bluuebunny/crossref_metadata_2025 huggingface dataset:
Hyperspectral Image Classification across Different Datasets: A Generalization to Unseen Categories
Authors: Pan Erting , Ma Yong , Fan Fan , Mei Xiaoguang , Huang Jun
Published: April 2021

With the rapid developments of hyperspectral imaging, the cost of collecting hyperspectral data has been lower, while the demand for reliable and detailed hyperspectral annotations has been much more substantial. However, limited by the difficulties of labelling annotations, most existing hyperspectral image (HSI) classification methods are trained and evaluated on a single hyperspectral data cube. It brings two significant challenges. On the one hand, many algorithms have reached a nearly perfect classification accuracy, but their trained models are hard to generalize to other datasets. On the other hand, since different hyperspectral datasets are usually not collected in the same scene, different datasets will contain different classes. To address these issues, in this paper, we propose a new paradigm for HSI classification, which is training and evaluating separately across different hyperspectral datasets. It is of great help to labelling hyperspectral data. However, it has rarely been studied in the hyperspectral community. In this work, we utilize a three-phase scheme, including feature embedding, feature mapping, and label reasoning. More specifically, we select a pair of datasets acquired by the same hyperspectral sensor, and the classifier learns from one dataset and then evaluated it on the other. Inspired by the latest advances in zero-shot learning, we introduce label semantic representation to establish associations between seen categories in the training set and unseen categories in the testing set. Extensive experiments on two pairs of datasets with different comparative methods have shown the effectiveness and potential of zero-shot learning in HSI classification.
Towards a Fully Automated Scanning Probe Microscope for Biomedical Applications
Authors: Szeremeta Witold K. , Harniman Robert L. , Bermingham Charlotte R. , Antognozzi Massimo
Published: April 2021

The increase in capabilities of Scanning Probe Microscopy (SPM) has resulted in a parallel increase in complexity that limits the use of this technique outside of specialised research laboratories. SPM automation could substantially expand its application domain, improve reproducibility and increase throughput. Here, we present a bottom-up design in which the combination of positioning stages, orientation, and detection of the probe produces an SPM design compatible with full automation. The resulting probe microscope achieves sub-femtonewton force sensitivity whilst preserving low mechanical drift (2.0±0.2 nm/min in-plane and 1.0±0.1 nm/min vertically). The additional integration of total internal reflection microscopy, and the straightforward operations in liquid, make this instrument configuration particularly attractive to future biomedical applications.
Automatic Number Plate Recognition:A Detailed Survey of Relevant Algorithms
Authors: Lubna  , Mufti Naveed , Shah Syed Afaq Ali
Published: April 2021

Technologies and services towards smart-vehicles and Intelligent-Transportation-Systems (ITS), continues to revolutionize many aspects of human life. This paper presents a detailed survey of current techniques and advancements in Automatic-Number-Plate-Recognition (ANPR) systems, with a comprehensive performance comparison of various real-time tested and simulated algorithms, including those involving computer vision (CV). ANPR technology has the ability to detect and recognize vehicles by their number-plates using recognition techniques. Even with the best algorithms, a successful ANPR system deployment may require additional hardware to maximize its accuracy. The number plate condition, non-standardized formats, complex scenes, camera quality, camera mount position, tolerance to distortion, motion-blur, contrast problems, reflections, processing and memory limitations, environmental conditions, indoor/outdoor or day/night shots, software-tools or other hardware-based constraint may undermine its performance. This inconsistency, challenging environments and other complexities make ANPR an interesting field for researchers. The Internet-of-Things is beginning to shape future of many industries and is paving new ways for ITS. ANPR can be well utilized by integrating with RFID-systems, GPS, Android platforms and other similar technologies. Deep-Learning techniques are widely utilized in CV field for better detection rates. This research aims to advance the state-of-knowledge in ITS (ANPR) built on CV algorithms; by citing relevant prior work, analyzing and presenting a survey of extraction, segmentation and recognition techniques whilst providing guidelines on future trends in this area.
Human Motion Tracking with Less Constraint of Initial Posture from a Single RGB-D Sensor
Authors: Liu Chen , Wang Anna , Bu Chunguang , Wang Wenhui , Sun Haijing
Published: April 2021

High-quality and complete human motion 4D reconstruction is of great significance for immersive VR and even human operation. However, it has inevitable self-scanning constraints, and tracking under monocular settings also has strict restrictions. In this paper, we propose a human motion capture system combined with human priors and performance capture that only uses a single RGB-D sensor. To break the self-scanning constraint, we generated a complete mesh only using the front view input to initialize the geometric capture. In order to construct a correct warping field, most previous methods initialize their systems in a strict way. To maintain high fidelity while increasing the easiness of the system, we updated the model while capturing motion. Additionally, we blended in human priors in order to improve the reliability of model warping. Extensive experiments demonstrated that our method can be used more comfortably while maintaining credible geometric warping and remaining free of self-scanning constraints.
Small Object Detection in Traffic Scenes Based on Attention Feature Fusion
Authors: Lian Jing , Yin Yuhang , Li Linhui , Wang Zhenghao , Zhou Yafu
Published: April 2021

