bluuebunny/crossref_metadata_2025 huggingface dataset:
Single-Satellite Integrated Navigation Algorithm Based on Broadband LEO Constellation Communication Links
Authors: Ye Lvyang , Yang Yikang , Jing Xiaolun , Ma Jiangang , Deng Lingyu , Li Hengnian
Published: February 2021

With the rapid development of satellite technology and the need to satisfy the increasing demand for location-based services, in challenging environments such as indoors, forests, and canyons, there is an urgent need to improve the position accuracy in these environments. However, traditional algorithms obtain the position solution through time redundancy in exchange for spatial redundancy, and they require continuous observations that cannot satisfy the real-time location services. In addition, they must also consider the clock bias between the satellite and receiver. Therefore, in this paper, we provide a single-satellite integrated navigation algorithm based on the elimination of clock bias for broadband low earth orbit (LEO) satellite communication links. First, we derive the principle of LEO satellite communication link clock bias elimination; then, we give the principle and process of the algorithm. Next, we model and analyze the error of the system. Subsequently, based on the unscented Kalman filter (UKF), we model the state vector and observation vector of our algorithm and give the state and observation equations. Finally, for different scenarios, we conduct qualitative and quantitative analysis through simulations, and the results show that, whether in an altimeter scenario or non-altimeter scenario, the performance indicators of our algorithm are significantly better than the inertial navigation system (INS), which can effectively overcome the divergence problem of INS; compared with the medium earth orbit (MEO) constellation, the navigation trajectory under the LEO constellation is closer to the real trajectory of the aircraft; and compared with the traditional algorithm, the accuracy of each item is improved by more than 95%. These results show that our algorithm not only significantly improves the position error, but also effectively suppresses the divergence of INS. The algorithm is more robust and can satisfy the requirements of cm-level real-time location services in challenging environments.
Potential Driving Factors on Surface Solar Radiation Trends over China in Recent Years
Authors: Wang Qiuyan , Zhang Hua , Yang Su , Chen Qi , Zhou Xixun , Shi Guangyu , Cheng Yueming , Wild Martin
Published: February 2021

The annual mean surface solar radiation (SSR) trends under all-sky, clear-sky, all-sky-no-aerosol, and clear-sky-no-aerosol conditions as well as their possible causes are analyzed during 2005–2018 across China based on different satellite-retrieved datasets to determine the major drivers of the trends. The results confirm clouds and aerosols as the major contributors to such all-sky SSR trends over China but play differing roles over sub-regions. Aerosol variations during this period result in a widespread brightening, while cloud effects show opposite trends from south to north. Moreover, aerosols contribute more to the increasing all-sky SSR trends over northern China, while clouds dominate the SSR decline over southern China. A radiative transfer model is used to explore the relative contributions of cloud cover from different cloud types to the all-types-of-cloud-cover-induced (ACC-induced) SSR trends during this period in four typical sub-regions over China. The simulations point out that the decreases in low-cloud-cover (LCC) over the North China Plain are the largest positive contributor of all cloud types to the marked annual and seasonal ACC-induced SSR increases, and the positive contributions from both high-cloud-cover (HCC) and LCC declines in summer and winter greatly contribute to the ACC-induced SSR increases over East China. The contributions from medium-low-cloud-cover (mid-LCC) and LCC variations dominate the ACC-caused SSR trends over southwestern and South China all year round, except for the larger HCC contribution in summer.
Target Localization Based on Bistatic T/R Pair Selection in GNSS-Based Multistatic Radar System
Authors: Shao Yu’e , Ma Hui , Zhou Shenghua , Wang Xue , Antoniou Michail , Liu Hongwei
Published: February 2021

To cope with the increasingly complex electromagnetic environment, multistatic radar systems, especially the passive multistatic radar, are becoming a trend of future radar development due to their advantages in anti-electronic jam, anti-destruction properties, and no electromagnetic pollution. However, one problem with this multi-source network is that it brings a huge amount of information and leads to considerable computational load. Aiming at the problem, this paper introduces the idea of selecting external illuminators in the multistatic passive radar system. Its essence is to optimize the configuration of multistatic T/R pairs. Based on this, this paper respectively proposes two multi-source optimization algorithms from the perspective of resolution unit and resolution capability, the Covariance Matrix Fusion Method and Convex Hull Optimization Method, and then uses a Global Navigation Satellite System (GNSS) as an external illuminator to verify the algorithms. The experimental results show that the two optimization methods significantly improve the accuracy of multistatic positioning, and obtain a more reasonable use of system resources. To evaluate the algorithm performance under large number of transmitting/receiving stations, further simulation was conducted, in which a combination of the two algorithms were applied and the combined algorithm has shown its effectiveness in minimize the computational load and retain the target localization precision at the same time.
Passive Equalization Networks—Efficient Synthesis Approach for High-Speed Signal Integrity Characterization
Authors: Brinaru Diana
Published: February 2021

