bluuebunny/crossref_metadata_2025 huggingface dataset:
Modeling Non-Cooperative Water Use in River Basins
Authors: Woldeyohanes Tesfaye , Kuhn Arnim , Heckelei Thomas , Duguma Lalisa
Published: July 2021

Conventional water use and management models have mostly emulated purposefully designed water use systems where centralized governance and rule-based cooperation of agents are assumed. However, water use systems, whether actively governed or not, involve multiple, independent decision makers with diverse and often conflicting interests. In the absence of adequate water management institutions to effectively coordinate decision processes on water use, water users’ behaviors are rather likely to be non-cooperative, meaning that actions by individual users generate externalities and lead to sub-optimal water use efficiency. The objective of this review is to evaluate the advantages and disadvantages of recently proposed modeling systems dealing with non-cooperative water use regarding their ability to realistically represent the features of complex hydrological and socioeconomic processes and their tractability in terms of modeling tools and computational efficiency. For that purpose, we conducted a systematic review of 47 studies that address non-cooperative water use in decentralized modeling approaches. Even though such a decentralized approach should aim to model decisions by individual water users in non-cooperative water use, we find that most studies assumed the presence of a coordinating agency or market in their model. It also turns out that most of these models employed a solution procedure that sequentially solved independent economic decisions based on pre-defined conditions and heuristics, while only few modeling approaches offered simultaneous solution algorithms. We argue that this approach cannot adequately capture economic trade-offs in resource allocation, in contrast to models with simultaneous solution procedures.
Single-Manufacturer Multi-Retailer Supply Chain Models with Discrete Stochastic Demand
Authors: Xu Yaqing , Zhang Jiang , Chen Zihao , Wei Yihua
Published: July 2021

Although there are highly discrete stochastic demands in practical supply chain problems, they are seldom considered in the research on supply chain systems, especially the single-manufacturer multi-retailer supply chain systems. There are no significant differences between continuous and discrete demand supply chain models, but the solutions for discrete random demand models are more challenging and difficult. This paper studies a supply chain system of a single manufacturer and multiple retailers with discrete stochastic demands. Each retailer faces a random discrete demand, and the manufacturer utilizes different wholesale prices to influence each retailer’s ordering decision. Both Make-To-Order and Make-To-Stock scenarios are considered. For each scenario, the corresponding Stackelberg game model is constructed respectively. By proving a series of theorems, we transfer the solution of the game model into non-linear integer programming model, which can be easily solved by a dynamic programming method. However, with the increase in the number of retailers and the production capacity of manufacturers, the computational complexity of dynamic programming drastically increases due to the Dimension Barrier. Therefore, the Fast Fourier Transform (FFT) approach is introduced, which significantly reduces the computational complexity of solving the supply chain model.
Organizational Agility in Industry 4.0: A Systematic Literature Review
Authors: Mrugalska Beata , Ahmed Junaid
Published: July 2021

Agility is the dynamic capability of an organization which helps it to manage a change and uncertainties in the environment. The purpose of this research is to review the literature from the perspective of agility in Industry 4.0. This paper systematically reviews 381 relevant articles from peer-reviewed academic journals in the period of the last five years. The results show that agility is important for an organization to adopt Industry 4.0 technologies as it helps companies to cope with the changes that arise along with the adoption of Industry 4.0 technologies. Further, it also indicates that by adopting Industry 4.0 technologies, companies can significantly enhance their agility capability into various aspects with different technologies. The technologies which enhance the agility are: smart manufacturing, internet of things, cyber-physical system, big data and analytics and cloud computing. On the other hand, important aspects of agility include supply chain, workforce, information system, facilities, management, manufacturing and technology agility.
Method of Assessing Bus Stops Safety Based on Three Groups of Criteria
Authors: Tubis Agnieszka A. , Skupień Emilia T. , Rydlewski Mateusz
Published: July 2021

Bus stops are an essential element of the public transport system and affect its users’ safety level. They are where the passengers gather who want to use bus transport, and where vehicles stop to exchange passenger flows. Most studies devoted to assessing bus stops’ safety focus on two evaluation methods: (1) statistical analysis of traffic crash data and (2) traffic conflict analysis. However, there is a need to develop a methodology to define priorities and scope for the improvement of increasing bus stops’ safety. For this reason, the aim of the article is to present a method of assessing bus stops’ safety, which is dedicated to the process of auditing and designing point infrastructure in the city. The use of the proposed method of evaluating bus stops is aimed not only at determining the current status, but above all at assigning priorities to actions aimed at increasing safety and improving the quality of life of residents. The article presents in detail the algorithm of the research procedure consisting of the proposed method and its implementation for the evaluation of stops in a selected city. In total, 151 bus stops serving all fast lines in the studied agglomeration were assessed. As part of the results, the ratings obtained by individual stops were presented. The level of fulfilment of individual evaluation criteria, divided into conducted classification procedures, was also analysed. The implementation of the method in the real system allowed us to assess the correctness of the procedure and the usefulness of the obtained results. The obtained results of the evaluation of bus stops and the fulfilment of individual criteria should constitute the basis for the created schedules of the required ongoing works related to the improvement of public transport passenger safety, but also the creation of long-term plans related to the improvement of the bus stop infrastructure and its adaptation to changing safety requirements and passengers’ expectations.
Collaborations in Environmental Initiatives for an Effective “Adaptive Governance” of Social–Ecological Systems: What Existing Literature Suggests
Authors: Andriollo Elena , Caimo Alberto , Secco Laura , Pisani Elena
Published: July 2021