There are many small objects in traffic scenes, but due to their low resolution and limited information, their detection is still a challenge. Small object detection is very important for the understanding of traffic scene environments. To improve the detection accuracy of small objects in traffic scenes, we propose a small object detection method in traffic scenes based on attention feature fusion. First, a multi-scale channel attention block (MS-CAB) is designed, which uses local and global scales to aggregate the effective information of the feature maps. Based on this block, an attention feature fusion block (AFFB) is proposed, which can better integrate contextual information from different layers. Finally, the AFFB is used to replace the linear fusion module in the object detection network and obtain the final network structure. The experimental results show that, compared to the benchmark model YOLOv5s, this method has achieved a higher mean Average Precison (mAP) under the premise of ensuring real-time performance. It increases the mAP of all objects by 0.9 percentage points on the validation set of the traffic scene dataset BDD100K, and at the same time, increases the mAP of small objects by 3.5%.
Exploring Equity in Public Transportation Planning Using Smart Card Data
Authors: Ghasemlou Kiarash , Ergun Murat , Dadashzadeh Nima
Published: April 2021

Existing public transport (PT) planning methods use a trip-based approach, rather than a user-based approach, leading to neglecting equity. In other words, the impacts of regular users—i.e., users with higher trip rates—are overrepresented during analysis and modelling because of higher trip rates. In contrast to the existing studies, this study aims to show the actual demand characteristic and users’ share are different in daily and monthly data. For this, 1-month of smart card data from the Kocaeli, Turkey, was evaluated by means of specific variables, such as boarding frequency, cardholder types, and the number of users, as well as a breakdown of the number of days traveled by each user set. Results show that the proportion of regular PT users to total users in 1 workday, is higher than the monthly proportion of regular PT users to total users. Accordingly, users who have 16–21 days boarding frequency are 16% of the total users, and yet they have been overrepresented by 39% in the 1-day analysis. Moreover, users who have 1–6 days boarding frequency, have a share of 66% in the 1-month dataset and are underrepresented with a share of 22% in the 1-day analysis. Results indicated that the daily travel data without information related to the day-to-day frequency of trips and PT use caused incorrect estimation of real PT demand. Moreover, user-based analyzing approach over a month prepares the more realistic basis for transportation planning, design, and prioritization of transport investments.
Ensuring Purpose Limitation in Large-Scale Infrastructures with Provenance-Enabled Access Control
Authors: Sultan Shizra , Jensen Christian D.
Published: April 2021

The amount of data generated in today’s world has a fair share of personal information about individuals that helps data owners and data processors in providing them with personalized services. Different legal and regulatory obligations apply to all data owners collecting personal information, specifying they use it only for the agreed-upon purposes and in a transparent way to preserve privacy. However, it is difficult to achieve this in large-scale and distributed infrastructures as data is continuously changing its form, such as through aggregation with other sources or the generation of new transformed resources, resulting often in the loss or misinterpretation of the collection purpose. In order to preserve the authorized collection purposes, we propose data is added as a part of immutable and append-only resource metadata (provenance), to be retrieved by an access control mechanism when required for data-usage verification. This not only ensures purpose limitation in large-scale infrastructures but also provides transparency for individuals and auditing authorities to track how personal information is used.
Unveiling the Crucial Factors of Women Entrepreneurship in the 21st Century
Authors: Ingalagi Sanjeev S. , Nawaz Nishad , Rahiman Habeeb Ur , Hariharasudan A. , Hundekar Vanishree
Published: April 2021

In the present era, women-owned firms are one of India’s fastest increasing entrepreneurial communities in the form of women entrepreneurs. The objective of the study is to identify the factors that influence women’s entrepreneurial orientation and firms’ performance. The research study discusses the influencing factors and their effect on firms’ performance and satisfaction in this regard. The proposed framework and hypotheses have been tested using data gathered from boutiques, beauty parlors, carpet manufacturers, and retail shops in Karnataka, India. Data analysis was done using univariate, bivariate, and multivariate techniques. In Structural Equation Modeling (SEM), paths were created for evaluating the cause-and-effect relationship between different factors viz., social, psychological, financial, and resource factors and entrepreneurial performance and satisfaction. Seven relationships were significant, while two relationships were insignificant in this structural equation. The key finding of the paper is that all factors have a significant impact on the firm’s performance. The implications of research results for researchers and practitioners are discussed, and suggestions have also been made.
Determinants of Success of Businesses of Female Entrepreneurs in Taiwan
Authors: Schröder Lisa-Marie , Bobek Vito , Horvat Tatjana
Published: April 2021

