bluuebunny/crossref_metadata_2025 huggingface dataset:
Factors Underlying Spatiotemporal Variations in Atmospheric PM2.5 Concentrations in Zhejiang Province, China
Authors: Li Xuan , Wu Chaofan , Meadows Michael E. , Zhang Zhaoyang , Lin Xingwen , Zhang Zhenzhen , Chi Yonggang , Feng Meili , Li Enguang , Hu Yuhong
Published: August 2021

Fine particulate matter in the lower atmosphere (PM2.5) continues to be a major public health problem globally. Identifying the key contributors to PM2.5 pollution is important in monitoring and managing atmospheric quality, for example, in controlling haze. Previous research has been aimed at quantifying the relationship between PM2.5 values and their underlying factors, but the spatial and temporal dynamics of these factors are not well understood. Based on random forest and Shapley additive explanation (SHAP) algorithms, this study analyses the spatiotemporal variations in selected key factors influencing PM2.5 in Zhejiang Province, China, for the period 2000–2019. The results indicate that, while factors influencing PM2.5 varied significantly during the period studied, SHAP values suggest that there is consistency in their relative importance as follows: meteorological factors (e.g., atmospheric pressure) > socioeconomic factors (e.g., gross domestic product, GDP) > topography and land cover factors (e.g., elevation). The contribution of GDP and transportation factors initially increased but has declined in the recent past, indicating that economic and infrastructural development does not necessarily result in increased PM2.5 concentrations. Vegetation productivity, as indicated by changes in NDVI, is demonstrated to have become more important in improving air quality, and the area of the province over which it constrains PM2.5 concentrations has increased between 2000 and 2019. Mapping of SHAP values suggests that, although the relative importance of industrial emissions has declined during the period studied, the actual area positively impacted by such emissions has actually increased. Despite developments in government policy, greater efforts to conserve energy and reduce emissions are still needed. The study further demonstrates that the combination of random forest and SHAP methods provides a valuable means to identify regional differences in key factors affecting atmospheric PM2.5 values and offers a reliable reference for pollution control strategies.
Aircraft Detection above Clouds by Sentinel-2 MSI Parallax
Authors: Heiselberg Peder , Heiselberg Henning
Published: August 2021

Detection of aircrafts in satellite images is a challenging problem when the background is strongly reflective clouds with varying transparency. We develop a fast and effective detection algorithm that can find almost all aircrafts above and between clouds in Sentinel-2 multispectral images. It exploits the time delay of a few seconds between the recorded multispectral images such that a moving aircraft is observed at different positions due to parallax effects. The aircraft speed, heading and altitude are also calculated accurately. Analysing images over the English Channel during fall 2020, we obtain a detection accuracy of 80%, where the most of the remaining were covered by clouds. We also analyse images in the 1.38 μm water absorption band, where only 61% of the aircrafts are detected.
Characteristic Analysis of Sea Surface Currents around Taiwan Island from CODAR Observations
Authors: Tseng Yu-Hao , Lu Ching-Yuan , Zheng Quanan , Ho Chung-Ru
Published: August 2021

Sea surface currents observed by high-frequency (HF) radars have been widely used in ocean circulation research. In this study, hourly sea surface currents observed by the Taiwan Coastal Ocean Dynamics Applications Radar (CODAR) system from 2015 to 2019 were analyzed by the empirical orthogonal function (EOF) analysis to reveal the characteristics of the sea surface currents around Taiwan Island. The study area is divided into two regions, the Kuroshio region east of Taiwan Island and the Taiwan Strait west of Taiwan Island. In the Kuroshio region, the first EOF mode shows that the Kuroshio is characterized by higher current speeds with greater variability in summer. The second and third EOF modes present a dipole eddy pair and single eddy impingement on the Kuroshio during different periods. The seasonal variation of the dipole eddy pair indicates that the cyclonic/anticyclonic eddy on the north/south side appears more frequently in summer. Single eddy impingement occurs at multiple periods, including daily, intraseasonal, interseasonal, and annual periods. For the Taiwan Strait, the first EOF mode displays the tide signals. The tides enter the Taiwan Strait from the north and south, forming strong sea surface currents around the northern tip of Taiwan Island and the Penghu Archipelago. The second EOF mode exhibits the seasonal changes of the sea surface currents driven by the monsoon winds. The sea surface currents in the northern Taiwan Strait are relatively strong, possibly due to the narrow and shallow terrain there. The high spatiotemporal resolution of sea surface currents derived from CODAR observations provide more detailed characteristics of sea surface circulation around Taiwan Island.
Pressure Membrane FBG Sensor Realized by 3D Technology
Authors: Fajkus Marcel , Nedoma Jan , Martinek Radek , Fridrich Michael , Bednar Emil , Zabka Stanislav , Zmij Petr
Published: August 2021

