bluuebunny/crossref_metadata_2025 huggingface dataset:
Uniform and Competency-Based 3D Keypoint Detection for Coarse Registration of Point Clouds with Homogeneous Structure
Authors: Ghorbani Fariborz , Ebadi Hamid , Pfeifer Norbert , Sedaghat Amin
Published: August 2022

Recent advances in 3D laser scanner technology have provided a large amount of accurate geo-information as point clouds. The methods of machine vision and photogrammetry are used in various applications such as medicine, environmental studies, and cultural heritage. Aerial laser scanners (ALS), terrestrial laser scanners (TLS), mobile mapping laser scanners (MLS), and photogrammetric cameras via image matching are the most important tools for producing point clouds. In most applications, the process of point cloud registration is considered to be a fundamental issue. Due to the high volume of initial point cloud data, 3D keypoint detection has been introduced as an important step in the registration of point clouds. In this step, the initial volume of point clouds is converted into a set of candidate points with high information content. Many methods for 3D keypoint detection have been proposed in machine vision, and most of them were based on thresholding the saliency of points, but less attention had been paid to the spatial distribution and number of extracted points. This poses a challenge in the registration process when dealing with point clouds with a homogeneous structure. As keypoints are selected in areas of structural complexity, it leads to an unbalanced distribution of keypoints and a lower registration quality. This research presents an automated approach for 3D keypoint detection to control the quality, spatial distribution, and the number of keypoints. The proposed method generates a quality criterion by combining 3D local shape features, 3D local self-similarity, and the histogram of normal orientation and provides a competency index. In addition, the Octree structure is applied to control the spatial distribution of the detected 3D keypoints. The proposed method was evaluated for the keypoint-based coarse registration of aerial laser scanner and terrestrial laser scanner data, having both cluttered and homogeneous regions. The obtained results demonstrate the proper performance of the proposed method in the registration of these types of data, and in comparison to the standard algorithms, the registration error was diminished by up to 56%.
Spectral-Spatial Interaction Network for Multispectral Image and Panchromatic Image Fusion
Authors: Nie Zihao , Chen Lihui , Jeon Seunggil , Yang Xiaomin
Published: August 2022

Recently, with the rapid development of deep learning (DL), an increasing number of DL-based methods are applied in pansharpening. Benefiting from the powerful feature extraction capability of deep learning, DL-based methods have achieved state-of-the-art performance in pansharpening. However, most DL-based methods simply fuse multi-spectral (MS) images and panchromatic (PAN) images by concatenating, which can not make full use of the spectral information and spatial information of MS and PAN images, respectively. To address this issue, we propose a spectral-spatial interaction Network (SSIN) for pansharpening. Different from previous works, we extract the features of PAN and MS, respectively, and then interact them repetitively to incorporate spectral and spatial information progressively. In order to enhance the spectral-spatial information fusion, we further propose spectral-spatial attention (SSA) module to yield a more effective spatial-spectral information transfer in the network. Extensive experiments on QuickBird, WorldView-4, and WorldView-2 images demonstrate that our SSIN significantly outperforms other methods in terms of both objective assessment and visual quality.
Optical Turbulence Characteristics in the Upper Troposphere–Lower Stratosphere over the Lhasa within the Asian Summer Monsoon Anticyclone
Authors: Zhang Kun , Wang Feifei , Weng Ningquan , Wu Xiaoqing , Li Xuebin , Luo Tao
Published: August 2022

The high elevation, complex topography, and unique atmospheric circulations of the Tibetan Plateau (TP) make its optical turbulence characteristics different from those in low-elevation regions. In this study, the characteristics of the atmospheric refractive index structure constant (Cn2) profiles in the Lhasa area at different strength states of the Asian summer monsoon anticyclone (ASMA) are analyzed based on precious in situ sounding data measured over the Lhasa in August 2018. Cn2 in the upper troposphere–lower stratosphere fluctuates significantly within a few days during the ASMA, particularly in the upper troposphere. The effect of the ASMA on Cn2 varies among the upper troposphere, tropopause, and lower stratosphere. The stronger and closer the ASMA is to Lhasa, the more pronounced is the “upper highs and lower lows” pressure field structure, which is beneficial for decreasing the potential temperature lapse rate. The decrease in static stability is an important condition for developing optical turbulence, elevating the tropopause height, and reducing the tropopause temperature. However, if strong high-pressure activity occurs at the lower pressure layer, such as at 500 hPa, an “upper highs and lower highs” pressure field structure forms over the Lhasa, increasing the potential temperature lapse rate and suppressing the convective intensity. Being almost unaffected by low-level atmospheric high-pressure activities, the ASMA, as the main influencing factor, mainly inhibits Cn2 in the tropopause and lower stratosphere. The variations of turbulence intensity in UTLS caused by ASMA activities also have a great influence on astronomical parameters, which will have certain guiding significance for astronomical site testing and observations.
Correction: Yang et al. Detecting Spatiotemporal Features and Rationalities of Urban Expansions within the Guangdong–Hong Kong–Macau Greater Bay Area of China from 1987 to 2017 Using Time-Series Landsat Images and Socioeconomic Data. Remote Sens. 2019, 11, 2215
Authors: Yang Chao , Li Qingquan , Zhao Tianhong , Liu Huizeng , Gao Wenxiu , Shi Tiezhu , Guan Minglei , Wu Guofeng
Published: August 2022