This paper deals with the topic area “female entrepreneurship,” and the research focuses on the determinants of female entrepreneurs’ business success and sustainability, together with their impact on Taiwan’s economic development. According to the Morgan Stanley Capital International (MSCI) and the Financial Times Stock Exchange (FTSE) classification, Taiwan can be considered an emerging economy. Various liberal and social theories and Hofstede’s cultural dimensions were analyzed to develop some hypotheses, including some relevant success factors connected to female entrepreneurship in Taiwan. The Global Entrepreneurship Monitor (GEM) and the Female Entrepreneurship Index (FEI) were relevant for the data analysis because the research was based on secondary data with 1098 observations, and a logistic regression model was performed. The factors of fear of failure and personal network correlated significantly to female entrepreneurs’ business success in Taiwan and the level of education had no significant correlation. Further research is recommended to include additional factors to achieve a higher accuracy of the model. A comparison of Taiwan with another region/country might also deliver some interesting insights.
Changes in Paleovegetation and Paleoclimate in China since the Late Middle Pleistocene: A Case Study of the Dajiuhu Basin
Authors: Wu Liwei , Li Xinling , Xu Qinghai , Li Manyue , Zheng Qiufeng , Zhang Maoheng , Wang Dandan , He Zhiguo
Published: April 2021

The East Asian monsoon system is an important part of global atmospheric circulation; however, records of the East Asian monsoon from different regions exhibit different evolutionary rhythms. Here, we show a high-resolution record of grain size and pollen data from a lacustrine sediment core of Dajiuhu Lake in Shennongjia, Hubei Province, China, in order to reconstruct the paleovegetation and paleoeclimate evolution of the Dajiuhu Basin since the late Middle Pleistocene (~237.9 ka to the present). The results show that grain size and pollen record of the core DJH-2 are consistent with the δ18O record of stalagmites from Sanbao Cave in the same area, which is closely related to the changes of insolation at the precessional (~20-kyr) scale in the Northern Hemisphere. This is different from the records of the Asian summer monsoon recorded in the Loess Plateau of North China, which exhibited dominant 100-kyr change cyclicities. We suggest that the difference between paleoclimatic records from North and South China is closely related to the east–west-oriented mountain ranges of the Qinling Mountains in central China that blocked weakened East Asia summer monsoons across the mountains during glacial periods.
Marketing Investments and Corporate Social Responsibility
Authors: Kim Yura , Kim Taeyeon , Nam Hye-Jeong
Published: April 2021

Although the short-term effects of marketing efforts that promote immediate consumer responses have been extensively investigated, the long-term impacts of marketing activities have received little attention. Marketing effects can be carried over time as consumers experience an emotional attachment to products and build trust and affection. In addition, a firm’s advertising spending not only improves customer awareness of the firm’s products and services but also serves to promote other company information, such as the firm’s corporate social responsibility (CSR), a long-term strategic commitment to improving the welfare of customers and society. This paper focuses on the long-term effects of marketing investments by examining the relation between advertising expenditures and a firm’s commitment to CSR, finding that firms with a higher advertising expenditure are more likely to have a higher CSR performance. The findings of this study demonstrate that marketing investments are related to a firm’s long-term sustainable activities. Additionally, the finding may indicate that a firm’s CSR initiatives are influenced by the extent to which the firm commits to advertising that promotes customer awareness of the firm’s products and services.
Examining Energy Consumption and Carbon Emissions of Microbial Induced Carbonate Precipitation Using the Life Cycle Assessment Method
Authors: Deng Xuejie , Li Yu , Liu Hao , Zhao Yile , Yang Yinchao , Xu Xichen , Cheng Xiaohui , Wit Benjamin de
Published: April 2021

Microbial induced carbonate precipitation (MICP) is a new geotechnical engineering technology used to strengthen soils and other materials. Although it is considered to be environmentally friendly, there is a lack of quantitative data and objective evaluation to support conclusions about its environmental impact. In this paper, the energy consumption and carbon emissions of MICP technology are quantitatively analyzed by using the life cycle assessment (LCA) method. The environmental effects of MICP technology are evaluated from the perspectives of resource consumption and environmental impact. The results show that for each tonne of calcium carbonate produced by MICP technology, 1.8 t standard coal is consumed and 3.4 t CO2 is produced, among which 80.4% of the carbon emissions and 96% of the energy consumption come from raw materials. Comparing using MICP with cement, lime, and sintered brick, the current MICP application process consumes less non-renewable resources but has a greater environmental impact. The major environmental impact that MICP has is the production of smoke and ash, with secondary impacts being global warming, photochemical ozone creation, acidification, and eutrophication. In five potential application scenarios of MICP, including concrete, sintered brick, lime mortar, mine cemented backfill, and foundation reinforcement, the carbon emissions of MICP are 3 to 7 times greater than the emissions of traditional technologies. The energy consumption is 15 to 23 times. Based on the energy consumption and carbon emissions characteristics of MICP technology at the current condition, suggestions are given for the future research of MICP.
A Topic-Based Bibliometric Review of Computers in Human Behavior: Contributors, Collaborations, and Research Topics
Authors: Chen Xieling , Zou Di , Xie Haoran , Cheng Gary
Published: April 2021

