bluuebunny/crossref_metadata_2025 huggingface dataset:
Combating Single-Frequency Jamming through a Multi-Frequency, Multi-Constellation Software Receiver: A Case Study for Maritime Navigation in the Gulf of Finland
Authors: Islam Saiful , Bhuiyan Mohammad Zahidul H. , Thombre Sarang , Kaasalainen Sanna
Published: March 2022

Today, a substantial portion of global trade is carried by sea. Consequently, the reliance on Global Navigation Satellite System (GNSS)-based navigation in the oceans and inland waterways has been rapidly growing. GNSS is vulnerable to various radio frequency interference. The objective of this research is to propose a resilient Multi-Frequency, Multi-Constellation (MFMC) receiver in the context of maritime navigation to identify any GNSS signal jamming incident and switch to a jamming-free signal immediately. With that goal in mind, the authors implemented a jamming event detector that can identify the start, end, and total duration of the detected jamming event on any of the impacted GNSS signal(s). By utilizing a jamming event detector, the proposed resilient MFMC receiver indeed provides a seamless positioning solution in the event of single-frequency jamming on either the lower or upper L-band. In addition, this manuscript also contains positioning performance analysis of GPS-L5-only, Galileo-E5a-only, and Galileo-E5b-only signals and their multi-GNSS combinations in a maritime operational environment in the Gulf of Finland. The positioning performance of lower L-band GNSS signals in a maritime environment has not been thoroughly investigated as per the authors’ knowledge.
A Hierarchical Blockchain-Assisted Conditional Privacy-Preserving Authentication Scheme for Vehicular Ad Hoc Networks
Authors: He Xingyu , Niu Xianhua , Wang Yangpeng , Xiong Ling , Jiang Zhizhong , Gong Cheng
Published: March 2022

Through information sharing, vehicles can know the surrounding road condition information timely in Vehicular Adhoc Networks. To ensure the validity of these messages and the security of vehicles, the message authentication, privacy-preserving, and delay problems are three important issues. Although many conditional privacy-preserving authentication schemes have been proposed to ensure secure communication, there still exist some imperfections such as frequent interactions or unlinkability. From this, our paper proposes a novel hierarchical blockchain-assisted authentication scheme to solve these existing issues comprehensively. First, unlinkability is achieved by a dynamic key derivation algorithm. Second, the proposed scheme can reduce correlation processing delay, queuing delay, and deployment costs by adopting hierarchical Vehicle Fog Computing. Third, cross-region authentication is achieved by taking advantage of the properties of blockchain. In addition, we demonstrate our scheme can fulfill the security criteria of the Vehicular Adhoc Network by security analysis. Furthermore, the simulations are carried out to show its availability by using JAVA and NS-3. The findings reveal that the suggested method outperforms earlier schemes in terms of computation cost and communication cost. All in all, making the authentication scheme more efficient and concise is the focus of our future research.
Digital Assessment and Classification of Wine Faults Using a Low-Cost Electronic Nose, Near-Infrared Spectroscopy and Machine Learning Modelling
Authors: Gonzalez Viejo Claudia , Fuentes Sigfredo
Published: March 2022

The winemaking industry can benefit greatly by implementing digital technologies to avoid guesswork and the development of off-flavors and aromas in the final wines. This research presents results on the implementation of near-infrared spectroscopy (NIR) and a low-cost electronic nose (e-nose) coupled with machine learning to detect and assess wine faults. For this purpose, red and white base wines were used, and treatments consisted of spiked samples with 12 faults that are traditionally formed in wines. Results showed high accuracy in the classification models using NIR and e-nose for red wines (94–96%; 92–97%, respectively) and white wines (96–97%; 90–97%, respectively). Implementing new and emerging digital technologies could be a turning point for the winemaking industry to become more predictive in terms of decision-making and maintaining and increasing wine quality traits in a changing and challenging climate.
Sensitivity—Bandwidth Optimization of PMUT with Acoustical Matching Using Finite Element Method
Authors: He Le-Ming , Xu Wei-Jiang , Wang Yan , Zhou Jia , Ren Jun-Yan
Published: March 2022

A new model in finite element method to study round-trip performance of piezoelectric micromachined ultrasonic transducers (pMUTs) is established. Most studies on the performance of pMUT are based only on the transmission sensibility, but the reception capacity is as much important as the transmission one, and is quite different from this latter. In this work, the round-trip sensitivity of pMUT is defined as the product of the frequency response of transmitted far field pressure to source voltage excitation and that of reception output to return wave pressure. Based on this sensitivity characteristic, firstly, a multi-parameter optimization for a cavity pMUT is performed using the sensitivity-bandwidth product parameter SBW as criterion. The radii of the electrode and the piezoelectric layer, the thicknesses of the piezoelectric layer and the vibration diaphragm are adjusted to maximize the performance. Secondly, an acoustic matching method is proposed and applied to pMUTs for the first time. As a result, the round-trip sensitivity can be evaluated and the pulse-echo response of wide-band excitation can be simulated, giving the most quantitative and intuitive feedback for pMUT design. The optimization enhances the sensitivity-bandwidth product by 52% when the top electrode and piezoelectric layer are both etched to 75% radius of the cavity beneath; the introduction of an acoustic matching layer shows significant bandwidth expansion in both the transmitting and receiving process.
New Cable Delay Measurement System for VGOS Stations
Authors: García-Carreño Pablo , González-García Javier , Patino-Esteban María , Beltrán-Martínez Francisco J. , Bautista-Durán Marta , López-Espí Pablo Luis , López-Pérez José A.
Published: March 2022

