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The mining industry makes up a large portion of the gross domestic product (GDP) in Australia, although securing human resources remains a problem in that field. The aim of this paper is to identify Australian university mining students' preferences, considering it as potential employees' preferences, for labour conditions at mining sites by means of a discrete choice experiment to promote efficient improvements in labour conditions in the mining industry. The data of 93 respondents analysed in this paper was collected by survey carried out in two universities in Australia. The result of the study showed that students have preferences on several factors such as wage, fatality rate, working position, commuting style, and company. Students having specific sociodemographic characters were found to show specific preferences on labour conditions. The results of this study indicate the potential average of appropriate monetary compensation for each factor.

Being one of the major energy consumers, cooking is a necessary part of daily life. Non renewable cooking fuel sources, such as wood or cow dung cause hazardous pollution and a poor ecosystem worldwide. Over the past few decades, solar-powered cooking has undergone numerous improvements. Solar cooking has been predominantly used as a substitute for reducing oil and gas dependence, increasing environmental sustainability, and reducing global warming threats. This paper talks about the recent development of the box-type solar cooker. The paper discusses the principles and classifications of various parameters that affect the performance, energy, and exergy related to the solar cooking system. In line with the sustainable development goals of the UN agenda 2030 and especially the heed to the accomplishment of SDG 7 and SDG 13, various economic factors, such as the payback period (PP), net present value (NPV), benefit–cost (B–C) ratios, internal rate of return (IRR), levelized cost of heat (LCOH), and levelized cost of cooking a meal (LCCM) have been discussed. The environmental analysis has also been presented to show the overall benefit of solar cooking. The review also focuses on the current development of a box-type solar cooker, its components, and its heat transfer characteristic. Various geometrical modifications, the use of reflectors, and transparent insulating materials that improve cooking have been discussed. The concept of energy storage in the form of Phase change material (Latent heat storage) with the latest studied designs improvements of solar cookers has been obtained to be efficient, which also help in late-evening cooking. It can be said that with better policy implications, the social and economic acceptability of the solar cooker can be achieved.

Regular inspection and monitoring of buildings and infrastructure, that is collectively called the built environment in this paper, is critical. The built environment includes commercial and residential buildings, roads, bridges, tunnels, and pipelines. Automation and robotics can aid in reducing errors and increasing the efficiency of inspection tasks. As a result, robotic inspection and monitoring of the built environment has become a significant research topic in recent years. This review paper presents an in-depth qualitative content analysis of 269 papers on the use of robots for the inspection and monitoring of buildings and infrastructure. The review found nine different types of robotic systems, with unmanned aerial vehicles (UAVs) being the most common, followed by unmanned ground vehicles (UGVs). The study also found five different applications of robots in inspection and monitoring, namely, maintenance inspection, construction quality inspection, construction progress monitoring, as-built modeling, and safety inspection. Common research areas investigated by researchers include autonomous navigation, knowledge extraction, motion control systems, sensing, multi-robot collaboration, safety implications, and data transmission. The findings of this study provide insight into the recent research and developments in the field of robotic inspection and monitoring of the built environment and will benefit researchers, and construction and facility managers, in developing and implementing new robotic solutions.

This paper explores the pace and direction of technological development by using a technology upgrade conceptual and measurement framework. This approach is applied to a sample of 164 economies worldwide between 2002 and 2019. Within the framework of technology upgrading, the paper focuses on digitalisation and “greening” as its two significant structural features. We explore their relationship with different components of technology upgrading and the relationship between technology upgrading components and different indicators of macroeconomic productivity. We have adopted a longitudinal fixed effects regression method with control for unobserved heterogeneity, clustered standard errors, and time dummies. Our results show that the growth of research and development (R&D) capabilities does not translate into aggregate productivity growth. There is a lack of unconditional relationship between aggregate productivity growth, digitalisation and greening. However, there are “latecomer advantages” to basic digitalisation for lower middle- and low-income economies and “latecomer liabilities” in the greening of the economy for upper-middle-income economies. In addition, levels of digitalisation and greening do not correlate, suggesting these two transformation processes are not yet integrated into ‘ICT-assisted greening’. When we control for income levels, the impact of components of technology upgrading on productivity is isolated to specific components and significant only for some income groups. The absence of a significant simultaneous effects of several components of technology upgrading on productivity points to large transformation failures. We conclude that the role of science and technology systems in spurring sustainable development would require a broad scope for science and technology (S&T) policies, their coordination, and integration with non-innovation policies.