Computers in Human Behavior (CHB) is a well-established source with a wide range of audiences in the field of human interactions with computers and has been one of the most widely acknowledged and leading venues with significant scientific impact for more than 35 years. This review provides an overview of the status, trends, and particularly the thematic structure of the CHB by adopting bibliometrics and structural topic modeling on 5957 studies. Specifically, we analyzed the trend of publications, identified major institutions and countries/regions, detected scientific collaboration patterns, and uncovered important topics. Significant findings were presented. For example, the contribution of the USA and Open University of Netherlands was highlighted. Important research topics such as e-commerce, social interactions and behaviors, public opinion and social media, cyberbullying, online sexual issues, and game andgamification were identified. This review contributes to the CHB community by justifying the interest in human behavior issues concerning computer use and identifying future research lines on this topic.
Employment Diversification as a Determinant of Economic Resilience and Sustainability in Provincial Cities
Authors: Bogdański Marcin
Published: April 2021

Differentiated response of selected economies to the global economic crisis caused by the collapse of the real estate market in the United States has drawn the attention of economists to the concept of economic resilience. At the same time, once again, it showed the importance of analysing and creating suitable conditions for sustainable development. Resilient economies are less exposed to the risk of economic crises or slowdowns, which is vital for ensuring stable incomes and high level of living standards. Therefore, the presented analysis was aimed at evaluating the level of economic resilience of provincial cities in Poland in relation to the situation on their labour markets. For this purposes, selected measures of the variation in the distribution feature (e.g., coefficient of variation) and the degree of structure diversification of the examined feature (Amemiya’s index) were used. Subsequently, using correlation analysis, the research determined whether any relationships could be observed between the investigated variables. The results of the research indicate that for provincial cities sub-regions in Poland, a statistically significant, moderate negative correlation could be observed between the degree of employment structure diversification in 2009 and the scale and scope of the collapse in the number of employed persons in subsequent years. This suggests that a high level of employment diversification restricted the level of economic resilience in this case.
Impact of Environmental Regulation Intensity on Green Technology Innovation: From the Perspective of Political and Business Connections
Authors: Ai Yu-Hong , Peng Di-Yun , Xiong Huan-Huan
Published: April 2021

With heavy air pollution and the highest CO2 emissions in the world, China is in urgent need of technology innovation to improve the energy efficiency and control the pollution emission. This study empirically investigates the impact of environmental regulation intensity, political connections, and business connections on green technology innovation in China’s firms. The authors employ a panel data regression analysis on a dataset that comprises 884 observations for A-share listed companies from 2016 to 2019, owing to the availability of data. The results show: (1) Environmental regulation intensity (ERI) has a U-shaped effect on green technology innovation (GTI), which means GTI is inhibited by ERI in the early stage but gets promoted in the long run; (2) Political connections positively moderate the relationship between ERI and GTI mainly because of crowding-out effect and resource effect; (3) Business connections have a negative impact on the relationship between ERI and GTI, resulting from knowledge acquisition and lock-in; (4) Business connections have a greater moderating effect than political connections probably because political ties lack an effective mechanism to ensure long-term cooperation with the enterprises; (5) However, with regard to those firms in the non-heavily polluting industry, both connections moderate the relationship between ERI and GTI in an opposite direction to the main effect. The research results help policy makers formulate relevant policies, based on the impact of environmental regulation and social connections on green technology innovation.
Shaping a Circular Economy in the Digital TV Industry: Focusing on Ecopreneurship through the Lens of Dynamic Capability
Authors: Moon Seungyeon , Lee Heesang
Published: April 2021

In this study, we investigate how companies can contribute to achieving a circular economy (CE) in the electronics industry viewed through the lens of dynamic capability. In particular, we examine how companies can contribute through idiosyncratic ecopreneurship according to dynamic capabilities with three points: the dynamic capabilities of established companies, the formation of ecopreneurship according to idiosyncratic dynamic capabilities, and the shaping of a CE through the interplay of ecopreneurship and dynamic capabilities of established companies. We conducted a case study of five leading TV manufacturers (Samsung, LG, Sony, Hisense, and TCL) to verify our conceptual framework, which we derived from a literature review. The case study shows that a company’s contribution to the CE and ecopreneurship type largely depend on a combination of dynamic capabilities and business strategies. Based on the case study results, we derived managerial implications with three points: the approach of leading companies to CE with consideration of business strategies, leveraging ecopreneurship to gain competitiveness in the market, and the influence of micro- and meso-level dynamic capabilities on a company’s contribution to CE.
Diagnosis of the Maturity Level of Implementing Industry 4.0 Solutions in Selected Functional Areas of Management of Automotive Companies in Poland
Authors: Stawiarska Ewa , Szwajca Danuta , Matusek Mirosław , Wolniak Radosław
Published: April 2021

