of the lava fountain, which is also the most dangerous. This routine can also be applied to other active volcanoes, allowing a prompt and uniform definition of the timing of the lava fountain eruptive activity, as well as the magnitude and intensity of the event.
Combining Passive Acoustics and Environmental Data for Scaling Up Ecosystem Monitoring: A Test on Coral Reef Fishes
Authors: Elise Simon , Guilhaumon François , Mou-Tham Gérard , Urbina-Barreto Isabel , Vigliola Laurent , Kulbicki Michel , Bruggemann J. Henrich
Published: May 2022

Ecological surveys of coral reefs mostly rely on visual data collected by human observers. Although new monitoring tools are emerging, their specific advantages should be identified to optimise their simultaneous use. Based on the goodness-of-fit of linear models, we compared the potential of passive acoustics and environmental data for predicting the structure of coral reef fish assemblages in different environmental and biogeographic settings. Both data types complemented each other. Globally, the acoustic data showed relatively low added value in predicting fish assemblage structures. The predictions were best for the distribution of fish abundance among functional entities (i.e., proxies for fish functional groups, grouping species that share similar eco-morphological traits), for the simplest functional entities (i.e., combining two eco-morphological traits), and when considering diet and the level in the water column of the species. Our study demonstrates that Passive Acoustic Monitoring (PAM) improves fish assemblage assessment when used in tandem with environmental data compared to using environmental data alone. Such combinations can help with responding to the current conservation challenge by improving our surveying capacities at increased spatial and temporal scales, facilitating the identification and monitoring of priority management areas.
Assessment of Maize Drought Risk in Midwestern Jilin Province: A Comparative Analysis of TOPSIS and VIKOR Models
Authors: Ma Yining , Guga Suri , Xu Jie , Liu Xingpeng , Tong Zhijun , Zhang Jiquan
Published: May 2022

Drought is a major natural disaster that causes a reduction in rain-fed maize yield. Agricultural drought risk assessment is conducive to improving regional disaster management ability, thereby reducing food security risks and economic losses. Considering the complexity of risk assessment research, an increasing number of researchers are focusing on the multiple-criteria decision-making (MCDM) method. However, the applicability of the MCDM method to agro-meteorological disaster risk assessments is not clear. Therefore, this study comprehensively evaluated hazard, exposure, vulnerability, and emergency response and recovery capability using the TOPSIS and VIKOR models to generate a maize drought risk map in mid-western Jilin Province and ranked the drought risk of each county. The results showed that: (1) maize drought risk in the middle and west of Jilin province showed an increasing trend. Spatially, the risk diminished from west to east. The drought risks faced by Tongyu, Changchun, and Dehui were more severe; (2) the evaluation results of the two models were verified using the yield reduction rate. The VIKOR model was found to be more suitable for agrometeorological drought risk assessments; (3) according to the damage degree of drought disaster to maize, the cluster analysis method was used to divide the study area into three sub-regions: safe, moderate drought, and severe drought. Combined with the characteristics of different regions, suggestions on disaster prevention and mitigation are proposed. The results of this study can provide a basis for formulating strategies to alleviate drought, reduce losses, and ensure the sustainable development of agriculture.
Effect of Assimilating SMAP Soil Moisture on CO2 and CH4 Fluxes through Direct Insertion in a Land Surface Model
Authors: Zhang Zhen , Chatterjee Abhishek , Ott Lesley , Reichle Rolf , Feldman Andrew F. , Poulter Benjamin
Published: May 2022

Soil moisture impacts the biosphere–atmosphere exchange of CO2 and CH4 and plays an important role in the terrestrial carbon cycle. A better representation of soil moisture would improve coupled carbon–water dynamics in terrestrial ecosystem models and could potentially improve model estimates of large-scale carbon fluxes and climate feedbacks. Here, we investigate using soil moisture observations from the Soil Moisture Active Passive (SMAP) satellite mission to inform simulated carbon fluxes in the global terrestrial ecosystem model LPJ-wsl. Results suggest that the direct insertion of SMAP reduces the bias in simulated soil moisture at in situ measurement sites by 40%, with a greater improvement at temperate sites. A wavelet analysis between the model and measurements from 26 FLUXNET sites suggests that the assimilated run modestly reduces the bias of simulated carbon fluxes for boreal and subtropical sites at 1–2-month time scales. At regional scales, SMAP soil moisture can improve the estimated responses of CO2 and CH4 fluxes to extreme events such as the 2018 European drought and the 2019 rainfall event in the Sudd (Southern Sudan) wetlands. The simulated improvements to land–surface carbon fluxes using the direct insertion of SMAP are shown across a variety of timescales, which suggests the potential of SMAP soil moisture in improving the model representation of carbon–water coupling.
Characteristics of Resistive PM Sensors for Onboard Diagnostics of Diesel Particulate Filter Failure
Authors: Oh Kwang Chul , Lee Kyoung Bok , Jeong Byeong Gyu
Published: May 2022