The publication describes the design, production, and practical verification of an alternative pressure sensor suitable for measuring the pressure of gas, based on a combination of fiber-optic technology and 3D printing methods. The created sensor uses FBG (Fiber Bragg Grating) suitably implemented on a movable membrane. The sensor is equipped with a reference FBG to compensate for the effect of ambient temperature on the pressure measurement. The sensor is characterized by its immunity to EM interference, electrical passivity at the measuring point, small size, and resistance to moisture and corrosion. The FBG pressure sensor has a pressure sensitivity of 9.086 pm/mbar in the range from 0 to 9 mbar with a correlation coefficient of 0.9982. The pressure measurement in the specified range shows an average measurement error of 0.049 mbar and a reproducibility parameter of 0.0269 ± 0.0135 mbar.
Energy and Performance Analysis of Lossless Compression Algorithms for Wireless EMG Sensors
Authors: Biagetti Giorgio , Crippa Paolo , Falaschetti Laura , Mansour Ali , Turchetti Claudio
Published: August 2021

Electromyography (EMG) sensors produce a stream of data at rates that can easily saturate a low-energy wireless link such as Bluetooth Low Energy (BLE), especially if more than a few EMG channels are being transmitted simultaneously. Compressing data can thus be seen as a nice feature that could allow both longer battery life and more simultaneous channels at the same time. A lot of research has been done in lossy compression algorithms for EMG data, but being lossy, artifacts are inevitably introduced in the signal. Some artifacts can usually be tolerable for current applications. Nevertheless, for some research purposes and to enable future research on the collected data, that might need to exploit various and currently unforseen features that had been discarded by lossy algorithms, lossless compression of data may be very important, as it guarantees no extra artifacts are introduced on the digitized signal. The present paper aims at demonstrating the effectiveness of such approaches, investigating the performance of several algorithms and their implementation on a real EMG BLE wireless sensor node. It is demonstrated that the required bandwidth can be more than halved, even reduced to 1/4 on an average case, and if the complexity of the compressor is kept low, it also ensures significant power savings.
Saliency-Based Gaze Visualization for Eye Movement Analysis
Authors: Yoo Sangbong , Jeong Seongmin , Kim Seokyeon , Jang Yun
Published: August 2021

Gaze movement and visual stimuli have been utilized to analyze human visual attention intuitively. Gaze behavior studies mainly show statistical analyses of eye movements and human visual attention. During these analyses, eye movement data and the saliency map are presented to the analysts as separate views or merged views. However, the analysts become frustrated when they need to memorize all of the separate views or when the eye movements obscure the saliency map in the merged views. Therefore, it is not easy to analyze how visual stimuli affect gaze movements since existing techniques focus excessively on the eye movement data. In this paper, we propose a novel visualization technique for analyzing gaze behavior using saliency features as visual clues to express the visual attention of an observer. The visual clues that represent visual attention are analyzed to reveal which saliency features are prominent for the visual stimulus analysis. We visualize the gaze data with the saliency features to interpret the visual attention. We analyze the gaze behavior with the proposed visualization to evaluate that our approach to embedding saliency features within the visualization supports us to understand the visual attention of an observer.
fastSW: Efficient Piecewise Linear Approximation of Quaternion-Based Orientation Sensor Signals for Motion Capturing with Wearable IMUs
Authors: Grützmacher Florian , Kempfle Jochen , Van Laerhoven Kristof , Haubelt Christian
Published: August 2021

In the past decade, inertial measurement sensors have found their way into many wearable devices where they are used in a broad range of applications, including fitness tracking, step counting, navigation, activity recognition, or motion capturing. One of their key features that is widely used in motion capturing applications is their capability of estimating the orientation of the device and, thus, the orientation of the limb it is attached to. However, tracking a human’s motion at reasonable sampling rates comes with the drawback that a substantial amount of data needs to be transmitted between devices or to an end point where all device data is fused into the overall body pose. The communication typically happens wirelessly, which severely drains battery capacity and limits the use time. In this paper, we introduce fastSW, a novel piecewise linear approximation technique that efficiently reduces the amount of data required to be transmitted between devices. It takes advantage of the fact that, during motion, not all limbs are being moved at the same time or at the same speed, and only those devices need to transmit data that actually are being moved or that exceed a certain approximation error threshold. Our technique is efficient in computation time and memory utilization on embedded platforms, with a maximum of 210 instructions on an ARM Cortex-M4 microcontroller. Furthermore, in contrast to similar techniques, our algorithm does not affect the device orientation estimates to deviate from a unit quaternion. In our experiments on a publicly available dataset, our technique is able to compress the data to 10% of its original size, while achieving an average angular deviation of approximately 2° and a maximum angular deviation below 9°.
Classification of Approximal Caries in Bitewing Radiographs Using Convolutional Neural Networks
Authors: Moran Maira , Faria Marcelo , Giraldi Gilson , Bastos Luciana , Oliveira Larissa , Conci Aura
Published: August 2021

