bluuebunny/crossref_metadata_2025 huggingface dataset:
University Students’ Engagement in Mobile Learning
Authors: Salhab Reham , Daher Wajeeh
Published: January 2023

The implementation of mobile learning seems to be an emerging topic in many educational institutions. As recently noticed, mobile technology has employed wireless technologies to communicate, think, learn, and share in order to spread and exchange information. Therefore, using mobile technologies in learning and teaching can create a positive environment in higher education. Hence, the purpose of this study is to evaluate mobile learning engagement among educational technology students. Data from three focus group discussions and 15 semi-structured interviews with students who experienced mobile learning were gathered using a qualitative approach design. A total of seventeen basic themes and four organizing themes were extracted, where the researchers categories of engagement, i.e., social engagement, cognitive engagement, emotional engagement, and behavioral engagement. In the present research, the findings indicate that social engagement themes included social–mobile interaction, building community, developing relationships, and competition. The cognitive engagement themes included attention, cognitive and meta-cognitive strategies, immersion, and cognitive curiosity. Emotional engagement themes included excitement and enjoyment, instructor comforting students, motivation, and emotional safety. Behavioral engagement themes included effort and time on task, attendance, participation, and positive conduct.
Agile Storyboard and Software Development Leveraging Smart Contract Technology in Order to Increase Stakeholder Confidence
Authors: Udvaros József , Forman Norbert , Avornicului Szilárd Mihály
Published: January 2023

We present a solution based on blockchain technology and smart contracts for agile project management in light of the continuing transition in the software development industry. Due to the fact that these technologies are self-executing, customized, and impervious to tampering, they are considered to be crucial for the transition to a more efficient, transparent, and transactive payment gateway between major stakeholders. These major stakeholders will be able to communicate through smart contracts, which will act as a bridge between them. As part of their responsibility, they will make sure that all of the terms of the contract are met and acknowledged by all members of the team. As a result of our research, we propose a model in which payouts could be automatically enabled and penalties or grants could be introduced based on performance. If any changes were to be made to the contract in the future, all parties involved would be automatically notified. To maintain the development cycle, they should accept these changes as soon as possible. Because of this, the product owner and client are able to concentrate their resources on more profitable and productive tasks, without the need to monitor this aspect of agile project management. Our proposed model brings together different partners with the objective of successfully developing different IT projects by leveraging software engineering solutions such as smart contracts.
Improved-Odd-Even-Prime Reconfiguration to Enhance the Output Power of Rectangular Photovoltaic Array under Partial Shading Conditions
Authors: Katiki Dileep , Yammani Chandrasekhar , Salkuti Surender Reddy
Published: January 2023

The output power of a PV (photovoltaic) array decreases due to the partial shading condition (PSC). If one or more PV modules receives less irradiance compared to other PV modules in a PV array then it is called PSC. To enhance the output power of PV array under PSC, Sudoku, and Optimal Sudoku Reconfiguration techniques are available in the literature for perfect squared PV arrays, such as 4 × 4, 9 × 9, and 16 × 16. Odd–Even and Odd–Even–Prime reconfigurations are available for rectangular PV arrays. To enhance the output power of rectangular PV array further, this paper proposed a new reconfiguration technique called Improved Odd–Even–Prime reconfiguration. To validate the proposed method, two PV arrays 9 × 9 and 8 × 9 have been implemented.
Telerehabilitation with Computer Vision-Assisted Markerless Measures: A Pilot Study with Rett Syndrome Patients
Authors: Nucita Andrea , Iannizzotto Giancarlo , Perina Michela , Romano Alberto , Fabio Rosa Angela
Published: January 2023

The use of telerehabilitation systems has shown a significant growth in the past years, demonstrating their crucial relevance in the time of the COVID-19 pandemic. Many devices and sensors have been proposed to analytically measure parameters for patient assessment, with limitations due to costs or feasibility. In this paper, we present a motor telerehabilitation system with computer vision-assisted markerless measures for patients with Rett syndrome. Twenty-one RTT (Rett syndrome) patients, with ages ranging from age 4 to 31 (Median: 12.50; IQR (interquartile range): 9.50–17.25) were recruited. The study follows a pre-test–post-test design, where the patients were submitted to a pre-test, treatment, post-test 1, treatment, post-test 2 procedure. Progress in patient outcomes was assessed by measuring joint passive range of movement (PRoM). Results show the reliability of our system, and the feasibility of a telerehabilitation treatment for RTT patients, with significant improvements in shoulder mobility and in elbow flexion and extension. Limited results in lower limbs suggest that home treatment should be fostered to reduce sedentary time.
Development of a Reference Device for the Calibration of Optical One-Shot Time-Interval Measurements
Authors: Kuhinek Dalibor , Bratko Tomislav , Vukošić Hrvoje , Gavranić Ivica
Published: January 2023

