bluuebunny/crossref_metadata_2025 huggingface dataset:
Separation of the Sound Power Spectrum of Multiple Sources by Three-Dimensional Sound Intensity Decomposition
Authors: Chai Shiyi , Liu Xiaoqin , Wu Xing , Xiong Yanjiao
Published: January 2021

The identification and separation of sources are the prerequisite of industrial noise control. Industrial machinery usually contains multiple noise sources sharing same-frequency components. There are usually multiple noise sources in mechanical equipment, and there are few effective methods available to separate the spectrum intensity of each sound source. This study tries to solve the problem by the radiation relationship between three-dimensional sound intensity vectors and the power of the sources. When the positions of the probe and the sound source are determined, the sound power of the sound source at each frequency can be solved by the particle swarm optimization algorithm. The solution results at each frequency are combined to obtain the sound power spectrum of each sound source. The proposed method is first verified by a simulation on two point sources. The experiment is carried out on a fault simulation test bed in an ordinary laboratory; we used three three-dimensional sound intensity probes to form a line array and conducted spectrum separation of the nine main noise sources. The sound intensity on the main frequency band of each sound source was close to the result of the near-field measurement of the one-dimensional sound intensity probe. The proposed spectral separation method of the sound power of multiple sound sources provides a new method for accurate noise identification in industrial environments.
Secure Patient Data Transfer Using Information Embedding and Hyperchaos
Authors: Aljuaid Hanan , Parah Shabir A.
Published: January 2021

Health 4.0 is an extension of the Industry standard 4.0 which is aimed at the virtualization of health-care services. It employs core technologies and services for integrated management of electronic health records (EHRs), captured through various sensors. The EHR is processed and transmitted to distant experts for better diagnosis and improved healthcare delivery. However, for the successful implementation of Heath 4.0 many challenges do exist. One of the critical issues that needs attention is the security of EHRs in smart health systems. In this work, we have developed a new interpolation scheme capable of providing better quality cover media and supporting reversible EHR embedding. The scheme provides a double layer of security to the EHR by firstly using hyperchaos to encrypt the EHR. The encrypted EHR is reversibly embedded in the cover images produced by the proposed interpolation scheme. The proposed interpolation module has been found to provide better quality interpolated images. The proposed system provides an average peak signal to noise ratio (PSNR) of 52.38 dB for a high payload of 0.75 bits per pixel. In addition to embedding EHR, a fragile watermark (WM) is also encrypted using the hyperchaos embedded into the cover image for tamper detection and authentication of the received EHR. Experimental investigations reveal that our scheme provides improved performance for high contrast medical images (MI) when compared to various techniques for evaluation parameters like imperceptibility, reversibility, payload, and computational complexity. Given the attributes of the scheme, it can be used for enhancing the security of EHR in health 4.0.
Oxygen Saturation Imaging Using LED-Based Photoacoustic System
Authors: Bulsink Rianne , Kuniyil Ajith Singh Mithun , Xavierselvan Marvin , Mallidi Srivalleesha , Steenbergen Wiendelt , Francis Kalloor Joseph
Published: January 2021

Oxygen saturation imaging has potential in several preclinical and clinical applications. Dual-wavelength LED array-based photoacoustic oxygen saturation imaging can be an affordable solution in this case. For the translation of this technology, there is a need to improve its accuracy and validate it against ground truth methods. We propose a fluence compensated oxygen saturation imaging method, utilizing structural information from the ultrasound image, and prior knowledge of the optical properties of the tissue with a Monte-Carlo based light propagation model for the dual-wavelength LED array configuration. We then validate the proposed method with oximeter measurements in tissue-mimicking phantoms. Further, we demonstrate in vivo imaging on small animal and a human subject. We conclude that the proposed oxygen saturation imaging can be used to image tissue at a depth of 6–8 mm in both preclinical and clinical applications.
System Performance Analysis for an Energy Harvesting IoT System Using a DF/AF UAV-Enabled Relay with Downlink NOMA under Nakagami-m Fading
Authors: Nguyen Anh-Nhat , Vo Van Nhan , So-In Chakchai , Ha Dac-Binh
Published: January 2021