High data rates challenges and long traces from current state-of-the-art systems imply high attenuation. In the present article, we will present a detailed process of synthesis of equalizers, for choosing the correct one for a given application. The methods are based on scattering parameters applied on interconnections modeled as microstrip or stripline. Firstly, one may have an overview of types of equalizers, passive, active, and adaptive ones, and a detailed filter synthesis is applied in microwave systems having as start point the insertion loss of a given trace on a given substrate. Next, time domain analyses offer a better understanding of the performance of the interconnect, based on eye diagram inspection and the variation of waveforms with time. Finally, we will present results based on simulation of the equalizers network in a microstrip technology followed by discussions and conclusions. The study proposes to use equalizers in either the transmitter or receiver point, proposes a bridge equalizer with the cost of additional elements but improved constant input, output impedance, and also a new variant for single ended trace based on microwave resonator is proposed. Performance is demonstrated by results from simulations.
Tactile and Thermal Sensors Built from Carbon–Polymer Nanocomposites—A Critical Review
Authors: Yuan Chenwang , Tony Anthony , Yin Ruixue , Wang Kemin , Zhang Wenjun
Published: February 2021

This paper provides a critical review of tactile and thermal sensors which are built from carbon nanomaterial-filled polymer composites (CNPCs). To make the review more comprehensive and systematic, the sensors are viewed as a system, and a general knowledge architecture for a system called function-context-behavior-principle-state-structure (FCBPSS) is employed to classify information as well as knowledge related to CNPC sensors. FCBPSS contains six basic concepts, namely, F: function, C: context, B: behavior, P: principle, and SS: state and structure. As such, the principle that explains why such composites can work as temperature and pressure sensors, various structures of the CNPC sensor, which realize the principle, and the behavior and performance of CNPC sensors are discussed in this review. This review also discusses the fabrication of the CNPC sensor. Based on the critical review and analysis, the future directions of research on the CNPC sensor are discussed; in particular, the need to have a network of CNPC sensors that can be installed on curved bodies such as those of robots is elaborated.
Constrained L1-Norm Minimization Method for Range-Based Source Localization under Mixed Sparse LOS/NLOS Environments
Authors: He Chengwen , Yuan Yunbin , Tan Bingfeng
Published: February 2021

Under mixed sparse line-of-sight/non-line-of-sight (LOS/NLOS) conditions, how to quickly achieve high positioning accuracy is still a challenging task and a critical problem in the last dozen years. To settle this problem, we propose a constrained L1 norm minimization method which can reduce the effects of NLOS bias for improve positioning accuracy and speed up calculation via an iterative method. We can transform the TOA-based positioning problem into a sparse optimization one under mixed sparse LOS/NLOS conditions if we consider NLOS bias as outliers. Thus, a relatively good method to deal with sparse localization problem is L1 norm. Compared with some existing methods, the proposed method not only has the advantages of simple and intuitive principle, but also can neglect NLOS status and corresponding NLOS errors. Experimental results show that our algorithm performs well in terms of computational time and positioning accuracy.
IoT Registration and Authentication in Smart City Applications with Blockchain
Authors: Ferreira Célio Márcio Soares , Garrocho Charles Tim Batista , Oliveira Ricardo Augusto Rabelo , Silva Jorge Sá , Cavalcanti Carlos Frederico Marcelo da Cunha
Published: February 2021

The advent of 5G will bring a massive adoption of IoT devices across our society. IoT Applications (IoT Apps) will be the primary data collection base. This scenario leads to unprecedented scalability and security challenges, with one of the first areas for these applications being Smart Cities (SC). IoT devices in new network paradigms, such as Edge Computing and Fog Computing, will collect data from urban environments, providing real-time management information. One of these challenges is ensuring that the data sent from Edge Computing are reliable. Blockchain has been a technology that has gained the spotlight in recent years, due to its robust security in fintech and cryptocurrencies. Its strong encryption and distributed and decentralized network make it potential for this challenge. Using Blockchain with IoT makes it possible for SC applications to have security information distributed, which makes it possible to shield against Distributed Denial of Service (DDOS). IoT devices in an SC can have a long life, which increases the chance of having security holes caused by outdated firmware. Adding a layer of identification and verification of attributes and signature of messages coming from IoT devices by Smart Contracts can bring confidence in the content. SC Apps that extract data from legacy and outdated appliances, installed in inaccessible, unknown, and often untrusted urban environments can benefit from this work. Our work’s main contribution is the development of API Gateways to be used in IoT devices and network gateway to sign, identify, and authorize messages. For this, keys and essential characteristics of the devices previously registered in Blockchain are used. We will discuss the importance of this implementation while considering the SC and present a testbed that is composed of Blockchain Ethereum and real IoT devices. We analyze the transfer time, memory, and CPU impacts during the sending and processing of these messages. The messages are signed, identified, and validated by our API Gateways and only then collected for an IoT data management application.
Application of a Low-Cost Electronic Nose for Differentiation between Pathogenic Oomycetes Pythium intermedium and Phytophthora plurivora
Authors: Borowik Piotr , Adamowicz Leszek , Tarakowski Rafał , Wacławik Przemysław , Oszako Tomasz , Ślusarski Sławomir , Tkaczyk Miłosz
Published: February 2021