The authors wish to make the following corrections to the paper [...]
Assessing Spatiotemporal Dynamics of Land Use and Cover Change and Carbon Storage in China’s Ecological Conservation Pilot Zone: A Case Study in Fujian Province
Authors: Li Shengpeng , Cao Yingui , Liu Jianling , Wang Shufei , Zhou Wenxiang
Published: August 2022

Many strategies have been put forward to seek green and low-carbon development, some of which are achieved through land use and cover change (LUCC). A series of land management policies related to LUCC and corresponding changes in carbon dynamics were released with the implementation of the Ecological Conservation Pilot Zone Program (ECPZP) in China. We explored the spatiotemporal dynamics of LUCC and carbon storage in the first ECPZP implementation region (Fujian province) at the time before and after ECPZP implementation using a simplified carbon pools model and quantified the relative impacts of human activities and climate change on net primary productivity (NPP) employing residual analysis. This can fill the gap of land use and vegetation changes and the corresponding carbon dynamics in the ECPZP region and can serve as a reference for future land management policy revisions and ECPZP project extensions. The results showed that: (1) In 1990–2020, woodland, cultivated land, and grassland were the leading land use type in Fujian province. The area of LUCC was 11,707.75 km2, and it was predominantly caused by the conversion from cultivated land to built-up land, and the interconversion between woodland and grassland. (2) An increase of 9.74 Tg in carbon storage was mainly caused by vegetation conversion from 1990 to 2020. (3) The statistically significant increased area of climate change-induced NPP was 2.3% primarily in the northwest, but the decreased area of it statistically significantly was only 0.1%. Correspondingly, the increased area of statistically significant human activity-induced NPP was 8.7% primarily in the southeast, but the decreased area of statistically significance was 6.5%, mostly in the central region. In addition, the statistically significant areas of NPP caused by the combination of human activities and climate change differed by 1.8%. To sum up, ECPZP makes full use of the vertical mountain landscape and property right reform to effectively secure ecological space and local income. Moreover, urbanization-related policies are an essential impetus for LUCC and carbon balance. The impact of other built-up land expansion on environmental change needs to be paid particular attention to. Moreover, land-use activities in the centre of the study region that are not conducive to NPP growth should be judiciously assessed in the future.
Canopy Height Mapping by Sentinel 1 and 2 Satellite Images, Airborne LiDAR Data, and Machine Learning
Authors: Torres de Almeida Catherine , Gerente Jéssica , Rodrigo dos Prazeres Campos Jamerson , Caruso Gomes Junior Francisco , Providelo Lucas Antonio , Marchiori Guilherme , Chen Xinjian
Published: August 2022

Continuous mapping of vegetation height is critical for many forestry applications, such as planning vegetation management in power transmission line right-of-way. Satellite images from different sensors, including SAR (Synthetic Aperture Radar) from Sentinel 1 (S1) and multispectral from Sentinel 2 (S2), can be used for producing high-resolution vegetation height maps at a broad scale. The main objective of this study is to assess the potential of S1 and S2 satellite data, both in a single and a multisensor approach, for modeling canopy height in a transmission line right-of-way located in the Atlantic Forest of Paraná, Brazil. For integrating S1 and S2 data, we used three machine learning algorithms (LR: Linear Regression, CART: Classification and Regression Trees, and RF: Random Forest) and airborne LiDAR (Light Detection and Ranging) measurements as the reference height. The best models were obtained using the RF algorithm and 20 m resolution features from only S2 data (cross-validated RMSE of 4.92 m and R2 of 0.58) or multisensor data (cross-validated RMSE of 4.86 m and R2 of 0.60). Although the multisensor model presented the best performance, it was not statistically different from the single-S2 model. Thus, the use of only S2 to estimate canopy height has practical advantages, as it reduces the need to process SAR images and the uncertainties due to S1 noise or differences between the acquisition dates of S2 and S1.
Fast Tree Detection and Counting on UAVs for Sequential Aerial Images with Generating Orthophoto Mosaicing
Authors: Han Pengcheng , Ma Cunbao , Chen Jian , Chen Lin , Bu Shuhui , Xu Shibiao , Zhao Yong , Zhang Chenhua , Hagino Tatsuya
Published: August 2022