The automotive sector is one of the key branches of the global economy. The automotive industry is also a very important sector of the Polish economy, as it generates over 8% of GDP and accounts for over 20% of the annual export value. Industry 4.0 and the effective use of modern technologies give a chance for its further dynamic development. The implementation of Industry 4.0 solutions in the business processes of automotive companies should not only take place in the area of production or logistics, as it is usually indicated, but also in their other functional areas, such as quality management, human resources management, and innovation management. The purpose of the article is to diagnose the level of maturity in the implementation of Industry 4.0 solutions in selected management areas of automotive companies operating in Poland. Using a maturity assessment tool, the authors assessed the level of maturity in six selected functional areas of an enterprise, such as production and logistics management, quality management, human resources management, social and environmental responsibility, and product innovation management. The authors also formulated conclusions and recommendations concerning actions that should be taken by automotive companies in order to achieve higher maturity levels in the implementation of Industry 4.0 solutions.
Model Based Analysis of Innovation in Sustainable Supply Chains
Authors: Morcillo-Bellido Jesús , Isasi-Sanchez Luis , Garcia-Gutierrez Isabel , Duran-Heras Alfonso
Published: April 2021

Innovation supports the development of Sustainable Supply Chains (SSCs) through Sustainability-Oriented Innovation (SOI) practices. This study aims to validate and further develop, through its practical application, a baseline SOI practices framework, which can be used as a benchmark model. While applying and validating this framework, several new, conceptually distinctive SOI practices were identified that were not included in the proposed baseline model. This led the authors to propose expanding the initial baseline model with a new category of “transversal” SOI practices, so that the expanded model provides a more comprehensive view of the mechanisms that foster innovation at SSCs. These “transversal” SOI practices are highly contingent on the adopting company’s traits and strategy, thus suggesting that they might be a major conduit through which its strategy is reflected in its SSCM. Besides their transversal and contingent nature, another key trait of the identified SOI practices is their integrated, dynamic, time-dependent, feedback-loop-based interrelationship. These findings suggest the potential effectiveness, for processes such as sustainability innovation that involve substantial time lags, to reposition top management focus and performance evaluation “upstream” in the causal chain. This potentially promising approach involves shifting focus from results (particularly short-term results) to its causes (processes, methods), and systematically managing the ensuing feedback loops.
An Application of the Walkability Index for Elderly Health—WIEH. The Case of the UNESCO Historic Centre of Porto, Portugal
Authors: Alves Fernando , Cruz Sara , Rother Sophia , Strunk Tino
Published: April 2021

This work provides a follow-up to the article Walkability Index for Elderly Health: A Proposal, published in 2020. Previous research linked the quality of public spaces, walkability characteristics relevant to older people, and the direct health benefits of walking for the same target group. The present article, on the other hand, aims to validate the conceptual design of the walkability index for elderly health (WIEH), developed by the authors in the previous study, by applying it to a study area located in the historic center of Porto, Portugal. Therefore, public spaces and the pedestrian network are analyzed according to their suitability for older people’s walkability. Presented in a visual format, the results show that only a few paths within the study area were strongly suited to older people, and emphasize the impact of existing steep slopes on the quality of the pedestrian network.
Life Cycle Assessment of Electric Vehicles and Hydrogen Fuel Cell Vehicles Using the GREET Model—A Comparative Study
Authors: Wong Eugene Yin Cheung , Ho Danny Chi Kuen , So Stuart , Tsang Chi-Wing , Chan Eve Man Hin
Published: April 2021

Facing global warming and recent bans on the use of diesel in vehicles, there is a growing need to develop vehicles powered by renewable energy sources to mitigate greenhouse gas and pollutant emissions. Among the various forms of non-fossil energy for vehicles, hydrogen fuel is emerging as a promising way to combat global warming. To date, most studies on vehicle carbon emissions have focused on diesel and electric vehicles (EVs). Emission assessment methodologies are usually developed for fast-moving consumer goods (FMCG) which are non-durable household goods such as packaged foods, beverages, and toiletries instead of vehicle products. There is an increase in the number of articles addressing the product carbon footprint (PCF) of hydrogen fuel cell vehicles in the recent years, while relatively little research focuses on both vehicle PCF and fuel cycle. Zero-emission vehicles initiative has also brought the importance of investigating the emission throughout the fuel cycle of hydrogen fuel cell and its environmental impact. To address these gaps, this study uses the life-cycle assessment (LCA) process of GREET (greenhouse gases, regulated emissions, and energy use in transportation) to compare the PCF of an EV (Tesla Model 3) and a hydrogen fuel cell car (Toyota MIRAI). According to the GREET results, the fuel cycle contributes significantly to the PCF of both vehicles. The findings also reveal the need for greater transparency in the disclosure of relevant information on the PCF methodology adopted by vehicle manufacturers to enable comparison of their vehicles’ emissions. Future work will include examining the best practices of PCF reporting for vehicles powered by renewable energy sources as well as examining the carbon footprints of hydrogen production technologies based on different methodologies.
Process Optimization of Waste Activated Sludge in Anaerobic Digestion and Biogas Production by Electrochemical Pre-Treatment Using Ruthenium Oxide Coated Titanium Electrodes
Authors: Heng Gan Chin , Isa Mohamed Hasnain , Lock Serene Sow Mun , Ng Choon Aun
Published: April 2021