This paper investigates system performance in the Internet of Things (IoT) with an energy harvesting (EH) unmanned aerial vehicle (UAV)-enabled relay under Nakagami-m fading, where the time switching (TS) and adaptive power splitting (APS) protocols are applied for the UAV. Our proposed system model consists of a base station (BS), two IoT device (ID) clusters (i.e., a far cluster and a near cluster), and a multiantenna UAV-enabled relay (UR). We adopt a UR-aided TS and APS (U-TSAPS) protocol, in which the UR can dynamically optimize the respective power splitting ratio (PSR) according to the channel conditions. To improve the throughput, the nonorthogonal multiple access (NOMA) technique is applied in the transmission of both hops (i.e., from the BS to the UR and from the UR to the ID clusters). The U-TSAPS protocol is divided into two phases. In the first phase, the BS transmits a signal to the UR. The UR then splits the received signal into two streams for information processing and EH using the APS scheme. In the second phase, the selected antenna of the UR forwards the received signal to the best far ID (BFID) in the far cluster and the best near ID (BNID) in the near cluster using the decode-and-forward (DF) or amplify-and-forward (AF) NOMA scheme. We derive closed-form expressions for the outage probabilities (OPs) at the BFID and BNID with the APS ratio under imperfect channel state information (ICSI) to evaluate the system performance. Based on these derivations, the throughputs of the considered system are also evaluated. Moreover, we propose an algorithm for determining the nearly optimal EH time for the system to minimize the OP. In addition, Monte Carlo simulation results are presented to confirm the accuracy of our analysis based on simulations of the system performance under various system parameters, such as the EH time, the height and position of the UR, the number of UR antennas, and the number of IDs in each cluster.
Neural Network Based Contact Force Control Algorithm for Walking Robots
Authors: Kim Byeongjin , Kim Soohyun
Published: January 2021

Walking algorithms using push-off improve moving efficiency and disturbance rejection performance. However, the algorithm based on classical contact force control requires an exact model or a Force/Torque sensor. This paper proposes a novel contact force control algorithm based on neural networks. The proposed model is adapted to a linear quadratic regulator for position control and balance. The results demonstrate that this neural network-based model can accurately generate force and effectively reduce errors without requiring a sensor. The effectiveness of the algorithm is assessed with the realistic test model. Compared to the Jacobian-based calculation, our algorithm significantly improves the accuracy of the force control. One step simulation was used to analyze the robustness of the algorithm. In summary, this walking control algorithm generates a push-off force with precision and enables it to reject disturbance rapidly.
A Lattice-Based Homomorphic Proxy Re-Encryption Scheme with Strong Anti-Collusion for Cloud Computing
Authors: Li Juyan , Qiao Zhiqi , Zhang Kejia , Cui Chen
Published: January 2021

The homomorphic proxy re-encryption scheme combines the characteristics of a homomorphic encryption scheme and proxy re-encryption scheme. The proxy can not only convert a ciphertext of the delegator into a ciphertext of the delegatee, but also can homomorphically calculate the original ciphertext and re-encryption ciphertext belonging to the same user, so it is especially suitable for cloud computing. Yin et al. put forward the concept of a strong collusion attack on a proxy re-encryption scheme, and carried out a strong collusion attack on the scheme through an example. The existing homomorphic proxy re-encryption schemes use key switching algorithms to generate re-encryption keys, so it can not resist strong collusion attack. In this paper, we construct the first lattice-based homomorphic proxy re-encryption scheme with strong anti-collusion (HPRE-SAC). Firstly, algorithm TrapGen is used to generate an encryption key and trapdoor, then trapdoor sampling is used to generate a decryption key and re-encryption key, respectively. Finally, in order to ensure the homomorphism of ciphertext, a key switching algorithm is only used to generate the evaluation key. Compared with the existing homomorphic proxy re-encryption schemes, our HPRE-SAC scheme not only can resist strong collusion attacks, but also has smaller parameters.
Formulation and Performance Analysis of Broadband and Narrowband OFDM-Based PLC Systems
Authors: García-Gangoso Fausto , Blanco-Velasco Manuel , Cruz-Roldán Fernando
Published: January 2021

The aim of this paper is to formulate the physical layer of the broadband and narrowband power line communication (PLC) systems described in standards IEEE 1901 and IEEE 1901.2, which address new communication technologies over electrical networks for Smart Grid and Internet of Things applications. Specifically, this paper presents a mathematical formulation by means of matrices of a transmitter and receiver system based on windowed OFDM. The proposed formulation is essential for obtaining the input–output relation, as well as an analysis of the interference present in the system. It is very useful for simulating PLC systems using software designed to operate primarily on whole matrices and arrays, such as Matlab. In addition, it eases the analysis and design of different receiver configurations, simply by modifying or adding a matrix. Since the relevant standards only describe the blocks corresponding to the transmitter, and leave the set-up of the receiver open to the manufacturer, we analysed four different possible schemes that include window functions in different configurations. In simulations, the behaviour of each of these schemes is analysed in terms of bit error and achievable data rates using artificial and real noises.
Automatic Resting Tremor Assessment in Parkinson’s Disease Using Smartwatches and Multitask Convolutional Neural Networks
Authors: Sigcha Luis , Pavón Ignacio , Costa Nélson , Costa Susana , Gago Miguel , Arezes Pedro , López Juan Manuel , De Arcas Guillermo
Published: January 2021