Compared with traditional gas chromatography–mass spectrometry techniques, electronic noses are non-invasive and can be a rapid, cost-effective option for several applications. This paper presents comparative studies of differentiation between odors emitted by two forest pathogens: Pythium and Phytophthora, measured by a low-cost electronic nose. The electronic nose applies six non-specific Figaro Inc. metal oxide sensors. Various features describing shapes of the measurement curves of sensors’ response to the odors’ exposure were extracted and used for building the classification models. As a machine learning algorithm for classification, we use the Support Vector Machine (SVM) method and various measures to assess classification models’ performance. Differentiation between Phytophthora and Pythium species has an important practical aspect allowing forest practitioners to take appropriate plant protection. We demonstrate the possibility to recognize and differentiate between the two mentioned species with acceptable accuracy by our low-cost electronic nose.
Accelerometer-Based Wheel Odometer for Kinematics Determination
Authors: Youssef Ahmed A. , Al-Subaie Naif , El-Sheimy Naser , Elhabiby Mohamed
Published: February 2021

Various high budget industries that utilize wheel-based vehicles rely on wheel odometry as an integral aspect of their navigation process. This research introduces a low-cost alternative for typical wheel encoders that are typically used to determine the on-track speed of vehicles. The proposed system is referred to as an Accelerometer-based Wheel Odometer for Kinematics determination (AWOK). The AWOK system comprises just a single axis accelerometer mounted radially at the center of any given wheel. The AWOK system can provide direct distances instead of just velocities, which are provided by typical wheel speedometers. Hence, the AWOK system is advantageous in comparison to typical wheel odometers. Besides, the AWOK system comprises a simple assembly with a highly efficient data processing algorithm. Additionally, the AWOK system provides a high capacity to handle high dynamics in comparison to similar approaches found in previous related work. Furthermore, the AWOK system is not affected by the inherited stochastic errors in micro-machined electro-mechanical systems (MEMS) inertial sensors, whether short-term or long-term errors. Above all, the AWOK system reported a relative accuracy of 0.15% in determining the distance covered by a car.
Analysing Touchscreen Gestures: A Study Based on Individuals with Down Syndrome Centred on Design for All
Authors: Martin-Gutierrez Jorge , Del Rio Guerra Marta Sylvia
Published: February 2021

There has been a conscious shift towards developing increasingly inclusive applications. However, despite this fact, most research has focused on supporting those with visual or hearing impairments and less attention has been paid to cognitive impairments. The purpose of this study is to analyse touch gestures used for touchscreens and identify which gestures are suitable for individuals living with Down syndrome (DS) or other forms of physical or cognitive impairments. With this information, app developers can satisfy Design for All (DfA) requirements by selecting adequate gestures from existing lists of gesture sets. Twenty touch gestures were defined for this study and a sample group containing eighteen individuals with Down syndrome was used. A tool was developed to measure the performance of touch gestures and participants were asked to perform simple tasks that involved the repeated use of these twenty gestures. Three variables are analysed to establish whether they influence the success rates or completion times of gestures, as they could have a collateral effect on the skill with which gestures are performed. These variables are Gender, Type of Down syndrome, and Socioeconomic Status. Analysis reveals that significant difference is present when a pairwise comparison is performed, meaning individuals with DS cannot perform all gestures with the same ease. The variables Gender and Socioeconomic Status do not influence success rates or completion times, but Type of DS does.
Speech-Based Surgical Phase Recognition for Non-Intrusive Surgical Skills’ Assessment in Educational Contexts
Authors: Guzmán-García Carmen , Gómez-Tome Marcos , Sánchez-González Patricia , Oropesa Ignacio , Gómez Enrique J.
Published: February 2021

Surgeons’ procedural skills and intraoperative decision making are key elements of clinical practice. However, the objective assessment of these skills remains a challenge to this day. Surgical workflow analysis (SWA) is emerging as a powerful tool to solve this issue in surgical educational environments in real time. Typically, SWA makes use of video signals to automatically identify the surgical phase. We hypothesize that the analysis of surgeons’ speech using natural language processing (NLP) can provide deeper insight into the surgical decision-making processes. As a preliminary step, this study proposes to use audio signals registered in the educational operating room (OR) to classify the phases of a laparoscopic cholecystectomy (LC). To do this, we firstly created a database with the transcriptions of audio recorded in surgical educational environments and their corresponding phase. Secondly, we compared the performance of four feature extraction techniques and four machine learning models to find the most appropriate model for phase recognition. The best resulting model was a support vector machine (SVM) coupled to a hidden-Markov model (HMM), trained with features obtained with Word2Vec (82.95% average accuracy). The analysis of this model’s confusion matrix shows that some phrases are misplaced due to the similarity in the words used. The study of the model’s temporal component suggests that further attention should be paid to accurately detect surgeons’ normal conversation. This study proves that speech-based classification of LC phases can be effectively achieved. This lays the foundation for the use of audio signals for SWA, to create a framework of LC to be used in surgical training, especially for the training and assessment of procedural and decision-making skills (e.g., to assess residents’ procedural knowledge and their ability to react to adverse situations).
Experiment Study for Wrist-Wearable Electro-Tactile Display
Authors: Lu Xiong , Lin Minxu , Wang Shouchun , Hu Xusheng , Yin Hongbin , Yan Yuxing
Published: February 2021