Moving from the scientific literature on the evaluation of environmental projects and programs, this study identifies how and under which conditions collaborations in environmentally sustainable projects are considered effective for the adaptive governance of SES. The method adopted is a systematic literature review based on the quantitative and qualitative analysis of 56 articles selected through specific queries on the SCOPUS database and published from 2004 to 2020. Results of the quantitative analysis identify conditions able to evaluate collaborations, highlighting the need to adopt a transdisciplinary approach analysing both social and ecological challenges and assessing both social and ecological results. Moreover, they suggest preferring using primary data involving multi-sector and multi-scale actors and enlarging the geographical context to the most vulnerable countries. The results of the qualitative analysis provide specific recommendations for collaborations being effective when related to communication, equity, foresight, and respect, which need to be further strengthened by all actors. Multiplicity in visions and approaches should be seen as a resource able to stimulate creativity in social arrangements and environmental practices, making collaborations in environmental projects instrumental for the effectiveness of adaptive governance of SES.
Spatial and Temporal Spread of the COVID-19 Pandemic Using Self Organizing Neural Networks and a Fuzzy Fractal Approach
Authors: Melin Patricia , Castillo Oscar
Published: July 2021

In this article, the evolution in both space and time of the COVID-19 pandemic is studied by utilizing a neural network with a self-organizing nature for the spatial analysis of data, and a fuzzy fractal method for capturing the temporal trends of the time series of the countries considered in this study. Self-organizing neural networks possess the capability to cluster countries in the space domain based on their similar characteristics, with respect to their COVID-19 cases. This form enables the finding of countries that have a similar behavior, and thus can benefit from utilizing the same methods in fighting the virus propagation. In order to validate the approach, publicly available datasets of COVID-19 cases worldwide have been used. In addition, a fuzzy fractal approach is utilized for the temporal analysis of the time series of the countries considered in this study. Then, a hybrid combination, using fuzzy rules, of both the self-organizing maps and the fuzzy fractal approach is proposed for efficient coronavirus disease 2019 (COVID-19) forecasting of the countries. Relevant conclusions have emerged from this study that may be of great help in putting forward the best possible strategies in fighting the virus pandemic. Many of the existing works concerned with COVID-19 look at the problem mostly from a temporal viewpoint, which is of course relevant, but we strongly believe that the combination of both aspects of the problem is relevant for improving the forecasting ability. The main idea of this article is combining neural networks with a self-organizing nature for clustering countries with a high similarity and the fuzzy fractal approach for being able to forecast the times series. Simulation results of COVID-19 data from countries around the world show the ability of the proposed approach to first spatially cluster the countries and then to accurately predict in time the COVID-19 data for different countries with a fuzzy fractal approach.
Stacking Ensemble Tree Models to Predict Energy Performance in Residential Buildings
Authors: Mohammed Ahmed Salih , Asteris Panagiotis G. , Koopialipoor Mohammadreza , Alexakis Dimitrios E. , Lemonis Minas E. , Armaghani Danial Jahed
Published: July 2021

In this research, a new machine-learning approach was proposed to evaluate the effects of eight input parameters (surface area, relative compactness, wall area, overall height, roof area, orientation, glazing area distribution, and glazing area) on two output parameters, namely, heating load (HL) and cooling load (CL), of the residential buildings. The association strength of each input parameter with each output was systematically investigated using a variety of basic statistical analysis tools to identify the most effective and important input variables. Then, different combinations of data were designed using the intelligent systems, and the best combination was selected, which included the most optimal input data for the development of stacking models. After that, various machine learning models, i.e., XGBoost, random forest, classification and regression tree, and M5 tree model, were applied and developed to predict HL and CL values of the energy performance of buildings. The mentioned techniques were also used as base techniques in the forms of stacking models. As a result, the XGboost-based model achieved a higher accuracy level (HL: coefficient of determination, R2 = 0.998; CL: R2 = 0.971) with a lower system error (HL: root mean square error, RMSE = 0.461; CL: RMSE = 1.607) than the other developed models in predicting both HL and CL values. Using new stacking-based techniques, this research was able to provide alternative solutions for predicting HL and CL parameters with appropriate accuracy and runtime.
The Influence of Media Usage on Iranian Students’ Pro-Environmental Behaviors: An Application of the Extended Theory of Planned Behavior
Authors: Karimi Saeid , Liobikienė Genovaitė , Saadi Heshmatollah , Sepahvand Fatemeh
Published: July 2021