Resting tremor in Parkinson’s disease (PD) is one of the most distinctive motor symptoms. Appropriate symptom monitoring can help to improve management and medical treatments and improve the patients’ quality of life. Currently, tremor is evaluated by physical examinations during clinical appointments; however, this method could be subjective and does not represent the full spectrum of the symptom in the patients’ daily lives. In recent years, sensor-based systems have been used to obtain objective information about the disease. However, most of these systems require the use of multiple devices, which makes it difficult to use them in an ambulatory setting. This paper presents a novel approach to evaluate the amplitude and constancy of resting tremor using triaxial accelerometers from consumer smartwatches and multitask classification models. These approaches are used to develop a system for an automated and accurate symptom assessment without interfering with the patients’ daily lives. Results show a high agreement between the amplitude and constancy measurements obtained from the smartwatch in comparison with those obtained in a clinical assessment. This indicates that consumer smartwatches in combination with multitask convolutional neural networks are suitable for providing accurate and relevant information about tremor in patients in the early stages of the disease, which can contribute to the improvement of PD clinical evaluation, early detection of the disease, and continuous monitoring.
Improving the Performance of Time-Relative GNSS Precise Positioning in Remote Areas
Authors: He Kaifei , Weng Duojie , Ji Shengyue , Wang Zhenjie , Chen Wu , Lu Yangwei , Nie Zhixi
Published: January 2021

Global navigation satellite systems (GNSS) can attain centimeter level positioning accuracy, which is conventionally provided by real-time precise point positioning (PPP) and real-time kinematic (RTK) techniques. Corrections from the data center or the reference stations are required in these techniques to reduce various GNSS errors. The time-relative positioning approach differs from the traditional PPP and RTK in the sense that it does not require external real-time corrections. It computes the differences in positions of a single receiver at different epochs using phase observations. As the code observations are not used in this approach, its performance is not affected by the noise and multipath of code observations. High reliability is another advantage of time-relative precise positioning because the ambiguity resolution is not needed in this approach. Since the data link is not required in the method, this approach has been widely used in remote areas where wireless data link is not available. The main limitation of time-relative positioning is that its accuracy degrades over time between epochs because of the temporal variation of various errors. The application of the approach is usually limited to be within a time interval of less than 20 min. The purpose of this study was to increase the time interval of time-relative positioning and to extend the use of this method to applications with a longer time requirement, especially in remote areas without wireless communication. In this paper, the main error sources of the time-relative method are first analyzed in detail, and then the approach to improve the accumulated time relative positioning method is proposed. The performance of the proposed method is assessed using both static and dynamic observations with a duration as long as several hours. The experiments presented in this paper show that, among the four scenarios tested (i.e., GPS, GPS/Galileo, GPS/Galileo/BeiDou, and GPS/Galileo/BeiDou/GLONASS), GPS/Galileo/BeiDou performed best and GPS/Galileo/BeiDou/GLONASS performed worst. The maximum positioning errors were mostly within 0.5 m in the horizontal direction, even after three hours with GPS/Galileo/BeiDou. It is expected that the method could be used for positioning and navigation for as long as several hours with decimeter level horizontal accuracy in remote areas without wireless communication.
Temperature Hysteresis Mechanism and Compensation of Quartz Flexible Accelerometer in Aerial Inertial Navigation System
Authors: Zhang Chunxi , Wang Xin , Song Lailiang , Ran Longjun
Published: January 2021

Strap-down inertial navigation systems (INSs) with quartz flexible accelerometers (QFAs) are widely used in many conditions, particularly in aerial vehicles. Temperature is one of the significant issues impacting the performance of INS. The variation and the gradient of temperature are complex under aerial conditions, which severely degrades the navigation performance of INS. Previous work has indicated that parts of navigation errors could be restrained by simple temperature compensation of QFA. However, the temperature hysteresis of the accelerometer is seldom considered in INS. In this paper, the temperature hysteresis mechanism of QFA and the compensation method would be analyzed. Based on the fundamental model, a comprehensive temperature hysteresis model is proposed and the parameters in this model were derived through a temperature cycling test. Furthermore, the comparative experiments in the laboratory were executed to refine the temperature hysteresis model and to verify the effectiveness of the new compensation method. Applying the temperature hysteresis compensation in flight condition, the result shows that the position error (CEP) is restrained from 1.54 nmile/h to 1.29 nmile/h. The proposed temperature hysteresis compensation method improves the performance of INS effectively and feasibly, which could be promoted to other applications of INS in similar temperature changing environment correspondingly.
Self-Perceptions on Digital Competences for M-Learning and Education Sustainability: A Study with Teachers from Different Countries
Authors: Betancourt-Odio Manuel Alejandro , Sartor-Harada Andresa , Ulloa-Guerra Oscar , Azevedo-Gomes Juliana
Published: January 2021