This paper presents the new cable delay measurement system (CDMS) designed at Yebes Observatory (IGN, Spain), which is required for the VLBI Global Observing System (VGOS) stations. This system measures the phase difference between the 5 MHz reference signal from the hydrogen maser and the 5 MHz signal that reaches the broadband receiver through a coaxial cable, for the generation of calibration tones. As a result, the system detects the changes in the length of that coaxial cable due to temperature variations along the cable run and flexures caused by VGOS radio telescope movements. This CDMS outperforms the previous versions: firstly, it does not require a frequency counter for phase/delay measurements; secondly, it largely reduces the use of digital circuits; hence, reducing digital noise; and thirdly, it has a remotely controlled automatic calibration subsystem. The system was tested in the laboratory and in the radio telescope, and the measurements of both set-ups are shown. These measurements include the total noise, accuracy, hysteresis, and stability. The results in the radio telescope can be correlated with the different factors that affect the cable, such as temperature and flexures. The system allows to achieve an RMS noise of less than 0.5 ps, significantly improving the requirements established in VGOS. The system is currently installed in the Red Atlántica de Estaciones Geodinámicas y Espaciales (RAEGE)Yebes VGOS 13.2 m radio telescope, and will be installed in the Norwegian Mapping Authority (NMA) twin VGOS radio telescopes, in the Finnish Geospatial Research Institute (FGI) VGOS station and in the RAEGE Santa María VGOS radio telescope (Açores, Portugal).
Dependency Factors in Evidence Theory: An Analysis in an Information Fusion Scenario Applied in Adverse Drug Reactions
Authors: Ribeiro Luiz Alberto Pereira Afonso , Garcia Ana Cristina Bicharra , dos Santos Paulo Sérgio Medeiros
Published: March 2022

Multisensor information fusion brings challenges such as data heterogeneity, source precision, and the merger of uncertainties that impact the quality of classifiers. A widely used approach for classification problems in a multisensor context is the Dempster–Shafer Theory. This approach considers the beliefs attached to each source to consolidate the information concerning the hypotheses to come up with a classifier with higher precision. Nevertheless, the fundamental premise for using the approach is that sources are independent and that the classification hypotheses are mutually exclusive. Some approaches ignore this premise, which can lead to unreliable results. There are other approaches, based on statistics and machine learning techniques, that expurgate the dependencies or include a discount factor to mitigate the risk of dependencies. We propose a novel approach based on Bayesian net, Pearson’s test, and linear regression to adjust the beliefs for more accurate data fusion, mitigating possible correlations or dependencies. We tested our approach by applying it in the domain of adverse drug reactions discovery. The experiment used nine databases containing data from 50,000 active patients of a Brazilian cancer hospital, including clinical exams, laboratory tests, physicians’ anamnesis, medical prescriptions, clinical notes, medicine leaflets packages, international classification of disease, and sickness diagnosis models. This study had the hospital’s ethical committee approval. A statistically significant improvement in the precision and recall of the results was obtained compared with existing approaches. The results obtained show that the credibility index proposed by the model significantly increases the quality of the evidence generated with the algorithm Random Forest. A benchmark was performed between three datasets, incremented gradually with attributes of a credibility index, obtaining a precision of 92%. Finally, we performed a benchmark with a public base of heart disease, achieving good results.
Permanent Laser Scanner and Synthetic Aperture Radar Data: Correlation Characterisation at a Sandy Beach
Authors: Di Biase Valeria , Kuschnerus Mieke , Lindenbergh Roderik C.
Published: March 2022

In recent years, our knowledge of coastal environments has been enriched by remotely sensed data. In this research, we co-analyse two sensor systems: Terrestrial Laser Scanning (TLS) and satellite-based Synthetic Aperture Radar (SAR). To successfully extract information from a combination of different sensors systems, it should be understood how these interact with the common environment. TLS provides high-spatiotemporal-resolution information, but it has high economic costs and limited field of view. SAR systems, despite their lower resolution, provide complete, repeated, and frequent coverage. Moreover, Sentinel-1 SAR images are freely available. In the present work, Permanent terrestrial Laser Scanning (PLS) data, collected in Noordwijk (The Netherlands), are compared with simultaneous Sentinel-1 SAR images to investigate their combined use on coastal environments: knowing the relationship between SAR and PLS data, the SAR dataset could be correlated to beach characteristics. Meteorological and surface roughness have also been taken into consideration in the evaluation of the correlation between PLS and SAR data. A generally positive linear correlation factor up to 0.5 exists between PLS and SAR data. This correlation occurs for low- or moderate-wind-speed conditions, whilst no particular correlation has been highlighted for high wind intensity. Furthermore, a dependence of the linear correlation on the wind direction has been detected.
Clash of Two Identities: What Happens to Industrial Identity in a Post-Industrial Society?
Authors: Bole David , Kumer Peter , Gašperič Primož , Kozina Jani , Pipan Primož , Tiran Jernej
Published: March 2022