This paper presents the development of a device that creates two or more light pulses with a precision time delay in a range from microseconds to several seconds and for the purpose of the calibration of velocity of detonation (VOD) measurement instruments. The device was assembled, programmed, and tested for functionality. Measurements were conducted using a reference counter. First, a precision OCXO (oven-controlled crystal oscillator) was used as a clock source. For verification of programmed subroutines, a counter oscillator output port was used as a source of clock signal for the microcontroller. This enabled the cancellation of possible oscillator errors. The signal had to be converted from an AC sine signal to a signal with positive values only using a clamper circuit. By the proposed solution, a calculable standard of time delay between two light pulses was achieved. According to the obtained results, this device can be used to calibrate field measurement devices for VOD measurements in explosives or some other use where the measurement device records the time interval between multiple light pulses. This enables more confidence in measurement results, faster recognition of instrument drift and increases the quality of measurement.
A Mixed Hardware-Software Implementation of a High-Performance PMSM Controller
Authors: Milik Adam , Rudnicki Tomasz
Published: January 2023

Implementation of the permanent magnet synchronous motor vector control implies strong time dependencies. The control process requires precise measurement of motor shaft position and winding currents to establish correct driving. The tight time dependencies are difficult to achieve using a programmatic approach. Specific controller architecture is proposed for programmable systems on chip architectures enabling operations precise timing and improved processing performance. The controller is decomposed into a dedicated hardware interface system and programmatic part for easy implementation and modification of the control algorithm. The proposed architecture offers precise and repeatable input-output operations timing and assures meeting tight time dependencies. The control algorithm is executed as an interrupt service requested by the interface system in a constant processing period with relatively weak time dependencies. Additionally, the interface system preprocesses input and output signals reducing the computation effort and saving time for algorithm computations. The specific implementation enabled improved measurement of the motor’s windings current with suppression of disturbances caused by inverter operation. There is shown an efficient implementation of Parke’s and Clarke’s transformations using specific resources of modern programmable logic devices. In opposite to the software-managed implementation presented implementation assures completing processing faster, using a minimal number of hardware resources of the FPGA platform and offering the highest flexibility of software part implementation.
Educators’ Utilizing One-Stop Mobile Learning Approach amid Global Health Emergencies: Do Technology Acceptance Determinants Matter?
Authors: Salem Mostafa Aboulnour , Elshaer Ibrahim A.
Published: January 2023

In July 2022, the World Health Organization (WHO) declared the rapidly spreading monkeypox outbreak a global health emergency; in the future, this may cause the closure of higher education institutions and a shift toward digital learning. As before, specifically in March 2020, the WHO expressed that COVID-19 is a worldwide pandemic. This transformation was accompanied by the widespread adoption of mobiles and their applications in learning with organised or non-organised forms. Although many articles have recorded the importance and effectiveness of mobile learning in higher education, other articles have indicated the weak utilisation of mobile learning amid the COVID-19 pandemic, especially by university educators (UEs). In addition, these articles often focus on the opportunities, challenges, and weaknesses of mobile learning amid COVID-19, but few studies have handled the acceptance of the UEs to adopt a mobile learning approach amid COVID-19 by the unified theory of acceptance and use of technology (UTAUT). This article’s main contribution is extending the (UTAUT) model in context and reviewing the acceptance of the adoption of mobiles and their applications in education as an approach amid global health emergencies, i.e., COVID-19 and monkeypox. The data were gathered from university educators (N = 392) in Saudi Arabia. The hypotheses were evaluated with data that were analysed using structural equation modelling (SEM). The results demonstrated that six of the eight hypotheses had high and significant effects on behaviour intention (performance expectancy (PE), effort expectancy (EF), social influence (SI), facilitating conditions (FC), self-efficacy (SE), and users’ awareness (UA)). Two of the eight factors have insignificant or negative impacts on behaviour intention (users’ perceptions (UP) and technology challenges (TC)), which need an additional review by policymakers, practitioners, mobile learning providers, and investigators looking to develop efficient strategies concerning mobile learning.
Glocal Retriever: Glocal Image Retrieval Using the Combination of Global and Local Descriptors
Authors: Kim Zeu , Kim Youngin , Suh Young-Joo
Published: January 2023

Development of deep learning has led to progress in computer vision, including metric learning tasks such as image retrieval, through convolutional neural networks. In image retrieval, the metric distance (i.e., the similarity) between the images needs to be computed and then compared to return similar images. Global descriptors are good at extracting holistic features of an image, such as the overall shape of the main object and the silhouette. On the other hand, the local features extract the detailed features which the model uses to help classify similar images together. This paper proposes a descriptor mixer which takes advantage of both local and global descriptors (group of features combined into one) as well as different types of global descriptors for an effect of a lighter version of an ensemble of models (i.e., fewer parameters and smaller model size than those of actual ensemble of networks). As a result, the model’s performance improved about 1.36% (recall @ 32) when the combination of the descriptors were used. We empirically found out that the combination of GeM and MAC achieved the highest performance.
Design and Implementation of an Efficient Hardware Coprocessor IP Core for Multi-axis Servo Control Based on Universal SoC
Authors: Xin Jitong , Cha Meiyi , Shi Luojia , Jiang Xiaoliang , Long Chunyu , Lin Qichun , Li Hairong , Wang Fangcong , Wang Peng
Published: January 2023

