bluuebunny/crossref_metadata_2025 huggingface dataset:
The Perceived Satisfaction in Utilizing Learning Management System among Engineering Students during the COVID-19 Pandemic: Integrating Task Technology Fit and Extended Technology Acceptance Model
Authors: Navarro Maricar M. , Prasetyo Yogi Tri , Young Michael Nayat , Nadlifatin Reny , Redi Anak Agung Ngurah Perwira
Published: September 2021

Online education has become the norm for higher education institutions (HEIs) during this COVID-19 pandemics. HEIs are required to implement a fully online learning system that is structured and readily accessible with the assistance of a learning management system (LMS), including in developing countries such as the Philippines. This study aims to assess factors that positively influence the perceived satisfaction of engineering students when using the LMS during the COVID-19 pandemic in the Philippines. Additionally, it aims to integrate two models: Task Technology Fit (TTF) and Technology Acceptance Model (TAM), with added variables such as the content of the learning management system, social presence, and social space. Upon deploying the convenience sampling, a total of 1011 engineering students responded in the online survey, which consisted of 81 questions. Structural equation modeling (SEM) showed that the Task Technology Fit was positively influenced by technology, individual, and task characteristics. Moreover, behavioral intention to use LMS was positively influenced by perceived usefulness and perceived ease of use. Furthermore, Task Technology Fit had a significant direct effect on behavioral intention to use LMS, which subsequently led to perceived satisfaction. This study is among the first to explore factors affecting perceived satisfaction among engineering students in using the LMS in the Philippines during the COVID-19 pandemic. To evaluate the perceived satisfaction of students in using the learning management system, future works can be extended and the model can be applied in other countries.
GIS Approach Applied to Tourist Bus Route Design on Lanzarote Island
Authors: Rendeiro Martín-Cejas Roberto , Suárez Vega Rafael , Ramírez Sánchez Pedro Pablo
Published: September 2021

Current public transport supply on the Island of Lanzarote is clearly insufficient, and opportunities to substitute private automobiles are extremely limited, for residents and tourists alike. Therefore, this paper analyzes the possibility of introducing a tourist bus service to connect Lanzarote’s main tourist attractions, and it also focuses on a move towards public transport by tourists to reduce the CO2 emitted by excessive private car usage. This work assesses the impact of road transport in accessing tourist activities on Lanzarote Island and its implications for sustainable tourism development. The evaluation is based on the volume of CO2 emissions for the current tourist mobility model on the island and an alternative option such as a tourist bus route. The methodology employed here is the application of a geographical information system (GIS). The study analyzes how to manage the impact of road access to tourist sites through the implementation of a new tourist bus line. The study seeks to evaluate the design of a new bus to deliver tourists to key tourist activities on Lanzarote Island. A GIS-T algorithm is used to compare the level of CO2 emissions from the current tourist mobility model versus the implementation of a new touristic bus. The levels of pollution produced by the present system and the tourist route are compared, and different levels of demand for the new circuit are considered. We conclude that in order to reduce the current levels of emissions by around 15%, some 19.4% of the tourists that currently use hire cars would have to switch to the new tourist bus service.
Multiobjective Railway Alignment Optimization Using Ballastless Track and Reduced Cross-Section in Tunnel
Authors: Biancardo Salvatore Antonio , Avella Francesco , Di Lisa Ernesto , Chen Xinqiang , Abbondati Francesco , Dell’Acqua Gianluca
Published: September 2021

The increasing need for railway planning and design to connect growing cities in inland mountainous areas has pushed engineering efforts toward the research of railway tracks that must comply with more restrictive constraints. In this study, a multiobjective alignment optimization (HAO), commonly used for highway projects, was carried out to identify a better solution for constructing a high-speed railway track considering technical and economic feasibilities. Then, two different and innovative scenarios were investigated: an unconventional ballastless superstructure, which is more environment-friendly than a gravel superstructure, and a reduced cross-section in a tunnel, which enables a slower design speed and then, less restrictive geometric constraints and earthmoving. The results showed that the first solution obtained a better performance with a slight increase in cost. Moreover, both scenarios improved the preliminary alignment optimization, reducing the overall cost by 11% for the first scenario and 20% for the second one.
Adsorption of Toxic Zinc by Functionalized Lignocellulose Derived from Waste Biomass: Kinetics, Isotherms and Thermodynamics
Authors: Dang Jiatao , Wang Hui , Wang Chongqing
Published: September 2021