High-temperature superconductor (HTS) bulks have demonstrated extremely intriguing potential for industrial and commercial applications due to their capability to trap significantly larger magnetic fields than conventional permanent magnets. The magnetic field in electrical rotating machines is a combination of alternating and rotational fields. In contrast, all previous research on the characterization of electromagnetic properties of HTS have solely engrossed on the alternating AC magnetic fields and the associated AC loss. This research paper gives a thorough examination of the AC loss measurement under various conditions. The obtained results are compared to the finite element-based H-formulation. The AC loss is measured at various amplitudes of circular flux density patterns and compared with the AC loss under one-dimensional alternating flux density. The loss variation has also been studied at other frequencies. The findings in this research paper provide more insights into material characterization, which will be useful in the design of future large-scale HTS applications.

The study of the resistance of plain concrete to high temperatures is a current topic across the field of civil engineering diagnostics. It is a type of damage that affects all components in a complex way, and there are many ways to describe and diagnose this degradation process and the resulting condition of the concrete. With regard to resistance to high temperatures, phenomena such as explosive spalling or partial creep of the material may occur. The resulting condition of thermally degraded concrete can be assessed by a number of destructive and nondestructive methods based on either physical or chemical principles. The aim of this paper is to present a comparison of nondestructive testing of selected concrete mixtures and the subsequent classification of the condition after thermal degradation. In this sense, a classification model based on supervised machine learning principles is proposed, in which the thermal degradation of the selected test specimens are known classes. The whole test set was divided into five mixtures, each with seven temperature classes in 200 °C steps from 200 °C up to 1200 °C. The output of the paper is a comparison of the different settings of the classification model and validation algorithm in relation to the observed parameters and the resulting model accuracy. The classification is done by using parameters obtained by the acoustic NDT Impact-Echo method and image-processing tools.

In an era ruled by data and information, engineers need new tools to cope with the increased complexity of industrial operations. New architectural models for industry enable open communication environments, where workflows can play a major role in providing flexible and dynamic interactions between systems. Workflows help engineers maintain precise control over their factory equipment and Information Technology (IT) services, from the initial design stages to plant operations. The current application of workflows departs from the classic business workflows that focus on office automation systems in favor of a manufacturing-oriented approach that involves direct interaction with cyber-physical systems (CPSs) on the shop floor. This paper identifies relevant industry-related challenges that hinder the adoption of workflow technology, which are classified within the context of a cohesive workflow lifecycle. The classification compares the various workflow management solutions and systems used to monitor and execute workflows. These solutions have been developed alongside the Eclipse Arrowhead framework, which provides a common infrastructure for designing systems according to the microservice architectural principles. This paper investigates and compares various solutions for workflow management and execution in light of the associated industrial requirements. Further, it compares various microservice-based approaches and their implementation. The objective is to support industrial stakeholders in their decision-making with regard to choosing among workflow management solutions., Validerad;2023;Nivå 2;2023-03-02 (joosat);Licens fulltext: CC BY License

In an era ruled by data and information, engineers need new tools to cope with the increased complexity of industrial operations. New architectural models for industry enable open communication environments, where workflows can play a major role in providing flexible and dynamic interactions between systems. Workflows help engineers maintain precise control over their factory equipment and Information Technology (IT) services, from the initial design stages to plant operations. The current application of workflows departs from the classic business workflows that focus on office automation systems in favor of a manufacturing-oriented approach that involves direct interaction with cyber-physical systems (CPSs) on the shop floor. This paper identifies relevant industry-related challenges that hinder the adoption of workflow technology, which are classified within the context of a cohesive workflow lifecycle. The classification compares the various workflow management solutions and systems used to monitor and execute workflows. These solutions have been developed alongside the Eclipse Arrowhead framework, which provides a common infrastructure for designing systems according to the microservice architectural principles. This paper investigates and compares various solutions for workflow management and execution in light of the associated industrial requirements. Further, it compares various microservice-based approaches and their implementation. The objective is to support industrial stakeholders in their decision-making with regard to choosing among workflow management solutions., Validerad;2023;Nivå 2;2023-03-02 (joosat);Licens fulltext: CC BY License