Anaerobic digestion (AD) appears to be a popular unit operation in wastewater treatment plant to treat waste activated sludge (WAS) and the produced methane gas can be harvested as renewable energy. However, WAS could inhibit hydrolysis stage during AD and hence pre-treatment is required to overcome the issue. This paper aimed to study the effect of electrochemical pre-treatment (EP) towards efficiency of AD using titanium coated with ruthenium oxide (Ti/RuO2) electrodes. The investigation has been carried out using in-house laboratory batch-scale mesophilic anaerobic digester, mixed under manipulation of important operating parameters. Optimization was performed on EP using response surface methodology and central composite design to maximize sludge disintegration and dewaterability. By operating at optimal conditions (pH 11.65, total solids 22,000 mg/L, electrolysis time 35 min, current density 6 mA/cm2, and 1000 mg/L of sodium chloride), the pre-treated WAS in terms of mixed liquor volatile suspended solids (MLVSS) removal, soluble chemical oxygen demand (sCOD), capillary suction time (CST) reduction, and extracellular polymeric substance (EPS) were 38%, 4800 mg/L (increased from 935 mg/L), 33%, and 218 mg/L, respectively. Following AD, the volatile solids (VS) removal and chemical oxygen demand (COD) removal by EP were enhanced from 40.7% and 54.7% to 47.2% and 61.5%, respectively, at steady-state. The biogas produced from control and electrochemical pre-treated WAS were in the ranges of 0.12 to 0.17 and 0.2 to 0.24 m3/kg VSfed, respectively, and the volume of biogas produced was 44–67% over the control. Based on the results obtained, suitability of EP for WAS prior to AD was confirmed.
Green Innovation Strategy and Ambidextrous Green Innovation: The Mediating Effects of Green Supply Chain Integration
Authors: Sun Yongbo , Sun Hui
Published: April 2021

Although the importance of green innovation strategy has been recognized, in the existing literature the relationship between green innovation strategy and corporate competitive advantage, as well as the relationship between green innovation strategy and green innovation are still unclear. Based on the resource dependence theory, this paper proposes a mediation model to promote ambidextrous green innovation. The relationship between green innovation strategy and ambidextrous green innovation is discussed, and the mediating role of green supply chain integration is investigated. Based on the questionnaire data from manufacturing companies in three developed economic zones in China, a structural equation model is established to verify our hypotheses. The empirical results show that the green innovation strategy has a positive impact on both exploitative and exploratory green innovation, and the impact on exploratory green innovation is greater than that on exploitative green innovation. Green supply chain integration plays a partial intermediating role in green innovation strategy and ambidextrous green innovation. The implementation of green innovation requires not only internal cross-department integration, but also integration with external supply chain partners such as suppliers and customers. By emphasizing the importance of green innovation strategy in the context of sustainable development, this research helps provide effective strategic directions and required capacity structures for companies to successfully implement green innovation practices, and reduces the uncertainty of green innovation. This study expands previous studies and enriches existing green innovation research.
Biochar Tablets with and without Embedded Fertilizer on the Soil Chemical Characteristics and Nutrient Use Efficiency of Zea mays
Authors: Lee Yit Leng , Ahmed Osumanu Haruna , Wahid Samsuri Abdul , AB Aziz Zakry Fitri
Published: April 2021

Densification of ashy biochar into tablet can enhance the handling and conveyance efficiencies of biochar. It was hypothesized that fertilizer-embedded biochar tablets can slowly release embedded nutrients in synchrony with optimum nutrient uptake by crops. The objectives of this research were to determine the effects of biochar tablets with and without embedded fertilizer on soil chemical properties and nutrient use efficiency of Zea mays (sweet corn). The biochar tablet (BT) was produced by blending a biochar mixture with starch followed by densification using a single punch tablet press whereas the fertilizer embedded biochar tablet (BF) was prepared using the same procedure except that NPK fertilizer was added during blending. A pot experiment with five fertilization treatments including control was carried out in an open field located in Perlis, Malaysia. Co-application of biochar and fertilizer increased soil total carbon, nitrogen, but it reduced soil electrical conductivity (EC). Additionally, the BF significantly increased leaf chlorophyll content, dry root weight, and total plant nutrient use efficiency of sweet corn. The findings suggest that BF can serve as a slow release fertilizer to improve crop nutrient use efficiency. Therefore, embedding fertilizer in biochar tablets is recommended for sweet corn production following a long term field study to confirm the findings of this pot study.
Business Analytics for Managing Performance of Microfinance Institutions: A Flexible Management of the Implementation Process
Authors: Piot-Lepetit Isabelle , Nzongang Joseph
Published: April 2021