Heavy metals pollution receives worldwide attention due to great toxicity, significant bio-accumulation and non-biodegradability. Adsorption is a promising technique for removing heavy metals from wastewater. Adsorption of zinc (Zn(II)) from aqueous solution was investigated by functionalized lignocellulose derived from fallen leaves. Alkalized lignocellulose (AC), xanthated lignocellulose (XC) and carboxylated lignocellulose (CC) were characterized by Fourier transform infrared spectrum (FTIR), X-ray photoelectron spectroscopy (XPS) and scanning electron microscopy (SEM). The effect of sorbent dosage, solution pH, sorption time and initial Zn(II) concentration on Zn(II) sorption was investigated by single-factor experiment. Sorption kinetics, isotherms and thermodynamics were examined to reveal sorption mechanism. The sorption capacity and removal rate remarkably depend on experimental variables. Zn(II) sorption onto AC, XC and CC is well described by the pseudo second order kinetics and Langmuir isotherm. The sorption process is fast, reaching sorption equilibrium at 30 min. The maximum sorption capacity of Zn(II) onto CC is 46.49 mg/g, higher than that onto AC, XC and other reported sorbents. Thermodynamic parameters indicate that Zn(II) sorption is a spontaneous process. Sorption mechanism is majorly attributed to surface complexation. This work shows the feasibility of removing toxic Zn(II) from aqueous solution by locally available biomass, providing a sustainable approach for wastewater treatment.
Information Systems, E-Learning and Knowledge Management (in the Times of COVID)
Authors: Alier Marc
Published: September 2021

In 1995, back when I was finishing my CS Engineering degree, the Barcelona School of Informatics started to use an intranet application called “Racó” [...]
Carpooling Platforms as Smart City Projects: A Bibliometric Analysis and Systematic Literature Review
Authors: Anthopoulos Leonidas G. , Tzimos Dimitrios N.
Published: September 2021

Carpooling schemes for mutual cost benefits between the driver and the passengers has a long history. However, the convenience of driving alone, the increasing level of car ownership, and the difficulties in finding travelers with matching timing and routes keep car occupancy low. Technology is a key enabler of online platforms which facilitate the ride matching process and lead to an increase in carpooling services. Smart carpooling services may be an alternative and enrichment for mobility, which can help smart cities (SCs) reduce traffic congestion and gas emissions but require the appropriate architecture to support connection with the city infrastructure such as high-occupancy vehicle lanes, parking space, tolls, and the public transportation services. To better understand the evolution of carpooling platforms in SCs, bibliometric analysis of three separate specialized literature collections, combined with a systematic literature review, is performed. It is identified that smart carpooling platforms could generate additional value for participants and SCs. To deliver this value to an SC, a multi-sided platform business model is proposed, suitable for a carpooling service provider with multiple customer segments and partners. Finally, after examining the SC structure, a carpooling platform architecture is presented, which interconnects with the applicable smart city layers.
Carbon Capture Systems for Building-Level Heating Systems—A Socio-Economic and Environmental Evaluation
Authors: Liyanage Don Rukmal , Hewage Kasun , Karunathilake Hirushie , Chhipi-Shrestha Gyan , Sadiq Rehan
Published: September 2021

The energy consumption of buildings contributes significantly to global greenhouse gas (GHG) emissions. Energy use for space and water heating in buildings causes a major portion of these emissions. Natural gas (NG) is one of the dominant fuels used for building heating, emitting GHG emissions directly to the atmosphere. Many studies have been conducted on improving energy efficiency and using cleaner energy sources in buildings. However, implementing carbon capture, utilization, and storage (CCUS) on NG building heating systems is overlooked in the literature. CCUS technologies have proved their potential to reduce GHG emissions in fossil fuel power plants. However, their applicability for building-level applications has not been adequately established. A critical literature review was conducted to understand the feasibility and viability of adapting CCUS technologies to co-function in building heating systems. This study investigated the technical requirements, environmental and socio-economic impacts, and the drivers and barriers towards implementing building-level CCUS technologies. The findings indicated that implementing building-level CCUS technologies has significant overall benefits despite the marginal increase in energy consumption, operational costs, and capital costs. The information presented in this paper is valuable to academics, building owners and managers, innovators, investors, and policy makers involved in the clean energy sector.
Socio-Economic and Governance Conditions Corresponding to Change in Animal Agriculture: South Dakota Case Study
Authors: Welles Jacqueline S. , Soriano Noelle Cielito T. , Dorbu Freda Elikem , Pereira G. M. , Rubeck Laura M. , Timmermans Erica L. , Ndayambaje Benjamin , Deviney Alison V. , Classen John J. , Koziel Jacek A. , Cortus Erin L.
Published: September 2021

Understanding sustainable livestock production requires consideration of both qualitative and quantitative factors in a temporal and/or spatial frame. This study adapted Qualitative Comparative Analysis (QCA) to relate conditions of social, economic, and governance factors to changes in livestock inventory across several counties and over time. This paper presents an approach that (1) identified factors with the potential to relate to a change in livestock inventory and (2) analyzed commonalities within these factors related to changes spatially and temporally. This paper illustrates the approach and results when applied to five counties in eastern South Dakota. The specific response variables were periods of increasing, no change, or decreasing beef cattle, dairy cattle, and swine inventories in the specific counties for five-year census periods between 1992 and 2017. In the spatial analysis of counties, stable beef inventories and decreasing dairy inventories related to counties with increasing gross domestic products. The presence of specific social communities related to increases in county swine inventories. In the temporal analysis of census periods, local governance and economic factors, particularly market price influences, were more prevalent. Swine inventory showed a stronger link to cash crop markets than to livestock markets, whereas cattle market price increases associated with stable inventories for all animal types. Local governance tools had mixed effects for the different animal types across space and time. The factors and analysis results are context-specific. However, the process considers the various socio-economic processes in livestock production and community development applicable to agricultural sustainability questions in the Midwest and beyond.
Evaluation of the Current Approach to Education of Security Issues at Selected Universities Preparing Future Pedagogues
Authors: Kavan Stepan
Published: September 2021