The multi-axis servo control system has been extensively used in industrial control. However, the applications of traditional MCU and DSP chips in high-performance multi-axis servo control systems are becoming increasingly difficult due to their lack of computing power. Although FPGA chips can meet the computing power requirements of high-performance multi-axis servo control systems, their versatility is insufficient, and the chip is too costly for large-scale use. Therefore, when designing the universal SoC, it is better to directly embed the coprocessor IP core dedicated to accelerating the multi-motor vector control current loop operation into the universal SoC. In this study, a coprocessor IP core that can be flexibly embedded in a universal SoC was designed. The IP core based on time division multiplexing (TDM) technology could accelerate the multi-motor vector control current loop operation according to the hardware–software coordination scheme proposed in this study. The IP was first integrated into a universal SoC to verify its performance, and then the FPGA prototype verification for the SoC was performed under three-axis servo control systems. Secondly, the ASIC implementation of the IP was also conducted based on the CSMC 90 nm process library. The experimental results revealed that the IP had a small area and low power consumption and was suitable for application in universal SoC. Therefore, the cheap and low-power single universal SoC with the coprocessor IP can be suitable for multi-axis servo control.
Machine Learning Approach towards LoRaWAN Indoor Localization
Authors: Perković Toni , Dujić Rodić Lea , Šabić Josip , Šolić Petar
Published: January 2023

The growth of the Internet of Things (IoT) continues to be rapid, making it an essential part of information technology. As a result, IoT devices must be able to handle data collection, machine-to-machine (M2M) communication, and preprocessing of data, while also considering cost, processing power, and energy consumption. This paper introduces a system for device indoor localization that uses variations in the strength of the wireless signal. The proposed system addresses logistics use cases in which it is imperative to achieve reliable end-to-end delivery, such as pharmaceutic delivery, delivery of confidential documents and court exhibits, and even food, since the same is introduced into human organism and presents a potential risk of terrorist or other attack. This work proposes a concept based on low-power and low-cost LoRaWAN based system that utilizes a Machine Learning technique based on Neural Networks to achieve high accuracy in device indoor localization by measuring the signal strength of a beacon device. Furthermore, using signal strength measurements, that is, RSSI and SNR captured by LoRaWAN gateways, it is possible to estimate the location of the device point with an accuracy of up to 98.8%.
Rolling Bearing Fault Feature Selection Method Based on a Clustering Hybrid Binary Cuckoo Search
Authors: Sun Lijun , Xin Yan , Chen Tianfei , Feng Binbin
Published: January 2023

In order to solve the low accuracy in rolling bearing fault diagnosis caused by irrelevant and redundant features, a feature selection method based on a clustering hybrid binary cuckoo search is proposed. First, the measured motor signal is processed by Hilbert–Huang transform technology to extract fault features. Second, a clustering hybrid initialization technique is given for feature selection, combining the Louvain algorithm and the feature number. Third, a mutation strategy based on Levy flight is proposed, which effectively utilizes high-quality information to guide subsequent searches. In addition, a dynamic abandonment probability is proposed based on population sorting, which can effectively retain high-quality solutions and accelerate the convergence of the algorithm. Experimental results from nine UCI datasets show the effectiveness of the proposed improvement strategy. The open-source bearing dataset is used to compare the fault diagnosis accuracy of different algorithms. The experimental results show that the diagnostic error rate of this method is only 1.13%, which significantly improves classification accuracy and effectively realizes feature dimension reduction in fault datasets. Compared to similar methods, the proposed method has better comprehensive performance.
Variable Delayed Dual-Core Lockstep (VDCLS) Processor for Safety and Security Applications
Authors: Marcinek Krzysztof , Pleskacz Witold A.
Published: January 2023

Dual-Core Lockstep (DCLS) is one of the most commonly used techniques in applications requiring functional safety. As the semiconductor process nodes keep shrinking, the DCLS technique is also more and more frequently seen in industrial or even consumer electronics. The paper presents the novel approach to the DCLS technique. While the typical approach is to set the slave core delay as a fixed number of clock cycles, we allow the checker core to run freely behind the main core within the constrained boundaries of clock cycles. This increases the temporal diversity needed for common mode failure mitigation. The system integrity provided by DCLS may also be used in the area of security applications. In this paper, we show that the proposed Variable Delayed Dual-Core Lockstep technique can flatten the power consumption correlation between the running cores, essential for a wide range of attacks. The proposed technique was implemented in the RISC-V processor core and verified in the Xilinx VCU108 FPGA platform.
Pre-Layout Parasitic-Aware Design Optimizing for RF Circuits Using Graph Neural Network
Authors: Li Chenfeng , Hu Dezhong , Zhang Xiaoyan
Published: January 2023