In accordance with the recently reinforced exhaust regulations and onboard diagnostics regulations, it is essential to adopt diesel particulate filter systems in diesel vehicles; a sensor that directly measures particulate matter (PM) in exhaust gas is installed to precisely monitor diesel particulate filter (DPF) failure. Because the reduction of particulate matter in the diesel particulate filter system is greatly influenced by the physical wall structure of the substrate, the presence or absence of damage to the substrate wall (cracks or local melting, etc.) determines the reliability of normal DPF operation. Therefore, an onboard diagnostics sensor for particle matter is being developed with a focus on monitoring damage to the DPF wall. In this study, as a sensor for determining damage to the substrate wall, an accumulation-type sensor whose resistance changes as soot particles are deposited between two electrodes was fabricated. The sensor characteristics were investigated by changing the gap between the sensor electrodes, sensor cap shape, and electrode bias voltage to improve resistive soot sensor sensitivity and response. From the signal characteristics of various sensor configurations, a combination sensor with improved signal stability and response time is manufactured, and they were compared with the characteristics of commercially available sensors in the engine-simulated NEDC mode in terms of the degree of DPF crack. As a result of transient mode, PM monitoring cycle was improved by 1.2~1.5 times during the same vehicle driving time compared to the existing commercial sensor.
Comparison of Three Prototypes of PPG Sensors for Continual Real-Time Measurement in Weak Magnetic Field
Authors: Přibil Jiří , Přibilová Anna , Frollo Ivan
Published: May 2022

This paper is focused on investigation of three developed prototypes of sensors based on the photoplethysmography (PPG) principle for continual measurement of the PPG signal in the magnetic field environment with the inherent radiofrequency and electromagnetic disturbance. The tested prototypes differ in the used optical part of the PPG sensor and their working mode, control unit, power supply, and applied Bluetooth (BT) communication methods. The main aim of the current work was motivated by finding suitable and universal parameter settings for PPG signal real-time recording in different working mode conditions. Comparative measurements in laboratory conditions by certified commercial pulse oximeter and blood pressure monitor (BPM) devices show good stability and proper accuracy of finally determined heart rate values. The supplementary investigation certifies the necessity of the placement of the pressure cuff of the BPM device on the opposite arm than the tested PPG sensor. Measurement experiments inside the scanning area of the running weak field magnetic resonance scanner verify proper function and practical usability of sensed PPG signals for further processing and analysis in all three prototype cases. Additional testing shows that the BT transmission in the scanning area has no visible influence on the quality of the finally obtained scanner images.
Agnostic Envelope Linearization of Dynamically Supplied Power Amplifiers for Mobile Terminals
Authors: Li Wantao , Montoro Gabriel , Gilabert Pere L.
Published: May 2022

This paper presents an envelope linearization technique to compensate for the nonlinear distortion of envelope tracking (ET) power amplifiers (PAs) for 5G new radio (NR) mobile terminals. The proposed envelope optimization (EOPT) method is agnostic of the nonlinear distortion generated in the envelope supply path and can compensate for the nonlinear distortion at the ET PA output without the need to monitor the output at the envelope tracking modulator (ETM). The linearization system in the envelope path is based on the envelope generalized memory polynomial (EGMP) behavioral model. Since the ETM output is not available, an iterative nonlinear least squares solution inspired in the deep deterministic policy gradient (DDPG) algorithm is proposed to extract the coefficients of the EGMP model. The EOPT method is validated on a system-on-chip (SoC) ET PA board designed for mobile terminal applications. Experimental results show the suitability of the proposed method to guarantee the linearity requirements (i.e., adjacent channel power ratio below −36 dBc) with 16.8% of power efficiency when operating the ET PA with 5G new radio test signals of 60 MHz bandwidth operating at 2.55 GHz (band 7). The linearization performance of the proposed EOPT method is comparable to the envelope leakage cancellation (ELC) approach (but saving the need for an analog to digital converter to monitor the ETM output), and can outperform a conventional I-Q digital predistorter based on the generalized memory polynomial (GMP) behavioral model.
Self-Stabilizing Capacitated Vertex Cover Algorithms for Internet-of-Things-Enabled Wireless Sensor Networks
Authors: Yigit Yasin , Dagdeviren Orhan , Challenger Moharram
Published: May 2022