This paper deals with education in security issues. The aim of this work is to examine and evaluate the current approach to education of future educators in the field of security issues at selected universities in the Czech Republic. The primary method of research was a survey through questionnaires, where information was collected at selected universities. The evaluation is performed using SWOT analysis. The fragmentation and inconsistency of the approach of individual universities is evident from the results of the survey. New knowledge, which is based on the research, is the identification of the current state of training of future teachers in the field of security. The result of the survey is used by an expert group of the Ministry of the Interior and the Ministry of Education, Youth and Sports of the Czech Republic as input information for the development of minimum standards for pedagogical universities.
Smart and Sustainable Aquaculture Farms
Authors: Kassem Taher , Shahrour Isam , El Khattabi Jamal , Raslan Ahmad
Published: September 2021

This paper presents the design and construction of a smart and sustainable fish farm. The farm is based on the hybrid aquaculture concept that combines the advantages of the recirculation aquaculture system (RAS), the zero-water discharge (ZWD), and smart technology. The system’s smartness consists of using the latest technology, including monitoring and automation, ensuring zero water discharge, good water quality, reduced energy consumption, and high biosecurity. In addition, the system does not use chemicals in the aquaculture process. The paper describes the design of this system, including the hydraulic system, the smart monitoring system, the feeding regime, and the control of the biological parameters. Tests conducted in Tabuk, Saudi Arabia, showed high performance of this system with around 90% survival rate. In addition, observations showed the system’s capacity to maintain the water quality parameters within the optimal water quality ranges, reduce energy consumption, and sustain efficient shrimp waste recycling.
Influence of Intraspecific Competition Stress on Soil Fungal Diversity and Composition in Relation to Tree Growth and Soil Fertility in Sub-Tropical Soils under Chinese Fir Monoculture
Authors: Farooq Taimoor Hassan , Kumar Uttam , Shakoor Awais , Albasher Gadah , Alkahtani Saad , Rizwana Humaira , Tayyab Muhammad , Dobaria Jalpa , Hussain Muhammad Iftikhar , Wu Pengfei
Published: September 2021

Soil microorganisms provide valuable ecosystem services, such as nutrient cycling, soil remediation, and biotic and abiotic stress resistance. There is increasing interest in exploring total belowground biodiversity across ecological scales to understand better how different ecological aspects, such as stand density, soil properties, soil depth, and plant growth parameters, influence belowground communities. In various environments, microbial components of belowground communities, such as soil fungi, respond differently to soil features; however, little is known about their response to standing density and vertical soil profiles in a Chinese fir monoculture plantation. This research examined the assemblage of soil fungal communities in different density stands (high, intermediate, and low) and soil depth profiles (0–20 cm and 20–40 cm). This research also looked into the relationship between soil fungi and tree canopy characteristics (mean tilt angle of the leaf (MTA), leaf area index (LAI), and canopy openness index (DIFN)), and general growth parameters, such as diameter, height, and biomass. The results showed that low-density stand soil had higher fungal alpha diversity than intermediate- and high-density stand soils. Ascomycota, Basidiomycota, Mucromycota, and Mortierellomycota were the most common phyla of the soil fungal communities, in that order. Saitozyma, Penicillium, Umbelopsis, and Talaromyces were the most abundant fungal genera. Stand density composition was the dominant factor in changing fungal community structure compared to soil properties and soil depth profiles. The most significant soil elements in soil fungal community alterations were macronutrients. In addition, the canopy openness index and fungal community structure have a positive association in the low-density stand. Soil biota is a nutrient cycling driver that can promote better plant growth in forest ecosystems by supporting nutrient cycling. Hence, this research will be critical in understanding soil fungal dynamics, improving stand growth and productivity, and improving soil quality in intensively managed Chinese fir plantations.
Polyhalite Positively Influences the Growth, Yield and Quality of Sugarcane (Saccharum officinarum L.) in Potassium and Calcium-Deficient Soils in the Semi-Arid Tropics
Authors: Bhatt Rajan , Singh Paramjit , Ali Omar M. , Abdel Latef Arafat Abdel Hamed , Laing Alison M. , Hossain Akbar
Published: September 2021