Individual tree counting (ITC) is a popular topic in the remote sensing application field. The number and planting density of trees are significant for estimating the yield and for futher planing, etc. Although existing studies have already achieved great performance on tree detection with satellite imagery, the quality is often negatively affected by clouds and heavy fog, which limits the application of high-frequency inventory. Nowadays, with ultra high spatial resolution and convenient usage, Unmanned Aerial Vehicles (UAVs) have become promising tools for obtaining statistics from plantations. However, for large scale areas, a UAV cannot capture the whole region of interest in one photo session. In this paper, a real-time orthophoto mosaicing-based tree counting framework is proposed to detect trees using sequential aerial images, which is very effective for fast detection of large areas. Firstly, to guarantee the speed and accuracy, a multi-planar assumption constrained graph optimization algorithm is proposed to estimate the camera pose and generate orthophoto mosaicing simultaneously. Secondly, to avoid time-consuming box or mask annotations, a point supervised method is designed for tree counting task, which greatly speeds up the entire workflow. We demonstrate the effectiveness of our method by performing extensive experiments on oil-palm and acacia trees. To avoid the delay between data acquisition and processing, the proposed framework algorithm is embedded into the UAV for completing tree counting tasks, which also reduces the quantity of data transmission from the UAV system to the ground station. We evaluate the proposed pipeline using sequential UAV images captured in Indonesia. The proposed pipeline achieves an F1-score of 98.2% for acacia tree detection and 96.3% for oil-palm tree detection with online orthophoto mosaicing generation.
A Hybrid Model Based on Superpixel Entropy Discrimination for PolSAR Image Classification
Authors: Sun Jili , Geng Lingdong , Wang Yize
Published: August 2022

Superpixel segmentation is widely used in polarimetric synthetic aperture radar (PolSAR) image classification. However, the classification method using simple majority voting cannot easily handle evidence conflicts in a single superpixel. At present, there is no method to evaluate the quality of superpixel classification. To solve the above problems, this paper proposes a hybrid classification model based on superpixel entropy discrimination (SED), and constructs a two-level cascade classifier. Firstly, a light gradient boosting machine (LGBM) was used to process large-dimensional input features, and simple linear iterative clustering (SLIC) was integrated to obtain the primary classification results based on superpixels. Secondly, information entropy was introduced to evaluate the quality of superpixel classification, and a complex-valued convolutional neural network (CV-CNN) was used to reclassify the high-entropy superpixels to obtain the secondary classification results. Experiments with two measured PolSAR datasets show that the overall accuracy of both classification methods exceeded 97%. This method suppressed the evidence conflict in a single superpixel and the inaccuracy of superpixel segmentation. The test time of our proposed method was shorter than that of CV-CNN, and using only 55% of CV-CNN test data could achieve the same accuracy as using CV-CNN for the whole image.
Frequency, Time, Representation and Modeling Aspects for Major Speech and Audio Processing Applications
Authors: Kacur Juraj , Puterka Boris , Pavlovicova Jarmila , Oravec Milos
Published: August 2022

There are many speech and audio processing applications and their number is growing. They may cover a wide range of tasks, each having different requirements on the processed speech or audio signals and, therefore, indirectly, on the audio sensors as well. This article reports on tests and evaluation of the effect of basic physical properties of speech and audio signals on the recognition accuracy of major speech/audio processing applications, i.e., speech recognition, speaker recognition, speech emotion recognition, and audio event recognition. A particular focus is on frequency ranges, time intervals, a precision of representation (quantization), and complexities of models suitable for each class of applications. Using domain-specific datasets, eligible feature extraction methods and complex neural network models, it was possible to test and evaluate the effect of basic speech and audio signal properties on the achieved accuracies for each group of applications. The tests confirmed that the basic parameters do affect the overall performance and, moreover, this effect is domain-dependent. Therefore, accurate knowledge of the extent of these effects can be valuable for system designers when selecting appropriate hardware, sensors, architecture, and software for a particular application, especially in the case of limited resources.
A Survey on 5G and LPWAN-IoT for Improved Smart Cities and Remote Area Applications: From the Aspect of Architecture and Security
Authors: Ogbodo Emmanuel Utochukwu , Abu-Mahfouz Adnan M. , Kurien Anish M.
Published: August 2022

Addressing the recent trend of the massive demand for resources and ubiquitous use for all citizens has led to the conceptualization of technologies such as the Internet of Things (IoT) and smart cities. Ubiquitous IoT connectivity can be achieved to serve both urban and underserved remote areas such as rural communities by deploying 5G mobile networks with Low Power Wide Area Network (LPWAN). The current architectures will not offer flexible connectivity to many IoT applications due to high service demand, data exchange, emerging technologies, and security challenges. Hence, this paper explores various architectures that consider a hybrid 5G-LPWAN-IoT and Smart Cities. This includes security challenges as well as endogenous security and solutions in 5G and LPWAN-IoT. The slicing of virtual networks using software-defined network (SDN)/network function virtualization (NFV) based on the different quality of service (QoS) to satisfy different services and quality of experience (QoE) is presented. Also, a strategy that considers the implementation of 5G jointly with Weightless-N (TVWS) technologies to reduce the cell edge interference is considered. Discussions on the need for ubiquity connectivity leveraging 5G and LPWAN-IoT are presented. In addition, future research directions are presented, including a unified 5G network and LPWAN-IoT architecture that will holistically support integration with emerging technologies and endogenous security for improved/secured smart cities and remote areas IoT applications. Finally, the use of LPWAN jointly with low earth orbit (LEO) satellites for ubiquitous IoT connectivity is advocated in this paper.
Evaluation of Different LiDAR Technologies for the Documentation of Forgotten Cultural Heritage under Forest Environments
Authors: Maté-González Miguel Ángel , Di Pietra Vincenzo , Piras Marco
Published: August 2022