This article examines the contemporary industrial semiotic landscape in the town of Velenje, Slovenia, to determine the (positive or negative) collective imaginaries and discourses about industry in the local community. To this end, the semiotic landscape is mapped for signs and symbols of past and present industry, 33 randomly selected short interviews are conducted to understand the residents’ attitudes towards industrial symbols and industrial development in general, and a content analysis of official strategic documents is conducted to determine how industry is represented by officials and whether there are efforts to reimage the town. We found that the industrial past and present are well represented by industrial symbols and are a matter of pride and collective identity for the residents. However, the industrial tradition is hardly represented in official documents: Influenced by the prevailing post-industrial discourses, local authorities have begun to construct new territorial identities in order to increase the town’s attractiveness and economic growth. Currently, both ideas seem to coexist in Velenje. We argue that industrial symbols can become a reference point to create an alternative perception of a modern consumer society based on past industrial values, such as collective well-being, solidarity, and equality.
The Problems with Care: A Feminist Care Scholar Retrospective
Authors: Klostermann Janna , Funk Laura , Symonds-Brown Holly , Cherba Maria , Ceci Christine , Armstrong Pat , Pols Jeanette
Published: March 2022

Seeking to support qualitative researchers in the artful development of feminist care scholarship, our goal here is to ‘look back’ on how we have conceptualized the problems of care and developed research that illuminates the social organization of care in distinct ways. As part of a ‘feminist care scholar retrospective’, we present five condensed ‘reverse research proposals’, which are retrospective accounts of past research or scholarly activity. From there, we discuss how each project begins with a particular problematic for investigation and a particular conception of care (e.g., as practices, as work, as a concept) to illuminate facets of the social organization of care shaping paid and unpaid care work and its interpretations. These approaches reveal multiple and overlapping ways that care is embodied, understood and organized, as well as ways care can be transformed.
COVID19 Pandemic and Physical Activity: An Observational Study on Sleep Quality and Anxiety
Authors: Elce Ausilia , Daniele Aurora , Loperto Ilaria , De Coppi Lucia , Sangiorgio Armando , Vivona Angelina , Sorrentino Clorinda , Iannaccone Simona , Martiniello Lucia , Nigro Ersilia
Published: March 2022

Mental alterations were described during the COVID-19 pandemic and sleep deprivation has been reported as a consequence of social isolation. In Italy, the COVID-19 pandemic spread out at the beginning of 2020 determining severe lockdown periods. The aim of our study was to observe the effects of lockdown on sleep and anxiety in trained non-professional subjects and professional athletes who continued to train during the lockdown period. Forty-six subjects (21 trained non-professional subjects and 25 professional athletes) were recruited from a variety of team and individual sports to complete a battery of previously validated and widely used questionnaires assessing psychometric and anthropometric parameters, physical activity levels, lifestyle habits, and sleep quality. Subjects were aged 27.0 ± 5.14. All items were evaluated as percentages and chi-square and Fisher’s exact tests were performed, as appropriate. Our data showed that the prevalence of the difficulty of falling asleep (over 30%), the tendency of nocturnal awakenings (over 30%), and moderate anxiety (over 38%) were at the same extent in the two groups. Of the professional athletes, 72.73% declared snoring during sleep vs 42.86% of non-professional subjects. No other significant differences were found between the two groups except for the perception of being constant in daily activity, significantly more reported by trained subjects (p < 0.005). Our data show a similar scenario of anxiety and sleep disturbances for the two groups, suggesting that lockdown by the COVID-19 pandemic has partially mitigated the known beneficial effects due to physical activity on mental health and sleep quality. Further analyses are necessary to define the associated risk factors.
Impact of Coastal Disasters on Women in Urban Slums: A New Index
Authors: Kantamaneni Komali , Panneer Sigamani , Sudha Rani N.N.V. , Palaniswamy Udhayakumar , Bhat Lekha D. , Jimenez-Bescos Carlos , Rice Louis
Published: March 2022