The current international landscape shows that the most common alternative for the continuity of formative learning processes during the coronavirus pandemic has been the use the of e-learning to support children’s learning in environments outside of school. This forced change in teaching methods has consolidated the recognition that the digital skills of teachers are a relevant factor for the sustainability of education, both during the pandemic and in a future post-pandemic period or in other emergencies. In this sense, the objective of this study carried out between May and September 2020 was to determine the perceptions of 427 teachers from 15 countries about their digital competences in working with m-learning in primary education using a Montessori approach. The results of the questionnaire showed that teachers perceive their digital competences as inert and not very effective for innovation compared with the subsistence of traditional pedagogical practices, to deal with unpredictable situations or to generate differentiated adaptations for an inclusive education. The results of this study also serve as empirical support for establishing four training dimensions that can be considered priorities for the construction and implementation of a teacher training model that contributes to the sustainable development of education.
Analyzing Temporal Variability in Inventory Data for Life Cycle Assessment: Implications in the Context of Circular Economy
Authors: Shoaib-ul-Hasan Sayyed , Roci Malvina , Asif Farazee M. A. , Salehi Niloufar , Rashid Amir
Published: January 2021

Life cycle assessment (LCA) is used frequently as a decision support tool for evaluating different design choices for products based on their environmental impacts. A life cycle usually comprises several phases of varying timespans. The amount of emissions generated from different life cycle phases of a product could be significantly different from one another. In conventional LCA, the emissions generated from the life cycle phases of a product are aggregated at the inventory analysis stage, which is then used as an input for life cycle impact assessment. However, when the emissions are aggregated, the temporal variability of inventory data is ignored, which may result in inaccurate environmental impact assessment. Besides, the conventional LCA does not consider the environmental impact of circular products with multiple use cycles. It poses difficulties in identifying the hotspots of emission-intensive activities with the potential to mislead conclusions and implications for both practice and policy. To address this issue and to analyze the embedded temporal variations in inventory data in a CE context, the paper proposes calculating the emission intensity for each life cycle phase. It is argued that calculating and comparing emission intensity, based on the timespan and amount of emissions for individual life cycle phases, at the inventory analysis stage of LCA offers a complementary approach to the traditional aggregate emission-based LCA approach. In a circular scenario, it helps to identify significant issues during different life cycle phases and the relevant environmental performance improvement opportunities through product, business model, and supply chain design.
Environmental Sensitivity and Awareness as Differentiating Factors in the Purchase Decision-Making Process in the Smartphone Industry—Case of Polish Consumers
Authors: Skowron Lukasz , Sak-Skowron Monika
Published: January 2021

The first of the research objectives discussed in this article was to analyze the differences related to the valuation of particular factors influencing the purchase process in the smartphone industry, expressed by respondents with different sensitivity and environmental awareness, as well as the assessment of their knowledge about the impact of smartphones on the natural environment. The second objective of the research was to determine whether the level of environmental sensitivity, awareness and knowledge about the impact of smartphones on the environment has a statistically significant influence on the respondents’ choice of smartphone brand. The survey was conducted using an on-line questionnaire, distributed by a specialized research agency on a representative sample of over 1000 Polish residents. In order to identify the various customers clusters, the expectation-maximization algorithm and the v-fold cross-validation were used. Additionally, in order to analyze the significance level of differences between clusters the nonparametric Mann-Whitney U-test was carried out. The results show unequivocally that people with a different approach to ecological issues demonstrate statistically significant differences in their purchasing behaviors in the smartphone industry. Furthermore, it was noticed that in the case of comparing some smartphones brands, there is a statistically confirmed difference in the environmental sensitivity and awareness of the customers who use them. Moreover, the research has shown that in Polish customers’ consciousness smartphones are mistakenly considered to be relatively safe and environmentally friendly products.
Study on the Spatial Pattern of Migration Population in Egypt and Its Flow Field Characteristics from the Perspective of “Source-Flow-Sink”
Authors: Ma Zhishan , Zhang Susu , Zhao Sidong
Published: January 2021

Based on the provinces as the spatial nodes of population migration, a “Source-Flow-Sink” analysis framework of population migration flow in Egypt was established by “Source-Sink” Theory and Flow Field Theory to study the migration population in Egypt. It reveals the spatial pattern of the migration population in Egypt and its flow field characteristics and provides theoretical basis for the formulation of population development policies and regional spatial governance planning. The results show that: (1) there are significant spatial differences in the size and rate of migration in Egypt. In 2017, the migration population in Egypt exceeded 2.2 million in total, with a migration rate of 2.33%, and the extreme multiple reached 80 and 12. (2) According to the spatial pattern of geographical distribution, the Source System is divided into five types: axis type, layer type, fan type, oblique symmetry type, and scattered jump type. There are only three types in Sink System, namely wide area coverage type, local development type, and scattered jump type. Source Places lie in the middle, Sink Places are symmetrical from east to west, and Exchange Places are concentrated along the Mediterranean coast in the north of Cairo on the whole, with the initial formation of a “core-periphery” spatial pattern. (3) The interprovincial population migration flow in Egypt is dominated by neighborhood penetration and polarization of high-rank nodes (capitals or regional economic centers), giving rise to 7 modes of central system spatial structures and 3 modes of pole-core interaction. The central system of flow fields with clear priorities and the streamline channel network with layered trunks and branches basically take shape, overall characterized by stepped runoff from east to west, and local convection from south to north.
Applying Artificial Intelligence in Physical Education and Future Perspectives
Authors: Lee Hyun Suk , Lee Junga
Published: January 2021