In the present work, three LiDAR technologies (Faro Focus 3D X130—Terrestrial Laser Scanner, TLS-, Kaarta Stencil 2–16—Mobile mapping system, MMS-, and DJI Zenmuse L1—Airborne LiDAR sensor, ALS-) have been tested and compared in order to assess the performances in surveying built heritage in vegetated areas. Each of the mentioned devices has their limits of usability, and different methods to capture and generate 3D point clouds need to be applied. In addition, it has been necessary to apply a methodology to be able to position all the point clouds in the same reference system. While the TLS scans and the MMS data have been geo-referenced using a set of vertical markers and sphere measured by a GNSS receiver in RTK mode, the ALS model has been geo-referenced by the GNSS receiver integrated in the unmanned aerial system (UAS), which presents different characteristics and accuracies. The resulting point clouds have been analyzed and compared, focusing attention on the number of points acquired by the different systems, the density, and the nearest neighbor distance.
Intellectual Capital and Sustainable S3 in the Regions of Central Macedonia and Western Macedonia, Greece
Authors: Martinidis George , Dyjakon Arkadiusz , Minta Stanisław , Ramut Rafał
Published: August 2022

European regions are facing many important challenges, as the need to recover from the pandemic coincides with the need to carry out the green and digital transitions foreseen in the European Green Deal, making the task harder, especially for less-developed regions. The paper considers making use of regional intellectual capital in the context of smart specialisation strategies (S3) as the most effective way to address these challenges and achieve smart, sustainable and inclusive growth. This is viewed through a closer look at two specific cases of Greek regions that are behind the EU mean in terms of development and innovation: Central Macedonia and Western Macedonia. Development trends, available intellectual capital and current smart specialisation strategies in these regions are examined. These result in concrete, evidence-based suggestions on how they can make maximum use of intellectual capital for the next generation of smart specialisation strategies to achieve growth via a focus on more innovative and sustainable activities.
Research on Coupling and Coordination of Agro-Ecological and Agricultural Economic Systems in the Ebinur Lake Basin
Authors: Yao Lei , Halike Abudureheman , Wei Qianqian , Tang Hua , Tuheti Buweiayixiemu
Published: August 2022

The Ebinur Lake Basin is an important ecological area in China. The sustainable development of the basin is imperative, particularly the coupling and coordination between the agro-ecological environment and economy. Six counties in the Ebinur Lake Basin were studied and CRITIC—the entropy weight method used in the construction of regional agro-ecosystem and economic evaluation index systems for 2001–2021. The entropy weight method and coupling coordination were used to evaluate and analyze the systems. The results indicate that: (1) The integrated index grew slowly, increasing from 0.15 in 2000 to 0.18 in 2020. The agro-economic integrated index grew rapidly, increasing from 0.08 in 2000 to 0.25 in 2020. (2) High quality coupling was achieved from 2000 to 2010, with 50% superior coupling in 2010, which then decreased to reach 17% in 2020. (3) The agro-ecological–economic system coupling was high at 0.8; however, the coordination degree was low, at 0.36. (4) Most counties suffered from economic lag before 2010, with an average Ue/Us of 0.93 in 2010. Ecological lag has dominated since 2010, and the average Ue/Us value reached 1.48 in 2015. Coupling and coordinating the agro-ecological and economic systems is important for the sustainable development of local agriculture.
Optimization and Performance Analysis of Francis Turbine Runner Based on Super-Transfer Approximate Method under Multi-Energy Complementary Conditions
Authors: Zheng Xiaobo , Zhao Yaping , Zhang Huan , Pu Yongjian , Li Zhihua , Guo Pengcheng
Published: August 2022

Hydropower unit is the compensation power generation of the energy regulating unit in wind–solar–water multi-energy complementary systems that often require the turbine to operate in a partial working condition area, thereby resulting in problems of low hydraulic efficiency and severe vibration during operation. A multi-objective and multi-condition optimization design method for Francis turbine runner based on the super-transfer approximation approach was proposed in this study. The proposed method aims to improve the hydraulic performance of the turbine, enhance and suppress the vibration of the turbine, and expand the operation range of the turbine on the basis of the actual situation given that Francis turbine frequently operates in low- and ultralow-load areas under the condition of multi-energy complementarity and continuous adjustment of operating conditions. Different operating conditions from low load to full load were selected as performance evaluation conditions. The super-transfer approximation method was used to select the weight co-efficient of water turbine operating conditions, and a multi-objective optimization function with the efficiency and cavitation performance of the water turbine as optimization objectives was constructed to ensure that the optimized water turbine can achieve the optimal performance in the full working condition range. Results showed that the pressure distribution on the blade surface of the optimized runner was uniform and the working ability was enhanced under the condition of ensuring the performance stability of optimal and rated conditions when the original runner was optimized. The hydraulic efficiency of the turbine under the low-load conditions OP1 and OP2 increased by 4.61 and 3.17%, respectively. Hence, the optimized runner is suitable for hydraulic turbines under multi-energy complementary conditions. The results of this study can provide a reference for the optimal design and operation of the turbine runner.
New Algorithm for a Fixed Right Shift Code to Support Different Quality of Services in Smart and Sustainable Optical Networks
Authors: Abd El-Mottaleb Somia A. , Métwalli Ahmed , Chehri Abdellah , Ahmed Hassan Yousif , Zeghid Medien , Khan Akhtar Nawaz
Published: August 2022