Microfinance institutions are social enterprises that focus on the provision of financial services to poor populations excluded from the conventional banking system. These organizations face a double-bottom line, dealing simultaneously with a financial and social objective. The challenge of putting it into action is great, especially when there is a need to involve all stakeholders and to replicate the experience to new communities. One way to sustain both financial performance and social impacts is to develop a business analytics solution aiming at measuring and expanding social impacts in a financially sustainable way. This paper describes main elements to be considered, in particular the organizational context, the development process, and implementation issues that would facilitate or impede the deployment of a business analytics initiative in practice. Finally, two main components of the implementation process are specifically pointed out: a behavioral fit of the business analytics solution to the cultural context of the organization, and the country where it is deployed, and a flexible commitment in the management of the business analytics initiative implementation.
Current Progress and Future Prospects of Agriculture Technology: Gateway to Sustainable Agriculture
Authors: Khan Nawab , Ray Ram L. , Sargani Ghulam Raza , Ihtisham Muhammad , Khayyam Muhammad , Ismail Sohaib
Published: April 2021

The agricultural industry is getting more data-centric and requires precise, more advanced data and technologies than before, despite being familiar with agricultural processes. The agriculture industry is being advanced by various information and advanced communication technologies, such as the Internet of Things (IoT). The rapid emergence of these advanced technologies has restructured almost all other industries, as well as advanced agriculture, which has shifted the industry from a statistical approach to a quantitative one. This radical change has shaken existing farming techniques and produced the latest prospects in a series of challenges. This comprehensive review article enlightens the potential of the IoT in the advancement of agriculture and the challenges faced when combining these advanced technologies with conventional agricultural systems. A brief analysis of these advanced technologies with sensors is presented in advanced agricultural applications. Numerous sensors that can be implemented for specific agricultural practices require best management practices (e.g., land preparation, irrigation systems, insect, and disease management). This review includes the integration of all suitable techniques, from sowing to harvesting, packaging, transportation, and advanced technologies available for farmers throughout the cropping system. Besides, this review article highlights the utilization of other tools such as unmanned aerial vehicles (UAVs) for crop monitoring and other beneficiary measures, such as optimizing crop yields. In addition, advanced programs based on the IoT are also discussed. Finally, based on our comprehensive review, we identified advanced prospects regarding the IoT, which are essential tools for sustainable agriculture.
Comprehensive Life Cycle Environmental Assessment of Preventive Maintenance Techniques for Asphalt Pavement
Authors: Zheng Mulian , Chen Wang , Ding Xiaoyan , Zhang Wenwu , Yu Sixin
Published: April 2021

Preventive maintenance (PM) is regarded as the most economical maintenance strategy for asphalt pavement, but the life cycle environmental impacts (LCEI) of different PM techniques have not yet been comprehensively assessed and compared, thus hindering sustainable PM planning. This study aims to comprehensively estimate and compared the LCEI of five PM techniques then propose measures to reduce environmental impacts in PM design by using life cycle assessment (LCA), including fog seal with sand, micro-surfacing, composite seal, ultra-thin asphalt overlay, and thin asphalt overlay. Afterwards, ten kinds of LCEI categories and energy consumption of PM techniques were compared from the LCA phases, and inventory inputs perspectives, respectively. Results show that fog seal with sand and micro-surfacing can lower all LCEI scores by more than 50%. The environmental performance of five PM techniques provided by sensitivity analysis indicated that service life may not create significant impact on LCA results to some extent. Moreover, four PM combination plans were developed and compared for environmental performance, and results show that the PM plan only includes seal coat techniques that can reduce the total LCEI by 7–29% in pavement life. Increasing the frequency of seal coat techniques can make the PM plans more sustainable.
A Simulation Model for Forecasting COVID-19 Pandemic Spread: Analytical Results Based on the Current Saudi COVID-19 Data
Authors: Hassanat Ahmad B. , Mnasri Sami , Aseeri Mohammed A. , Alhazmi Khaled , Cheikhrouhou Omar , Altarawneh Ghada , Alrashidi Malek , Tarawneh Ahmad S. , Almohammadi Khalid S. , Almoamari Hani
Published: April 2021