The video classification task has gained significant success in the recent years. Specifically, the topic has gained more attention after the emergence of deep learning models as a successful tool for automatically classifying videos. In recognition of the importance of the video classification task and to summarize the success of deep learning models for this task, this paper presents a very comprehensive and concise review on the topic. There are several existing reviews and survey papers related to video classification in the scientific literature. However, the existing review papers do not include the recent state-of-art works, and they also have some limitations. To provide an updated and concise review, this paper highlights the key findings based on the existing deep learning models. The key findings are also discussed in a way to provide future research directions. This review mainly focuses on the type of network architecture used, the evaluation criteria to measure the success, and the datasets used. To make the review self-contained, the emergence of deep learning methods towards automatic video classification and the state-of-art deep learning methods are well explained and summarized. Moreover, a clear insight of the newly developed deep learning architectures and the traditional approaches is provided. The critical challenges based on the benchmarks are highlighted for evaluating the technical progress of these methods. The paper also summarizes the benchmark datasets and the performance evaluation matrices for video classification. Based on the compact, complete, and concise review, the paper proposes new research directions to solve the challenging video classification problem.

Construction has long been identified as an industry resistant to change and innovation, a reality that has prevailed to shape its overall reputation. The public sector includes an influential client type that dominates the major percentage of construction demand and is subject to public law. The Modern Methods of Construction (MMC) have been championed recently by the UK government and early adopters upon the emergence of data indicating their effectiveness in addressing key construction challenges. However, the uptake of MMC has been low among UK construction clients, particularly among public client organisations. Theories emerge across decades to inform researchers of variable clusters that can aid a broader understanding of decision-making and innovation adoption. One of the popular innovation theories suggests a relation between the characteristics of decision-makers and their own innovation decisions. This paper, therefore, aims to investigate the characteristics that are responsible for public clients’ low MMC uptake despite the associated relative advantages. Overall, 91 public client organisations have responded to this research’s survey, reflecting their organisation’s characteristics in line with the constructs adapted from the Diffusion of Innovation (DOI) theory. Results suggest that among the ten influences that are captured from a detailed review of the literature, confidence in MMC firms supersedes all other factors in critically influencing the organisation’s favourable decision towards using MMC. Evidence provided in this paper suggests that a communication issue is presenting itself in the public construction sector, which is evident by the lack of confidence that public clients have in MMC businesses. This is the first study to utilise quantitative means to examine construction clients’ characteristics and relate the same to the adoption of construction innovation. Future research is encouraged to acknowledge the most influencing characteristics

In a previous paper, the authors implemented a machine learning k-nearest neighbors (KNN) algorithm and Python libraries to create two 3D interactive models of the stratigraphic architecture of the Quaternary onshore Llobregat River Delta (NE Spain) for groundwater exploration purposes. The main limitation of this previous paper was its lack of routines for evaluating the confidence of the 3D models. Building from the previous paper, this paper refines the programming code and introduces an additional algorithm to evaluate the confidence of the KNN predictions. A variant of the Similarity Ratio method was used to quantify the KNN prediction confidence. This variant used weights that were inversely proportional to the distance between each grain-size class and the inferred point to work out a value that played the role of similarity. While the KNN algorithm and Python libraries demonstrated their efficacy for obtaining 3D models of the stratigraphic arrangement of sedimentary porous media, the KNN prediction confidence verified the certainty of the 3D models. In the Llobregat River Delta, the KNN prediction confidence at each prospecting depth was a function of the available data density at that depth. As expected, the KNN prediction confidence decreased according to the decreasing data density at lower depths. The obtained average-weighted confidence was in the 0.44−0.53 range for gravel bodies at prospecting depths in the 12.7−72.4 m b.s.l. range and was in the 0.42−0.55 range for coarse sand bodies at prospecting depths in the 4.6−83.9 m b.s.l. range. In a couple of cases, spurious average-weighted confidences of 0.29 in one gravel body and 0.30 in one coarse sand body were obtained. These figures were interpreted as the result of the quite different weights of neighbors from different grain-size classes at short distances. The KNN algorithm confidence has proven its suitability for identifying these anomalous results in the supposedly well-depurated grain-size da

The main result of this paper is a fixed-point theorem for multivalued contractions obtained through an inequality with rational terms. The contraction is an F-type contraction. The results are obtained in a metric space endowed with a graph. The main theorem is supported by illustrative examples. Several results as special cases are obtained by specific choices of the control functions involved in the inequality. The study is broadly in the domain of setvalued analysis. The methodology of the paper is a blending of both graph theoretic and analytic methods.

The main result of this paper is a fixed-point theorem for multivalued contractions obtained through an inequality with rational terms. The contraction is an F-type contraction. The results are obtained in a metric space endowed with a graph. The main theorem is supported by illustrative examples. Several results as special cases are obtained by specific choices of the control functions involved in the inequality. The study is broadly in the domain of setvalued analysis. The methodology of the paper is a blending of both graph theoretic and analytic methods.