Dental caries is an extremely common problem in dentistry that affects a significant part of the population. Approximal caries are especially difficult to identify because their position makes clinical analysis difficult. Radiographic evaluation—more specifically, bitewing images—are mostly used in such cases. However, incorrect interpretations may interfere with the diagnostic process. To aid dentists in caries evaluation, computational methods and tools can be used. In this work, we propose a new method that combines image processing techniques and convolutional neural networks to identify approximal dental caries in bitewing radiographic images and classify them according to lesion severity. For this study, we acquired 112 bitewing radiographs. From these exams, we extracted individual tooth images from each exam, applied a data augmentation process, and used the resulting images to train CNN classification models. The tooth images were previously labeled by experts to denote the defined classes. We evaluated classification models based on the Inception and ResNet architectures using three different learning rates: 0.1, 0.01, and 0.001. The training process included 2000 iterations, and the best results were achieved by the Inception model with a 0.001 learning rate, whose accuracy on the test set was 73.3%. The results can be considered promising and suggest that the proposed method could be used to assist dentists in the evaluation of bitewing images, and the definition of lesion severity and appropriate treatments.
Analysis of Occlusion Effects for Map-Based Self-Localization in Urban Areas
Authors: Endo Yuki , Javanmardi Ehsan , Kamijo Shunsuke
Published: August 2021

A high-definition (HD) map provides structural information for map-based self-localization, enabling stable estimation in real environments. In urban areas, there are many obstacles, such as buses, that occlude sensor observations, resulting in self-localization errors. However, most of the existing HD map-based self-localization evaluations do not consider sudden significant errors due to obstacles. Instead, they evaluate this in terms of average error over estimated trajectories in an environment with few occlusions. This study evaluated the effects of self-localization estimation on occlusion with synthetically generated obstacles in a real environment. Various patterns of synthetic occlusion enabled the analyses of the effects of self-localization error from various angles. Our experiments showed various characteristics that locations susceptible to obstacles have. For example, we found that occlusion in intersections tends to increase self-localization errors. In addition, we analyzed the geometrical structures of a surrounding environment in high-level error cases and low-level error cases with occlusions. As a result, we suggested the concept that the real environment should have to achieve robust self-localization under occlusion conditions.
A 3.0 Gsymbol/s/lane MIPI C-PHY Receiver with Adaptive Level-Dependent Equalizer for Mobile CMOS Image Sensor
Authors: Choi Seokwon , Song Changmin , Jang Young-Chan
Published: August 2021

A 3.0 Gsymbol/s/lane receiver is proposed herein to acquire near-grounded high-speed signals for the mobile industry processor interface (MIPI) C-PHY version 1.1 specification used for CMOS image sensor interfaces. Adaptive level-dependent equalization is also proposed to improve the signal integrity of the high-speed receivers receiving three-level signals. The proposed adaptive level-dependent equalizer (ALDE) is optimized by adjusting the duty cycle ratio of the clock recovered from the received data to 50%. A pre-determined data pattern transmitted from a MIPI C-PHY transmitter is established to perform the adaptive level-dependent equalization. The proposed MIPI C-PHY receiver with three data lanes is implemented using a 65 nm CMOS process with a 1.2 V supply voltage. The power consumption and area of each lane are 4.9 mW/Gsymbol/s/lane and 0.097 mm2, respectively. The proposed ALDE improves the peak-to-peak time jitter of 12 ps and 34 ps, respectively, for the received data and the recovered clock at a symbol rate of 3 Gsymbol/s/lane. Additionally, the duty cycle ratio of the recovered clock is improved from 42.8% to 48.3%.
Handover Parameters Optimisation Techniques in 5G Networks
Authors: Saad Wasan Kadhim , Shayea Ibraheem , Hamza Bashar J. , Mohamad Hafizal , Daradkeh Yousef Ibrahim , Jabbar Waheb A.
Published: August 2021

The massive growth of mobile users will spread to significant numbers of small cells for the Fifth Generation (5G) mobile network, which will overlap the fourth generation (4G) network. A tremendous increase in handover (HO) scenarios and HO rates will occur. Ensuring stable and reliable connection through the mobility of user equipment (UE) will become a major problem in future mobile networks. This problem will be magnified with the use of suboptimal handover control parameter (HCP) settings, which can be configured manually or automatically. Therefore, the aim of this study is to investigate the impact of different HCP settings on the performance of 5G network. Several system scenarios are proposed and investigated based on different HCP settings and mobile speed scenarios. The different mobile speeds are expected to demonstrate the influence of many proposed system scenarios on 5G network execution. We conducted simulations utilizing MATLAB software and its related tools. Evaluation comparisons were performed in terms of handover probability (HOP), ping-pong handover probability (PPHP) and outage probability (OP). The 5G network framework has been employed to evaluate the proposed system scenarios used. The simulation results reveal that there is a trade-off in the results obtained from various systems. The use of lower HCP settings provides noticeable enhancements compared to higher HCP settings in terms of OP. Simultaneously, the use of lower HCP settings provides noticeable drawbacks compared to higher HCP settings in terms of high PPHP for all scenarios of mobile speed. The simulation results show that medium HCP settings may be the acceptable solution if one of these systems is applied. This study emphasises the application of automatic self-optimisation (ASO) functions as the best solution that considers user experience.
The Use of Public Data from Low-Cost Sensors for the Geospatial Analysis of Air Pollution from Solid Fuel Heating during the COVID-19 Pandemic Spring Period in Krakow, Poland
Authors: Danek Tomasz , Zaręba Mateusz
Published: August 2021