In semi-arid tropics, sugarcane yield and quality are affected by deficiencies in soil nutrients, including potassium and calcium. We examined the effects of two different potassium fertilizers, a traditional muriate of potash (MOP) and polyhalite (which contains potassium and calcium), on sugarcane growth, yield, and quality. Experimental treatments compared a control 0 kg K ha−1 (T1) to potassium applied as MOP only at 80 kg K ha−1 (T2) and at 120 kg K ha−1 (T3), and potassium applied as an equal split of MOP and polyhalite at 80 kg K ha−1 (T4) and at 120 kg K ha−1 (T5). Relative to the control the potassium-enhanced treatments had improved rates of key growth parameters, and of cane yields, which were 4.4, 6.2, 8.2, and 9.9% higher in T2, T3, T4,, and T5, respectively, than in T1. Regardless of fertilizer used, potassium applied at 80 kg K ha−1 achieved the highest sugar purity and commercial cane sugar content. All potassium fertilizer treatments had reduced (although non-significant) incidences of three key sugarcane insect pests. The economic benefits of polyhalite were reduced due to its higher cost relative to MOP. Combining MOP and polyhalite equally to achieve an application rate of 80 kg K ha−1 is recommended to enhance sugarcane growth and yield.
Assessing the Performance of Deep Learning Algorithms for Short-Term Surface Water Quality Prediction
Authors: Choi Heelak , Suh Sang-Ik , Kim Su-Hee , Han Eun Jin , Ki Seo Jin
Published: September 2021

This study aimed to investigate the applicability of deep learning algorithms to (monthly) surface water quality forecasting. A comparison was made between the performance of an autoregressive integrated moving average (ARIMA) model and four deep learning models. All prediction algorithms, except for the ARIMA model working on a single variable, were tested with univariate inputs consisting of one of two dependent variables as well as multivariate inputs containing both dependent and independent variables. We found that deep learning models (6.31–18.78%, in terms of the mean absolute percentage error) showed better performance than the ARIMA model (27.32–404.54%) in univariate data sets, regardless of dependent variables. However, the accuracy of prediction was not improved for all dependent variables in the presence of other associated water quality variables. In addition, changes in the number of input variables, sliding window size (i.e., input and output time steps), and relevant variables (e.g., meteorological and discharge parameters) resulted in wide variation of the predictive accuracy of deep learning models, reaching as high as 377.97%. Therefore, a refined search identifying the optimal values on such influencing factors is recommended to achieve the best performance of any deep learning model in given multivariate data sets.
Complementary Cooperation of CCTV and UAV Systems for Tourism Security and Sustainability
Authors: Ko Young Dae , Song Byung Duk
Published: September 2021

The meaning of sustainability is very broad and has many pillars such as the economy, environment and society. In the tourism industry, another important pillar is security. Tourism security affects the satisfaction and pleasure of tourists on a trivial level, and life and injuries on a significant level. Thus, unless security is guaranteed, tourists will not be able to fully enjoy the attractions and will not even consider the travel itself. Such tourist behavior has a significant impact on short-term and long-term tourism sustainability. Therefore, to enhance tourism security, many policies and frameworks have been suggested and announced in recent years. However, without efficient guidelines for the installation and operation of security devices, it may be hard to obtain actual effectiveness. To support real implementation of security systems in the tourism industry, this study quantitatively addresses the installation and operation issue of security devices in an optimal manner. A complementary cooperation of Closed-Circuit Television (CCTV) and Unmanned Aerial Vehicles (UAV) is suggested to efficiently monitor the key locations of tourism destinations and improve the security. Two mathematical models are developed to derive the optimal location of CCTVs, and the optimal operation schedule of UAVs over multiple time periods. Security requirements, service range, and budget are considered as realistic constraints. The validity of the models is demonstrated through a realistic case study of Nice, France.
Mapping Regional Vulnerability to Energy Poverty in Poland
Authors: Karpinska Lilia , Śmiech Sławomir , Gouveia João Pedro , Palma Pedro
Published: September 2021

Raising concerns about the effectiveness of the energy poverty policy actions in Poland, such as Clean Air and Stop Smog, brings forward the need to apply different strategies to identify the energy poor. More than 13.7% of Polish households were energy poor in 2018 according to the ability-to-keep-home-warm indicator. This study proposes enhancing the model-based approach to measure households’ energy poverty. Our goal is to assess regional vulnerability to energy poverty in Poland. The study relies on three national datasets and is conducted in two steps. The Energy Consumption Survey (2018) and the Household Budget Survey (2018) provide data for modeling household’s energy poverty in the first step. The Local Data Bank (2019) gives information on the potential factors increasing regional vulnerability to energy poverty evaluated in the second step. We apply multiple linear regression to identify energy-poor households and principal components analysis to examine the regions’ vulnerability factors. As a result, we produce several maps showing the spatial distribution of vulnerability to energy poverty in 380 Polish districts. Our results indicate that some northern, southern and eastern districts in Poland are primary targets of energy poverty policy actions.
An Energy-Fraud Detection-System Capable of Distinguishing Frauds from Other Energy Flow Anomalies in an Urban Environment
Authors: Calamaro Netzah , Beck Yuval , Ben Melech Ran , Shmilovitz Doron
Published: September 2021