This article analyzes the integrated effect of industrial by-products (spent uidized bed catalytic cracking catalyst waste (FCCCw) and paper sludge waste (PSw) generated in paper manufacturing) combined with nano-SiO2 (NS) on the properties of cement binder, when a certain part of the binder is replaced with the said by-products in the cement mix. Standard testing methods were used to analyze the physical and mechanical properties of cement-based materials. For structure analysis, we used X-ray diffraction (XRD), derivative thermogravimetry (DTG), mercury intrusion porosimetry (MIP) and scanning electron microscopy (SEM). It was found that the replacement of cement by a combined additive of FCCCw, PSw and NS is important not only for ecological reasons (abatement of CO2 emissions and recovery of waste through secondary raw materials), but also in order to enhance the properties of cement-based binders. Presumably, higher amounts of calcium silicate hydrate (CSH) and calcium alumina silicate hydrate (CASH) in the compound binder are the result of the low content of portlandite and alite in the test specimens. The specimens modied with all three additives had the highest density (~2100 kg/m3), ultrasonic pulse velocity (UPV) (~4160 m/s) and compressive strength (~105 MPa), which was ~40% higher than in the control specimens. The average pore diameter of the complex binder decreased by 21%, whereas the median pore diameter decreased by 47%., Tento článek analyzuje integrovaný účinek průmyslových vedlejších produktů (vyhořelého lože odpad katalyzátoru z katalytického krakování (FCCCw) a odpad z papírového kalu (PSw) vznikající při výrobě papíru) v kombinaci s nano-SiO2 (NS) o vlastnostech cementového pojiva, když je určitá část pojiva nahrazena uvedenými vedlejšími produkty v cementová směs. K analýze fyzikálních a mechanických vlastností materiálů na bázi cementu byly použity standardní zkušební metody. Pro strukturní analýzu jsme použili rentgenovou difrakci (XRD), derivační termogravimetrii (DTG), rtuťovou vnikovou porozimetrii (MIP) a rastrovací elektronovou mikroskopii (SEM). Bylo zjištěno, že nahrazení cementu kombinovanou přísadou FCCCw, PSw a NS je důležité nejen z ekologických důvodů (snížení emisí CO2 a využití odpadu prostřednictvím druhotných surovin), ale také za účelem zlepšení vlastností cementu - pojiva na bázi. Pravděpodobně vyšší množství hydrátu křemičitanu vápenatého (CSH) a hydrátu křemičitanu vápenato-hlinitého (CASH) ve složeném pojivu jsou výsledkem nízkého obsahu portlanditu a alitu ve zkušebních vzorcích. Vzorky modifikované všemi třemi přísadami měly nejvyšší hustotu (~ 2100 kg / m3), rychlost ultrazvukového pulzu (UPV) (~ 4 160 m / s) a pevnost v tlaku (~ 105 MPa), která byla o ~ 40% vyšší než u kontrolních vzorků. Průměrný průměr pórů komplexního pojiva se snížil o 21%, zatímco střední průměr pórů se snížil o 47%.