In this paper, we present a detailed analysis of the public data provided by low-cost sensors (LCS), which were used for spatial and temporal studies of air quality in Krakow. A PM (particulate matter) dataset was obtained in spring in 2021, during which a fairly strict lockdown was in force as a result of COVID-19. Therefore, we were able to separate the effect of solid fuel heating from other sources of background pollution, mainly caused by urban transport. Moreover, we analyzed the historical data of PM2.5 from 2010 to 2019 to show the effect of grassroots efforts and pro-clean-air legislation changes in Krakow. We designed a unique workflow with a time-spatial analysis of PM1, PM2.5, and PM10, and temperature data from Airly(c) sensors located in Krakow and its surroundings. Using geostatistical methods, we showed that Krakow’s neighboring cities are the main sources of air pollution from solid fuel heating in the city. Additionally, we showed that the changes in the law in Krakow significantly reduced the PM concentration as compared to neighboring municipalities without a fossil fuel prohibition law. Moreover, our research demonstrates that informative campaigns and education are important initiating factors in order to bring about cleaner air in the future.
Ultra-Wideband Positioning Sensor with Application to an Autonomous Ultraviolet-C Disinfection Vehicle
Authors: Huang Shih-Ping , Neo Jin-Feng , Chen Yu-Yao , Chen Chien-Bang , Wu Ting-Wei , Peng Zheng-An , Tsai Wei-Ting , Liou Chong-Yi , Sheng Wang-Huei , Mao Shau-Gang
Published: August 2021

Due to the COVID-19 virus being highly transmittable, frequently cleaning and disinfecting facilities is common guidance in public places. However, the more often the environment is cleaned, the higher the risk of cleaning staff getting infected. Therefore, strong demand for sanitizing areas in automatic modes is undoubtedly expected. In this paper, an autonomous disinfection vehicle with an Ultraviolet-C (UVC) lamp is designed and implemented using an ultra-wideband (UWB) positioning sensor. The UVC dose for 90% inactivation of the reproductive ability of COVID-19 is 41.7 J/m2, which a 40 W UVC lamp can achieve within a 1.6 m distance for an exposure time of 30 s. With this UVC lamp, the disinfection vehicle can effectively sterilize in various scenarios. In addition, the high-accuracy UWB positioning system, with the time difference of arrival (TDOA) algorithm, is also studied for autonomous vehicle navigation in indoor environments. The number of UWB tags that use a synchronization protocol between UWB anchors can be unlimited. Moreover, this proposed Gradient Descent (GD), which uses Taylor method, is a high-efficient algorithm for finding the optimal position for real-time computation due to its low error and short calculating time. The generalized traversal path planning procedure, with the edge searching method, is presented to improve the efficiency of autonomous navigation. The average error of the practical navigation demonstrated in the meeting room is 0.10 m. The scalability of the designed system to different application scenarios is also discussed and experimentally demonstrated. Hence, the usefulness of the proposed UWB sensor applied to UVC disinfection vehicles to prevent COVID-19 infection is verified by employing it to sterilize indoor environments without human operation.
Sequence Set Design for a New LFM-PC Hybrid Modulated Radar Signal
Authors: Li Shiyi , Wang Yuying , Zhang Jindong , Zhu Daiyin
Published: August 2021

In this paper we study the code design problem of a new form of linear frequency modulation phase-coded (LFM-PC) hybrid signal with wide Doppler tolerance based on a range-Doppler discrete ambiguity function (DAF) to get better detection performance and anti-jamming capability. The DAF of the LFM-PC inter pulse signal is derived within the Doppler tolerance. Two optimization models are established. One is single pulse sequence design (SSD) for Doppler tolerance extension based on minimum integral normalized sidelobe level (INSL); the other is multi pulse sequence set design (MSSD) for signal orthogonality based on the minimizing sum of the normalized DAF sidelobe (NDAFSL) and discrete cross ambiguity function (DCAF). Two low-complexity signal optimization methods based on alternating direction method of multiplier (ADMM) are proposed, respectively. The simulation results show that the optimized signals have either wide Doppler tolerance or good orthogonal performance, and the optimization methods (i.e., SSD-ADMM and MSSD-ADMM) have the characteristics of fast convergence speed and low operation amount.
Simultaneous Target Classification and Moving Direction Estimation in Millimeter-Wave Radar System
Authors: Kim Jin-Cheol , Jeong Hwi-Gu , Lee Seongwook
Published: August 2021

In this study, we propose a method to identify the type of target and simultaneously determine its moving direction in a millimeter-wave radar system. First, using a frequency-modulated continuous wave (FMCW) radar sensor with the center frequency of 62 GHz, radar sensor data for a pedestrian, a cyclist, and a car are obtained in the test field. Then, a You Only Look Once (YOLO)-based network is trained with the sensor data to perform simultaneous target classification and moving direction estimation. To generate input data suitable for the deep learning-based classifier, a method of converting the radar detection result into an image form is also proposed. With the proposed method, we can identify the type of each target and its direction of movement with an accuracy of over 95%. Moreover, the pre-trained classifier shows an identification accuracy of 85% even for newly acquired data that have not been used for training.
ESCOVE: Energy-SLA-Aware Edge–Cloud Computation Offloading in Vehicular Networks
Authors: Ismail Leila , Materwala Huned
Published: August 2021