Tactile sensation is a promising information display channel for human beings that involves supplementing or replacing degraded visual or auditory channels. In this paper, a wrist-wearable tactile rendering system based on electro-tactile stimulation is designed for information expression, where a square array with 8 × 8 spherical electrodes is used as the touch panel. To verify and improve this touch-based information display method, the optimal mode for stimulus signals was firstly investigated through comparison experiments, which show that sequential stimuli with consecutive-electrode-in-active mode have a better performance than those with single-electrode-in-active mode. Then, simple Chinese and English characters and 26 English characters’ recognition experiments were carried out and the proposed method was verified with an average recognition rate of 95% and 82%, respectively. This wrist-wearable tactile display system would be a new and promising medium for communication and could be of great value for visually impaired people.
Raman Spectroscopy-Based Quality Control of “Silicon-On-Insulator” Nanowire Chips for the Detection of Brain Cancer-Associated MicroRNA in Plasma
Authors: Malsagova Kristina A. , Popov Vladimir P. , Kupriyanov Igor N. , Pleshakova Tatyana O. , Galiullin Rafael A. , Kozlov Andrey F. , Shumov Ivan D. , Larionov Dmitry I. , Tikhonenko Fedor V. , Kapustina Svetlana I. , Ziborov Vadim S. , Petrov Oleg F. , Gadzhieva Olga A. , Bashiryan Boris A. , Shimansky Vadim N. , Archakov Alexander I. , Ivanov Yuri D.
Published: February 2021

Application of micro-Raman spectroscopy for the monitoring of quality of nanowire sensor chips fabrication has been demonstrated. Nanowire chips have been fabricated on the basis of «silicon-on-insulator» (SOI) structures (SOI-NW chips). The fabrication of SOI-NW chips was performed by optical litography with gas-phase etching. The so-fabricated SOI-NW chips are intended for highly sensitive detection of brain cancer biomarkers in humans. In our present study, two series of experiments have been conducted. In the first experimental series, detection of a synthetic DNA oligonucleotide (oDNA) analogue of brain cancer-associated microRNA miRNA-363 in purified buffer solution has been performed in order to demonstrate the high detection sensitivity. The second experimental series has been performed in order to reveal miRNA-363 itself in real human plasma samples. To provide detection biospecificity, the SOI-NW chip surface was modified by covalent immobilization of probe oligonucleotides (oDNA probes) complementary to the target biomolecules. Using the SOI-NW sensor chips proposed herein, the concentration detection limit of the target biomolecules at the level of 3.3 × 10−17 M has been demonstrated. Thus, the approach employing the SOI-NW chips proposed herein represents an attractive tool in biomedical practice, aimed at the early revelation of oncological diseases in humans.
Cutting Force Transition Model Considering the Influence of Tool System by Using Standard Test Table
Authors: Chen Xi , Zhang Dinghua , Wang Qi
Published: February 2021

The cutting force prediction model usually uses the classical oblique transformation method, which introduces the orthogonal cutting parameters into the oblique milling edge shape, and combines the geometric parameters of the tool to convert the orthogonal cutting force into the actual cutting force, thereby predicting the cutting force. However, this cutting force prediction method ignores the impact of tool vibration in actual machining, resulting in a large difference between the prediction model and the actual measurement. This paper proposes a cutting force conversion model considering the influence of the tool system. The proposed model fully considers the impact of tool vibration on the cutting force. On the basis of the orthogonal model, superimposing the additional cutting force generated by tool vibration makes the predicted value of the model closer to the actual cutting force. The results of milling experiments show that the conversion model can obtain higher prediction accuracy. Moreover, compared with the original conversion model, the accuracy of the proposed model is significantly improved.
Hierarchical Porous Carbon Electrodes with Sponge-Like Edge Structures for the Sensitive Electrochemical Detection of Heavy Metals
Authors: Lee Jongmin , Kim Soosung , Shin Heungjoo
Published: February 2021