Wireless sensor networks (WSNs) achieving environmental sensing are fundamental communication layer technologies in the Internet of Things. Battery-powered sensor nodes may face many problems, such as battery drain and software problems. Therefore, the utilization of self-stabilization, which is one of the fault-tolerance techniques, brings the network back to its legitimate state when the topology is changed due to node leaves. In this technique, a scheduler decides on which nodes could execute their rules regarding spatial and temporal properties. A useful graph theoretical structure is the vertex cover that can be utilized in various WSN applications such as routing, clustering, replica placement and link monitoring. A capacitated vertex cover is the generalized version of the problem which restricts the number of edges covered by a vertex by applying a capacity constraint to limit the covered edge count. In this paper, we propose two self-stabilizing capacitated vertex cover algorithms for WSNs. To the best of our knowledge, these algorithms are the first attempts in this manner. The first algorithm is stabilized under an unfair distributed scheduler (that is, the scheduler which does not grant all enabled nodes to make their moves but guarantees the global progress of the system) at most O(n2) step, where n is the count of nodes. The second algorithm assumes 2-hop (degree 2) knowledge about the network and runs under the unfair scheduler, which subsumes the synchronous and distributed fair scheduler and stabilizes itself after O(n) moves in O(n) step, which is acceptable for most WSN setups. We theoretically analyze the algorithms to provide proof of correctness and their step complexities. Moreover, we provide simulation setups by applying IRIS sensor node parameters and compare our algorithms with their counterparts. The gathered measurements from the simulations revealed that the proposed algorithms are faster than their competitors, use less energy and offer better vertex cover solutions.
Teleoperation of High-Speed Robot Hand with High-Speed Finger Position Recognition and High-Accuracy Grasp Type Estimation
Authors: Yamakawa Yuji , Yoshida Koki
Published: May 2022

This paper focuses on the teleoperation of a robot hand on the basis of finger position recognition and grasp type estimation. For the finger position recognition, we propose a new method that fuses machine learning and high-speed image-processing techniques. Furthermore, we propose a grasp type estimation method according to the results of the finger position recognition by using decision tree. We developed a teleoperation system with high speed and high responsiveness according to the results of the finger position recognition and grasp type estimation. By using the proposed method and system, we achieved teleoperation of a high-speed robot hand. In particular, we achieved teleoperated robot hand control beyond the speed of human hand motion.
Modeling of High-Power Tonpilz Terfenol-D Transducer Using Complex Material Parameters
Authors: Wei Yanfei , Yang Xin , Chen Yukai , Zhang Zhihe , Zheng Haobin
Published: May 2022

The loss effect in smart materials, the active part of a transducer, is of significant importance to acoustic transducer designers, as it directly affects the important characteristics of the transducer, such as the impedance spectra, frequency response, and the amount of heat generated. It is therefore beneficial to be able to incorporate energy losses in the design phase. For high-power low-frequency transducers requiring more smart materials, losses become even more appreciable. In this paper, similar to piezoelectric materials, three losses in Terfenol-D are considered by introducing complex quantities, representing the elastic loss, piezomagnetic loss, and magnetic loss. The frequency-dependent eddy current loss is also considered and incorporated into the complex permeability of giant magnetostrictive materials. These complex material parameters are then successfully applied to improve the popular plane-wave method (PWM) circuit model and finite element method (FEM) model. To verify the accuracy and effectiveness of the proposed methods, a high-power Tonpilz Terfenol-D transducer with a resonance frequency of around 1 kHz and a maximum transmitting current response (TCR) of 187 dB/1A/μPa is manufactured and tested. The good agreement between the simulation and experimental results validates the improved PWM circuit model and FEA model, which may shed light on the more predictable design of high-power giant magnetostrictive transducers in the future.
Research on the Extraction of Hazard Sources along High-Speed Railways from High-Resolution Remote Sensing Images Based on TE-ResUNet
Authors: Pan Xuran , Yang Lina , Sun Xu , Yao Jingchuan , Guo Jiliang
Published: May 2022