The vehicular network is an emerging technology in the Intelligent Smart Transportation era. The network provides mechanisms for running different applications, such as accident prevention, publishing and consuming services, and traffic flow management. In such scenarios, edge and cloud computing come into the picture to offload computation from vehicles that have limited processing capabilities. Optimizing the energy consumption of the edge and cloud servers becomes crucial. However, existing research efforts focus on either vehicle or edge energy optimization, and do not account for vehicular applications’ quality of services. In this paper, we address this void by proposing a novel offloading algorithm, ESCOVE, which optimizes the energy of the edge–cloud computing platform. The proposed algorithm respects the Service level agreement (SLA) in terms of latency, processing and total execution times. The experimental results show that ESCOVE is a promising approach in energy savings while preserving SLAs compared to the state-of-the-art approach.
Values and Virtues as Correlates of Quality and Stability of Romantic Relationships and Marriage in a Post-Socialist Transitional Society
Authors: Kus Ambrož Maja , Suklan Jana , Jelovac Dejan
Published: August 2021

An individual’s value system plays an important role in their intimate relationship or marriage. Most marital satisfaction research to date has been carried out in high-income liberal Western societies. We conducted an original quantitative empirical survey of virtues and values to examine their effect on relationship quality and stability in a sample of 511 respondents from Slovenia, a post-socialist society in transition. The results showed that respondents rated health, love, and safety at the top of their hierarchy of values. The key finding was that the presence of love was associated with an individual’s subjective perception of relationship quality but had no effect on the self-evaluation of relationship stability. In addition to love, both family safety and comfort were significant correlates of relationship quality while self-respect was negatively correlated with relationship quality. Only excitement was found to have a statistically significant effect on relationship stability.
Young Children’s Learning about Hunger and Satiety through the Lens of the Norms of Those Who Feed Them
Authors: Dupuy Anne , Nicklaus Sophie , Schwartz Camille , Goirand Stéphanie , Tibère Laurence
Published: August 2021

This article focuses on parental perceptions of signs of hunger and satiety in children under 4 years of age and their effects on feeding practices, in a sample of parents of children with typical development. Discourse analysis shows the close relationships between social food norms, nutritional norms, medicalized child care norms, and educational norms in adults’ determination of children’s appetites according to their perceived needs and psychomotor development. The results also indicate how these norms are expressed according to social position, parental experience and context. More broadly, this article addresses top-down education—from adults to children—in food socialization, and points to the varying attention paid to the signals given by the child. It thus highlights some of the processes by which biological, psychological and social factors interact in socializing children to food.
Quantifying Accelerations and Decelerations in Elite Women Soccer Players during Regular In-Season Training as an Index of Training Load
Authors: Douchet Tom , Humbertclaude Allex , Cometti Carole , Paizis Christos , Babault Nicolas
Published: August 2021

Accelerations (ACC) and decelerations (DEC) are important and frequent actions in soccer. We aimed to investigate whether ACC and DEC were good indicators of the variation of training loads in elite women soccer players. Changes in the training load were monitored during two different selected weeks (considered a “low week” and a “heavy week”) during the in-season. Twelve elite soccer women playing in the French first division wore a 10-Hz Global Positioning System unit recording total distance, distance within speed ranges, sprint number, ACC, DEC, and a heart rate monitor during six soccer training sessions and rated their perceived exertion (RPE). They answered the Hooper questionnaire (sleep, stress, fatigue, DOMS) to get an insight of their subjective fitness level at the start (Hooper S) and at the end of each week (Hooper E). A countermovement jump (CMJ) was also performed once a week. During the heavy week, the training load was significantly greater than the low week when considering number of ACC >2 m·s−2 (28.2 ± 11.9 vs. 56.1 ± 10.1, p < 0.001) and number of DEC < −2 m·s−2 (31.5 ± 13.4 vs. 60.9 ± 14.4, p < 0.001). The mean heart rate percentage (HR%) (p < 0.05), RPE (p < 0.001), and Hooper E (p < 0.001) were significantly greater during the heavy week. ACC and DEC showed significant correlations with most outcomes: HR%, total distance, distance per min, sprint number, Hooper index of Hooper E, DOMS E, Fatigue E, RPE, and session RPE. We concluded that, for elite women soccer players, quantifying ACC and DEC alongside other indicators seemed to be essential for a more complete training load monitoring. Indeed, it could lead to a better understanding of the reasons why athletes get fatigued and give insight into neuromuscular, rather than only energetic, fatigue.
Development Trends in the Crop Production in Slovakia after Accession to the European Union—Case Study, Slovakia
Authors: Némethová Jana , Rybanský Ľubomír
Published: August 2021