Energy fraud detection bears significantly on urban ecology. Reduced losses and power consumption would affect carbon dioxide emissions and reduce thermal pollution. Fraud detection also provides another layer of urban socio-economic correlation heatmapping and improves city energy distribution. This paper describes a novel algorithm of energy fraud detection, utilizing energy and energy consumption specialized knowledge poured into AI front-end. The proposed algorithm improves fraud detection’s accuracy and reduces the false positive rate, as well as reducing the preliminary required training dataset. The paper also introduces a holistic algorithm, specifying the major phenomena that disguises as energy fraud or affects it. Consequently, a mathematical foundation for energy fraud detection for the proposed algorithm is presented. The results show that a unique pattern is obtained during fraud, which is independent of a reference non-fraud pattern of the same customer. The theory is implemented on real data taken from smart metering systems and validated in real life scenarios.
The Formal Agricultural Input Sector: A Missing Asset in Developing Nations?
Authors: Anglade Boaz , Swisher Marilyn E. , Koenig Rose
Published: September 2021

The formal input supply sector has received little attention in developing nations, including Haiti. We interviewed input store owners in Haiti and collected information on the availability and sources of inputs and challenges facing vendors. Three large suppliers import most inputs available to farmers. Second tier traders, mostly small stores that purchase from the major suppliers, play a critical role in making inputs accessible to rural communities. These formal stores have significant potential to transform the agricultural sector but face three major challenges. (1) Improved seed is a critically needed input, but older cultivars dominate because there is limited breeding in Haiti, few seed importers, and inadequate patent protections that make holders reluctant to move new varieties into Haiti. (2) The types of fertilizers and pesticides available to farmers are limited and many are technologically outdated. (3) In-country transportation is slow and relatively expensive and needed inputs often do not reach farmers in a timely manner. We conclude that approaches that bring together the strengths and assets of the public sector, the non-profit private sector and the for-profit private sector and increased attention to policy measures that benefit all three sectors are requisites for supply chain development in Haiti.
Design and Implementation of a High Step-Up DC-DC Converter Based on the Conventional Boost and Buck-Boost Converters with High Value of the Efficiency Suitable for Renewable Application
Authors: Rahimi Tohid , Islam Md Rabiul , Gholizadeh Hossein , Mahdizadeh Saeed , Afjei Ebrahim
Published: September 2021

This paper introduces a novel topology of the proposed converter that has these merits: (i) the topology of the converter is based on conventional boost and buck-boost converters, which has caused its simplicity; (ii) the voltage gain of the converter has provided higher values by the lower value of the duty cycle; (iii) due to the use of high-efficiency conventional topologies in its structure, the efficiency of the converter keeps its high value for a great interval of duty cycle; (iv) besides the increase of the voltage gain, the current/voltage stresses of the semiconductors have been kept low; (v) the continuous input current of this converter reduces the current stress of the capacitor in the input filter. It is worth noting that the proposed converter has been discussed in both ideal and non-ideal modes. Moreover, the operation of the converter has been discussed in both continuous/discontinuous current modes. The advantages of the converter have been compared with recently suggested converters. In addition, the different features of the converter have been discussed for different conditions. In the small-signal analysis, the appropriate compensator has been designed. Finally, the simulation and experimental results have been reported for 90 W output power, 90 V output voltage, 3-times voltage gain, and 100 kHz switching frequency.
Optimization of Safety System Structures in Railway Transport
Authors: Gill Adrian , Smoczyński Piotr
Published: September 2021

One of the basic strategies for reacting to unacceptable risk is introducing new elements to the analyzed domain. These elements and the relations between them can be treated as a safety system. Although expanding the safety system usually reduces the risk of specific hazards, it often leads to new problems resulting from its excessive development: the system becomes costly and difficult to understand. One of the methods of avoiding the negative issues is to apply an approach described in this paper, which is based on an optimization method making use of the results of risk analysis. The article contains a detailed mathematical description of an optimal solution search algorithm, enabling the selection of a configuration of safety system components that will be the most appropriate in terms of the degree of risk reduction and the related costs. The theoretical part was supplemented with a working example concerning railway traffic control systems. Using the proposed method, it is possible to obtain an optimal structure of a safety system, ensuring at least a tolerated level of risk, adequate to the identified hazards.
Entrepreneurship Recovery in Romania after the Great Recession. A Dynamic Spatial Panel Approach
Authors: Goschin Zizi , Antonia Mihai , Tigau Horia
Published: September 2021