There are many potential hazard sources along high-speed railways that threaten the safety of railway operation. Traditional ground search methods are failing to meet the needs of safe and efficient investigation. In order to accurately and efficiently locate hazard sources along the high-speed railway, this paper proposes a texture-enhanced ResUNet (TE-ResUNet) model for railway hazard sources extraction from high-resolution remote sensing images. According to the characteristics of hazard sources in remote sensing images, TE-ResUNet adopts texture enhancement modules to enhance the texture details of low-level features, and thus improve the extraction accuracy of boundaries and small targets. In addition, a multi-scale Lovász loss function is proposed to deal with the class imbalance problem and force the texture enhancement modules to learn better parameters. The proposed method is compared with the existing methods, namely, FCN8s, PSPNet, DeepLabv3, and AEUNet. The experimental results on the GF-2 railway hazard source dataset show that the TE-ResUNet is superior in terms of overall accuracy, F1-score, and recall. This indicates that the proposed TE-ResUNet can achieve accurate and effective hazard sources extraction, while ensuring high recall for small-area targets.
Effects of Central and Peripheral Fatigue on Impact Characteristics during Running
Authors: Encarnación-Martínez Alberto , García-Gallart Antonio , Sanchis-Sanchis Roberto , Pérez-Soriano Pedro
Published: May 2022

Fatigue and impact can represent an injury risk factor during running. The objective of this study was to compare the impact transmission along the locomotor system between the central and peripheral fatigued states during running. Tibial and head acceleration as well as shock attenuation in the time- and frequency-domain were analyzed during 2-min of treadmill running in the pre- and post-fatigue state in eighteen male popular runners (N = 18). The impact transmission was measured before and after a 30-min central fatigue protocol on the treadmill or a peripheral fatigue protocol in the quadricep and hamstring muscles using an isokinetic dynamometer. The time-domain acceleration variables were not modified either by peripheral or central fatigue (p > 0.05). Nevertheless, central fatigue increased the maximum (p = 0.006) and total (p = 0.007) signal power magnitude in the high-frequency range in the tibia, and the attenuation variable in the low- (p = 0.048) and high-frequency area (p = 0.000), while peripheral fatigue did not cause any modifications in the frequency-domain variables (p > 0.05). Furthermore, the attenuation in the low (p = 0.000)- and high-frequency area was higher with central fatigue than peripheral fatigue (p = 0.003). The results demonstrate that central fatigue increases the severity of impact during running as well as the attenuation of low and high components.
Frequency Bandwidth of Pressure Sensors Dedicated to Blast Experiments
Authors: Chalnot Mathieu , Pons Patrick , Aubert Hervé
Published: May 2022

New broadband (>1 MHz) pressure sensors are regularly reported in the literature to measure the overpressure of blast waves. However, the frequency bandwidth needed to accurately measure such overpressure has not yet been clearly discussed. In this article, we present a methodology to determine the bandwidth required to estimate the overpressure magnitude at the front of a blast wave, in order to obtain a desired estimation accuracy. The bandwidth is derived here by using Kingery and Bulmash data.
Efficient User-Serving Scheme in the User-Centric Cell-Free Massive MIMO System
Authors: Oh Ji-Hye , Shin Beom-Sik , Kim Min-A , You Young-Hwan , Hwang Duck-Dong , Song Hyoung-Kyu
Published: May 2022

A cell-free massive multiple input multiple output (MIMO) system is an attractive network model that is in the spotlight in 5G and future communication systems. Despite numerous advantages, the cell-free massive MIMO system has a problem in that it is difficult to operate in reality due to its vast amount of calculation. The user-centric cell-free massive MIMO model has a more feasible and scalable benefit than the cell-free massive MIMO model. However, this model has the disadvantage that as the number of users in the area increases, there are users who do not receive the service. In this paper, the proposed scheme creates connections for unserved users under a user-centric scheme without additional access point (AP) installation and disconnection for existing users. A downlink user-centric cell-free massive MIMO system model in which the APs are connected to the central processing unit (CPU) and the APs and users are geographically distributed is considered. First, the downlink spectral efficiency formula is derived and applied to the user-centric cell-free massive MIMO system. Then, the proposed scheme and power control algorithm are applied to the derived formula. The simulation results show that the unserved users within the area disappear by using the proposed scheme, while the bit error rate (BER) performance and sum rate improve compared to the existing scheme. In addition, it is shown that the proposed scheme works well even with a very large number of users in the area, and a significant service performance improvement for the worst 10% of users and the overall improvement of per-user throughput for the bottom 70% of users are ensured.
Domain Knowledge-Based Evolutionary Reinforcement Learning for Sensor Placement
Authors: Song Mingxuan , Hu Chengyu , Gong Wenyin , Yan Xuesong
Published: May 2022