Smart and sustainable cities require a network that can ensure many exchanges of information. In this sense, the deployment of optical fiber seems essential in order to guarantee urban interconnection. In this work, a new algorithm for the right shift code to be used in optical fiber communication (OFC) is proposed. The algorithm was designed to support different quality of services (audio, video, and data) for smart cities. This algorithm was based on varying the code weight for a certain number of users and transmitting a service to them. This algorithm was used for a spectral amplitude-coding optical code division multiple-access (SAC-OCDMA) system. Two detection scheme approaches were used, which are the single photodiode (SPD) detection technique and the direct detection (DD) technique. The performance was analytically studied for the proposed system in terms of BER, SNR, and the maximum number of users. The obtained results, when our system used SPD, showed an improvement in the number of users, about 2.5% at 622 Mbps and 1.4% at 1.25 Gbps and 2.5 Gbps. It can support a number of users up to 151 for video services at BER = 10−12, 300 for audio services with BER = 10−3, and 162 for data services at BER = 10−9 at a data rate of 1.25 Gbps. Furthermore, the system was simulated and showed transmission distances of 30 km at 1.25 Gbps and 6 km at 2.5 Gbps for video services, 80 km at 1.25 Gbps and 30 km at 2.5 Gbps for audio services, and 44 km at 1.25 Gbps and 13 km at 2.5 Gbps for data services. Our proposed system is suggested to be implemented in a fixed fifth-generation passive optical network (F5G PON).
A Combination of FDM, DEMATEL, and DANP for Disclosing the Interrelationship of Influencing Factors in Rural Homestay Business: Empirical Evidence from China
Authors: Peng Lei-Yi , Lu Jia , Luo Jian-Ji , Wang Yu-Xuan
Published: August 2022

As a rural tourism product, homestays play an essential role in sustainability. The operation of homestay business is directly linked to the success or failure of community-based tourism development. By taking rural homestay business in Zhejiang as a research object, the paper aims to clarify the interrelationships among influencing factors in the operation of rural homestay business from a performance perspective. Based on multi-criteria decision making (MCDM) techniques, this paper not only constructed the evaluation system of homestay business in the Chinese context by the Fuzzy Delphi Method (FDM), but also disclosed the interrelationships of criteria and aspects by a decision-making trial and evaluation laboratory (DEMATEL) and the DEMATEL-based analytical network process (DANP). Results show that: (1) 5 aspects and 31 criteria comprise the evaluation system of homestay business, (2) the aspects and criteria with high global weight are nearly clustered into the effect group, (3) the weight of service quality and homestay geist and community co-prosperity as the rank top two, (4) more than these, hardware facilities construct the product features of homestays because of the role of driving elements, (5) owing to the core elements, criteria about operational efficiency become guiding principles of homestay business, and (6) service quality and integrated utilization of socio-cultural resources underpin the sustainable development of homestay business in the long run. Therefore, the interrelationships of aspects and criteria provide further insights and underline the focus on homestay business for practitioners. At the same time, these serve as an effective administration tool for industry administrations. These will lay a solid foundation to enhance the level of homestay business and boost the sustainable development of community-based tourism.
China and the United States Hierarchical International Competitiveness Analysis
Authors: Dai Shugeng , Tan Dong
Published: August 2022

In this study, novel methods were used to evaluate the international manufacturing competitiveness of China and the U.S. under the value-added statistical caliber. The results obtain indicated that China’s manufacturing power was greater than that of the United States. However, the Chinese manufacturing index, performance, and international competitiveness were lower than those of the United States. The levels of low technology and medium technology in China were lower than those in the United States, but the level of high technology in China was the same as that in the United States. In addition, the Chinese and the United States three-level indexes were different, which indicated that China and the United States had differences in manufacturing.
An Optimal Scheduling Strategy of a Microgrid with V2G Based on Deep Q-Learning
Authors: Wen Yuxin , Fan Peixiao , Hu Jia , Ke Song , Wu Fuzhang , Zhu Xu
Published: August 2022