Artificial intelligence (AI) is gradually influencing every aspect of everyday life, including education. AI can also provide special support to learners through academic sustainability or discontinuation predictions. While AI research remains in its early stages, we must examine how it evolves and exerts its potential over time. By utilizing AI in physical education (PE), we can increase its potential use in sports applications, and enact changes upon the nature of PE, its visualization, and repeatability. Based on the concept of AI and related research areas, this study explores its principles and use in PE, and presents a focused, in-depth analysis of the areas of PE technology where AI could be applied—customized PE classes, knowledge provision, learner evaluation, and learner counseling methods. Our findings highlight the expertise required for future PE teachers in applying AI. Regarding practice implications, this study addresses the topic of AI innovations affecting all life domains, including PE; it highlights AI applications’ relevance to PE technology, based on existing research; it proposes that the implications of AI for PE may apply to other educational domains; and finally, it contributes to existing literature and also shares future research prospects regarding AI applications in education and sports.
A Proposal for Measuring In-Use Buildings’ Impact through the Ecological Footprint Approach
Authors: Pomè Alice Paola , Tagliaro Chiara , Ciaramella Gianandrea
Published: January 2021

To reduce the environmental impact of the construction sector, sustainable strategies for managing the in-use phase of buildings must be integrated urgently. Current green certifications present several limitations and, in particular, do not help determine where to focus for reducing the environmental demand of buildings. Among existing indicators, the ecological footprint (EF) is the most useful for assessing the buildings’ environmental performance through impact sources that reveal the over-consumption of resources. The present paper expands EF by taking into account the role of human behavior in over-consumption, and thus the efficiency in buildings’ use. After comparing ecological footprint with the existing green certifications, the paper demonstrates how a new integrated ecological footprint assessment can describe the impact of built-up, energy consumption, water consumption, material consumption, food and drink, mobility, waste generation, recycling potential, and occupants in the environmental efficiency of a building. The application of a case study demonstrates the reliability and the effectiveness of the model and shows that the estimated ecological deficit reflects not only the consumption of energy and materials, but also the behaviors of building users. This highlights the need for integrating a sustainable culture in the users of buildings.
Pedestrians-Cyclists Shared Spaces Level of Service: Comparison of Methodologies and Critical Discussion
Authors: Nikiforiadis Andreas , Basbas Socrates , Mikiki Foteini , Oikonomou Aikaterini , Polymeroudi Efrosyni
Published: January 2021

Pedestrians–cyclists shared spaces, sidewalks and streets are now a commonly implemented urban design solution in many cities, due to the willingness to promote sustainable mobility and the non-availability of public space. The proper design and management of these infrastructures requires an accurate evaluation of their performance. The most dominant evaluation metric is the level of service (LOS) and various methodologies have been proposed in the literature for its assessment in infrastructures that are being used by pedestrians, cyclists or by both of these two types of users. The present paper gathers and presents various methodologies, and it applies some of them on two pedestrians-cyclists shared spaces in a medium-sized city in Greece. The outcomes of the methodologies are being compared both among themselves and in relation to the opinions of the users, who participated in a questionnaire survey. The review of the literature, along with the application of some of the methodologies, leads to a fruitful discussion, which sets the groundwork for future research in the field of LOS and it also assists practitioners in selecting the appropriate methodologies for the assessment of pedestrian–cyclists shared spaces.
ACS: Construction Data Auto-Correction System—Taiwan Public Construction Data Example
Authors: Yu Meng-Lin , Tsai Meng-Han
Published: January 2021

This study aims to develop an automatic data correction system for correcting the public construction data. The unstructured nature of the construction data presents challenges for its management. The different user habits, time-consuming system operation, and long pretraining time all make the data management system full of data in an inconsistent format or even incorrect data. Processing the construction data into a machine-readable format is not only time-consuming but also labor-intensive. Therefore, this study used Taiwan’s public construction data as an example case to develop a natural language processing (NLP) and machine learning-based text classification system, coined as automatic correction system (ACS). The developed system is designed to automatically correct the public construction data, meanwhile improving the efficiency of manual data correction. The ACS has two main features: data correction that converts unstructured data into structured data; a recommendation function that provides users with a recommendation list for manual data correction. For implementation, the developed system was used to correct the data in the public construction cost estimation system (PCCES) in Taiwan. We expect that the ACS can improve the accuracy of the data in the public construction database to increase the efficiency of the practitioners in executing projects. The results show that the system can correct 18,511 data points with an accuracy of 76%. Additionally, the system was also validated to reduce the system operation time by 51.69%.
Is Gender Inequality a Barrier to Economic Growth? A Panel Data Analysis of Developing Countries
Authors: Altuzarra Amaia , Gálvez-Gálvez Catalina , González-Flores Ana
Published: January 2021