Reducing pollutant detection time based on a reasonable sensor combination is desirable. Clean drinking water is essential to life. However, the water supply network (WSN) is a vulnerable target for accidental or intentional contamination due to its extensive geographic coverage, multiple points of access, backflow, infrastructure aging, and designed sabotage. Contaminants entering WSN are one of the most dangerous events that may cause sickness or even death among people. Using sensors to monitor the water quality in real time is one of the most effective ways to minimize negative consequences on public health. However, it is a challenge to deploy a limited number of sensors in a large-scale WSN. In this study, the sensor placement problem (SPP) is modeled as a sequential decision optimization problem, then an evolutionary reinforcement learning (ERL) algorithm based on domain knowledge is proposed to solve SPP. Extensive experiments have been conducted and the results show that our proposed algorithm outperforms meta-heuristic algorithms and deep reinforcement learning (DRL).
Internal Heat Exchanger Influence in Operational Cost and Environmental Impact of an Experimental Installation Using Low GWP Refrigerant for HVAC Conditions
Authors: Méndez-Méndez Dario , Pérez-García Vicente , Belman-Flores Juan M. , Riesco-Ávila José M. , Barroso-Maldonado Juan M.
Published: May 2022

The use of an internal heat exchanger in vapor compression refrigeration systems of one stage is a common practice because it helps to increase the cooling capacity in the evaporator. Furthermore, the use of refrigerants with low global warming potential is becoming more frequent due to environmental regulations worldwide. Thus, this paper presents an evaluation of the improvement produced by the inclusion of an internal heat exchanger cycle (IHXC) in an experimental installation from the viewpoint of exergy, economic and environmental through to exergy, exergoeconomics, and Specific Life Cycle Climate Performance (SLCCP) studies. The tests were conducted using R1234ze(E) as a replacement alternative to R134a in three evaporating temperature conditions: 4 °C, 9 °C, and 14 °C. Comparisons were made considering R134a in BRC mode versus R1234ze(E) in BRC and IHXC modes. Results show that a lower environmental impact is produced by an evaporating temperature of 14 °C with a reduction in SLCCP of 13.3% using IHXC and R1234ze(E). Moreover, the highest increase in exergy efficiency was observed for an evaporating temperature of 4 °C, with this increase being 9%, while the lowest increase in the total cost rate was observed for the same evaporating temperature, being 12.3% and 21.2% for BRC and IHXC modes using R1234ze(E), respectively.
Cost Efficiency and CO2 Emission Reduction in Short Sea Shipping: Evidence from Ciwandan Port–Panjang Port Routes, Indonesia
Authors: Arianto Dedy , Marpaung Edward , Malisan Johny , Humang Windra Priatna , Puriningsih Feronika Sekar , Mutharuddin  , Mardiana Tetty Sulastry , Siahaan Wilmar Jonris , Pairunan Teguh , Kurniawan Abdy
Published: May 2022

Merak Port of Java and Bakauheni Port of Sumatera are connected by ferry lines. However, the number of ferry ships and facilities of the two ports are not able to accommodate the number of vehicles that cross. Queues of vehicles often occur and waiting times at the port are very high and have an impact on the accumulation of vehicles on the road to the port. Anticipating these conditions, it is possible to open a short sea shipping (SSS) route from Ciwandan port to Panjang port as an alternative route for shifting some of the vehicles served by those ferry ships. This research aims to analyze the efficiency of opening the Ciwandan–Panjang SSS route in terms of benefits for stakeholders, cost efficiency for vehicle users, and the potential for CO2 reduction from exhaust gases. We use a descriptive quantitative method. The analytical techniques used include port cost analysis, benefit analysis (for the government and ship operators), comparative analysis of transportation costs, and analysis of the impact of reducing CO2 emissions, which are valued monetarily. The results of the analysis show that the operation of the Ciwandan–Panjang SSS can reduce the total cost of vehicles compared to the Merak–Bakuheni route. Owners of cargo vehicles are able to save on logistics costs of IDR 332 billion per year. Estimated state revenue through non-tax state revenues (NTSI) and value-added tax (VAT) is increased. Losses due to CO2 emissions are estimated to be reduced, with a value of up to IDR 511 billion per year.
A New Step-by-Step Model for Implementing Open Innovation
Authors: Arvaniti Eleni N. , Dima Agapi , Stylios Chrysostomos D. , Papadakis Vagelis G.
Published: May 2022