Coastal hazards, particularly cyclones, floods, erosion and storm surges, are emerging as a cause for major concern in the coastal regions of Vijayawada, Andhra Pradesh, India. Serious coastal disaster events have become more common in recent decades, triggering substantial destruction to the low-lying coastal areas and a high death toll. Further, women living in informal and slum housing along the Vijayawada coastline of Andhra Pradesh (CAP), India, suffer from multiple social, cultural and economic inequalities as well. These conditions accelerate and worsen women’s vulnerability among this coastal population. The existing literature demonstrates these communities’ susceptibility to diverse coastal disasters but fails to offer gender-specific vulnerability in urban informal housing in the Vijayawada area. Accordingly, the current study developed a novel gender-specific Women’s Coastal Vulnerability Index (WCVI) to assess the impact of coastal disasters on women and their preparedness in Vijayawada. Field data was collected from over 300 women through surveys (2) and workshops (2) between November 2018 and June 2019, and Arc-GIS tools were used to generate vulnerability maps. Results show that women are more vulnerable than men, with a higher death rate during coastal disaster strikes. The current study also found that gender-specific traditional wear is one of the main factors for this specific vulnerability in this area. Furthermore, the majority of the women tend to be located at home to care for the elders and children, and this is associated with more fatalities during disaster events. Homes, particularly for the urban poor, are typically very small and located in narrow and restricted sites, which are a barrier for women to escape from unsafe residential areas during disasters. Overall, the research reveals that most of the coastal disaster events had a disproportionately negative impact on women. The results from this present study offer valuable information to aid evidence-based policy- and decision-makers to improve existing or generate innovative policies to save women’s lives and improve their livelihood in coastal areas.
Determinants/Motivations of Corporate Social Responsibility Disclosure in Developing Economies: A Survey of the Extant Literature
Authors: Ali Waris , Wilson Jeffrey , Husnain Muhammad
Published: March 2022

The main purpose of this study is to systematically analyse and synthesise the empirical literature on the drivers and motivations of CSR disclosure in developing countries. Previous studies on CSR disclosure have primarily investigated the accuracy of disclosure claims, impact on various actors, and the factors deriving CSR disclosure. While literature on CSR disclosure dates back to 1983, the number of studies have increased substantially in recent years, with 86% of studies being published in the last decade and a half. The results revealed that both internal and external factors influence the disclosure of CSR information. Internal factors influencing CSR disclosure include company characteristics such as size, industry, financial performance, corporate governance elements such as board size and board independence, and types of ownership. In addition, corporate polices and concerns also influence the disclosure of CSR-related information. External category factors influencing CSR disclosure include, regulatory pressures, government pressure, media concerns, social-cultural factors, and industry-level factors such as the level of industry competition, customers’ concerns, and multiple listing of a firm. Furthermore, global value chains, international buyers, international NGOs, and international regulatory bodies pressure companies in developing countries to disclose social and environmental information. In terms of motivations, companies disclose CSR information to improve their corporate reputation, improve their financial performance, access investment opportunities, and manage key stakeholders. The dominant theoretical frameworks used to explain the determinants of CSR disclosure include legitimacy theory and stakeholder theory.
Machine Learning for Pan Evaporation Modeling in Different Agroclimatic Zones of the Slovak Republic (Macro-Regions)
Authors: Novotná Beáta , Jurík Ľuboš , Čimo Ján , Palkovič Jozef , Chvíla Branislav , Kišš Vladimír
Published: March 2022

Global climate change is likely to influence evapotranspiration (ET); as a result, many ET calculation methods may not give accurate results under different climatic conditions. The main objective of this study is to verify the suitability of machine learning (ML) models as calculation methods for pan evaporation modeling on the macro-regional scale. The most significant PE changes in the different agroclimatic zones of the Slovak Republic were compared, and their considerable impacts were analyzed. On the basis of the agroclimatic zones, 35 meteorological stations distributed across Slovakia were classified into six macro-regions. For each of the meteorological stations, 11 variables were applied during the vegetation period in the years from 2010 to 2020 with a daily time step. The performance of eight different ML models—the neural network (NN) model, the autoneural network (AN) model, the decision tree (DT) model, the Dmine regression (DR) model, the DM neural network (DM NN) model, the gradient boosting (GB) model, the least angle regression (LARS) model, and the ensemble model (EM)—was employed to predict PE. It was found that the different models had diverse prediction accuracies in various geographical locations. In this study, the results of the values predicted by the individual models are compared.
Leverage of Local State-Owned Enterprises, Implicit Contingent Liabilities of Government and Economic Growth
Authors: Duan Yixuan , Guo Min , Huang Yixuan
Published: March 2022

Local state-owned enterprises (SOEs) working together with local governments can promote economic growth. However, an increase in the implicit contingent liabilities of local governments due to implicit guarantees given to SOEs has a negative effect on economic growth. The classical socialist theories and the economic stability in each financial crisis of China show that the macroeconomic efficiency of SOEs is more important than the microeconomic efficiency, and microeconomic efficiency in neoclassical economic theory cannot reflect the nature of SOEs. It is of great practical and theoretical significance to make a more comprehensive and accurate judgment on the efficiency of SOEs. This paper constructs an index of local governments’ implicit contingent liabilities in 31 provinces based on the 488 local SOEs to study the impact of implicit contingent liabilities, and the time period is the year 2007 to the year 2020. Our findings show that an increase in local SOEs’ assets suppresses economic fluctuations at the cost of increasing government’s implicit contingent debt and has a negative impact on economic growth. Unlike the fiscal influence path of explicit debt, implicit contingent debt restrains local economic growth through financial markets. The deleveraging of local SOEs and improving their efficiency can improve the overall efficiency of local funds and reduce the negative effect of local governments’ implicit contingent liabilities on economic growth.
Space Syntax in Analysing Bicycle Commuting Routes in Inner Metropolitan Adelaide
Authors: Soltani Ali , Allan Andrew , Javadpoor Masoud , Lella Jaswanth
Published: March 2022