The current study attempted to understand factors influencing students’ pro-environmental intentions and behaviors in a developing nation, namely Iran. To do so, a theoretical research model was established by adding media use and environmental knowledge into the theory of planned behavior (TPB). Data were collected using a self-administered questionnaire survey from a sample of 327 Iranian students and analyzed with the help of partial least squares structural equation modeling (PLS-SEM). The results supported the applicability of including additional constructs in the TPB, as it has improved the predictive utility of the proposed model. The results indicated that perceived behavioral control, subjective norms, and environmental knowledge were positively associated with pro-environmental intentions. Furthermore, pro-environmental intentions, perceived behavioral control, and environmental knowledge were related to pro-environmental behaviors. Perceived behavioral control and environmental knowledge were also indirectly related to pro-environmental behaviors through pro-environmental intentions. Notably, media use was directly related to pro-environmental behaviors and indirectly related to pro-environmental intentions through perceived behavioral control and environmental knowledge. The theoretical and practical implications of the findings are highlighted.
Indoor Air Quality and Human Health Risk Assessment in the Open-Air Classroom
Authors: Kaewrat Jenjira , Janta Rungruang , Sichum Surasak , Kanabkaew Thongchai
Published: July 2021

Indoor air quality is associated with academic performance and harmful health effects on students and teachers who participate in the classroom. Outdoor sources always contribute to classroom air quality. This study aims to estimate the amounts of indoor and outdoor pollutants and the influence of outdoor sources on open-air classrooms in a school located in the city. A health risk assessment was applied to assess the non-carcinogenic risk to students and teachers from exposure to the pollutants in the classroom. The concentrations of indoor NO2 ranged between 46.40 and 77.83 µg/m3, which is about 0.8 times that of outdoor NO2. A strong correlation and a high indoor/outdoor (I/O) ratio (>0.5) without a source, indicated that indoor NO2 is significantly influenced by outdoor sources. The range of indoor PM2.5 concentrations was 1.66 to 31.52 µg/m3 which was influenced by meteorological conditions. The indoor PM2.5 concentrations were affected by both indoor and outdoor sources. Although the level of indoor air pollutants met the official standard, the young children were exposed to indoor air pollutants which were above the recommended limits to human health with regard to the hazard index (HI) of 1.12. Instant measures such as regularly cleaning the classrooms, zoning the students, and installation of solid and vegetation barriers are recommended to reduce the daily dose of pollutants affecting students in open-air classrooms.
Spatial Heterogeneity of Factors Influencing CO2 Emissions in China’s High-Energy-Intensive Industries
Authors: Yang Shijie , Wang Yunjia , Han Rongqing , Chang Yong , Sun Xihua
Published: July 2021

In recent years, China has overtaken the United States as the world’s largest carbon dioxide (CO2) emitter. CO2 emissions from high-energy-intensive industries account for more than three-quarters of the total industrial carbon dioxide emissions. Therefore, it is important to enhance our understanding of the main factors affecting carbon dioxide emissions in high-energy-intensive industries. In this paper, we firstly explore the main factors affecting CO2 emissions in high-energy-intensive industries, including industrial structure, per capita gross domestic product (GDP), population, technological progress and foreign direct investment. To achieve this, we rely on exploratory regression combined with the threshold criteria. Secondly, a geographically weighted regression model is employed to explore local-spatial heterogeneity, capturing the spatial variations of the regression parameters across the Chinese provinces. The results show that the growth of per capita GDP and population increases CO2 emissions; by contrast, the growth of the services sector’s share in China’s gross domestic product could cause a decrease in CO2 emissions. Effects of technological progress on CO2 emissions in high-energy-intensive industries are negative in 2007 and 2013, whereas the coefficient is positive in 2018. Throughout the study period, regression coefficients of foreign direct investment are positive. This paper provides valuable insights into the relationship between driving factors and CO2 emissions, and also gives provides empirical support for local governments to mitigate CO2 emissions.
The Demerger Impact upon Sustainable Development of Economic Entities: Evidence from Romania
Authors: Baba Camelia Mirela , Duguleană Constantin , Dincă Marius Sorin , Duguleană Liliana , Dincă Gheorghița
Published: July 2021