This study provides empirical evidence about the effects of various dimensions of gender inequalities (education, labour market and institutional representation) on economic growth. We use data from the World Bank Development Indicators database for the period 1990–2017. We initially use a large panel of 105 developing countries. Subsequently we study a panel with the sub-Saharan African (SSA) countries since this region is one of the poorest regions in the world. We estimate cross-country and panel regressions. The results suggest that gender equality in education contributes to economic growth and this is a common feature in developing countries. The contribution of equality in education to growth seems to be greater in the SSA countries than in the entire sample of developing countries. The female–male ratio of labour market participation is not statistically significant. We also find a significant link between the presence of women in parliaments and growth in the sample of all developing countries, while this relationship is negative for the SSA countries. It is likely that despite the increased participation of women in the political arena in these countries, women may still encounter major obstacles to altering political priorities and affecting economic growth.
Low Cost, Multi-Pollutant Sensing System Using Raspberry Pi for Indoor Air Quality Monitoring
Authors: Zhang He , Srinivasan Ravi , Ganesan Vikram
Published: January 2021

Deteriorating levels of indoor air quality is a prominent environmental issue that results in long-lasting harmful effects on human health and wellbeing. A concurrent multi-parameter monitoring approach accounting for most crucial indoor pollutants is critical and essential. The challenges faced by existing conventional equipment in measuring multiple real-time pollutant concentrations include high cost, limited deployability, and detectability of only select pollutants. The aim of this paper is to present a comprehensive indoor air quality monitoring system using a low-cost Raspberry Pi-based air quality sensor module. The custom-built system measures 10 indoor environmental conditions including pollutants: temperature, relative humidity, Particulate Matter (PM)2.5, PM10, Nitrogen dioxide (NO2), Sulfur dioxide (SO2), Carbon monoxide (CO), Ozone (O3), Carbon dioxide (CO2), and Total Volatile Organic Compounds (TVOCs). A residential unit and an educational office building was selected and monitored over a span of seven days. The recorded mean PM2.5, and PM10 concentrations were significantly higher in the residential unit compared to the office building. The mean NO2, SO2, and TVOC concentrations were comparatively similar for both locations. Spearman rank-order analysis displayed a strong correlation between particulate matter and SO2 for both residential unit and the office building while the latter depicted strong temperature and humidity correlation with O3, SO2, PM2.5, and PM10 when compared to the former.
Dynamic Accessibility Analysis of Urban Road-to-Freeway Interchanges Based on Navigation Map Paths
Authors: Yan Yadan , Guo Tianzhao , Wang Dongwei
Published: January 2021

Accessibility is important for road network planning and design, especially the accessibility of freeway entrances and exits, which reflects the convenience of travelers using freeways and the rationality of the connection between urban roads and freeways. Based on the path information of navigation map software, a new comprehensive travel impedance model to dynamically analyze the accessibility of freeway entrances and exits was proposed. The dynamic accessibility of freeway entrances and exits in Zhengzhou was studied using the proposed comprehensive impedance model, and the calculation results were analyzed. The accessibility of freeway entrances and exits is characterized by dynamic changes; the accessibility during the off-peak evening period is the highest, while that during the morning peak period and evening peak period is lower. The results of the comprehensive impedance model are roughly consistent with reality. From a location perspective, regardless of the period of time, the accessibility of freeway entrances and exits in the central and surrounding areas of Zhengzhou is always at a lower level, and during the off-peak afternoon period, the accessibility of the eastern part of the city is notably higher than that of the western part. Additionally, the accessibility of freeway entrances and exits is closely related to the traffic status of the road network and the characteristics of regional land use. The information can provide feedback for planning road networks and provide a reference for road network planning and traffic facility design.
Special Issue on Assessing the Modern Bioenergy Potential and Strategies for Sustainable Development: Transformations through Nexus, Policy, and Innovations
Authors: Khatiwada Dilip , Purohit Pallav
Published: January 2021

This editorial aims to summarize the five scientific contributions that contributed to the Special Issue assessing the modern bioenergy potential and strategies for sustainable development, considering the several aspects, viz [...]
University Teaching in Times of Confinement: The Light and Shadows of Compulsory Online Learning
Authors: del Arco Isabel , Silva Patricia , Flores Oscar
Published: January 2021

A quantitative study was carried out with the aim of analyzing the perspective of the students in relation to the factors that have influenced quality teaching during the confinement period resulting from the SARS-CoV-2 pandemic. To do this, an ad hoc questionnaire was designed and conducted in the months of June–July 2020. The sample consisted of 893 people who were studying at various Spanish universities. The results show little diversity in teaching methodologies; virtual teaching was carried out with the same parameters as face-to-face teaching. The role of the student body was one of passivity, consisting of little interaction with the teachers. Although it is true that there were no difficulties in following the course, there was limited attention paid to the emotional well-being of the students. Amongst the conclusions garnered significant, we point out the need to develop the adaptability of university teaching staff to unforeseen situations, as well as a continuing reflection on the model used in the teaching process mediated by digital technologies and the importance of promoting greater autonomy and self-regulation during learning.
Potential of Bioenergy in Rural Ghana
Authors: Nelson Nii , Darkwa Jo , Calautit John , Worall Mark , Mokaya Robert , Adjei Eunice , Kemausuor Francis , Ahiekpor Julius
Published: January 2021