Open innovation has been found to have many benefits and tangible results for those who partake in it. This study aims to showcase the importance of open innovation, and through a theoretical example present how an organization (university, research center, company, firm, etc.) can take action to implement open innovation guidelines. In this paper, firstly, a demonstration showing how open innovation can work with multiple partners is shown. Secondly, a model is presented that shows the steps an organization must follow to successfully implement open innovation. This model covers the introduction of an organization to open innovation from the initial interest to the implementation of the final product. Several success stories are also presented to demonstrate how these steps have been used by major organizations during several collaborations as well as the results produced from implementing open innovation.
Environmental, Social, Governance & Financial Performance Disclosure for Large Firms: Is This Different for SME Firms?
Authors: Gholami Amir , Murray Peter A. , Sands John
Published: May 2022

This study examines the association between a firm’s environmental, social and governance (ESG) performance and financial performance by examining the extent to which stakeholder and legitimacy theory help explain the effects on explanatory variables used in the study. Moreover, the study makes a novel contribution to existing ESG and performance-based studies by exploring the explanatory effects of ESG and firm performance over ten years. In addition, the study discusses the ESG-performance link of SMEs, thus advancing existing knowledge related to ESG in respect of SME performance. The study uses an extensive Australian sample from Bloomberg’s database from 2007 to 2017, while panel regression analysis is applied to investigate the relationship between a firm’s ESG performance and profitability. The robustness of the results is evaluated after incorporating several robustness checks to address methodological, endogeneity and causality issues related to a firm’s ESG performance disclosure. The empirical findings of this study suggest that improving a firm’s ESG performance is beneficial to all stakeholders of large firms in the long run but not for SME companies. The theoretical model suggests that listed SMEs do not disclose their ESG activities for various reasons, such as a lack of necessary resources. Specifically, the study extends scholarly understanding of existing theory and discusses the significance of the findings for future research.
Responsible Leadership and Sustainable Development in East Asia Economic Group: Application of Social Exchange Theory
Authors: Xuecheng Wei , Ahmad Noor Hazlina , Iqbal Qaisar , Saina Bai
Published: May 2022

This study aimed to investigate the integrated relationship of responsible leadership, knowledge sharing, and sustainable performance, drawing from social exchange theory. Data from 264 employees of manufacturing firms in China were collected using online survey forms, exhibiting a response rate of 52.80 percent. Subsequently, the partial least square-structural equation modelling (PLS-SEM) was applied to examine responsible leadership’s direct and indirect effect on sustainable performance. Current empirical evidence revealed that responsible leaders influence sustainable performance significantly among these firms. Moreover, knowledge sharing has partially mediated the link between responsible leadership-sustainable performance. Overall, the present study contributed to the responsible leadership theory and enriched the literature on sustainable development, where it was found that responsible leaders play a critical role in the latter. Policymakers and practitioners in organisations should take the initiative in fostering specific leadership training and knowledge sharing activities. Accordingly, several recommendations were suggested to policymakers, in which strong leadership is considered the primary role behind several organisational aspects. These aspects include success, knowledge, and information, encouraging sustainable development goals.
The Application of Sem–Neural Network Method to Determine the Factors Affecting the Intention to Use Online Banking Services in Vietnam
Authors: Pham An Ha Thi , Pham Dong Xuan , Thalassinos Eleftherios I. , Le Anh Hoang
Published: May 2022