The Covid-19 induced economic crisis has significantly affected almost all businesses from nearly every sector, causing severe financial problems, lack of cash assets, and decrease of revenues. In this context, the economic entities were forced to look for adjustment and rescue solutions of their activities. One possible solution for the recovery and reorganization of economic entities’ activities is demerger. This paper evaluates the impact of demerger upon the sustainable development of economic entities in terms of economic efficiency and financial performances. To achieve this goal, a statistical analysis of profitability ratios before and after the demerger, as well as a structural analysis of 268 demerger projects for the April 2012–April 2021 period, were performed. The results attest there are no significant differences between the ex-ante and ex-post financial performances. However, demerger seems to have a positive effect upon analyzed companies helping them to overcome economic hardships, rethink their business strategies, and continue their activity in the medium and long-term time horizon.
Sustainability of Regional Agroecological Economic System Based on Emergy Theory: A Case Study of Anhui Province, China
Authors: Wu Xue , Yang Yaliu , Liu Conghu , Xu Guowei , Guo Yuxia , Liu Fan , Wang Yuan
Published: July 2021

The agroecological economic system is the basic system on which human beings depend for survival. In order to better evaluate the operation status of a regional agroecological economic system and deepen the cognition of the input and output of the regional agroecological economic system from the angle of emergy, the evaluation method of sustainable development of the regional agroecological economic system with comprehensive consideration of resources, economy, and environment was proposed by constructing a unified dimensional measurement model. This paper analyzed and evaluated the data of the agroecological economic system in Anhui Province from 2010 to 2019. The results showed that the agroecological economic system in Anhui Province bore less environmental pressure and gradually decreased, and had a good system efficiency and economic benefits. The average emergy sustainability index (ESI) was 3.12, indicating that the agroecological economic system in Anhui Province had certain vitality of sustainable development. Based on this, the paper puts forward some suggestions on sustainable and high-quality agricultural development in Anhui Province, which provides theoretical and methodical support for sustainable development of a regional agricultural economy.
Climate Change and Water Dynamics in Rural Uganda
Authors: McKinney Laura , Wright Devin C.
Published: July 2021

The purpose of this case study is to examine the effects of climate change on agricultural life in rural Uganda. Based on primary data, the authors examine major themes related to climate change and disasters as conveyed by individuals in a small agricultural region in Eastern Uganda. Specifically, we focus on the effects of living in constant threat of flooding and landslides. Results show that water is a major source of loss for most people, ranging from crop loss to contaminated water. Findings also point to the chronic nature of dealing with water issues, as opposed to acute. Further, our results indicate that disasters are a great equalizer among affected populations, with only neighbors to depend on in the aftermath.
Participatory Management to Improve Accessibility in Consolidated Urban Environments
Authors: Pérez-delHoyo Raquel , Andújar-Montoya María Dolores , Mora Higinio , Gilart-Iglesias Virgilio , Mollá-Sirvent Rafael Alejandro
Published: July 2021

There is a wide range of regulations on universal accessibility, but our cities are still inaccessible in many cases. Most accessibility problems in cities occur in consolidated areas that were developed prior to the development of current accessibility regulations. This leads to consider the importance of focusing more effort on managing the improvement of the accessibility of existing public urban environments. As such, the objective of this research is to design a conceptual model for accessibility management in consolidated urban environments. Unlike other research focusing on city users to collect information on accessibility problems or to provide services to improve wayfinding, this method has a focus on urban accessibility managers. The model is based on the assessment of the level of accessibility of urban environments together with the assessment of management processes in which city users are actively involved. It consists of a set of basic indicators for the identification of accessible pedestrian routes, and provides a dynamic accessibility index for the evaluation of their efficient management by the responsible governments. The inclusion of this assessment framework in the management process itself enables the necessary improvement actions to be identified and taken in time. ICT (Information and Communication Technologies) provide the communication channel between the responsible governments and city users, making this a more dynamic and efficient management model based on assessment possible.
Evaluation of Critical Limit of Sulphur in Soils for Wheat (Triticum aestivum L.) and Mustard (Brassica napus L.)
Authors: Yesmin Rubina , Hossain Mahmud , Kibria Mohammad Golam , Jahiruddin Mohammad , Solaiman Zakaria M. , Bokhtiar Shaikh Mohammad , Hossain Md Baktear , Satter Md Abdus , Abedin Md Anwarul
Published: July 2021