This article presents the development of a highly sensitive electrochemical heavy metal sensor based on hierarchical porous carbon electrodes with sponge-like edge structures. Micrometer-scale hierarchical nanoporous carbon electrodes were fabricated at a wafer-scale using cost-effective batch microfabrication technologies, including the carbon microelectromechanical systems technology and oxygen plasma etching. The sponge-like hierarchical porous structure and sub-micrometer edges of the nanoporous carbon electrodes facilitate fast electron transfer rate and large active sites, leading to the efficient formation of dense heavy metal alloy particles of small sizes during the preconcentration step. This enhanced the peak current response during the square wave anodic stripping voltammetry, enabling the detection of Cd(II) and Pb(II) at concentrations as low as 0.41 and 0.7 μg L−1, respectively, with high sensitivity per unit sensing area (Cd: 109.45 nA μg−1 L mm−2, Pb: 100.37 nA μg−1 L mm−2).
GNSS Precise Relative Positioning Using A Priori Relative Position in a GNSS Harsh Environment
Authors: Kim Euiho
Published: February 2021

To enable Global Navigation Satellite System (GNSS)-based precise relative positioning, real-time kinematic (RTK) systems have been widely used. However, an RTK system often suffers from a wrong integer ambiguity fix in the GNSS carrier phase measurements and may take a long initialization time over several minutes, particularly when the number of satellites in view is small. To facilitate a reliable GNSS carrier phase-based relative positioning with a small number of satellites in view, this paper introduces a novel GNSS carrier phase-based precise relative positioning method that uses a fixed baseline length as well as heading measurements in the beginning of the operation, which allows the fixing of integer ambiguities with rounding schemes in a short time. The integer rounding scheme developed in this paper is an iterative process that sequentially resolves integer ambiguities, and the sequential order of the integer ambiguity resolution is based on the required averaging epochs that vary for each satellite depending on the geometry between the baseline and the double difference line-of-sight vectors. The required averaging epochs with respect to various baseline lengths and heading measurement uncertainties were analyzed through simulations. Static and dynamic field tests with low cost GNSS receivers confirmed that the positioning accuracy of the proposed method was better than 10 cm and significantly outperformed a conventional RTK solution in a GNSS harsh environment.
Assessment of the Propulsion System Operation of the Ships Equipped with the Air Lubrication System
Authors: Giernalczyk Mariusz , Kaminski Piotr
Published: February 2021

This paper is an attempt to evaluate the effectiveness of the ship’s hull air lubrication system in order to reduce the drag leading to fuel consumption reduction by ships. The available papers and reports were analyzed, in which records of the operation parameters of the propulsion system of ships equipped with this system were presented. These reports clearly show the advantages of using air lubrication system. On the basis of collected operating parameters of the propulsion system the authors performed analysis of operation effectiveness of the Air Lubrication System on the modern passenger ship was. The results of this analysis do not allow for a clearly positive opinion about its effectiveness. Additionally, the conditions that should be met for the system to be more effective and to significantly increase the propulsion efficiency were indicated.
An Uneven Node Self-Deployment Optimization Algorithm for Maximized Coverage and Energy Balance in Underwater Wireless Sensor Networks
Authors: Yan Luoheng , He Yuyao , Huangfu Zhongmin
Published: February 2021

The underwater wireless sensor networks (UWSNs) have been applied in lots of fields such as environment monitoring, military surveillance, data collection, etc. Deployment of sensor nodes in 3D UWSNs is a crucial issue, however, it is a challenging problem due to the complex underwater environment. This paper proposes a growth ring style uneven node depth-adjustment self-deployment optimization algorithm (GRSUNDSOA) to improve the coverage and reliability of UWSNs, meanwhile, and to solve the problem of energy holes. In detail, a growth ring style-based scheme is proposed for constructing the connective tree structure of sensor nodes and a global optimal depth-adjustment algorithm with the goal of comprehensive optimization of both maximizing coverage utilization and energy balance is proposed. Initially, the nodes are scattered to the water surface to form a connected network on this 2D plane. Then, starting from sink node, a growth ring style increment strategy is presented to organize the common nodes as tree structures and each root of subtree is determined. Meanwhile, with the goal of global maximizing coverage utilization and energy balance, all nodes depths are computed iteratively. Finally, all the nodes dive to the computed position once and a 3D underwater connected network with non-uniform distribution and balanced energy is constructed. A series of simulation experiments are performed. The simulation results show that the coverage and reliability of UWSN are improved greatly under the condition of full connectivity and energy balance, and the issue of energy hole can be avoided effectively. Therefore, GRSUNDSOA can prolong the lifetime of UWSN significantly.
On the Optimization of Fermentation Conditions for Enhanced Bioethanol Yields from Starchy Biowaste via Yeast Co-Cultures
Authors: Hashem Mohamed , Alamri Saad A. , Asseri Tahani A. Y. , Mostafa Yasser S. , Lyberatos Gerasimos , Ntaikou Ioanna
Published: February 2021

The present study aims to assess the impact of the type of yeast consortium used during bioethanol production from starchy biowastes and to determine the optimal fermentation conditions for enhanced bioethanol production. Three different yeast strains, Saccharomyces cerevisiae, Pichia barkeri, and Candida intermedia were used in mono- and co-cultures with pretreated waste-rice as substrate. The optimization of fermentation conditions i.e., fermentation time, temperature, pH, and inoculum size, was investigated in small-scale batch cultures and subsequently, the optimal conditions were applied for scaling-up and validation of the process in a 7-L fermenter. It was shown that co-culturing of yeasts either in couples or triples significantly enhanced the fermentation efficiency of the process, with ethanol yield reaching 167.80 ± 0.49 g/kg of biowaste during experiments in the fermenter.
Workplace Situation and Well-Being of Ecuadorian Self-Employed
Authors: Ceular-Villamandos Nuria , Navajas-Romero Virginia , Caridad y López del Río Lorena , Zambrano-Santos Lucia Zita
Published: February 2021