The development of agriculture in Slovakia in the last three decades has been influenced by two events: the transformation of agriculture after 1989 and Slovakia’s accession to the European Union in 2004. In this paper, we analyze the effects of Slovakia’s accession to the European Union on the development and structure of crop production. The aim of the paper was to identify connections, parallels and differences between the developments of the sown areas of the most important crops at the level of Slovakia and its regions in the period 2004–2020. Cluster analysis based on the similarity of the development of the sown areas divided the crops into four clusters (cereals; sugar-beet; oilseeds, multiannual fodder crops, maize; legumes, vegetables, potatoes). Multivariate analyses of the time series of sown areas also revealed similarities and differences between the regions of Slovakia. The results of the analysis point to regional differentiation and the identify two clusters. The first cluster comprises the Nitra and Trnava Regions, while the second cluster consists of the remaining six regions. The study has shown that changes in the agrarian sector after 2004, conditioned by Slovakia’s accession to the European Union, have been reflected in changes in the area and structure of cultivated crops, and in the differentiated development of sown areas.
Game Theory, Tourism and Land Ethics
Authors: Kopf Dennis A. , Hsu Maxwell K.
Published: August 2021

This paper combines game theory with Land Ethics to demonstrate a path forward for sustainable development. Our findings indicate that two likely equilibria can be reached. One equilibrium focuses on high short-term profits, but with ecological damage leading to less cumulative profits. The second equilibrium requires ecological maintenance costs (thus less short-term profits) yet yields greater cumulative profits. The comparison of the two equilibria and using the historical perspective of the Wisconsin Dells demonstrates how communities that embrace a Land Ethic can reach the equilibrium that produces greater long-term benefits.
Creation of Annual Order Forecast for the Production of Beverage Cans—The Case Study
Authors: Kacmary Peter , Rosova Andrea , Sofranko Marian , Bindzar Peter , Saderova Janka , Kovac Jan
Published: August 2021

This article is focused on the creation of a system for forecasting of future orders for a specific beverage cans manufacturer. The problem comes from the irregular ordering of cans from different customers; not only national companies, but also from companies abroad. This causes fluctuations in production and consequently an irregular transport regime. That is why the beverage can producer demanded a forecasting system that would help to create an annual production plan. The aim is to analyze the ordering process for the last two years and on that basis to create a forecast system of the possible ordering process for the following year. This is necessary for the introduction of regularity of production, because the frequent transitions of the line to another assortment range or other surface printing requires long downtimes due to the technological setting, thus creating large losses due to inactivity of the production line. As drinking habits of final customers reflect the sale of cans, it was expected that sale data would have a seasonable character; this was proved after a brief analysis of the former data. After that, the appropriate forecasting methods were chosen. The methodology was created to combine multiple forecast results into one to increase the forecast objectivity. Forecasting is performed at three different levels: forecasting of assortment, forecasting of region sale and total forecasting of all orders. In spite of the change in market behavior in 2020, due to the pandemic situation in the first wave of the COVID-19 crisis, the sale of beverage cans is expected to stabilize and return to pre-crisis level as early as 2021. Then the forecasting system will fully meet the company’s requirements.
The Collaborative Process in Environmental Projects, a Place-Based Coevolution Perspective
Authors: Daudin Kevin , Weber Christiane , Colin François , Cernesson Flavie , Maurel Pierre , Derolez Valérie
Published: August 2021

Environmental research and management organizations are mutually dependent when it comes to produce and use knowledge in favor of responsible action in an increasingly uncertain world. Still, science and practice interfacing remains a challenge when it comes to implementing and sustaining a collaborative process. In this paper, we develop a descriptive framework to study the coevolution of scientific and planning activities embedded in a territorial system. Scientists and managers dynamically interact through institutional arrangements, operationalization of knowledge and information and communication tools. We propose an approach to systematically document transdisciplinary pathways and characterize the bounding process between organizations on a typical case-study, the coastal Thau territoire (Mediterranean Sea, France). By tracing, illustrating and analyzing coupled trajectories of environmental sciences and planning for the last decades, the Systemic Timeline Multistep methodology tackles cross-fertilization mechanisms. The relational analysis draws on the elaboration of a synchronic timeline to question co-evolution and grasp causal mechanisms of research projects interactions with management pathways. Its application on the Thau territoire shows that scientific activities and public actions shaped each other in a continuous process of interaction. It also gives insights into the contributive roles of long-term place-based research and intermediate organizations for the emergence of new sociotechnical arrangements.
Integrated Design Process for High-Performance Buildings; a Case Study from Dubai
Authors: Shibeika Amna , Khoukhi Maatouk , Al Khatib Omar , Alzahmi Nouf , Tahnoon Shamma , Al Dhahri Maryam , Alshamsi Nouf
Published: August 2021