Cycling is a particularly favoured for short urban trips because it is a healthy and environmentally benign activity. As a result, urban mobility, quality of life, and public health are enhanced, while traffic congestion and pollution are decreased. In looking beyond the street network in terms of how it affects cyclists’ behavior choices, Bill Hillier’s (1984) outstanding legacy research on spatial space syntax is investigated in this study. The goal of this study is to determine if an urban area’s street network morphology influences commuters’ inclination to ride their bicycles to work. To further understand the nonlinear consequences of street network geometry on the estimation of cycling to work, a logarithmic-transformed regression model that includes base socioeconomic components, urban form, and street network variables represented by space syntax measure factors is developed. In conclusion, this model determined that bike commuting choice is significantly associated with the centrality index of Connectivity, although this is in combination with socioeconomic factors (age, gender, affluence, housing type, and housing price) and built environment factors (share of commercial, educational activities and distance to the CBD) factors. The findings of this study would be of value to planners and policy makers in support of evidence-based policy formulation to improve the design of bicycle networks in suburban regions.
Perceived Overqualification and Innovative Behavior: High-Order Moderating Effects of Length of Service
Authors: Sun Yongbo , Qiu Zichen
Published: March 2022

Perceived overqualification has been a hot topic in the field of organizational behavior in recent years and has become very common with the spread of education. In addition, in the current era of open innovation, the demand for innovative behaviors by enterprises is increasing day by day. Therefore, this study intended to link the two to explore the relationship between them. Based on self-evaluation theory and face theory, taking enterprise employees as the research object, this paper discusses the impact of perceived overqualifications on employees’ innovative behavior and the internal mechanism and examines the first-order and high-order moderating effects of ability–face pressure and length of service in turn. The results showed that perceived overqualifications had a positive impact on employees’ innovation behavior, and felt trust had a mediating role in the relationship. Ability face pressure played a negative moderating role in the impact of felt trust on innovative behavior and played a negative moderating role in the impact of perceived overqualifications on innovative behavior. With the increase in the length of service, the negative moderating effect of ability face pressure on the relationship between perceived overqualifications and employees’ innovative behavior weakened. It is expected that these results will enable companies to understand the internal mechanisms of employee perceived overqualification, enlighten leaders to give more trust to employees, help companies to improve employees’ innovative behavior, and pay attention to the psychological factors of employees, which will help to create a sustainable work environment and promote sustainable business development.
Charge Scheduling Optimization of Plug-In Electric Vehicle in a PV Powered Grid-Connected Charging Station Based on Day-Ahead Solar Energy Forecasting in Australia
Authors: S. Sheik Mohammed , Titus Femin , Thanikanti Sudhakar Babu , M. Sulaiman S. , Deb Sanchari , Kumar Nallapaneni Manoj
Published: March 2022

Optimal charge scheduling of electric vehicles in solar-powered charging stations based on day-ahead forecasting of solar power generation is proposed in this paper. The proposed algorithm’s major objective is to schedule EV charging based on the availability of solar PV power to minimize the total charging costs. The efficacy of the proposed algorithm is validated for a small-scale system with a capacity of 3.45 kW and a single charging point, and the annual cost analysis is carried out by modelling a 65 kWp solar-powered EV charging station The reliability and cost saving of the proposed optimal scheduling algorithm along with the integration and the solar PV system is validated for a charging station with a 65 kW solar PV system having charging points with different charging powers. A comprehensive comparison of uncontrolled charging, optimal charging without solar PV system, and optimal charging with solar PV system for different vehicles and different time slots are presented and discussed. From the results, it can be realized that the proposed charging algorithm reduces the overall charging cost from 10–20% without a PV system, and while integrating a solar PV system with the proposed charging method, a cost saving of 50–100% can be achieved. Based on the selected location, system size, and charging points, it is realized that the annual charging cost under an uncontrolled approach is AUS $28,131. On the other hand, vehicle charging becomes completely sustainable with net-zero energy consumption from the grid and net annual revenue of AUS $28,134.445 can be generated by the operator. New South Wales (NSW), Australia is selected as the location for the study. For the analysis Time-Of-Use pricing (ToUP) scheme and solar feed-in tariff of New South Wales (NSW), Australia is adopted, and the daily power generation of the PV system is computed using the real-time data on an hourly basis for the selected location. The power forecasting is carried out using an ANN-based forecast model and is developed using MATLAB and trained using the Levenberg–Marquardt algorithm. Overall, a prediction accuracy of 99.61% was achieved using the selected algorithm.
What Is Engineering and Who Are Engineers? Student Reflections from a Sustainability-Focused Energy Course
Authors: Forbes Marissa , Lord Susan , Hoople Gordon , Chen Diana , Mejia Joel
Published: March 2022