Due to novel coronavirus 2019 (COVID-19), the labor market is going to undergo a profound restructuring. The creation of a new labor paradigm by all stakeholders is essential. This document contributes to the current political and social debates about self-employment, the need for economic growth, and how these labor measures, which are deeply institutionalized, need a change of attitude for an adequate job reconstruction in terms of welfare and sustainability. Currently, policy makers are proposing actions and policies because the new labor paradigm is being designed in the countries of Latin America. This research aims to analyze the JDCS model (Job Demand-Control-Support) and well-being in the self-employed in Ecuador. Unlike previous studies, this research takes a comprehensive approach by considering this theoretical model and the figure of the self-employed in terms of well-being. The logistic model, using cases of more than one thousand workers, generated estimated results that indicate the existence of a significant effect of physical and psychological demands at work on the balance between well-being and the management of angry clients; the speed of execution; and the complexity of the tasks. Regarding labor control, the ability to solve problems and make decisions for the company are detected as influencing factors; finally, social support is another factor influencing global well-being for the self-employed. These results show that with an effective management of the self-employed labor environment, it is possible to achieve an adequate level of workplace satisfaction.
Measuring Financial Impacts of the Renewable Energy Based Fiscal Policy in Colombia under Electricity Price Uncertainty
Authors: Castillo-Ramírez Alejandro , Mejía-Giraldo Diego
Published: February 2021

This paper analyses the financial implications, from the point of view of an investor in renewable energy, which sells the energy for an uncertain price of electricity and decides to take advantage of the Colombian tax policy over the renewable energy. The policy, known as Investment Tax Allowance (ITA), encourages installation of renewable projects in a country traditionally dominated by hydro power. Price is modeled as a non-stationary autoregressive stochastic process with normally distributed error terms. Costs, and uncertain revenue and taxes are considered to assess the financial impact on a solar project when the policy is implemented. Since impact varies according to project ownership, two cases are evaluated: a generation company (GENCO-1) that only owns the solar project; and, an existent generation company (GENCO-2) that owns a portfolio of projects. Results indicate that if ITA is applied, it is likely that the GENCO-1 cannot take the full advantage of the incentive, as opposed to the GENCO-2. Although this policy might not satisfy planner objectives since it does not guarantee the construction of significantly high capacity of new renewable energy projects, it definitely represents an attractive mechanism to decrease tax obligations at the GENCO-2 level. Finally, a theoretical analysis shows that investment cost affects the mean of the present value; whereas tax rates impacts both its mean and standard deviation.
The Effects of School Climate on Sixth Form Teachers’ Self-Efficacy in Malaysia
Authors: Mansor Azlin Norhaini , Nasaruddin Mohd Zabil Ikhsan Mohamed , A. Hamid Aida Hanim
Published: February 2021

In Malaysia, sixth form is a post-secondary education that is comparable to pre-university programs such as A-level and Foundation qualifications. Enrolment in sixth forms has dwindled over the past ten years due to assumptions that the curriculum is difficult and because it is offered in regular secondary schools. Thus, the sixth form transformation program was introduced in 2015 with the purpose to rebrand sixth form education to a new setting comparable to other pre-university education, with a focus on improving the school climate and increasing teacher self-efficacy. Therefore, this study was conducted to identify the level and relationship of the school climate on teacher self-efficacy. This survey was carried out using a questionnaire instrument, involving 695 sixth form teachers currently in Selangor. The findings showed that the level of school climate and teacher self-efficacy in all sixth form centers were at a high level. There was also a strong positive relationship between the school climate and sixth form teachers’ self-efficacy. Social and academic dimensions contributed significantly to the teacher self-efficacy of 38%. Hence, further studies looking at aspects that suggestively contribute to the school climate should be given due attention to ensure that transformation planning can be implemented as intended.
Sustainable Building Materials and Life Cycle Assessment
Authors: Estokova Adriana , Samesova Dagmar
Published: February 2021

Today, sustainability principles should be applied to all industries, including the building sector, which ranks among the sectors with the most negative environmental impacts [...]
Modeling Resilience and Sustainability of Water-Subsidized Systems: An Example from Northwest Costa Rica
Authors: Vazquez Kathleen , Muneepeerakul Rachata
Published: February 2021