Due to the scarcity of water and the harsh desert climate of the United Arab Emirates (UAE), water and energy are two of the main challenges for the design of sustainable buildings in the UAE. Relevant literature calls for the consideration of building systems and materials at the design stage to achieve high-performing buildings and to save on the operational costs of the building. The aim of this research was to design a high-performance building that meets the environmental sustainability requirements for water and energy, in the city of Dubai to reflect the technological advancements of the UAE Mars mission. This has been achieved through following an integrated design process, which was mainly focused on the evaluation and specification of the building engineering systems based on performance, besides the goal of achieving visually appealing building with advanced structural design. The performance verification of the final building design, which considered engineering systems design from conception and through the design and detailed design stages, revealed a 15% reduction in water consumption and a 60% reduction in energy consumption. This provides a valuable contribution to architectural engineering practice, by demonstrating a case study for enhancing energy and water efficiency via building design, which consequently contributes to the environmental sustainability of the built environment.
Does Staying at Home during the COVID-19 Pandemic Help Reduce CO2 Emissions?
Authors: Aruga Kentaka , Islam Md. Monirul , Jannat Arifa
Published: August 2021

Quarantining at home during the COVID-19 pandemic significantly restricted human mobility such as visits to parks, grocery stores, workplaces, retail places, and transit stations. In this research, we analyzed how the changes in human mobility during the first wave of the COVID-19 pandemic, from February to April 2020 (i.e., between 17 February and 30 April 2020), affected the daily CO2 emissions for countries having a high number of coronavirus cases at that time. Our daily time-series analyses indicated that when average hours spent at home increased, the amount of daily CO2 emissions declined significantly. The findings suggest that for all three countries (the US, India, and France), a 1% increase in the average duration spent in residential areas reduced daily CO2 emissions by 0.17 Mt, 0.10 Mt, and 0.01 Mt, respectively, during the first wave period. Thus, confining people into their homes contributes to cutting down CO2 emissions remarkably. However, the study also reveals those activities such as visiting parks and going grocery shopping increase CO2 emissions, suggesting that unnecessary human mobility is undesirable for the environment.
Does the Presence of Shade Trees and Distance to the Forest Affect Detection Rates of Terrestrial Vertebrates in Coffee Home Gardens?
Authors: Campera Marco , Hedger Katherine , Birot Hélène , Manson Sophie , Balestri Michela , Budiadi Budiadi , Imron Muhammad Ali , Nijman Vincent , Nekaris K. A. I.
Published: August 2021

Complex agroforestry systems can host similar biodiversity levels to adjacent continuous forests and can offer important ecosystem services for wildlife. Species inhabiting adjacent forests, as well as species that prefer agroforestry systems, can benefit from this habitat matrix. It is necessary, however, to understand the species-specific adaptability to such a complex matrix. Indonesia is a biodiversity hotspot and hosts many endemic species that are threatened with extinction. Its human population relies heavily on agriculture, meaning that finding a balance between crop productivity and biodiversity is key for the long-term sustainability of local communities and wildlife. We aim to determine the influence of the presence of shade trees and distance to the forest on the detection rates of wildlife in coffee home gardens. In West Java, Indonesia, we monitored 23 gardens between April 2018 and March 2021 via camera traps, totalling 3856 days of monitoring in shade-grown and 3338 days in sun-exposed gardens. We also collected data in the nearby montane rainforest, totalling 1183 days of monitoring. We used Generalized Additive Models to estimate the influence of shade cover and distance to the forest on the detection rates of wildlife. The Sunda leopard cat Prionailurus javanensis was found more frequently in shade-grown gardens and used both the forest and agroforest matrix. Wild boars Sus scrofa mostly occurred in gardens adjacent to the forest, while barred buttonquails Turnix suscitator were associated with gardens far (>1 km) from the forest. Several species (civets Viverricula indica and Paradoxus musangus javanicus, Horsfield’s treeshrew Tupaia javanica, Javan ferret badger Melogale orientalis, Javan mongoose Herpestes javanicus) were not influenced by shade cover and distance to the forest, suggesting they are well adapted to the agroforestry system. Still, species of high conservation importance, such as Javan leopard Panthera pardus melas, Sunda porcupine Hystrix javanica, and grizzled langur Presbytis comata, were present in the forest but not in the agroforest, suggesting that the replacement of the forest by the agroforestry matrix is still detrimental. Nevertheless, it is important to maintain the complexity of the agroforestry system and connectivity with the neighbouring continuous forest to favour the long-term sustainability of this environment and the conservation of endemic species.
Beyond the Socio-Economic Impact of Transport Megaprojects
Authors: Montrimas Andrius , Bruneckienė Jurgita , Gaidelys Vaidas
Published: August 2021