Developing banking services based on technology is an inevitable and objective trend in the era of international economic integration. This study aims to determine the factors impacting the adoption and use of online banking services in Vietnam. The proposed research model is based on the adjustment of Unified Theory of Acceptance and Use of Technology (UTAUT2). We employed the structural equation modeling (SEM) and artificial neural network model (ANN) to comprehensively evaluate the linear and non-linear effects of factors on the adoption and use of online banking services in Vietnam. With survey data of 433 customers from three key economic areas in Vietnam, the result shows that the factors of expected efficiency, cost, expected effort, brand image, perceived risk, and social influence impact behavioral intention to use online banking services. At the same time, the behavioral intention to use online banking services also increases the decision to choose online banking services. Based on the results, we propose some implications for Vietnamese commercial banks to increase the acceptance of online banking.
Local Wisdom of West Timorese Farmers in Land Management
Authors: Ngongo Yohanis , Basuki Tony , deRosari Bernard , Hosang Evert Y. , Nulik Jacob , daSilva Helena , Hau Debora Kana , Sitorus Alfonso , Kotta Noldy R. E. , Njurumana Gerson N. , Pujiono Eko , Ishaq Lily , Simamora Agnes V. , Mau Yosep Seran
Published: May 2022

This paper’s working hypothesis is that the indigenous farming practices of Timorese farmers are those most suitable and adaptable with regard to these farmers’ circumstances. Intensive farming and the acceleration of land conversion in Java lead to a reduction in favorable cropland and the degradation of soil biology. To meet the demand for food production, unfavorable areas outside Java, including marginal semi-arid areas on Timor Island, East Nusa Tenggara province, have become an important option. Unfortunately, the national crop production policy has paid less attention to the specific biophysical characteristics of the region and how local people have adapted to the diverse marginal environment. We review the literature in the areas of soil nutrition retention and soil biology, vegetation/crop diversity, and farming practices/management, including local wisdom on soil management. This paper highlights that the values of the chemical parameters of the soils in question are varied, but generally range from low to high. The existence of beneficial micro-organisms is important both for improving soil fertility and due to their association with local vegetation/crops. Traditional farming practices, such as the local agroforestry of Mamar, have effectively preserved the existence of micro-organisms that promote conservation practices, crop/vegetation diversity, and sustainable agriculture. We recommend that the expansion of croplands and crop production into marginal semi-arid areas needs to be considered and adapted while taking into consideration sustainability and environmentally sound traditional practices.
Should I Stay or Should I Go? Explaining the Turnover Intentions with Corporate Social Responsibility (CSR), Organizational Identification and Organizational Commitment
Authors: Shaikh Erum , Brahmi Mohsen , Thang Pham Chien , Watto Waqas Ahmad , Trang Ta Thi Nguyet , Loan Nguyen Thi
Published: May 2022

The aim of this paper was to investigate the relationship between corporate social responsibility (CSR), organizational commitment, and organizational identification with turnover intentions. This paper also explains the mediating relationship between organizational commitment and organizational identification with the corporate social responsibility and turnover intentions. The data were gathered from banking professionals working in different banks in Pakistan. The participants were recruited through convenient sampling; in total, three hundred participants were involved in this study. The resulting data were analyzed, and the conclusions were drawn through regression and correlation analysis using the SPSS Software. The findings of this study show that corporate social responsibility plays a significant role in determining the organizational commitment and organizational identification of internal stakeholders and employees in financial institutions. This study will be help organizations determine their social responsibility and all the benefits that they can receive through the implementation of CSR practices.
Risk Levels Classification of Near-Crashes in Naturalistic Driving Data
Authors: Naji Hasan A. H. , Xue Qingji , Lyu Nengchao , Duan Xindong , Li Tianfeng
Published: May 2022

Identifying dangerous events from driving behavior data has become a vital challenge in intelligent transportation systems. In this study, we compared machine and deep learning-based methods for classifying the risk levels of near-crashes. A dataset was built for the study by considering variables related to naturalistic driving, temporal data, participants, and road geometry, among others. Hierarchical clustering was applied to categorize the near-crashes into several risk levels based on high-risk driving variables. The adaptive lasso variable model was adopted to reduce factors and select significant driving risk factors. In addition, several machine and deep learning models were used to compare near-crash classification performance by training the models and examining the model with testing data. The results showed that the deep learning models outperformed the machine learning and statistical models in terms of classification performance. The LSTM model achieved the highest performance in terms of all evaluation metrics compared with the state-of-the-art models (accuracy = 96%, recall = 0.93, precision = 0.88, and F1-measure = 0.91). The LSTM model can improve the classification accuracy and prediction of most near-crash events and reduce false near-crash classification. The finding of this study can benefit transportation safety in predicting and classifying driving risk. It can provide useful suggestions for reducing the incidence of critical events and forward road crashes.