In recent years, the access of various distributed power sources and electric vehicles (EVs) has brought more and more randomness and uncertainty to the operation and regulation of microgrids. Therefore, an optimal scheduling strategy for microgrids with EVs based on Deep Q-learning is proposed in this paper. Firstly, a vehicle-to-grid (V2G) model considering the mobility of EVs and the randomness of user charging behavior is proposed. The charging time distribution model, charging demand model, state-of-charge (SOC) dynamic model and the model of travel location are comprehensively established, thereby realizing the construction of the mathematical model of the microgrid with EVs: it can obtain the charging/discharging situation in the EV station, so as to obtain the overall output power of the EV station. Secondly, based on Deep Q-learning, the state space and action space are set up according to the actual microgrid system, and the design of the optimal scheduling reward function is completed with the goal of economy. Finally, the calculation example results show that compared with the traditional optimization algorithm, the strategy proposed in this paper has the ability of online learning and can cope with the randomness of renewable resources better. Meanwhile, the agent with experience replay ability can be trained to complete the evolution process, so as to adapt to the nonlinear influence caused by the mobility of EVs and the periodicity of user behavior, which is feasible and superior in the field of optimal scheduling of microgrids with renewable resources and EVs.
Efficient Utilization of Siderite- and Hematite-Mixed Ore by Suspension Magnetization Roasting: A Pilot-Scale Study
Authors: Chen Chao , Han Yuexin , Zhang Yushu , Liu Yachuan , Liu Yingzhi
Published: August 2022

Steel is an important industrial raw material and plays an important role in industrial construction. Studying the efficient utilization of complex refractory iron ore with large reserves is of great significance to ensure the strategic safety of China’s iron and steel industry. Focusing on the typical mixed iron ore of siderite (FeCO3) and hematite (Fe2O3), this paper analyzes the possible ways of magnetization roasting from the perspective of thermodynamics and highlights that oxidation–reduction roasting is an easy way to realize industrial application. On this basis, a pilot-scale test of suspension magnetization roasting followed by low-intensity magnetic separation is carried out by using a newly developed suspension magnetization roasting furnace. The effects of roasting temperature, CO consumption, and N2 consumption on the magnetization roasting process are investigated, and 24 h continuous tests are carried out. Here, we find continuous suspension magnetization roasting followed by low-intensity magnetic separation can obtain a total iron grade of over 56% with an average value of 57.18% and a total iron recovery rate of over 91% with an average value of 92.22%. Product analysis shows that after SMR, iron minerals such as siderite and hematite transform into magnetite, with a substantial increase in magnetism, which is conducive to the separation of iron ore. The results provide a reference for the development and utilization of siderite- and hematite-mixed iron ore.
An Image Retrieval Framework Design Analysis Using Saliency Structure and Color Difference Histogram
Authors: Chugh Himani , Gupta Sheifali , Garg Meenu , Gupta Deepali , Mohamed Heba G. , Noya Irene Delgado , Singh Aman , Goyal Nitin
Published: August 2022

This paper focuses on retrieving plant leaf images based on different features that can be useful in the plant industry. Various images and their features can be used to identify the type of leaf and its disease. For this purpose, a well-organized computer-assisted plant image retrieval approach is required that can use a hybrid combination of the color and shape attributes of leaf images for plant disease identification and botanical gardening in the agriculture sector. In this research work, an innovative framework is proposed for the retrieval of leaf images that uses a hybrid combination of color and shape features to improve retrieval accuracy. For the color features, the Color Difference Histograms (CDH) descriptor is used while shape features are determined using the Saliency Structure Histogram (SSH) descriptor. To extract the various properties of leaves, Hue and Saturation Value (HSV) color space features and First Order Statistical Features (FOSF) features are computed in CDH and SSH descriptors, respectively. After that, the HSV and FOSF features of leaf images are concatenated. The concatenated features of database images are compared with the query image in terms of the Euclidean distance and a threshold value of Euclidean distance is taken for retrieval of images. The best results are obtained at the threshold value of 80% of the maximum Euclidean distance. The system’s effectiveness is also evaluated with different performance metrics like precision, recall, and F-measure, and their values come out to be respectively 1.00, 0.96, and 0.97, which is better than individual feature descriptors.
Food Waste in Saudi Arabia: Causes, Consequences, and Combating Measures
Authors: Baig Mirza Barjees , Alotaibi Bader Alhafi , Alzahrani Khodran , Pearson David , Alshammari Ghedeir M. , Shah Ashfaq Ahmad
Published: August 2022

The enormous amounts of food going as waste to landfills is of great concern in Saudi Arabia. The issue of food waste is complex, with its numerous social, cultural, economic, and environmental sustainability dimensions warranting further investigations. Food waste is one of the prime issues threatening food security in Saudi Arabia. This article aims to gauge the real issue, to create awareness among those who waste large amounts of food, and to encourage planners and policy makers to implement corrective measures. This article aims to stimulate interest within the scientific community, seek support from different branches of Saudi Arabian government, and engage all major segments of society. A thorough search of the international scientific publications and the grey literature published in English and Arabic was made. It was discovered that the available literature is scarce, and tends to focus on finding knowledge about the problem rather than on generating solutions. Thus, further research should attempt to find ways to form strategies and to test new ideas and interventions that could reduce food waste, particularly in the hospitality sector and within households. Based on the analysis presented in this paper, the recommended course of action for Saudi Arabia is to launch an integrated “Stop Wasting Food” campaign that would include all stakeholders. Raising awareness about the detrimental consequences of food waste and encouraging behavioral changes to reduce this squandering of precious resources is the first step in addressing the issue. There is an urgent need to promote behavioral changes in Saudi Arabian society, particularly among prime food wasters: women and youth.
A Fuzzy Simultaneous Evaluation of Criteria and Alternatives (F-SECA) for Sustainable E-Waste Scenario Management
Authors: Keshavarz-Ghorabaee Mehdi , Amiri Maghsoud , Zavadskas Edmundas Kazimieras , Turskis Zenonas , Antucheviciene Jurgita
Published: August 2022