This article analyzes the integrated effect of industrial by-products (spent uidized bed catalytic cracking catalyst waste (FCCCw) and paper sludge waste (PSw) generated in paper manufacturing) combined with nano-SiO2 (NS) on the properties of cement binder, when a certain part of the binder is replaced with the said by-products in the cement mix. Standard testing methods were used to analyze the physical and mechanical properties of cement-based materials. For structure analysis, we used X-ray diffraction (XRD), derivative thermogravimetry (DTG), mercury intrusion porosimetry (MIP) and scanning electron microscopy (SEM). It was found that the replacement of cement by a combined additive of FCCCw, PSw and NS is important not only for ecological reasons (abatement of CO2 emissions and recovery of waste through secondary raw materials), but also in order to enhance the properties of cement-based binders. Presumably, higher amounts of calcium silicate hydrate (CSH) and calcium alumina silicate hydrate (CASH) in the compound binder are the result of the low content of portlandite and alite in the test specimens. The specimens modied with all three additives had the highest density (~2100 kg/m3), ultrasonic pulse velocity (UPV) (~4160 m/s) and compressive strength (~105 MPa), which was ~40% higher than in the control specimens. The average pore diameter of the complex binder decreased by 21%, whereas the median pore diameter decreased by 47%., Tento článek analyzuje integrovaný účinek průmyslových vedlejších produktů (vyhořelého lože odpad katalyzátoru z katalytického krakování (FCCCw) a odpad z papírového kalu (PSw) vznikající při výrobě papíru) v kombinaci s nano-SiO2 (NS) o vlastnostech cementového pojiva, když je určitá část pojiva nahrazena uvedenými vedlejšími produkty v cementová směs. K analýze fyzikálních a mechanických vlastností materiálů na bázi cementu byly použity standardní zkušební metody. Pro strukturní analýzu jsme použili rentgenovou difrakci (XRD), derivační termogravimetrii (DTG), rtuťovou vnikovou porozimetrii (MIP) a rastrovací elektronovou mikroskopii (SEM). Bylo zjištěno, že nahrazení cementu kombinovanou přísadou FCCCw, PSw a NS je důležité nejen z ekologických důvodů (snížení emisí CO2 a využití odpadu prostřednictvím druhotných surovin), ale také za účelem zlepšení vlastností cementu - pojiva na bázi. Pravděpodobně vyšší množství hydrátu křemičitanu vápenatého (CSH) a hydrátu křemičitanu vápenato-hlinitého (CASH) ve složeném pojivu jsou výsledkem nízkého obsahu portlanditu a alitu ve zkušebních vzorcích. Vzorky modifikované všemi třemi přísadami měly nejvyšší hustotu (~ 2100 kg / m3), rychlost ultrazvukového pulzu (UPV) (~ 4 160 m / s) a pevnost v tlaku (~ 105 MPa), která byla o ~ 40% vyšší než u kontrolních vzorků. Průměrný průměr pórů komplexního pojiva se snížil o 21%, zatímco střední průměr pórů se snížil o 47%.

The main result of this paper is a fixed-point theorem for multivalued contractions obtained through an inequality with rational terms. The contraction is an F-type contraction. The results are obtained in a metric space endowed with a graph. The main theorem is supported by illustrative examples. Several results as special cases are obtained by specific choices of the control functions involved in the inequality. The study is broadly in the domain of setvalued analysis. The methodology of the paper is a blending of both graph theoretic and analytic methods.

The operation of so-called Zero Emission Buildings (ZEB) does not result in harmful emissions to water, soil and air. In contrast, ZEBs produce energy, water and resources. Therefore, the definition of ZEBs in this paper goes well beyond the definition of (Net) Zero Energy Buildings, which focuses primarily on greenhouse gas emissions resulting from the combustion of fossil fuels. The concept of ZEB is based on the decentralization of urban infrastructure systems on the building level. The aim is to avoid environmental impacts during the building operation through sustainable production, management, consumption, and recycling of resources. In order to facilitate an easy evaluation of ZEBs a ZEB assessment tool needed to be developed. This paper discusses the development of the general framework, the assessment method, and the ZEB Assessment Tool (ZEBAT), which facilitates the evaluation of the environmental performance of potential ZEBs. The exemplary evaluation of selected case studies from Switzerland and South Korea illustrates the method and the practicability of the ZEBAT for the evaluation of potential ZEBs. The holistic integration of environmental performance factors and their specific environmental impacts facilitates the successful application of the ZEBAT independently from the specific use of a building and its geographical location.

The operation of so-called Zero Emission Buildings (ZEB) does not result in harmful emissions to water, soil and air. In contrast, ZEBs produce energy, water and resources. Therefore, the definition of ZEBs in this paper goes well beyond the definition of (Net) Zero Energy Buildings, which focuses primarily on greenhouse gas emissions resulting from the combustion of fossil fuels. The concept of ZEB is based on the decentralization of urban infrastructure systems on the building level. The aim is to avoid environmental impacts during the building operation through sustainable production, management, consumption, and recycling of resources. In order to facilitate an easy evaluation of ZEBs a ZEB assessment tool needed to be developed. This paper discusses the development of the general framework, the assessment method, and the ZEB Assessment Tool (ZEBAT), which facilitates the evaluation of the environmental performance of potential ZEBs. The exemplary evaluation of selected case studies from Switzerland and South Korea illustrates the method and the practicability of the ZEBAT for the evaluation of potential ZEBs. The holistic integration of environmental performance factors and their specific environmental impacts facilitates the successful application of the ZEBAT independently from the specific use of a building and its geographical location.