In the spring of 2021, the University of San Diego’s Department of Integrated Engineering taught the course, “Integrated Approach to Energy”, the second offering of a new required course, to nine second-year engineering students. The sociotechnical course covered modern energy concepts, with an emphasis on renewable energies and sustainability, and it exposed the students to other ways of being, knowing, and doing that deviated from the dominant masculine Western White colonial discourse. Following the course completion, we interviewed five students by using a semistructured protocol to explore how they perceived of and communicated about engineers and engineering. We sought to identify the takeaways from their course exposure to sustainability and the sociotechnical paradigm, which were central to the course. The findings suggest that the students were beginning to form sociotechnical descriptions, and that they were still developing their understanding and perceptions of engineers and engineering. Moreover, we observed that they were still wrestling with how best to integrate sustainability into those perceptions. There was an a-la-carte feel to the students’ conceptualizations of sustainability as it related to engineering, as in, “you can ‘do’ sustainability with engineering, but do not have to”. We argue that engineering students likely need these pedagogical paradigms (sociotechnical engineering and sustainability) woven through the entirety of their engineering courses if they are to fully accept and integrate them into their own constructs about engineers and engineering.
Canada’s Impact Assessment Act, 2019: Indigenous Peoples, Cultural Sustainability, and Environmental Justice
Authors: Tsuji Stephen R. J.
Published: March 2022

It is well documented that the colonizers of Canada have long coveted the ancestral homelands of the Canadian Indigenous peoples for settlement and development. With this end goal in mind, it is not surprising that there exists an extensive history of assimilative efforts by the colonizers with respect to the Indigenous peoples of Canada—for example, legal assimilation through enfranchisement (voluntary and involuntary) and blood quantum requirements, and cultural assimilation through residential schools and the “sixties scoop”. Another form of assimilation is environmental assimilation, that is, colonial development on Indigenous homelands to the extent whereby Indigenous cultural activities can no longer be supported in the development-transformed environment. Herein, I examine Bill C-69, a Government of Canada omnibus bill, through an environmental justice lens in the context of development across Canada on Indigenous homelands and impacts on Indigenous cultural sustainability. Specifically, Part 1 (i.e., the Impact Assessment Act, 2019) and Part 3 (i.e., the Canadian Navigable Waters Act, 2019) of Bill C-69 pose significant threats to Indigenous cultural sustainability. Through an environmental justice lens, procedural aspects include the use of the project list and scheduled waterways, the discretionary decision-making powers of the Government of Canada representatives, and the lack of acknowledgement of procedural elements of the environmental assessment processes that are constitutionally protected in comprehensive land claims. While, distributive justice aspects consist of unsustainable development from an Indigenous perspective, whereby environmental costs and benefits have been (and will be) distributed inequitably. Bill C-69 is a flawed statute that reinforces the colonial policy of assimilation.
Antecedents and Impacts of Enterprise Resource Planning System Adoption among Jordanian SMEs
Authors: Lutfi Abdalwali , Alshira’h Ahmad Farhan , Alshirah Malek Hamed , Al-Okaily Manaf , Alqudah Hamza , Saad Mohamed , Ibrahim Nahla , Abdelmaksoud Osama
Published: March 2022

Businesses need accounting information to support their decision-making. In this regard, the extensive use of Information Technology (IT) has enhanced the effectiveness and efficiency of accounting functions that support accounting-related information. Specifically, an enterprise resource planning (ERP) system ensures reporting accuracy, large amounts of transaction processing, and the generation of reports for analysis. Regardless of the numerous benefits that an ERP system provides, small and medium-sized enterprises (SMEs) have yet to catch up with their system usage. Hence, this study draws upon the technology-organisation-environment (TOE) framework to propose an integrated model that includes diffusion of innovation (DOI), institutional factors, and TOE to examine ERP adoption antecedents in the context of SMEs in Jordan. A mixed method is applied in this work, and it uses a self-administered questionnaire survey as the main data collection instrument along with interviews. Quantitative data are obtained from 102 respondents through the questionnaire, after which the research model is validated using SMEs in Jordan. The survey results show that relative advantage, top management support, organisational readiness, training, competitive pressure, government support compatibility, and service provider support significantly influence ERP adoption among the SMEs. The findings are expected to shed light on the way SMEs can enhance their ERP adoption for optimum performance, as well as extend the literature dedicated to the antecedents of information system, IT adoption, and their impact.
How Does New Infrastructure Investment Affect Economic Growth Quality? Empirical Evidence from China
Authors: Du Xin , Zhang Hengming , Han Yawen
Published: March 2022