Entrepreneurship plays a key role in transforming the economy and society by stimulating economic development, testing innovative ideas, creating new jobs, and by enriching the quality of life and human existence. Entrepreneurship dynamics depend upon a series of local and national economic factors, but are also affected by the international environment, such as the current COVID-19 pandemic. Statistical data show that new businesses are created at a slower rate during an economic crisis, when the economic climate is harsh, and business opportunities are scarce. Nevertheless, there are local differences in the reaction to crises, and new business formation tends to decline with variable intensity from one region to another, even in the same country. The crises are acting as a trigger for some opportunity-driven entrepreneurs, and resilient regions can thrive even in times of crisis or recover faster after a depression. To capture spatial interactions, as well as spatial short- and long-term effects, the method employed in our analysis relies on the estimation of dynamic spatial panel models. We tested the potential impact of a large variety of social and economic indicators on the creation of new firms and found that the most consequential factors of influence are the economic crisis (expressed through a binary variable), GDP per capita, FDI per capita, inflation, unemployment, and education. Our results convey a powerful policy message for both national and regional decision makers. We believe that, while putting entrepreneurial initiative to the test, the current COVID-19 crisis might act as a catalyst that leads to innovation and reshapes the economy and society.
Comparative Traffic Flow Prediction of a Heuristic ANN Model and a Hybrid ANN-PSO Model in the Traffic Flow Modelling of Vehicles at a Four-Way Signalized Road Intersection
Authors: Olayode Isaac Oyeyemi , Tartibu Lagouge Kwanda , Okwu Modestus O. , Severino Alessandro
Published: September 2021

The accurate and effective prediction of the traffic flow of vehicles plays a significant role in the construction and planning of signalized road intersections. The application of artificially intelligent predictive models in the prediction of the performance of traffic flow has yielded positive results. However, much uncertainty still exists in the determination of which artificial intelligence methods effectively resolve traffic congestion issues, especially from the perspective of the traffic flow of vehicles at a four-way signalized road intersection. A hybrid algorithm, an artificial neural network trained by a particle swarm optimization model (ANN-PSO), and a heuristic Artificial Neural Network model (ANN) were compared in the prediction of the flow of traffic of vehicles using the South Africa transportation system as a case study. Two hundred and fifty-nine (259) traffic datasets were obtained from the South African road network using inductive loop detectors, video cameras, and GPS-controlled equipment. For the ANN and ANN-PSO training and testing, 219 traffic data were used for the training, and 40 were used for the testing of the ANN-PSO model, while training (160), testing (40), and validation (59) was used for the ANN. The ANN result presented a logistic sigmoid transfer function with a 13–6–1 model and a testing R2 of 0.99169 compared to the ANN-PSO result, which showed a testing performance of R2 0.99710. This result shows that the ANN-PSO model is more efficient and effective than the ANN model in the prediction of the traffic flow of vehicles at a four-way signalized road intersection. Furthermore, the ANN and ANN-PSO models are robust enough to predict traffic flow due to their better testing performance. The modelling approaches proposed in this study will assist transportation engineers and urban planners in designing a traffic control system for traffic lights at four-way signalized road intersections. Finally, the results of this research will assist transportation engineers and traffic controllers in providing traffic flow information and travel guidance for motorists and pedestrians in the optimization of their travel time decision-making.
Identification of Promising Smart Farm Technologies and Development of Technology Roadmap Using Patent Map Analysis
Authors: Chun Eunsuk , Jun Sungchan , Lee Chulung
Published: September 2021

In this study, we suggest methodologies for identifying promising and vacant technologies on smart farms by analyzing patent information. Additionally, a technology roadmap for smart farms is suggested using network analysis. The database of patents related to smart farms was extracted from the United States Patent and Trademark Office (USPTO) by keyword search, and valid patents data was selected and clustered using the Latent Dirichlet Allocation (LDA) algorithm. We also conducted the technical importance analysis and trend analysis to identify promising technology topics. By developing a patent map based on a self-organizing map (SOM), we were able to identify vacant technologies among smart farm technology groups. In order to develop vacant technologies, we presented a stepwise technology roadmap by analyzing the relationship between technology elements using network analysis. The proposed procedure and analysis method provides useful insights in establishing research and development (R&D) strategies for the development of smart farm technology roadmaps.
Special Employment Centres, Time Factor and Sustainable Human Resources Management in Spanish Hotel Industry: Can Corporate Social Marketing Improve the Labour Situation of People with Disabilities?
Authors: Cruz-Morato Marco Antonio , García-Mestanza Josefa , Dueñas-Zambrana Carmen
Published: September 2021