The conception of critical limit (CL) of a nutrient element distinguishes its deficiency from sufficiency, which could advise fertilizer application. A pot culture experiment was conducted during Rabi season (2019–2020) to study the CL of sulphur (S) in soil and plant. A total of 20 soil samples collected from intensive cropping areas of three agroecological zones (AEZs) of Bangladesh were used in the experiment. The 0.15% CaCl2 extractable S (expressed as available S) contents of the test soils ranged from 6.84 mg/kg to 38 mg/kg. Wheat (Triticum aestivum L.) cv. BARI gom 30 and mustard (Brassica napus L.) cv. BINA sorisha 9 were used as test crops in this study. There were two rates of S application to soil-0 and 15 mg/kg for wheat and 0 and 18 mg/kg for mustard from gypsum (CaSO4.2H2O). Each S treatment was replicated thrice. Dry matter yield, S content and S uptake by the crops increased with added S. For mustard, the CL of soil S was estimated to be 14 mg/kg by graphical procedure and 11 mg/kg in statistical method while plant tissue concentration showed the CL of 0.35% in both methods. The CL of soil S for wheat was found to be 14 mg/kg and 11 mg/kg in graphical and statistical methods, respectively, and the CL of plant tissue concentration was recorded as 0.14%, in both methods. It is expected that mustard and wheat crops would respond to S fertilization in soils containing S at or below the CL. The results would be useful for predicting crop (wheat and mustard) response to S fertilizer and developing efficient S fertilizer management to promote sustainable crop production.
Effects of Evocative Audio-Visual Installations on the Restorativeness in Urban Parks
Authors: Masullo Massimiliano , Maffei Luigi , Pascale Aniello , Senese Vincenzo Paolo , De Stefano Simona , Chau Chi Kwan
Published: July 2021

Road traffic noise is responsible for several negative health effects for citizens in modern cities. Inside urban parks, which citizens use for social inclusion and cohesion, psychological and physical restoration, and physical activities, road traffic noise may significantly reduce the potential of these places to induce or enhance well-being. Although access restriction schemes and screens could be effective solutions to limit noise inside urban park areas, preserving their potential regenerative role may engender mobility, social, aesthetic, and architectural issues. Due to the positive effects that natural elements and water sounds can have on human perception, and based on the previous findings of the beneficial effects of audio-visual installations, this paper investigates the possibility of using audio-visual installations that simply evoke some natural features to improve the restoration of individuals inside urban parks. The study has been carried out using immersive virtual environments in two different experimental laboratory sessions in Hong Kong (China) and Aversa (Italy). The results showed that the positive effects provided by evocative installations were similar to those provided by traditional installations. Furthermore, the effects on the restoration increased as the installations became larger and included enveloping shapes. Furthermore, we found that the amount of evocative water installations’ material was responsible for changes in restoration. In contrast, the Chinese groups were less influenced by these installations.
Spatial Effects of Urban-Rural Ditch Connectivity Gradient Changes on Water Quality to Support Ditch Optimization and Management
Authors: Qiu Chunqi , Li Yufeng , Wright Alan L. , Wang Cheng , Xu Jiayi , Zhou Shiwei , Huang Wanchun , Wu Yanhui , Zhang Yinglei , Liu Hongyu
Published: July 2021

Ditch networks play crucial roles in regulating water fluxes with their surroundings. The connectivity of ditches can have great impacts on nutrient migration and transformations. However, connectivity patterns related to ditch networks have rarely been studied, especially the relationships with water quality assessed through spatial analysis. This paper considered ditch connectivity and water quality indicators comprehensively, using spatial autocorrelation and geographically weighted regression (GWR) models, to analyze the impact of ditch connectivity on water quality from urban to rural gradients. The results suggested that water quality in rural areas and towns was better than in suburbs and transition zones, and the different areas exhibited variable spatial ditch connectivity. The Moran’s I index of the connectivity indicators showed the clustering state of spatial distribution, with ditch connectivity explaining 61.06% of changes in water quality. The circularity and network connectivity of the ditches had the most influence on water quality. However, the degree of influence varied with region. Circularity had the greatest impact on water quality in urban areas, and network connectivity had the greatest impact on water quality in township areas. Therefore, future water improvement projects, based on ditch optimization and management, need to consider the more related influencing factors and their spatial differences.
The Quality Control System of Green Composite Wind Turbine Blade Supply Chain Based on Blockchain Technology
Authors: Yu Hang , Zhu Senlai , Yang Jie
Published: July 2021

Nowadays, blockchain technology is expected to promote the quality control of traditional industry due to its traceability, transparency and non-tampering characteristics. Although blockchain could offer the traditional industry new energy, there are still some predictable difficulties in the early stage of its application, such as the structure of the blockchain-based system, the role of regulators in the system and high transaction fee by block packing. In this paper, we establish a pioneering quality control system for the green composite wind turbine blade supply chain based on blockchain technology. Firstly, the framework of this system is proposed to ensure that the quality of the product could not only be examined and verified by regulator, but also be monitored by other related nodes. Next, we develop a new way to store the data by hash fingerprint and the cost of transaction fees is significantly reduced in the case of a large amount of data. Then, the information on-chain method is developed to realize the data traceability of each node. At last, the tests of this system are carried out to prove its validity, the satisfactory results are obtained and information supervision and sharing role of the regulators are discussed.
Sustainable Consumer Behavior in Purchasing, Using and Disposing of Clothes
Authors: Soyer Mirella , Dittrich Koen
Published: July 2021