The current phase of the technological revolution and the accelerated rate of industrial change have encouraged the structural transformation of global infrastructure investment. This study aims to identify and evaluate the impact of new infrastructure investment on economic growth quality. This paper explains the theoretical mechanisms in terms of their effects on technological innovation, industrial structure, and productivity, using the three-dimensional analysis framework of economic growth conditions, process, and results. We then carry out an empirical examination based on provincial panel data for China from 2004 to 2019. The findings demonstrate that new infrastructure investment can significantly improve economic growth quality, and this conclusion still seems valid after conducting endogeneity treatments and robustness tests. Further mechanism evaluations indicate that new infrastructure investments contribute to boosting economic growth quality in terms of the condition, process, and results of economic growth by promoting technological innovation, improving industrial structure, and enhancing production efficiency. Moreover, the magnitude and mechanism of the positive effects differ depending on the heterogeneity of the region examined. In terms of the nonlinear change characteristics, the significant dual-threshold effect reveals that the marginal effects of new infrastructure investment on economic growth quality tend to be incremental under the threshold condition. This study provides a theoretical and factual basis for governments to enforce new infrastructure investments in the digital economy era, and it also has some value as a reference regarding the economic sustainability of developing countries.
The 2020 Maize Production Failure in Ghana: A Case Study of Ejura-Sekyedumase Municipality
Authors: Obour Peter Bilson , Arthur Isaac Kwamena , Owusu Kwadwo
Published: March 2022

This paper examines the causes of widespread maize production failure in Ghana during the 2020 minor growing season. A mixed-methods approach was used to study smallholder maize farmers in the Ejura-Sekyedumase Municipality to provide a holistic understanding of the factors behind the maize production failure and to inform policy interventions. The results show that the decline in maize grain yield was caused by the failure of the minor season rains and, more importantly, the destruction of maize plants by fall armyworms. Other factors including poor soils and inadequate farm inputs contributed minimally to the observed maize failures. The agronomic practices adopted by the farmers to mitigate crop failures were undermined by their inability to master the onset and cessation of rainfall, the ineffectiveness of pesticides to control the fall armyworms and financial challenges. It is recommended that the government promotes and supports rainwater harvesting to address the impacts of drought and pests on food crop production. Furthermore, to ensure sustainable food production, a combination of indigenous knowledge and scientific farm practices are crucial to accurately forecast the weather and to control the fall armyworms.
Synthesis of Bis(N,N-diethyl)aniline-Based, Nonlinear, Optical Chromophores with Increased Electro-Optic Activity by Optimizing the Thiolated Isophorone Bridge
Authors: Huang Xiaoqing , Li Ziheng , Peng Meishan , Zeng Ziying , Huang Zeling , Liu Fenggang , Chen Xunyu , Liang Zhiwei , Wang Jiahai
Published: March 2022

Six nonlinear, optical chromophores, Z1–Z6, based on the bis(N,N-diethyl)aniline-derived donor and thiolated isophorone bridge, were designed and synthesized. The bis(N,N-diethyl)aniline-derived donor was applied in a chromophore with thiolated isophorone as an electron bridge for the first time. In particular, the bridge parts of chromophores Z2–Z6 were modified with different functional groups, including tert-butyltrimethylsilane and tert-butyl(methyl)diphenylsilane derivative: 1,3-bis(trifluoromethyl)benzene and alkylaniline cyanoacetate, respectively. Density functional theory calculations suggested this series of chromophores show much greater hyperpolarizability than traditional, nonlinear, optical chromophores due to strong electron donor ability. These chromophores, Z1–Z6, showed very high poling efficiencies due to the large steric hindrance and hyperpolarizability of the chromophores. A large poling efficiency (2.04 ± 0.08 nm2/V2) and r33 value (193 pm/V) were achieved for polymeric thin films doped with 25 wt% chromophore Z6 at 1310 nm.
An Evolutionary Numerical Method of Supply Chain Trust Networks with the Degree of Distribution
Authors: Zhang Xuelong , Zhang Maojun , Luo Yuxi , Yi Yanling
Published: March 2022

We study the structure of supply chain trust networks (SCTNs) by analyzing the evolution of the networks. An SCTN here comprises enterprises in a fully competitive market connected through the preferential attachment mechanism. A Markov chain analysis is used to understand how various factors affect the structure of the SCTNs. The evolution of the SCTNs is also analyzed to identify the asymmetric conditions required for the degree distribution of the SCTNs to obey the power law distribution. The simulation results show that, when the degree of willingness to initiate a trust relationship and the attractiveness index of the supply chain networks meet certain criteria, the underlying network is of a scale-free nature.
Runtime Software Architecture-Based Reliability Prediction for Self-Adaptive Systems
Authors: Li Qiuying , Lu Minyan , Gu Tingyang , Wu Yumei
Published: March 2022