Crop residues are common in rural Ghana due to the predominant role agriculture plays in livelihood activities in these communities. In this paper we investigate the prospects of exploiting agricultural crop residues for rural development in Ghana through bioenergy schemes. A theoretical energy potential of 623.84 PJ per year, which is equivalent to 19,781 MW was estimated using crop production data from the Food and Agricultural Organization of the United Nations and residue-to-product ratios. Ghana has a total installed generation capacity of 4577 MW which is four times less the energy potential of crop residues in the country. Cocoa pod husks were identified as important biomass resources for energy generation as they are currently wasted. To further assess the energy potential of cocoa pod husks, different cocoa pod husks samples were collected across the six cocoa growing regions in Ghana and thermo-chemically characterised using proximate and ultimate analysis. The low levels of nitrogen and sulphur observed, together with the high heating value, suggest that cocoa pod husks and for that matter crop residues are eco-friendly feedstock that can be used to power rural communities in Ghana.
Interrelationships between Land Use Land Cover (LULC) and Human Thermal Comfort (HTC): A Comparative Analysis of Different Spatial Settings
Authors: Yeo Lee Bak , Ling Gabriel Hoh Teck , Tan Mou Leong , Leng Pau Chung
Published: January 2021

A few studies on outdoor human thermal comfort (HTC) have been conducted in the tropical region in a hot and humid climate; however, there is a paucity of discussions on how exactly different spatial settings influence HTC. Thus, this paper aims to examine how land use land cover (LULC) affects HTC on the basis of the simulation of Predicted Mean Vote (PMV) and Physiologically Equivalent Temperature (PET) indices via ENVI-met and Rayman. The results reveal that people living in the urban area have a higher tendency to experience strong heat stress (25% of the areas with PMV ranging from 3.4 to 3.9 and 2% of the areas, where PMV reached 4.1), followed by the rural area (43% of the areas with PMV ranging from 2.1 to 2.4), and the suburban area (more than 50% of the areas with PMV values less than 2.4). Surprisingly, a concrete LULC in the suburb area exhibits a higher air temperature than an asphalt surface at 4 p.m., due to the large area of high albedo that increases the reflection of solar radiation, subsequently contributing to warming up the airmass. Similarly, sandy, and loamy LULC tend to emit more heat during nighttime, while the heat is absorbed slowly during daytime, and it is then slowly released during nighttime after 6 p.m. Spatial settings that promote heat stress in the urban area are mainly contributed by an LULC of asphalt, concrete, sandy, and loamy areas. Meanwhile, people in the suburban and rural areas are less likely to experience heat stress, due to agricultural plantations and lowland forest that provide shade, except for the barren lands-loamy areas. The result also indicates that tree-covered areas near the river in the suburban area afforded the best thermal experience with PMV of 2.1 and PET of 30.7. From the LULC comparison, it is pivotal to consider tree species (canopy density), surface material (albedo), sky-view factor, wind direction, and speed toward designing a more comfortable and sustainable environment.
ENER-BI: Integrating Energy and Spatial Data for Cities’ Decarbonisation Planning
Authors: Urrutia-Azcona Koldo , Usobiaga-Ferrer Elena , De Agustín-Camacho Pablo , Molina-Costa Patricia , Benedito-Bordonau Mauricia , Flores-Abascal Iván
Published: January 2021

Given the current climate emergency, our planet is suffering. Mitigation measures must be urgently deployed in urban environments, which are responsible for more than 70% of global CO2 emissions. In this sense, a deeper integration between energy and urban planning disciplines is a key factor for effective decarbonisation in urban environments. This is addressed in the Cities4ZERO decarbonisation methodology. This method specifically points out the need for technology-based solutions able to support that integration among both disciplines at a local level, enriching decision-making in urban decarbonisation policy-making, diagnosis, planning, and follow-up tasks, incorporating the spatial dimension to the whole process (GIS-based), as well as the possibilities of the digital era. Accordingly, this paper explores the demands of both integrated urban energy planning and European/Basque energy directives, to set the main requisites and functionalities that Decision Support Systems (DSSs) must fulfil to effectively support city managers and the urban decarbonisation process.
Towards a Successful Post COVID-19 Transition of Monitoring, Evaluation, and Learning in Complex Sustainability Science Research-to-Policy Projects
Authors: Szabo Sylvia , Nhau Brighton , Tsusaka Takuji W. , Kadigi Reuben M. J. , Payne Tanya , Kangile Joseph Rajabu , Park Kwang Soon , Couto Matheus , Runsten Lisen , Burgess Neil D.
Published: January 2021