Background: Low-quality jobs, long working hours and difficult scheduling of hours have been usually reported in the hotel industry. The situation is more difficult for people with disabilities (PWD), even more in the COVID-19 crisis, especially in terms of labour inclusion (due to the labour discrimination usually suffered by this collective). Thus, Special Employment Centres (SEC) have been created in Spain to spread protected employment of PWD. Although they are improving the situation in the short term, the long-term impact developing sustainable employment is not clear. The objective of this paper is to analyze the Spanish situation, the possible differences between sheltered employment and the ordinary labour market, how SEC could be improving (or not) their labour situation in the hotel sector in the long term, and the potential of incorporating Corporate Social Marketing to overcome the problem. Methods: A content bibliographic analysis has been carried out according to the latest research about this topic, using a ProKnow-C methodology. Results: There seems to be two different groups of papers (supply and demand sides), being the supply side one (focused on HR practices about PWD inclusion and managers’ perceptions of workers with disabilities) more related to our research objective. Furthermore, few articles were found about SEC and Corporate Social Marketing in relation to this topic, highlighting the originality of this research approach. Conclusions: According to our bibliographic portfolio, the presence of labour discrimination in the regular market is more evident; and, in the long term, two opposite situations could be happening simultaneously: (a) SEC would be reinforcing the social stigma, hindering the labour situation of PWD; (b) SEC could be changing the social perspectives of clients and all society in a positive manner. Therefore, it would be necessary to go in-depth into the present subject, from an academic but also practical perspective, incorporating an innovative Corporate Social Marketing approach in order to shed new light on this issue and improving effective sustainable employment of PWD.
Sound-Absorbing Acoustic Concretes: A Review
Authors: Amran Mugahed , Fediuk Roman , Murali Gunasekaran , Vatin Nikolai , Al-Fakih Amin
Published: September 2021

Noise is continuously treated as an annoyance to humans and indeed commotion contamination shows up within the environment, causing inconvenience. This is likewise interesting to the engineering tactic that inclines to develop this noise proliferation. The basics of the sound-retaining proliferation, sound-absorbing properties, and its variables were rarely considered by previous researchers. Thus, the acoustic performance and sound insulation of constructions have gained significance over the last five decades due to the trend for accommodating inner-city flat and multi-story residential building condominiums. Due to this dilemma, the proliferation of high-driven entertaining schemes has engaged extraordinary demands on building for its acoustic performance. Yet, construction industries worldwide have started to mainly use sound-absorbing concrete to reduce the frequency of sounds in opened-and-closed areas and increase sound insulation. As reported, the concrete acoustic properties generally rely on its density, exhibiting that the lighter ones, such as cellular concrete, will absorb more sound than high-density concretes. However, this paper has an objective to afford a wide-ranging review of sound-absorbing acoustic concretes, including the measurement techniques and insulation characteristics of building materials and the sound absorption properties of construction materials. It is also intended to extensively review to provide insights into the possible use of a typical sound-absorbing acoustic concrete in today’s building industry to enhance housing occupants’ efficiency, comfort, well-being, and safety.
DuoTurbo: Implementation of a Counter-Rotating Hydroturbine for Energy Recovery in Drinking Water Networks
Authors: Biner Daniel , Hasmatuchi Vlad , Rapillard Laurent , Chevailler Samuel , Avellan François , Münch-Alligné Cécile
Published: September 2021

To enhance the sustainability of water supply systems, the development of new technologies for micro scale hydropower remains an active field of research. The present paper deals with the implementation of a new micro-hydroelectric system for drinking water facilities, targeting a gross capacity between 5 kW and 25 kW. A counter-rotating microturbine forms the core element of the energy recovery system. The modular in-line technology is supposed to require low capital expenditure, targeting profitability within 10 years. One stage of the DuoTurbo microturbine is composed of two axial counter-rotating runners, each one featured with a wet permanent magnet rim generator with independent speed regulation. This compact mechanical design facilitates the integration into existing drinking water installations. A first DuoTurbo product prototype is developed by means of a Computational Fluid Dynamics based hydraulic design along with laboratory tests to assess system efficiency and characteristics. The agreements between simulated and measured hydraulic characteristics with absolute errors widely below 5% validate the design approach to a large extent. The developed product prototype provides a maximum electrical power of 6.5 kW at a maximum hydraulic head of 75 m, reaching a hydroelectric peak efficiency of 59%. In 2019, a DuoTurbo pilot was commissioned at a drinking water facility to assess its long-term behavior and thus, to validate advanced technology readiness levels. To the best of the authors knowledge, it is the first implementation of a counter-rotating microturbine with independent runner speed regulation and wet rim generators in a real-world drinking water facility. A complete year of operation is monitored without showing significant drifts of efficiency and vibration. The demonstration of the system in operational environment at pre-commercial state is validated that can be attributed to a technology readiness level of 7. The overall results of this study are promising regarding further industrialization steps and potential broad-scale applicability of the DuoTurbo microturbine in the drinking water industry.
Kabul River Flow Prediction Using Automated ARIMA Forecasting: A Machine Learning Approach
Authors: Musarat Muhammad Ali , Alaloul Wesam Salah , Rabbani Muhammad Babar Ali , Ali Mujahid , Altaf Muhammad , Fediuk Roman , Vatin Nikolai , Klyuev Sergey , Bukhari Hamna , Sadiq Alishba , Rafiq Waqas , Farooq Waqas
Published: September 2021