In this study we investigate how consumers in The Netherlands can be persuaded to adopt sustainable practices when purchasing, using and disposing of clothes. This study investigates the attitude-behavior gap for the sustainable choices for purchase, use and disposing of clothes. For each consumption phase we ran a two-step multiple regression. The findings showed that the importance of the factors vary in the three consumption phases. For purchasing and disposal decisions, the core motivator social motivation predicts sustainable practices best, while it has no role in the usage phase. The factor ability appeared to have a significant role in the disposal phase, but not in the other phases. Finally, the trigger appears to lower the consumers’ ability in the purchasing phase, while it enhances the core motivator social evaluation in the disposal phase.
Integrated Water Resource Management: Rethinking the Contribution of Rainwater Harvesting
Authors: Huang Zhe , Nya Esther Laurentine , Rahman Mohammad Azizur , Mwamila Tulinave Burton , Cao Viet , Gwenzi Willis , Noubactep Chicgoua
Published: July 2021

Rainwater harvesting (RWH) is generally perceived as a promising cost-effective alternative water resource for potable and non-potable uses (water augmentation) and for reducing flood risks. The performance of RWH systems has been evaluated for various purposes over the past few decades. These systems certainly provide economic, environmental, and technological benefits of water uses. However, regarding RWH just as an effective alternative water supply to deal with the water scarcity is a mistake. The present communication advocates for a systematic RWH and partial infiltration wherever and whenever rain falls. By doing so, the detrimental effects of flooding are reduced, groundwater is recharged, water for agriculture and livestock is stored, and conventional water sources are saved. In other words, RWH should be at the heart of water management worldwide. The realization of this goal is easy even under low-resource situations, as infiltration pits and small dams can be constructed with local skills and materials.
Students’ Preference Analysis on Online Learning Attributes in Industrial Engineering Education during the COVID-19 Pandemic: A Conjoint Analysis Approach for Sustainable Industrial Engineers
Authors: Ong Ardvin Kester S. , Prasetyo Yogi Tri , Young Michael Nayat , Diaz John Francis T. , Chuenyindee Thanatorn , Kusonwattana Poonyawat , Yuduang Nattakit , Nadlifatin Reny , Redi Anak Agung Ngurah Perwira
Published: July 2021

The decline of enrollees for industrial engineering during the COVID-19 pandemic and the increasing demand for professional industrial engineers should be explored. The purpose of this study was to determine the preference of industrial engineering students of different educational levels on online learning during the COVID-19 pandemic. Specifically, this study utilized conjoint analysis with orthogonal design considering seven attributes: delivery type, layout, term style, final requirements, Coursera requirements, seatwork and practice sets, and platforms. Among the attributes, 20 stimuli were created through SPSS and were answered voluntarily by 126 respondents utilizing a 7-point Likert Scale. The respondents were comprised of 79 undergraduate, 30 fully online master’s degree, and 17 master’s and doctorate degree students collected through purposive sampling. One university from the two available universities that offer all educational levels of IE in the Philippines was considered. The results showed that undergraduate students considered the final requirements with multiple-choice as the highest preference, followed by non-modular term style, and no seatwork and practice sets. In addition, fully online master’s degree students considered delivery type with the mix as the highest preference, followed by layout, and no seatwork and practice sets. Finally, master’s and doctorate degree students considered final requirements with publication as the highest preference, followed by no seatwork and practice sets, and mix delivery type. The students are technologically inclined, want to learn at their own pace, know where and how to get additional online learning materials, but still need the guidance of teachers/professors. The results would help contribute to the theoretical foundation for further students’ preference segmentation, specifically on online learning during the COVID-19 pandemic worldwide. Moreover, the design created could be utilized for other courses in measuring students’ preference for online learning even after the COVID-19 pandemic.
A Factorial Ecological-Extended Physical Input-Output Model for Identifying Optimal Urban Solid Waste Path in Fujian Province, China
Authors: Liu Jing , Li Yongping , Huang Gordon , Yang Yujin , Wu Xiaojie
Published: July 2021