The performance of analog and RF circuits is widely affected by the interconnection parasitic in the circuit. With the progress of technology, interconnection parasitics plays a larger role in performance deterioration. To solve this problem, designers must repeat layout design and validation process. In order to achieve an upgrade in the design efficiency, in this paper, a Graph Neural Network (GNN)-based pre-layout parasitic parameter prediction method is proposed and applied to the design optimization of a 28 nm PLL. With the new method adopted, the frequency band overlap rate of the VCO is improved by 2.3 percents for an equal design effort. Similarly, the optimized CP is superior to the traditional method with a 15 ps mismatch time. These improvements are achieved under the premise of greatly saving the optimization iteration and verification costs.
Wind Microturbine with Adjustable Blade Pitch Angle
Authors: Chudzik Stanisław
Published: January 2023

The article presents the results of research on the operation of a wind microturbine model with an adjustable blade pitch angle. The physical basics of wind turbine operation and the methods of its optimal control are discussed. The results of the measurements carried out for the selected blade geometry with the possibility of adjusting the pitch angle are presented. The tests were carried out for a resistive load with a linear characteristic and for a load with a non-linear characteristic of a Li-Po battery. The results of the operation of a simple MPPT control algorithm are presented. The practical methods of controlling larger wind turbines are not optimal for small and very small turbines. The conducted research focused on determining the possibility of using blades with an adjustable angle setting, depending on the rotational speed in wind microturbines. The use of a simple mechanism for changing the pitch angle of the blades depending on the rotational speed of the turbine can increase the efficiency of the microturbine in a wider range of wind speeds.
Impact of Plastic Blends on the Gaseous Product Composition from the Co-Pyrolysis Process
Authors: Muzyka Roksana , Gałko Grzegorz , Ouadi Miloud , Sajdak Marcin
Published: January 2023

The co-pyrolysis of various biomasses mixed with two types of plastic waste was investigated in this study. Mixture M1 consisted of 30% m/m styrene–butadiene rubber (SBR), 40% m/m polyethylene terephthalate (PET), and 30% m/m polypropylene (PP). M2 consisted of 40% m/m PET, 30% m/m PP, and 30% m/m acrylonitrile–butadiene–styrene copolymer (ABS). The SBR, ABS, and PP used in this study were from the automotive industry, while the PET originated from scrap bottles. Co-pyrolysis was performed using wood biomass, agricultural biomass, and furniture trash. Thermal treatment was performed on samples from room temperature to 400 or 600 °C at a heating rate of 10 °C/min under N2 at a flow rate of 3 dm3/min. Based on the findings of the experiments, an acceptable temperature was found for the fixed-bed pyrolysis of biomass–plastic mixtures with varying ratios, and the raw materials were pyrolyzed under the same conditions. The composition of the derived gaseous fraction was investigated. The co-pyrolysis studies and variance analysis revealed that combining biomass with plastic materials had a good influence on the gaseous fraction, particularly in the presence of 6.6–7.5% v/v hydrogen and a lower heating value of 15.11 MJ/m3. This type of gaseous product has great potential for use as a replacement for coke oven gas in metallurgy and other applications.
Advancements in Giant Reed (Arundo donax L.) Biomass Pre-Treatments for Biogas Production: A Review
Authors: Vasmara Ciro , Galletti Stefania , Cianchetta Stefano , Ceotto Enrico
Published: January 2023

Giant reed is a non-food, tall, rhizomatous, spontaneous perennial grass that is widely diffused in warm-temperate environments under different pedo-climatic conditions. In such environments, it is considered one of the most promising energy crops in terms of economic and environmental sustainability, as it can also be cultivated on marginal lands. Owing to its complex and recalcitrant structure due to the lignin content, the use of giant reed as a feedstock for biogas production is limited. Thus, pre-treatment is necessary to improve the methane yield. The objective of this review was to critically present the possible pre-treatment methods to allow the giant reed to be transformed in biogas. Among the studied pre-treatments (i.e., hydrothermal, chemical, and biological), alkaline pre-treatments demonstrated better effectiveness in improving the methane yield. A further opportunity is represented by hybrid pre-treatments (i.e., chemical and enzymatic) to make giant reed biomass suitable for bio-hydrogen production. So far, the studies have been carried out at a laboratory scale; a future challenge to research is to scale up the pre-treatment process to a pilot scale.
Evaluation of Eco-Innovation and Green Economy in EU Countries
Authors: Domaracká Lucia , Seňová Andrea , Kowal Dominik
Published: January 2023