The water level in a river defines the nature of flow and is fundamental to flood analysis. Extreme fluctuation in water levels in rivers, such as floods and droughts, are catastrophic in every manner; therefore, forecasting at an early stage would prevent possible disasters and relief efforts could be set up on time. This study aims to digitally model the water level in the Kabul River to prevent and alleviate the effects of any change in water level in this river downstream. This study used a machine learning tool known as the automatic autoregressive integrated moving average for statistical methodological analysis for forecasting the river flow. Based on the hydrological data collected from the water level of Kabul River in Swat, the water levels from 2011–2030 were forecasted, which were based on the lowest value of Akaike Information Criterion as 9.216. It was concluded that the water flow started to increase from the year 2011 till it reached its peak value in the year 2019–2020, and then the water level will maintain its maximum level to 250 cumecs and minimum level to 10 cumecs till 2030. The need for this research is justified as it could prove helpful in establishing guidelines for hydrological designers, the planning and management of water, hydropower engineering projects, as an indicator for weather prediction, and for the people who are greatly dependent on the Kabul River for their survival.
Comparing Competency Assessment in Electronics Engineering Education with and without Industry Training Partner by Challenge-Based Learning Oriented to Sustainable Development Goals
Authors: Dieck-Assad Graciano , Ávila-Ortega Alfonso , González Peña Omar Israel
Published: September 2021

This study assessed the “creation of technological solutions for electronic devices” competencies evaluation when faculty–industry liaison is available. This experience at Tecnológico de Monterrey (TEC) was developed with challenge-based learning provided by the automotive electronics industry addressing subjects oriented toward some objectives of the Sustainable Development Goals (SDGs). The Electronics Engineering faculty and project engineers from automotive electronics and instrumentation companies promote design competencies in college students. This study analyzed the competency performance and outcome results of students who took applied electronics courses for the undergraduate level under the “i-Semester with industrial partner” for one semester and compared results with students that took the course under the traditional program. The competence evaluation was classified into three preliminary domain levels: 1 or low-level, 2 or medium-level, and 3 or high-level. Students were exposed to the conceptual, procedural, and attitudinal contents applied to solve the challenge assigned by the industrial partner. Students with an industrial partner showed a higher engagement, and they were more motivated in learning the subject, compared to students having classes in the traditional way. This study showed that in developing the competency “create technological solutions for electronic devices”, 55 students with an industrial partner obtained higher domain levels than 61 students with the traditional course.
How to Improve Users’ Loyalty to Smart Health Devices? The Perspective of Compatibility
Authors: Liao Xin , Wu Dongming , Zhang Qianqian , Han Ge
Published: September 2021

Despite the explosive growth of smart health devices in recent years, the industry faces serious sustainability challenges. From the perspective of compatibility, this study proposed a theoretical model to help understand the formation of users’ loyalty. Using an online survey method, we collected empirical data from 375 users with experience of smart health devices. The results indicate that compatibility with online health management and compatibility with value positively affect users’ satisfaction, which in turn contributes to users’ loyalty to smart health devices. Meanwhile, both compatibility with online and offline health management have significant impacts on users’ compatibility with value. Finally, the mediation tests suggested that user satisfaction significantly mediates the effects of compatibility with online practice and compatibility with value on loyalty. Theoretically, this study contributes to the literature by investigating the influence of three compatibilities on loyalty and verifying the underlying mechanism linking them. Practically, the findings of this study can provide valuable insights for practitioners to increase consumers’ loyalty.
Ferulated Pectins from Sugar Beet Bioethanol Solids: Extraction, Macromolecular Characteristics, and Enzymatic Gelling Properties
Authors: Ohlmaier-Delgadillo Federico , Carvajal-Millan Elizabeth , López-Franco Yolanda L. , Islas-Osuna Maria A. , Lara-Espinoza Claudia , Marquez-Escalante Jorge A. , Sanchez-Villegas Jose Alfonso , Rascon-Chu Agustín
Published: September 2021

Pectin from sugar beet (Beta vulgaris L.) (SBP) was extracted from a sugar beet waste (SBW) registering a 4.4% (w/w) yield. SBP presented a weight-average molar mass of 459 kDa, galacturonic acid content of 52.2%, and a low esterification degree (30%). The macromolecular characteristics of SBP revealed a flexible and extended coil chain conformation. The main neutral sugars in SBP were galactose (20.7%), mannose (5.0%), and arabinose (3.60%) while ferulic acid (FA) content was 2.1 µg·mg−1 sample. FA remained in the SBP chain mainly in RG I region even after suffering both, industrial processing and harsh weathering conditions. Consequently, SBP formed covalent gels induced by laccase. Covalent cross-linking content (dimers and trimer of FA) was 0.97 mg·g−1 SBP. The 8-5′, 5-5′, and 8-O-4′ dimers of FA isomers proportions were 75, 17, and 8%, respectively. SBP gels at 4% (w/v ) registered storage (G′) and loss (G″) moduli final values of 44 and 0.66 Pa, respectively. SBP gels were soft and adhesive according to texture profile analysis. Scanning electron microscopy analysis of SBP lyophilized gels revealed an imperfect honeycomb-like structure with 4.5 ± 1.4 µm average cavities diameter.