Effective management of an urban solid waste system (USWS) is crucial for balancing the tradeoff between economic development and environment protection. A factorial ecological-extended physical input-output model (FE-PIOM) was developed for identifying an optimal urban solid waste path in an USWS. The FE-PIOM integrates physical input-output model (PIOM), ecological network analysis (ENA), and fractional factorial analysis (FFA) into a general framework. The FE-PIOM can analyze waste production flows and ecological relationships among sectors, quantify key factor interactions on USWS performance, and finally provide a sound waste production control path. The FE-PIOM is applied to managing the USWS of Fujian Province in China. The major findings are: (i) waste is mainly generated from primary manufacturing (PM) and advanced manufacturing (AM), accounting for 30% and 38% of the total amount; (ii) AM is the biggest sector that controls the productions of other sectors (weight is from 35% to 50%); (iii) the USWS is mutualistic, where direct consumption coefficients of AM and PM are key factors that have negative effects on solid waste production intensity; (iv) the commodity consumption of AM and PM from other sectors, as well as economic activities of CON, TRA and OTH, should both decrease by 20%, which would be beneficial to the sustainability of the USWS.
Understanding the Impacts of the COVID-19 Pandemic on Public Transportation Travel Patterns in the City of Lisbon
Authors: Aparicio Joao T. , Arsenio Elisabete , Henriques Rui
Published: July 2021

The ongoing COVID-19 pandemic is creating disruptive changes in urban mobility that may compromise the sustainability of the public transportation system. As a result, worldwide cities face the need to integrate data from different transportation modes to dynamically respond to changing conditions. This article combines statistical views with machine learning advances to comprehensively explore changing urban mobility dynamics within multimodal public transportation systems from user trip records. In particular, we retrieve discriminative traffic patterns with order-preserving coherence to model disruptions to demand expectations across geographies and show their utility to describe changing mobility dynamics with strict guarantees of statistical significance, interpretability and actionability. This methodology is applied to comprehensively trace the changes to the urban mobility patterns in the Lisbon city brought by the current COVID-19 pandemic. To this end, we consider passenger trip data gathered from the three major public transportation modes: subway, bus, and tramways. The gathered results comprehensively reveal novel travel patterns within the city, such as imbalanced demand distribution towards the city peripheries, going far beyond simplistic localized changes to the magnitude of traffic demand. This work offers a novel methodological contribution with a solid statistical ground for the spatiotemporal assessment of actionable mobility changes and provides essential insights for other cities and public transport operators facing mobility challenges alike.
Valorisation of Organic Waste By-Products Using Black Soldier Fly (Hermetia illucens) as a Bio-Convertor
Authors: Magee Kieran , Halstead Joe , Small Richard , Young Iain
Published: July 2021

One third of food produced globally is wasted. Disposal of this waste is costly and is an example of poor resource management in the face of elevated environmental concerns and increasing food demand. Providing this waste as feedstock for black soldier fly (Hermetia illucens) larvae (BSFL) has the potential for bio-conversion and valorisation by production of useful feed materials and fertilisers. We raised BSFL under optimal conditions (28 °C and 70% relative humidity) on seven UK pre-consumer food waste-stream materials: fish trimmings, sugar-beet pulp, bakery waste, fruit and vegetable waste, cheese waste, fish feed waste and brewer’s grains and yeast. The nutritional quality of the resulting BSFL meals and frass fertiliser were then analysed. In all cases, the volume of waste was reduced (37–79%) and meals containing high quality protein and lipid sources (44.1 ± 4.57% and 35.4 ± 4.12%, respectively) and frass with an NPK of 4.9-2.6-1.7 were produced. This shows the potential value of BSFL as a bio-convertor for the effective management of food waste.
Different Object Functions for SWIPT Optimization by SADDE and APSO
Authors: Chien Wei , Chiu Chien-Ching , Chen Po-Hsiang , Cheng Yu-Ting , Lim Eng Hock , Liang Yue-Li , Wang Jia-Rui
Published: July 2021

Multiple objective function with beamforming techniques by algorithms have been studied for the Simultaneous Wireless Information and Power Transfer (SWIPT) technology at millimeter wave. Using the feed length to adjust the phase for different objects of SWIPT with Bit Error Rate (BER) and Harvesting Power (HP) are investigated in the broadband communication. Symmetrical antenna array is useful for omni bearing beamforming adjustment with multiple receivers. Self-Adaptive Dynamic Differential Evolution (SADDE) and Asynchronous Particle Swarm Optimization (APSO) are used to optimize the feed length of the antenna array. Two different object functions are proposed in the paper. The first one is the weighting factor multiplying the constraint BER and HP plus HP. The second one is the constraint BER multiplying HP. Simulations show that the first object function is capable of optimizing the total harvesting power under the BER constraint and APSO can quickly converges quicker than SADDE. However, the weighting for the final object function requires a pretest in advance, whereas the second object function does not need to set the weighting case by case and the searching is more efficient than the first one. From the numerical results, the proposed criterion can achieve the SWIPT requirement. Thus, we can use the novel proposed criterion (the second criterion) to optimize the SWIPT problem without testing the weighting case by case.
Numerical Investigation on the Formation and Penetration Behavior of Explosively Formed Projectile (EFP) with Variable Thickness Liner
Authors: Yang Dong , Lin Jiajian
Published: July 2021