A businesses with a green label is associated with resources that are sustainable. This business is linked to the green economy, which can be described as a form of economy that is responsible in relation to the environment and economic growth, and thus complementary. In this type of economy, viable products are created, but also solutions and practices that take the environment into account. It is well known that eco-innovation activities are closely linked to the development of an eco-business. The research sample consisted of 10 countries, namely the Slovak Republic, the Czech Republic, Poland, Hungary, Austria, Germany, France, Italy, Sweden, and Finland, which were selected by purposive sampling. In this article, we look at eco innovations in selected countries, specifically ranking them, where we have divided countries into different levels, from countries that are at the super eco-innovation level, to countries that are in the middle zone, to countries that are significantly lagging in this trend. To classify countries into each level, we looked at the following variables: eco-innovation inputs, eco-innovation activities, environmental outcomes, socio-economic outcomes, and the eco-innovation index itself. Taking these sub-results into account, we determined where countries are, in other words, which level they have reached. We found that there are significant differences between countries. As we conclude, there are several reasons for this, but one of them is the lack of communication, coordination, and synergy between institutions, government, and SMEs, which are the drivers of eco-innovation. The supporting quantitative data collection method was data collection and structured observation, which is more precise and therefore provides more detailed information about the reality under study. For the purpose of this thesis, data were obtained from the Statistical Office of the European Union, that is, Eurostat, which is responsible for publishing pan-European statistics and indicators that allowed us to compare countries. In the survey, we compared the five most recent years for which Eurostat data were available, namely 2017, 2018, 2019, 2020, and 2021. The overall score of a European Union member state is calculated as the unweighted average of 16 sub-indicators. It shows how well each Member State performs in terms of eco-innovation compared to the European Union average of 100.
A Hybrid Master–Slave Control Strategy for Multiple Distributed Generators in Microgrid
Authors: Chen Yanxia , Li Jing , Wen Yu , Sehnan Moeed , Xu Wanyu
Published: January 2023

The problem of insufficient regulation ability in isolated microgrid operations in traditional master–slave control is targeted in this research. A hybrid master–slave control strategy is proposed to operate multiple distributed generators (DGs) in a microgrid with alleviated regulation characteristics. Firstly, a virtual synchronous generator control is adopted in the master DG to provide voltage and frequency support for the system; however, the lack of participation of the slave DG control in traditional PQ droop control in the system regulation makes a master DG susceptible to any load variation. The problem is resolved by proposing an improved droop control strategy, which ensures that the slave DG has similar output droop characteristics as the master DG and thus can respond to system load disturbances alongside the master DG. Secondly, virtual coordinate transformation and virtual impedance control are introduced to realize the decoupling and precise distribution of output power of multiple DGs. Finally, a simulation and experimental platform for a multi-DGs parallel system are established to verify the effectiveness of the proposed strategy.
Application of Alkali-Activated Sustainable Materials: A Step towards Net Zero Binder
Authors: Lanjewar Bhagyashri A. , Chippagiri Ravijanya , Dakwale Vaidehi A. , Ralegaonkar Rahul V.
Published: January 2023

Economic growth and rapid urbanization have resulted in the increase in demand for infrastructure development. To meet this ever increasing demand, conventional construction materials such as concrete are used, which requires an energy intensive process that in turn impacts the environment adversely. Ordinary Portland Cement, being the dominant binder in the industry, contributes around 8% of worldwide annual carbon emissions, and this is expected to reach around 20% by 2050. Population growth has resulted in the significant increase in agro-industrial waste generation during recent years. Inadequate waste management raises a number of environmental concerns. With the growing economy and rising living standards, global raw material consumption is expected to double by 2060. The reutilization of waste materials will aid in their management, while conserving the available resources. Alkali-activated materials (AAM) have recently been introduced as an eco-friendly alternative to conventional binders with fewer environmental impacts. AAM reduce the need for Ordinary Portland Cement (OPC) by substituting it with supplementary cementitious materials (SCM), and therefore, reducing the amount of subsequent carbon emissions. Alkali activation is a complex chemical process between the precursors (alumino-silicate materials) and their dissolution in the activators. Different materials react to alkali activators in different ways depending on their properties. The current study aims to provide a critical review of potential agro-industrial wastes on the fresh and hardened properties of alkali-activated concrete (AAC). To understand the design and development of AAC, influencing the parameters such as the molarity of NaOH, alkali activators, and the ratio of the activators have been discussed in detail. The curing regime and its effect on the behavior of alkali-activated concrete are mentioned. The different admixtures used to regulate the properties of AAC are highlighted. AAC exhibited optimized embodied energy, operational energy, life cycle cost, CO2 emission, and raw material consumption rates than the conventional concrete did. However, these results varied based on the precursors used in them. This paper focuses on the design and development of AAC, and it should be viewed as an important contribution towards the adoption of AAC in practical applications. The study presents the potential of AAM as a net zero binder in the making of sustainable concrete with enhanced properties.
Carbon Analysis, Life Cycle Assessment, and Prefabrication: A Case Study of a High-Rise Residential Built-to-Rent Development in the UK
Authors: Arslan Dilek , Sharples Steve , Mohammadpourkarbasi Haniyeh , Khan-Fitzgerald Raheela
Published: January 2023