There is an emerging body of literature focusing on the COVID-19 livelihoods and environmental impacts, as well as the effects of the pandemics on evidence generation. However, little attention has been paid to how COVID-19 has—and is likely to continue to—affect monitoring, evaluation, and learning (MEL) systems, specifically in the context of large sustainability science research-to-policy project consortia. Here, we provide a conceptual framework of MEL responsiveness to COVID-19 effects and discuss the specific pathways to successful MEL transition. Using the UKRI GCRF TRADE Hub as a case study, we provide some examples of possible adjustments within the new context.
Response of Morphological Characters and Photosynthetic Characteristics of Haloxylon ammodendron to Water and Salt Stress
Authors: Hu Dong , Lv Guanghui , Qie Yadong , Wang Hengfang , Yang Fang , Jiang Lamei
Published: January 2021

In arid desert areas, Haloxylon ammodendron plays an important role in maintaining the ecological balance of desert oases. However, there are few studies on the physiological characteristics of Haloxylon ammodendron under an environmental gradient. Here, we studied the changes in the morphological and photosynthetic characteristics and their correlations in Haloxylon ammodendron in the four habitats of the Ebinur Lake wetland. Our results show that in high-water and high-salt habitats, photosynthesis is affected by “stomata restriction,” while in other habitats, photosynthesis is mainly affected by “non-stomata restriction.” In addition, when the soil conditions were good, Haloxylon ammodendron chose leaf construction featuring high specific leaf area, while when the soil conditions were worse, it chose an opposite leaf construction model to ensure the optimal allocation of carbon assimilation products in heterogeneous habitats. This study will deepen our understanding of the trade-off strategy between the accumulation and distribution of plant photosynthate in special habitats in arid areas. The results are of theoretical value for analysis of the ecological adaptation mechanisms of plants in arid desert areas.
Commercial Spirits for Surfactant-Free Syntheses of Electro-Active Platinum Nanoparticles
Authors: Quinson Jonathan , Simonsen Søren Bredmose , Theil Kuhn Luise , Arenz Matthias
Published: January 2021

The Co4CatTM process is a simple, surfactant-free method to produce colloidal dispersions of precious metal nanoparticles in alkaline mono-alcohols. The synthesis is performed in low-boiling-point solvents and is relevant for industrial production. The robustness of the process is demonstrated by using three different commercial spirits as solvents to obtain Pt nanoparticles. The results demonstrate that careful control of the solvent purity is not needed to achieve the synthesis of stable 2 nm platinum nanoparticle colloids readily active electrocatalysts for energy conversion reactions like the methanol oxidation.
Modeling the Settling Velocity of a Sphere in Newtonian and Non-Newtonian Fluids with Machine-Learning Algorithms
Authors: Rushd Sayeed , Hafsa Noor , Al-Faiad Majdi , Arifuzzaman Md
Published: January 2021

The traditional procedure of predicting the settling velocity of a spherical particle is inconvenient as it involves iterations, complex correlations, and an unpredictable degree of uncertainty. The limitations can be addressed efficiently with artificial intelligence-based machine-learning algorithms (MLAs). The limited number of isolated studies conducted to date were constricted to specific fluid rheology, a particular MLA, and insufficient data. In the current study, the generalized application of ML was comprehensively investigated for Newtonian and three varieties of non-Newtonian fluids such as Power-law, Bingham, and Herschel Bulkley. A diverse set of nine MLAs were trained and tested using a large dataset of 967 samples. The ranges of generalized particle Reynolds number (ReG) and drag coefficient (CD) for the dataset were 10−3 < ReG (-) < 104 and 10−1 < CD (-) < 105, respectively. The performances of the models were statistically evaluated using an evaluation metric of the coefficient-of-determination (R2), root-mean-square-error (RMSE), mean-squared-error (MSE), and mean-absolute-error (MAE). The support vector regression with polynomial kernel demonstrated the optimum performance with R2 = 0.92, RMSE = 0.066, MSE = 0.0044, and MAE = 0.044. Its generalization capability was validated using the ten-fold-cross-validation technique, leave-one-feature-out experiment, and leave-one-data-set-out validation. The outcome of the current investigation was a generalized approach to modeling the settling velocity.
Consonance, Symmetry and Extended Outputs
Authors: Liao Yu-Hsien
Published: January 2021

In many real-world situations, performers always adopt different energy levels (strategies) to participate. Different from pre-existing results, this paper is devoted to proposing several generalized power outputs of the marginal index, the Banzhaf–Coleman index, and the Banzhaf–Owen index, respectively, by assigning different energy levels to all performers. Since these extended power outputs may not be efficacious, we further define the efficacious extensions of these power outputs, respectively. For each of these efficacious power outputs, we demonstrate that there exists a corresponding reduced game and related consonance property that can be used to characterize it. By focusing on the properties of symmetry and accordance, several axiomatic results are also introduced.