For more than two decades, scholars have been escalating asymmetric information issues in megaproject management linking them to enhanced public debt concerns. Most megaprojects turn out to be a burden on economy when constructions are completed. Authorities, meanwhile, continue to promote the advancement of megaprojects with overly optimistic public messages on expected socio-economic benefits. A combination of expertise in the topic, in-depth literature analysis, independent cost-benefit reassessment, and empirical survey of related documentation of three EU transport megaprojects shows political implications to be the essential causes of information asymmetries in megaproject management. Socio-economic over-estimations imply to be useful for obtaining and securing funding commitments at the political level, but then the real project value is often omitted from the assessment. This work takes a wider, strategic approach beyond the usual socio-economic reasoning. The article argues that socio-economic assessment practice is too narrow to grasp the full potential impact of a megaproject. Therefore, a strategic assessment should be performed by public authorities along with an appropriate funding mechanism. This work contributes to science by suggesting a direction to more constructive discussions between scholars and politicians that could lead to more effective future decisions on the overall sustainability of economies.
Remaining Useful Life Prediction-Based Maintenance Decision Model for Stochastic Deterioration Equipment under Data-Driven
Authors: Cao Xiangang , Li Pengfei , Ming Song
Published: August 2021

Currently, the Remaining Useful Life (RUL) prediction accuracy of stochastic deterioration equipment is low. Existing researches did not consider the impact of imperfect maintenance on equipment degradation and maintenance decisions. Therefore, this paper proposed a remaining useful life prediction-based maintenance decision model under data-driven to extend equipment life, promoting sustainable development. The stochastic degradation model was established based on the nonlinear Wiener process. A combination of real-time update and offline estimation estimated the degradation model’s parameters and deduced the equipment’s RUL distribution. Based on the RUL prediction results, we established a maintenance decision model with the lowest long-term cost rate as the goal. Case analysis shows that the model proposed in this paper can improve the accuracy of RUL prediction and realize equipment sustainability.
The Future We Want: A Learning Experience to Promote SDGs in Higher Education from the United Nations and University of Valencia
Authors: Vázquez-Verdera Victoria , Domingo Juan , Dura Esther , Gabaldón-Estevan Daniel , López-Baeza Ernesto , Machause López Sonia , Meco-Tébar Fabiola , Rueda Silvia , Serrano-Lara José Javier , Signes-Soler Isabel , Vázquez de Ágredos Pascual María Luisa , Martínez-García Elena
Published: August 2021

This article shares the strategy for mainstreaming the Sustainable Development Goals (SDGs) at the University of Valencia (UV), which, although limited in its scale, may compel other Higher Education Institutions to think in technological and social progress aligned with the 2030 Agenda. It explicates a process driven by the UV, on the occasion of the 75th anniversary of the United Nations (UN), and in collaboration with the Service for Geospatial, Information, and Telecommunications Technologies from the UN Support Base in Valencia (Spain) to prepare the online event: “The United Nations We Want”. It was the culmination of a collaborative project between students and faculties from different scientific, technological, social, legal, humanistic, and health disciplines that structure the University of Valencia. The intention was that new generations experience the role they can have to shape the future we want, while the university community as a whole can become part of transformative institutional change that draws on both top-down and bottom-up strategies in pursuit of Education for Sustainable Development.
Estimation of Harmonic Emission of Electric Vehicles and Their Impact on Low Voltage Residential Network
Authors: Iqbal Muhammad Naveed , Kütt Lauri , Daniel Kamran , Asad Bilal , Shams Ghahfarokhi Payam
Published: August 2021

The EV penetration in the low voltage residential grids is expected to increase rapidly in the coming years. It is expected that EV consumers will prefer overnight home charging because of its convenience and lack of charging infrastructure. The EV battery chargers are nonlinear loads and likely to increase the current harmonic emission in the distribution network. The imminent increase of EV load requires upgrading or managing the existing power system to support the additional charging load. This paper provides the estimation of the current harmonic emission of the EV charging load at different voltage distortions using the stochastic EV load model. The impact of EV charging on the distribution transformer is also presented.
Corridor-Wise Eco-Friendly Cooperative Ramp Management System for Connected and Automated Vehicles
Authors: Zhao Zhouqiao , Wu Guoyuan , Barth Matthew
Published: August 2021

Safety, mobility, and environmental sustainability are three fundamental issues that our transportation system has been confronting for decades. Intelligent transportation systems (ITS) aim to address these problems by leveraging disruptive technologies, such as connected and automated vehicles (CAVs). The cooperative potential of CAVs enable more efficient maneuvers and operation of a group of vehicles, or even the entire traffic system. In addition, CAVs may couple with other emerging technologies such as electrification to boost overall system performance and to further mitigate the aforementioned issues. In this study, we propose a hierarchical eco-friendly cooperative ramp management system, where macroscopically, a stratified ramp metering algorithm, is deployed to coordinate all of the ramp inflow rates along a corridor according to the real-time traffic condition; microscopically, a model predictive control (MPC)-based algorithm is designed for the detailed speed control of individual CAVs. Using the shared information from CAVs, the proposed ramp management system can smooth traffic flow, improve system mobility, and decrease the energy consumption of the network. Moreover, traffic simulation has been conducted using PTV VISSIM under various congestion levels for vehicles with different powertrain types, i.e., an internal combustion engine and an electric motor. Compared to conventional ramp metering, the proposed ramp management system may improve mobility by 48.6–56.7% and save energy by 24.0–35.1%. Compared to no control scenarios, savings in travel time and energy consumption are in the ranges of 79.4–89.1% and 0.8–2.5%, respectively.