Recent research relating to energy use and carbon emissions by buildings has started to move from operational energy carbon impacts to the embodied energy/carbon impacts of buildings, and the methods and approaches used in architectural design to reduce embodied carbon have become more prominent. From a practitioner’s perspective, working with an ‘in-house’ Life Cycle Assessment (LCA) tool has become a growing trend for architects, and one perceived way of improving the LCA outcomes of a proposed building is to consider prefabrication of the construction process. Initiatives such as the Low Energy Transformation Initiative (LETI) and government bodies such as Greater London Authorities (GLA) provide guidance on LCA and upfront carbon emission targets for transitioning to net zero by 2050. The aim of this study was to establish (i) the LCA impacts from prefabricated residential buildings against current benchmarks; (ii) boundaries and opportunities in architectural practice in the UK when conducting an LCA; (iii) the effectiveness of an in-house LCA tool. This study shows that, although the life-cycle emissions of this prefabricated building achieved a low band in the LETI labelling system, with 1076 kgCO2e/m², it still performs better than the business-as-usual model value of 1200 kgCO2e/m². The results also reveal that the construction industry is not ready to provide realistic data on the prefabrication process to test its advantages compared to conventional constructional methods. However, having an in-house LCA tool provides a faster and more comprehensive LCA due to the commitment to carbon assessment in the office and saves time compared to manual calculations.
Intelligent Control Schemes for Maximum Power Extraction from Photovoltaic Arrays under Faults
Authors: Ul-Haq Azhar , Fahad Shah , Gul Saba , Bo Rui
Published: January 2023

Investigation of power output from PV arrays under different fault conditions is an essential task to enhance performance of a photovoltaic system under all operating conditions. Significant reduction in power output can occur during various PV faults such as module disconnection, bypass diode failure, bridge fault, and short circuit fault under non-uniform shading conditions. These PV faults may cause several peaks in the characteristics curve of PV arrays, which can lead to failure of the MPPT control strategy. In fact, impact of a fault can differ depending on the type of PV array, and it can make the control of the system more complex. Therefore, consideration of suitable PV arrays with an effective control design is necessary for maximum power output from a PV system. For this purpose, the proposed study presents a comparative study of two intelligent control schemes, i.e., fuzzy logic (FL) and particle swarm optimization (PSO), with a conventional control scheme known as perturb and observe (P&O) for power extraction from a PV system. The comparative analysis is based on the performance of the control strategies under several faults and the types of PV modules, i.e., monocrystalline and thin-film PV arrays. In this study, numerical analysis for complex fault scenarios like multiple faults under partial shading have also been performed. Different from the previous literature, this study will reveal the performance of FL-, PSO-, and P&O-based MPPT strategies to track maximum peak power during multiple severe fault conditions while considering the accuracy and fast-tracking efficiencies of the control techniques. A thorough analysis along with in-depth quantitative data are presented, confirming the superiority of intelligent control techniques under multiple faults and different PV types.
Structural and Electrochemical Properties of Musa acuminata Fiber Derived Hard Carbon as Anodes of Sodium-Ion Batteries
Authors: Thenappan Meenatchi , Mathiyalagan Kouthaman , Abdollahifar Mozaffar , Rengapillai Subadevi , Marimuthu Sivakumar
Published: January 2023

Hard carbon (HC) was successfully synthesized using a bio-waste precursor from Musa acuminata fiber (MaF) as an eco-friendly option through the pyrolysis process at 500 °C. Further, it was activated using the chemical activating agents, NaOH and ZnCl2, at 900 °C, named Na–MaFDHC and Zn–MaFDHC. The MaFDHCs are employed as anode materials for emerging sodium-ion batteries (NIBs). The nitrogen (N2) adsorption and desorption studies and HRTEM images resulted that the MaFDHCs have a mesoporous nature. The surface area and pore diameter of the carbon materials are increased significantly after the treatment with activating agents, which are important factors for anodes of NIBs. The electrochemical performance of the MaFDHCs depends on the activation agent. Zn–MaFDHC with a higher surface area showed better results, yielding a charge capacity of about 114 mAh g−1 at a 1C rate.
The Negative Impact of Electrical Energy Subsidies on the Energy Consumption—Case Study from Jordan
Authors: Albatayneh Aiman , Juaidi Adel , Manzano-Agugliaro Francisco
Published: January 2023

Many developing countries subsidise energy (petroleum fuel products, natural gas and electricity), which was reflected in an extra pressure on the national budget, and this will support inefficient use of energy. In this study, the effects of electrical energy subsidies on the total electrical energy consumption in the residential sector were examined. Data on more than 260,000 Jordanian ordinary customers were collected, and the energy consumption of more than 1000 energy-extra subsidised Irbid District Electricity Distribution Company (IDECO) staff members was recorded over a 2-year period (2017 and 2018). These two groups were compared to examine the consequences of subsidising energy on the energy consumption and the consumption behaviour in the residential sector. The analysis revealed that ordinary householders consume around 296 kWh/month, while for the subsidised group 615 kWh/month was noted. Energy consumption increased during the summer and winter months, especially in the subsidised group, due to the heavy reliance on mechanical systems for cooling and heating. Electricity full price (without any subsidies) can be a very effective way to control the demand profile. It can be structured to encourage customers (generally those that have significant electricity demand) to reduce their total usage as well as peak demand (thus reducing the pressure on the grid and the power plant) by charging them full electricity prices.
A New Cloud-Based IoT Solution for Soiling Ratio Measurement of PV Systems Using Artificial Neural Network
Authors: Ul Mehmood Mussawir , Ulasyar Abasin , Ali Waleed , Zeb Kamran , Zad Haris Sheh , Uddin Waqar , Kim Hee-Je
Published: January 2023