Water-subsidized systems are growing in number and maintaining the sustainability of such complex systems presents unique challenges. Interbasin water transfer creates new sociohydrological dynamics that come with tradeoffs and potential regime shifts. The Tempisque-Bebedero watershed in Northwest Costa Rica typifies this class of watershed: Transferred water is used for power generation and irrigated agriculture with significant downstream environmental impacts. To improve and clarify our understanding of the effects of social and biophysical factors on the resilience of such systems, a stylized dynamical systems model was developed, using as a guide the situation in the Tempisque-Bebedero watershed. This model was analyzed to understand the nature of socio-hydrologic regimes that exist in this class of basins and what factors determine these regimes. The model analysis revealed five distinct regimes and different regime shift behaviors dependent on environmental and policy conditions. This work offers insights into other complex socio-hydrologic systems with similar processes.
Biochar Volatile Matter and Feedstock Effects on Soil Nitrogen Mineralization and Soil Fungal Colonization
Authors: Maaz Tai McClellan , Hockaday William C. , Deenik Jonathan L.
Published: February 2021

Biochar has important biogeochemical functions in soil—first as a means to sequester carbon, and second as a soil conditioner to potentially enhance soil quality and fertility. Volatile matter (VM) content is a property of biochar that describes its degree of thermal alteration, which can have a direct influence on carbon and nitrogen dynamics in soil. In this study, we characterized the VM in biochars derived from two locally sourced feedstocks (corncob and kiawe wood) and evaluated the relationship of VM content to nitrogen transformations and culturable fungal biomass. Using 13C nuclear magnetic resonance (NMR) spectroscopy, we found that the VM content of biochar primarily consisted of alkyl (5.1–10.1%), oxygen-substituted alkyl (2.2–6.7%), and phenolic carbon (9.4–11.6%). In a series of laboratory incubations, we demonstrated that corncob biochars with high VM (23%) content provide a source of bioavailable carbon that appeared to support enhanced viable, culturable fungi (up to 8 fold increase) and cause nitrogen immobilization in the short-term. Corncob biochar with bioavailable VM was nitrogen-limited, and the addition of nitrogen fertilizer resulted in a four-fold increase in total hydrolytic enzyme activity and the abundance of culturable fungal colonies. In contrast, kiawe biochar with an equivalent VM content differed substantially in its composition and effect on these same biological parameters. Therefore, the rapid measurement of VM content is too coarse to differentiate chemical composition and to predict the behavior of biochars across feedstocks and production methods.
Human Capital in Digital Economy: An Empirical Analysis of Central and Eastern European Countries from the European Union
Authors: Grigorescu Adriana , Pelinescu Elena , Ion Amalia Elena , Dutcas Monica Florica
Published: February 2021

The hypercompetitive global economy of the 21st century is a hub of innovation, technology, talent, skills, speed, efficiency, productivity, and satisfaction. Within this context, the organizations are looking intensely for people with skills and talents that can differentiate themselves in all that noise. The human capital became slowly but surely a mean of efficiency and growth, especially through the premises of digitization, and a key issue of sustainability. The current research is meant to identify and highlight any correlations that might appear between the population’s welfare of 11 Central and Eastern European Countries (CEECs) which are members of the European Union (EU), and the components of the digitization trend, including the new human cloud industry, ICT, and the connectivity to the Internet of Things. In order to achieve the needed insights, the multiple regression analysis was employed, and the latter tested the panel models with fixed effects, both from a temporal and country perspective. The results showcased a positive connection between the dependent and independent variables, confirming that the digitization of the economy and the developed human capital will ultimately lead to the increase of population’s welfare. Moreover, the findings are consistent with specific insights for each of the 11 CEECs, showing that digitization and the influence of human capital is differentiated across the latter in terms of their overall effect and amplitude. The research is limited by the timeframe and countries included in the study, and it can be furthered by determining the impact of digitization on the economies of the EU28 countries grouped by level of development, and by using other significant indicators for analysis.
Avoiding the Dark Side of Digital Transformation in Teaching. An Institutional Reference Framework for eLearning in Higher Education
Authors: García-Peñalvo Francisco José
Published: February 2021

The purpose of this paper is to define a reference framework for introducing eLearning practices in mainly face-to-face higher education institutions. We suggest a suitable adoption and management of associated infrastructures and processes, in order to guarantee the ethical use of data in the related academic and learning analytics. A theoretical framework is proposed after years of practice and experience in the institutional government of IT processes related to learning technology. The digital transformation of teaching should imply the right technological decisions made by people and for people, in order to achieve a more inclusive, participative, and human university supported by technology. digital transformation is a social requirement of governments, companies, and institutions, and it should take into account the associated risks of the unethical use of technology, which leads to the dark side of transformation processes. eLearning approaches, especially with the influence of the COVID-19 outbreaks, are increasing the need for digital mechanisms in universities. Further, there is a need for strategical support and reference models if we are to avoid these undesired effects.
Consumer Adoption of Consumer-Created vs. Expert-Created Information: Moderating Role of Prior Product Attitude
Authors: Park Do-Hyung
Published: February 2021