Modern software systems need to autonomously adapt their behavior at runtime in order to maintain their utility in response to continuous environmental changes. Most studies on models at runtime focus on providing suitable techniques to manage the complexity of software at runtime but neglect reliability caused by adaptation activities. Therefore, adaptive behaviors may lead to a decrease in reliability, which may result in severe financial loss or life damage. Runtime software architecture (RSA) is an abstract of a running system, which describes the elements of the current system, the states of these elements and the relation between the elements and their states at runtime. The main difference between RSA and software architecture at design time (DSA) is that RSA has a causal connection with the running system, whereas DSA does not. However, RSA and DSA have both symmetry and asymmetry in software architecture. To ensure that architecture-centric software can provide reliable services after adaptation adjustment, a method is proposed to analyze the impact of changes caused by adaptation strategy on the overall software reliability, which will be predicted at the runtime architecture model layer. Based on a Java platform, through non-intrusive monitoring, an RSA behavioral model is obtained followed by runtime reliability analysis model. Following this, reliability prediction results are obtained through a discrete-time Markov chain (DTMC). Finally, an experiment is conducted to verify the feasibility of the proposed method.
A Novel Decision-Making Method for Selecting Superintendent Based on a Q-Rung Dual Hesitant Fuzzy Power Partitioned Bonferroni Mean Operator
Authors: Chen Tiedong , Ye Long
Published: March 2022

The Q-rung dual hesitant fuzzy (q-RDHF) set is famous for expressing information composed of asymmetry evaluations, because it allows for several possible evaluations in both the membership degree and non-membership degree. Compared with some existing extended fuzzy theories, the q-RDHF set is more superior and flexible because it can handle asymmetric assessments. In order to assemble the evaluation information expressed by q-RDHF elements, this paper aims to propose new operators to integrate q-RDHF elements. The partitioned Bonferroni mean (PBM) operator is well-known for its advantages in coping with the inhomogeneous relationship between asymmetry input arguments. In this paper, we combine the PBM operator with the power average operator, and propose a family of q-RDHF power PBM operators. Some theorems and special cases for the new proposed operators are discussed. Furthermore, we provide a general framework for dealing with multiple attribute decision-making (MADM) problems using the novel proposed method. To better show the calculation details, a numerical case study of the application of the proposed method in a superintendent selection problem is introduced. In addition, we utilize the proposed method to compare it with some existing methods in order to show its flexibility and superiority. The results show that our method is much more advantageous when considering flexible actual situations. Finally, the conclusion is given. The main contributions of this study are to propose an appropriate method to solve unbalanced and asymmetry information in a q-RDHF environment, and to apply it into a realistic superintendent selection problem.
Decision Making of Software Release Time at Different Confidence Intervals with Ohba’s Inflection S-Shape Model
Authors: Chang Ting-Cheng , Lin Ying , Shi Kunquan , Meen Teen-Hang
Published: March 2022

Software developers need information for deciding the optimal time for software release with improved software reliability. However, it is not easy for them to decide when and how to release newly developed software to the market. For a decision, the reliability and test costs of the software need to be balanced carefully for avoiding unnecessary confusion and users’ complaints. To address this need, related research has been carried out to propose an appropriate tool for such decisions. In many studies, software reliability growth models (SRGMs) were applied using the concept of confidence intervals to estimate the reliability of software. Confidence intervals were calculated on the basis of the assumption of a normal distribution showing the symmetrical occurrence of data with the mean as a center. However, the reliability data of software do not always have such symmetry for assuming the normal distribution. Therefore, it is necessary to propose a method for overcoming the mean value randomness that causes asymmetry in the related data. In previous studies, estimating variance and mean of errors of software was not considered, which led to the unreliable estimation of the confidence intervals of the mean value for decision making. Previous studies also lacked practicability in applications due to statistics from the asymmetrical data distribution. As a result, software developers could not effectively evaluate the possible risk related to the software release time. To improve the estimation, we employ the inflection S-shape model to propose the SRGM on the basis of confidence intervals assumed to come from the normal distribution. The proposed model allows determining the optimal time for software release with the consideration of its potential risk. For efficient determination, the architecture and user interface of the computation system are also proposed.
Can Good Government Save Us? Extending a Climate-Population Model to Include Governance and Its Effects
Authors: Homer Jack
Published: March 2022

Many believe good government to be essential for a nation’s progress, but, in fact, governance is a multidimensional concept with uncertain implications for economic development and global sustainability. The World Bank has tracked six country-level Worldwide Governance Indicators since 1996. Statistical regression analysis across 150 countries identified two of these indicators, Government Effectiveness and Regulatory Quality, that consistently help to explain changes in economic growth and CO2 emissions. The regression results provided the evidence needed to incorporate the effects of governance in an existing climate-population simulation model. Policy testing of the revised model led to findings about what improved governance can and cannot do. The testing suggested that the best combination of such improvements could boost progress on emissions reduction without hindering economic development—but not enough to strongly mitigate climate change. Achieving the double goal of economic development and strong climate change mitigation would thus require some kind of extra effort that does not fall under the usual definitions of good national governance.