The coronavirus pandemic (COVID-19) spreads worldwide during the first half of 2020. As is the case for all countries, the Kingdom of Saudi Arabia (KSA), where the number of reported cases reached more than 392 K in the first week of April 2021, was heavily affected by this pandemic. In this study, we introduce a new simulation model to examine the pandemic evolution in two major cities in KSA, namely, Riyadh (the capital city) and Jeddah (the second-largest city). Consequently, this study estimates and predicts the number of cases infected with COVID-19 in the upcoming months. The major advantage of this model is that it is based on real data for KSA, which makes it more realistic. Furthermore, this paper examines the parameters used to understand better and more accurately predict the shape of the infection curve, particularly in KSA. The obtained results show the importance of several parameters in reducing the pandemic spread: the infection rate, the social distance, and the walking distance of individuals. Through this work, we try to raise the awareness of the public and officials about the seriousness of future pandemic waves. In addition, we analyze the current data of the infected cases in KSA using a novel Gaussian curve fitting method. The results show that the expected pandemic curve is flattening, which is recorded in real data of infection. We also propose a new method to predict the new cases. The experimental results on KSA’s updated cases reveal that the proposed method outperforms some current prediction techniques, and therefore, it is more efficient in fighting possible future pandemics.
Sustainable Building Legislation and Incentives in Korea: A Case-Study-Based Comparison of Building New and Renovation
Authors: Amoruso Fabrizio M. , Sonn Min-Hee , Chu Soyeon , Schuetze Thorsten
Published: April 2021

More than one quarter of buildings in the Republic of Korea (RoK) are aged, approaching the end of their projected lifetimes, and require renovation. Aged buildings in the RoK are generally demolished, and new buildings with higher gross floor areas are realized on the same properties. That kind of redevelopment is associated with increased resource consumption, related greenhouse gas emissions, and other environmental impacts, as well as the generation of construction waste and the displacement of existing building tenants. This study analyzes the legislative framework for sustainable building in the RoK. Legally mandated basic standards for new buildings and renovation were analyzed, and differences were identified. Calculation methods and criteria for sustainable building incentives were determined. Incentive calculation methods were applied to three case-study buildings, which represented the three most common building types in Korea. Maximum building height, floor-to-area and building coverage ratios, and fiscal incentives for energy-efficient technical systems were quantified for new buildings and renovations. The findings identified the current legislative privileges for new buildings. To increase future sustainable building renovations, the criteria and tools for improving the existing legal framework, and economic feasibility, were identified and discussed.
A Review of Technological Solutions to Prevent or Reduce Marine Plastic Litter in Developing Countries
Authors: Winterstetter Andrea , Grodent Marie , Kini Venkatesh , Ragaert Kim , Vrancken Karl C.
Published: April 2021

Growing global plastic production combined with poor waste collection has led to increasing amounts of plastic debris being found in oceans, rivers and on shores. The goal of this study is to provide an overview on currently available technological solutions to tackle marine plastic litter and to assess their potential use in developing countries. To compile an inventory of technological solutions, a dedicated online platform was developed. A total of 51 out of initially 75 submitted solutions along the plastics value chain were assessed by independent experts. Collection systems represent more than half of the shortlisted solutions. A quarter include processing and treatment technologies, either as a stand-alone solution (30%) or, more commonly, in combination with a first litter capturing step. Ten percent offer digital solutions. The rest focuses on integrated waste management solutions. For each stage in the source-to-sea spectrum—land, rivers, sea—two illustrative examples are described in detail. This study concludes that the most cost-effective type of solution tackles land-based sources of marine litter and combines technology with people-oriented practices, runs on own energy sources, connects throughout the plastics value chain with a convincing valorization plan for captured debris, and involves all relevant stakeholders.
Carbon Price Forecasting Based on Improved CEEMDAN and Extreme Learning Machine Optimized by Sparrow Search Algorithm
Authors: Zhou Jianguo , Chen Dongfeng
Published: April 2021

Effective carbon pricing policies have become an effective tool for many countries to encourage emission reduction. An accurate carbon price prediction model is helpful for the implementation of energy conservation and emission reduction policies and the decision-making of governments and investors. However, it is difficult for a single prediction model to achieve high prediction accuracy because of the high complexity of the carbon price series. Many studies have proved the nonlinear characteristics of carbon trading prices, but there are very few studies on the chaotic nature of carbon price series. As a consequence, this paper proposes an innovative hybrid model for carbon price prediction. A decomposition-reconstruction-prediction-integration scheme is designed to predict carbon prices. Firstly, several intrinsic mode functions (IMFs) and one residue were obtained from the raw data decomposed by ICEEMDAN. Next, the decomposed subsection is reconstructed into a new sequence according to the calculation results by the Lempel-Ziv complexity algorithm. Then, considering the chaotic characteristics of sequence, the input variables of the models are determined through the phase space reconstruction (PSR) algorithm combined with the partial autocorrelation function (PACF). Finally, the Sparrow search algorithm (SSA) is introduced to optimize the extreme learning machine (ELM) model, which is applied in the carbon price prediction for the purpose of verifying the validity of the proposed combination model, which is applied to the pilots of Hubei, Beijing, and Guangdong. The empirical results show that the combination model outperformed the 13 other models in predicting accuracy, speed, and stability. The decomposition-reconstruction-prediction-integration strategy is a method for predicting the carbon price efficiently.