Solar energy is considered the most abundant form of energy available on earth. However, the efficiency of photovoltaic (PV) panels is greatly reduced due to the accumulation of dust particles on the surface of PV panels. The optimization of the cleaning cycles of a PV power plant through condition monitoring of PV panels is crucial for its optimal performance. Specialized equipment and weather stations are deployed for large-scale PV plants to monitor the amount of soil accumulated on panel surface. However, not much focus is given to small- and medium-scale PV plants, where the costs associated with specialized weather stations cannot be justified. To overcome this hurdle, a cost-effective and scalable solution is required. Therefore, a new centralized cloud-based solar conversion recovery system (SCRS) is proposed in this research work. The proposed system utilizes the Internet of Things (IoT) and cloud-based centralized architecture, which allows users to remotely monitor the amount of soiling on PV panels, regardless of the scale. To improve scalability and cost-effectiveness, the proposed system uses low-cost sensors and an artificial neural network (ANN) to reduce the amount of hardware required for a soiling station. Multiple ANN models with different numbers of neurons in hidden layers were tested and compared to determine the most suitable model. The selected ANN model was trained using the data collected from an experimental setup. After training the ANN model, the mean squared error (MSE) value of 0.0117 was achieved. Additionally, the adjusted R-squared (R2) value of 0.905 was attained on the test data. Furthermore, data is transmitted from soiling station to the cloud server wirelessly using a message queuing telemetry transport (MQTT) lightweight communication protocol over Wi-Fi network. Therefore, SCRS depicts a complete wireless sensor network eliminating the need for extra wiring. The average percentage error in the soiling ratio estimation was found to be 4.33%.
Species Sensitivity to Hydrologic Whiplash in The Tree-Ring Record of the High Sierra Nevada
Authors: Winitsky Anabel G. , Meko David M. , Taylor Alan H. , Biondi Franco
Published: January 2023

The year-to-year variability of precipitation has significant consequences for water management and forest health. “Whiplash” describes an extreme mode of this variability in which hydroclimate switches abruptly between wet and dry conditions. In this study, a pool of total-ring-width indices from five conifer species (Abies magnifica, Juniperus grandis, Pinus ponderosa, Pinus jeffreyi, and Tsuga mertensiana) in the Sierra Nevada is used to develop reconstructions of water-year precipitation using stepwise linear regression on lagged chronologies, and the reconstructions are analyzed for their ability to track whiplash events. A nonparametric approach is introduced to statistically classify positive and negative events, and the success of matching observed events with the reconstructions is evaluated using a hypergeometric test. Results suggest that reconstructions can effectively track whiplash events, but that tracking ability differs among species and sites. Although negative (dry-to-wet) events (1921–1989) are generally tracked more consistently than positive events, Tsuga stands out for strong tracking of positive events. Tracking ability shows no clear relationship to variance explained by reconstructions, suggesting that efforts to extend whiplash records with tree-ring data should consider optimizing reconstruction models for the whiplash signal.
Urban Metabolism-Based Approaches for Promoting Circular Economy in Buildings Refurbishment
Authors: Fernandes Joana , Ferrão Paulo
Published: January 2023

The systemic transformation towards climate neutral cities depends on a dramatic reduction in the use of natural resources, whose use are directly or indirectly associated with greenhouse gas emissions. This means improving Urban Metabolism (UM) and one of the most promising pathways is to promote Circular Economy (CE) practices in the existing building stock, as this approach could reduce global CO2e emissions from building materials by 38% in 2050. However, although resource efficiency is at core of CE, there are still only a few established connections between CE and UM. This paper aims to fill this gap by adopting a three-tier approach based on the dimensions and the spatial implementation of CE (building, neighbourhood and UM scales), with the aim of discussing strategies for CE implementation. Although this not a one-size-fits-all process and cities must adapt these strategies to their local contexts, the strategic actions offered by this paper will facilitate the future development of a dedicated framework for buildings refurbishment using the principles of CE and the definition of multisectoral policy-based actions, in line with the decarbonization goals for cities, which will contribute to improving UM.
Effects of Post-Fire Management on a Mediterranean Small Mammal Community
Authors: Torre Ignasi , Ribas Alexis , Puig-Gironès Roger
Published: January 2023

Wildfires simplify ecosystems, modifying the ecological niches of the fauna living in the recently burned areas. Small mammals respond rapidly to changes in habitat structure and composition after fire, but the effects of fire can be ameliorated by some management strategies (e.g., salvage logging). Hence, it is necessary to explore whether alternative management strategies may be able to return the ecosystem to its initial state. We studied the small mammal community by live trapping on eight plots under different post-fire treatments in Sant Llorenç del Munt i l’Obac Natural Park (Barcelona province, NE Spain). At the community level, an increase in overall relative abundance and species density was observed in the burned areas. Apodemus sylvaticus, the most abundant mammal in study area, used woody debris piles as a shelter against predators. Mus spretus was more abundant in post-fire sites with large open areas interspersed with woody debris piles. Crocidura russula steadily increased its presence in later successional stages when ground cover became more complex. Our results suggest that combining different management strategies may be appropriate to improve the habitat suitability and biodiversity of small mammals and other key open-land species throughout the burned area.
Hybrid Approach of Fractional Generalized Pareto Motion and Cosine Similarity Hidden Markov Model for Solar Radiation Forecasting
Authors: Song Wanqing , Deng Wujin , Chen Dongdong , Jin Rong , Kudreyko Aleksey
Published: January 2023