The process of production, consumption, and final disposal of electrical and electronic equipment usually leads to harmful waste to the environment called e-waste. Eliminating and decreasing this type of waste could be considered as an essential goal for many enterprises working toward sustainable management systems. In this paper, we aim at introducing a new methodology for evaluation of sustainable e-waste management scenarios. The evaluation is defined as an MCDM (Multi-Criteria Decision-Making) problem, and the scenarios are the alternatives of the problem that need to be evaluated with respect to several sustainability criteria. An extended fuzzy SECA (Simultaneous Evaluation of Criteria and Alternatives) integrated with SMART (Simple Multi-Attribute Rating Technique), named F-SECA, is proposed to deal with the evaluation process. The α-cut approach is used to consider different levels of uncertainty and obtain interval values for assessment of criteria and alternatives. The proposed methodology helps us to make the evaluation with incorporation of subjective and objective data, opinions of multiple experts and uncertainty of information. We applied the methodology to evaluate sustainable e-waste management scenarios in a case. Through comparative and sensitivity analyses, the paper shows that the proposed methodology is efficient and gives reliable results.
Resilient Agile Education for Lifelong Learning Post-Pandemic to Meet the United Nations Sustainability Goals
Authors: Ossiannilsson Ebba S. I.
Published: August 2022

The World Health Organization officially classified COVID-19 as a pandemic in early March 2020. Extraordinary security measures, health restrictions, and social isolation left hardly any aspect of daily life untouched. One area that underwent major changes was education, whose cornerstones and foundations were challenged as schools and universities around the world were forced to close their doors to prevent the spread of the virus. In this article, the reasons resilience and agility are critical to achieving social justice, human rights, and the United Nations Sustainability goals (SDG) in the post-pandemic era are studied. It is also argued that the role of education needs to be redesigned to be resilient and agile and to ensure lifelong learning. In addition, a post-pandemic quality agenda is the focus of the article. Some of the emerging quality dimensions are empathy, satisfaction, well-being, the social dimensions of learning, and their impact at the nano, micro, meso, and macro levels. This article was prepared as part of a systematic literature review based mainly on official reports from organizations working in this field worldwide. The author selected examples from ongoing discourse and debate about the challenges in this field in addition to examples from the author’s research, experiences, and perspectives. In summary, questions regarding educational landscapes may be the same, but in the context of post-pandemic and resilient agile education for lifelong learning to meet the SDGs and the new social contract for education, the answers to the questions of why, who, when, what, and at what levels will be different. It is time not just to talk, but to act. Each of us can and must commit to the new social contract. It is time to collectively reimagine our futures to include the ecosystem of education in all learning environments, i.e., formal, non-formal, and informal, and to value resilient, agile, seamless, and rhizomatic learning in the context of lifelong learning.
Sense of Place of Heritage Conservation Districts under the Tourist Gaze—Case of the Shichahai Heritage Conservation District
Authors: Wei Hanbin , Zhou Mengru , Kang Sunju , Zhang Jiahao
Published: August 2022

The tourists gaze can deeply trigger the most real thoughts and feelings in tourists’ hearts. The sense of place of Heritage Conservation Districts (HCDs) under the tourist gaze takes a mental perception of tourists’ feeling and is an important factor in the connection between values protection and development. Famous heritage districts function as important signs, causing the formation of mental images and an emotional sense of belonging to the place in tourists. The present research aims to determine a suitable methodology for recognizing the sense of place of HCDs under the tourist gaze. This study used image-based interviews through the Zaltman Metaphor Elicitation Technique (ZMET) and examined sense of place factors in the Shichahai HCD of Beijing. The result shows that the sense of place in the Shichahai HCD consists of three important factors, the physical environment, immaterial environment, and activity experience. We tested these factors as determinants in a sense of place model of tourist selection and emotional state during travel, exhibiting substantial explanatory potential. This study supports the idea that the sense of place of the Shichahai HCD under the tourist gaze can be re-made, and provides novel methods for evaluating the value of HCDs.
Durability of Engineered Cementitious Composites Incorporating High-Volume Fly Ash and Limestone Powder
Authors: Turk Kazim , Kina Ceren , Nehdi Moncef
Published: August 2022