Today, consumer-created information such as online consumer reviews have become important and popular, playing a key role in consumer decision making. Compared with expert-created information, each piece of information is less powerful or persuasive, but their aggregation can be more credible and acceptable. This concept is called collective intelligence knowledge. This study focuses on the persuasive effect on consumer product attitudes of consumer-created information compared to expert-created information. Using source credibility and familiarity theory, the study reveals how prior brand attitudes can play a moderating role in the persuasive effect of consumer-created information and expert-created information. Specifically, this study shows how consumer-created information is more persuasive when consumers have more favorable prior brand attitudes, while expert-created information is more persuasive when consumers have less favorable prior brand attitudes. Based on the results, this study proposes practical strategies for information structure, curation, and presentation. If a company has a good-quality brand evaluation of its products, it should increase the weight of consumer-created information such as online consumer reviews. Otherwise, the company needs to first improve brand evaluation through expert-created information such as third-parties or power-blogger reviews.
Artificial Intelligence and Business Strategy towards Digital Transformation: A Research Agenda
Authors: Kitsios Fotis , Kamariotou Maria
Published: February 2021

In the past decade, current literature and businesses have drawn attention to Artificial Intelligence (AI) tools and in particular to the advances in machine learning techniques. Nevertheless, while the AI technology offers great potential to solve difficulties, challenges remain implicated in practical implementation and lack of expertise in the strategic usage of AI to create business value. This paper aims to implement a systematic literature review analyzing convergence of the AI and corporate strategy and develop a theoretical model incorporating issues based on the existing research in this field. Eighty-one peer-reviewed articles were discussed on the basis of research methodology from Webster and Watson (2002). In addition to gaps in future research, a theoretical model is developed, discussing the four sources of value creation: AI and Machine Learning in organizations; alignment of AI tools and Information Technology (IT) with organizational strategy; AI, knowledge management and decision-making process; and AI, service innovation and value. These outcomes lead to both theoretical and managerial viewpoints, with extensive possibilities to generate new methods and types of management practices.
Learning How to Learn from Disasters through a Comparative Dichotomy Analysis: Grenfell Tower and Hurricane Katrina Case Studies
Authors: Iglesias-Mendoza Maria , Yunusa-Kaltungo Akilu , Hadleigh-Dunn Sara , Labib Ashraf
Published: February 2021

We describe two well-established, practice-based Master’s programmes as examples of existing competence development opportunities for practitioners and how such links between theory and practice can be developed and taught within the Higher Education (HE) context. We hypothesise that learning from major failures is essential in linking theory with practice in both engineering and management education. We investigate how to train emergency response teams on coping with, and learning from, rare events; a major challenge to other practitioners in the fields of safety and risk management. Comparison is undertaken between two disasters—Hurricane Katrina in the USA and the relatively recent Grenfell Tower in the UK—using a balanced dual approach of paradoxes, a dichotomy. In this paper, we demonstrate the enhancement of both engineering and management education. This was achieved through using the two case studies to emphasize the relevance of incorporating advanced mental modelling approaches for root cause analysis in training and by comparing the two cases with respect to the black swan and black elephant concepts. It is recommended that future training has a balanced approach that encompasses the outlined features of dichotomies.
A Reference Framework to Combine Model-Based Design and AR to Improve Social Sustainability
Authors: Grandi Fabio , Khamaisi Riccardo Karim , Peruzzini Margherita , Raffaeli Roberto , Pellicciari Marcello
Published: February 2021

Product and process digitalization is pervading numerous areas in the industry to improve quality and reduce costs. In particular, digital models enable virtual simulations to predict product and process performances, as well as to generate digital contents to improve the general workflow. Digital models can also contain additional contents (e.g., model-based design (MBD)) to provide online and on-time information about process operations and management, as well as to support operator activities. The recent developments in augmented reality (AR) offer new specific interfaces to promote the great diffusion of digital contents into industrial processes, thanks to flexible and robust applications, as well as cost-effective devices. However, the impact of AR applications on sustainability is still poorly explored in research. In this direction, this paper proposed an innovative approach to exploit MBD and introduce AR interfaces in the industry to support human intensive processes. Indeed, in those processes, the human contribution is still crucial to guaranteeing the expected product quality (e.g., quality inspection). The paper also analyzed how this new concept can benefit sustainability and define a set of metrics to assess the positive impact on sustainability, focusing on social aspects.
Railway System Design by Adopting the Merry-Go-Round (MGR) Paradigm
Authors: D’Acierno Luca , Botte Marilisa
Published: February 2021

Public transport systems can be characterised by a schedule-based or a frequency-based framework according to the kind of service to be operated. In the former case, specific departure and arrival times are set for each run and disclosed to the users; in the latter, instead, it is necessary to maintain a certain headway between two successive runs, rather than a specific timetable structure. This paper focuses on modelling frequency-based systems, which can be described by means of the so-called Merry-Go-Round (MGR) paradigm. The paradigm is first discussed and the related analytical formulation is presented; the role of the terminal station layout is then investigated within this framework. Finally, in order to show the effectiveness of the proposed formulation, it was implemented in the case of a real-scale metro line.