Explosively formed projectiles (EFPs) are widely used in civil applications and the military field for their excellent impact performance. How to give full play to the energy accumulation effect of explosives and improve the penetration performance has become the main problem of EFP design. The aim of the present study was to investigate the effect of liner structure on EFP formation and its penetration behavior. In order to achieve this, a finite element (FE) model was first established on the basis of the Lagrange and ALE method. Then, formation and penetration performance tests of EFP were performed to verify the validity and feasibility of the proposed FE model, where the configuration, velocity of EFP, and penetration diameter left on the target plate were compared. Finally, by using the proposed FE model, the entire process of the formation and penetration behavior of EFP with axial symmetrical variable thickness liners were analyzed, where spherical-segment liners with uniform and non-uniform thickness were developed. The results were drawn as follows: the numerical simulation error of EFP velocity was less than 5%, and the simulated penetration diameter was compared to the 8.6% error obtained from the experimental method. It demonstrated that the proposed FE model had higher prediction precision. After the explosive was detonated, a forward-folding EFP was formed by the liner with a thin edge thickness, while the EFP formed by the liner with uniform thickness had a backward-folded configuration. It was also found that the liner with a thin edge thickness gave the largest steady velocity of EFP, and it was the lowest by using the liner with uniform thickness. There were two types of loads generated after the formation of an EFP, those were shock wave loading and an EFP, both causing damage in the target plate during the process of an EFP’s penetration into it. The shock wave induced by liners with non-uniform thickness caused higher damage in the target plate, the maximum value of stress was reached at about 4.0 GPa. The forward-folding EFP formed by the liner with the thinnest edge thickness had the largest penetration ability. The backward-folded EFP, owing to the hollow structure, had the worst penetration ability, which failed to penetrate the target plate.
A Multivariate Flexible Skew-Symmetric-Normal Distribution: Scale-Shape Mixtures and Parameter Estimation via Selection Representation
Authors: Mahdavi Abbas , Amirzadeh Vahid , Jamalizadeh Ahad , Lin Tsung-I
Published: July 2021

Multivariate skew-symmetric-normal (MSSN) distributions have been recognized as an appealing tool for modeling data with non-normal features such as asymmetry and heavy tails, rendering them suitable for applications in diverse areas. We introduce a richer class of MSSN distributions based on a scale-shape mixture of (multivariate) flexible skew-symmetric normal distributions, called the SSMFSSN distributions. This very general class of SSMFSSN distributions can capture various shapes of multimodality, skewness, and leptokurtic behavior in the data. We investigate some of its probabilistic characterizations and distributional properties which are useful for further methodological developments. An efficient EM-type algorithm designed under the selection mechanism is advocated to compute the maximum likelihood (ML) estimates of parameters. Simulation studies as well as applications to a real dataset are employed to illustrate the usefulness of the presented methods. Numerical results show the superiority of our proposed model in comparison to several existing competitors.
Neuromodulated Dopamine Plastic Networks for Heterogeneous Transfer Learning with Hebbian Principle
Authors: Magotra Arjun , Kim Juntae
Published: July 2021

The plastic modifications in synaptic connectivity is primarily from changes triggered by neuromodulated dopamine signals. These activities are controlled by neuromodulation, which is itself under the control of the brain. The subjective brain’s self-modifying abilities play an essential role in learning and adaptation. The artificial neural networks with neuromodulated plasticity are used to implement transfer learning in the image classification domain. In particular, this has application in image detection, image segmentation, and transfer of learning parameters with significant results. This paper proposes a novel approach to enhance transfer learning accuracy in a heterogeneous source and target, using the neuromodulation of the Hebbian learning principle, called NDHTL (Neuromodulated Dopamine Hebbian Transfer Learning). Neuromodulation of plasticity offers a powerful new technique with applications in training neural networks implementing asymmetric backpropagation using Hebbian principles in transfer learning motivated CNNs (Convolutional neural networks). Biologically motivated concomitant learning, where connected brain cells activate positively, enhances the synaptic connection strength between the network neurons. Using the NDHTL algorithm, the percentage of change of the plasticity between the neurons of the CNN layer is directly managed by the dopamine signal’s value. The discriminative nature of transfer learning fits well with the technique. The learned model’s connection weights must adapt to unseen target datasets with the least cost and effort in transfer learning. Using distinctive learning principles such as dopamine Hebbian learning in transfer learning for asymmetric gradient weights update is a novel approach. The paper emphasizes the NDHTL algorithmic technique as synaptic plasticity controlled by dopamine signals in transfer learning to classify images using source-target datasets. The standard transfer learning using gradient backpropagation is a symmetric framework. Experimental results using CIFAR-10 and CIFAR-100 datasets show that the proposed NDHTL algorithm can enhance transfer learning efficiency compared to existing methods.