Power from solar energy is not reliable, due to weather-related factors, which diminishes the power system’s reliability. Therefore, this study suggests a way to predict the intensity of solar irradiance using various statistical algorithms and artificial intelligence. In particular, we suggest the use of a hybrid predictive model, combining statistical properties and historical data training. In order to evaluate the maximum prediction steps of solar irradiance, the maximum Lyapunov exponent was applied. Then, we used the cosine similarity algorithm in the hidden Markov model for the initial prediction. The combination of the Hurst exponent and tail parameter revealed the self-similarity and long-range dependence of the fractional generalized Pareto motion, which enabled us to consider the iterative predictive model. The initial prediction was substituted into a stochastic differential equation to achieve the final prediction, which prevents error propagation. The effectiveness of the hybrid model was demonstrated in the case study.
Non-Linear Analysis of Novel Equivalent Circuits of Single-Diode Solar Cell Models with Voltage-Dependent Resistance
Authors: Vellingiri Mahendiran , Rawa Muhyaddin , Alghamdi Sultan , Alhussainy Abdullah A. , Althobiti Ahmed S. , Calasan Martin , Micev Mihailo , Ali Ziad M. , Abdel Aleem Shady H. E.
Published: January 2023

The most commonly used model of solar cells is the single-diode model, with five unknown parameters. First, this paper proposes three variants of the single-diode model, which imply the voltage dependence of the series resistance, parallel resistance, and both resistors. Second, analytical relationships between the current and the voltage expressed were derived using the Lambert W function for each proposed model. Third, the paper presents a hybrid algorithm, Chaotic Snake Optimization (Chaotic SO), combining chaotic sequences with the snake optimization algorithm. The application of the proposed models and algorithm was justified on two well-known solar photovoltaic (PV) cells—RTC France solar cell and Photowatt-PWP201 module. The results showed that the root-mean-square-error (RMSE) values calculated by applying the proposed equivalent circuit with voltage dependence of both resistors are reduced by 20% for the RTC France solar cell and 40% for the Photowatt-PWP201 module compared to the standard single-diode equivalent circuit. Finally, an experimental investigation was conducted into the applicability of the proposed models to a solar laboratory module, and the results obtained proved the relevance and effectiveness of the proposed models.
Structure-Related Mechanical Properties and Bioactivity of Silica–Gelatin Hybrid Aerogels for Bone Regeneration
Authors: Reyes-Peces María V. , Fernández-Montesinos Rafael , Mesa-Díaz María del Mar , Vilches-Pérez José Ignacio , Cárdenas-Leal Jose Luis , de la Rosa-Fox Nicolás , Salido Mercedes , Piñero Manuel
Published: January 2023

We report the synthesis of mesoporous silica–gelatin hybrid aerogels with 15, 25, and 30 wt. % gelatin contents, using 3-glycidoxypropyl trimethoxysilane (GPTMS) as a coupling agent, for tissue-engineering applications. Aerogels were obtained using a one-step sol–gel process followed by CO2 supercritical drying, resulting in crack-free monolith samples with bulk densities ranging from 0.41 g cm−3 to 0.66 g cm−3. Nitrogen adsorption measurements revealed an interconnected mesopore network and a general decrease in the textural parameters: specific surface areas (651–361 m2 g−1), pore volume (1.98–0.89 cm3 g−1), and pore sizes (10.8–8.6 nm), by increasing gelatin content. Thermogravimetric analysis (TGA), Fourier-transform infrared (FTIR) spectroscopy and uniaxial compression experiments confirmed that the structure, thermal properties and mechanical behavior of these aerogels changed significantly when the concentration of gelatin reached 25 wt.%, suggesting that this composition corresponds to the percolation threshold of the organic phase. In addition, the samples exhibited hydrophilic behavior and extremely fast swelling in phosphate-buffered saline (PBS), with swelling ratios from 2.32 to 3.32. Furthermore, in vitro bioactivity studies revealed a strong relationship between the kinetics of the nucleation and growth processes of hydroxyapatite in simulated body fluid (SBF) and the gelatin content. The live/dead assay revealed no cytotoxicity in HOB® osteoblasts in vitro and a positive influence on cell growth, focal adhesion development, and cytoskeletal arrangement for cell adhesion. Mineralization assays confirmed the positive effects of the samples on osteoblast differentiation. The biomaterials described are versatile, can be easily sterilized and are suitable for a wide range of applications in bone tissue-engineering, either alone or in combination with bioactive-reinforced phases.