This study investigates the effects of using limestone powder (LSP) and high-volume fly ash (FA) as partial replacement for silica sand (SS) and portland cement (PC), respectively, on the durability properties of sustainable engineered cementitious composites (ECC). The mixture design of ECC included FA/PC ratio of 1.2, 2.2 and 3.2, while LSP was used at 0%, 50% and 100% of SS by mass for each FA/PC ratio. Freeze-thaw and rapid chloride ions penetrability (RCPT) tests were performed to assess the durability properties of ECC, while the compressive and flexural strength tests were carried out to appraise the mechanical properties. Moreover, mercury intrusion porosimetry (MIP) tests were performed to characterize the pore structure of ECC and to associate porosity with the relative dynamic modulus of elasticity, RCPT and mechanical strengths. It was found that using FA/PC ratio of more than 1.2 worsened both the mechanical and durability properties of ECC. Replacement of LSP for SS enhanced both mechanical strengths and durability characteristics of ECC, owing to refined pore size distribution caused by the microfiller effect. It can be further inferred from MIP test results that the total porosity had a vital effect on the resistance to freezing–thawing cycles and chloride ions penetration in sustainable ECC.
Adapting to Socio-Environmental Change: Institutional Analysis of the Adaptive Capacity of Interacting Formal and Informal Cooperative Water Governance
Authors: Gilmore Sarah , Cosens Barbara , Griffith David L. , Alessa Lilian , Kliskey Andrew
Published: August 2022

Much of the world’s agricultural lands are projected to face hydrologic and climatic changes that will lead to water scarcity and corresponding food insecurity. The emergent response of complex social-ecological systems to change requires rapid response and tailored solutions. Top-down responses without room for local self-organization may fail to implement effective solutions, yet self-organization alone may be too slow to respond in a period of rapid change and may lack the accountability necessary in the management of a public resource such as water. This research relies on concepts of governing complexity to assess the role of local self-organization nested within formal institutions in developing adaptive solutions to conflict involving irrigated agriculture in Idaho’s Upper Snake River Basin. While formal institutions have provided a framework, steering, and resources for local action, the organization of water users dependent on the resource plays a large role in the ability of the region to adapt to water supply disturbances, highlighting the importance of local capacity within an umbrella of governmental steering to respond to rising water resources issues in semi-arid regions.
A Study on the Effects of Consumers' Perception and Purchasing Behavior for Second-Hand Luxury Goods by Perceived Value
Authors: Tu Jui-Che , Hsu Ching-Fen , Creativani Kharisma
Published: August 2022

Finding insights into consumers’ perceptions and behavior regarding purchasing second-hand luxury goods could promote the vigorous and sound development of the second-hand luxury industry. The research objectives included: (1) probing into the relationship between consumers’ perceptions and purchase behavior regarding second-hand luxury goods; (2) discussing the current state and future trends of the market for second-hand luxury goods; (3) learning about consumers’ perceived value of second-hand luxury goods so that it can be applied to other types of commodities in the future to develop corresponding second-hand markets; and (4) analyzing the differences between factors that influence different types of consumers’ perceptions and purchase behavior regarding second-hand luxury goods and allowing second-hand dealers in the industry to use them as a reference. This study discussed relevant studies and theories on second-hand luxury goods, perceived value, and consumer behavior, and shed light on the follow-up research and development. It used the method of semi-structured expert interviews of the respondents. The outline of the expert interviews was created according to the current state and future development of the second-hand luxury market, consumer behaviors, and consumers’ perceived value of second-hand luxury goods. The content of the interviews was sampled, analyzed, and summarized according to the research scope to develop a questionnaire for consumers of the survey. Factor analysis was used to carry out statistical data analyses on the statistics converted from the collected questionnaire data. This study sorted out the main factors that consumers consider when purchasing second-hand luxury goods, and at the same time learned how consumers’ purchase behavior is shaped by a good’s perceived value. The factors under consideration included the purchase intention orientation, commodity quality orientation, market cycle orientation, consumption value orientation, individual condition orientation, and environmental sustainability orientation.
The Influence of Human Values, Environmental Awareness, and Attitudes on the Intention to Purchase Cannabis-Based Skincare Cosmetics
Authors: Ribeiro Najla Gonzaga , Añaña Edar Silva , Barbosa Belem
Published: August 2022

This article analyzes consumer intentions to purchase cannabis-based skincare cosmetics by considering the role of human values, environmental awareness, and attitudes toward cannabis-based skincare cosmetics and their industrial use. The literature enabled the definition of a set of nine hypotheses, which were tested by a quantitative study with 230 participants from Portugal. Data were collected online in 2021 using snowball sampling. Structural equation modeling and mean difference tests were used for the hypothesis testing. The results suggest that personal values regarding openness to change and conservation indirectly influence the acceptance of cannabis-derived cosmetic products by reinforcing attitudes toward cannabis-based skincare cosmetics, and that environmental awareness influences the intention to purchase cannabis-based skincare cosmetics. This article provides relevant insights for both practitioners and researchers, as it demonstrates that both attitudes toward cannabis-based skincare cosmetics and the attitude toward the use of cannabis by the cosmetic industry predict purchase intentions of cannabis-based skin care cosmetics and therefore, should be considered for the development of the strategy for communicating with consumers. The article also makes some suggestions about the profiles of consumers most willing to buy this type of product, highlighting the role of environmental awareness and human values as strong determinants that influence the purchase intention of cannabis-based skincare cosmetics.