Based on a welfare approach using a partial equilibrium model coming from microeconomics, this paper analyzes whether a local regulation aimed at reducing risks due to pesticides should be imposed at the production level or the consumption level. This paper characterizes the economic impact of these possible regulations from a theoretical point of view. Local and non-local producers compete only in the local market regarding selling conventional and organic products. Local producers incur variable costs related to reducing the risk of damage resulting from their new organic production methods. A local policymaker maximizing local welfare chooses either a regulation that is imposed on its local producers via production requirements or on all local and non-local producers via retail requirements that directly affect consumption. We show that local regulation is selected for relatively large values of damage. In this case, the organic regulation is influenced by whether the damage is incurred by residents and the environment close to the production site or by consumers. If the damage is incurred by residents and the environment close to the production site, only regulations targeting the local producers are selected, which improves the profits for non-local producers. Concerning damage incurred by consumers after their consumption, each type of regulation is selected depending on the cost of the safe technology, but the regulation targeting the consumption level harms non-local producers.

Based on a welfare approach using a partial equilibrium model coming from microeconomics, this paper analyzes whether a local regulation aimed at reducing risks due to pesticides should be imposed at the production level or the consumption level. This paper characterizes the economic impact of these possible regulations from a theoretical point of view. Local and non-local producers compete only in the local market regarding selling conventional and organic products. Local producers incur variable costs related to reducing the risk of damage resulting from their new organic production methods. A local policymaker maximizing local welfare chooses either a regulation that is imposed on its local producers via production requirements or on all local and non-local producers via retail requirements that directly affect consumption. We show that local regulation is selected for relatively large values of damage. In this case, the organic regulation is influenced by whether the damage is incurred by residents and the environment close to the production site or by consumers. If the damage is incurred by residents and the environment close to the production site, only regulations targeting the local producers are selected, which improves the profits for non-local producers. Concerning damage incurred by consumers after their consumption, each type of regulation is selected depending on the cost of the safe technology, but the regulation targeting the consumption level harms non-local producers.

Based on a welfare approach using a partial equilibrium model coming from microeconomics, this paper analyzes whether a local regulation aimed at reducing risks due to pesticides should be imposed at the production level or the consumption level. This paper characterizes the economic impact of these possible regulations from a theoretical point of view. Local and non-local producers compete only in the local market regarding selling conventional and organic products. Local producers incur variable costs related to reducing the risk of damage resulting from their new organic production methods. A local policymaker maximizing local welfare chooses either a regulation that is imposed on its local producers via production requirements or on all local and non-local producers via retail requirements that directly affect consumption. We show that local regulation is selected for relatively large values of damage. In this case, the organic regulation is influenced by whether the damage is incurred by residents and the environment close to the production site or by consumers. If the damage is incurred by residents and the environment close to the production site, only regulations targeting the local producers are selected, which improves the profits for non-local producers. Concerning damage incurred by consumers after their consumption, each type of regulation is selected depending on the cost of the safe technology, but the regulation targeting the consumption level harms non-local producers.

Based on a welfare approach using a partial equilibrium model coming from microeconomics, this paper analyzes whether a local regulation aimed at reducing risks due to pesticides should be imposed at the production level or the consumption level. This paper characterizes the economic impact of these possible regulations from a theoretical point of view. Local and non-local producers compete only in the local market regarding selling conventional and organic products. Local producers incur variable costs related to reducing the risk of damage resulting from their new organic production methods. A local policymaker maximizing local welfare chooses either a regulation that is imposed on its local producers via production requirements or on all local and non-local producers via retail requirements that directly affect consumption. We show that local regulation is selected for relatively large values of damage. In this case, the organic regulation is influenced by whether the damage is incurred by residents and the environment close to the production site or by consumers. If the damage is incurred by residents and the environment close to the production site, only regulations targeting the local producers are selected, which improves the profits for non-local producers. Concerning damage incurred by consumers after their consumption, each type of regulation is selected depending on the cost of the safe technology, but the regulation targeting the consumption level harms non-local producers.

This paper describes the fabrication opportunities that Printed Circuit Boards (PCBs) offer for electronic and biomedical engineering. Historically, PCB substrates have been used to support the components of the electronic devices, linking them using copper lines, and providing input and output pads to connect the rest of the system. In addition, this kind of substrate is an emerging material for biomedical engineering thanks to its many interesting characteristics, such as its commercial availability at a low cost with very good tolerance and versatility, due to its multilayer characteristics; that is, the possibility of using several metals and substrate layers. The alternative uses of copper, gold, Flame Retardant 4 (FR4) and silver layers, together with the use of vias, solder masks and a rigid and flexible substrate, are noted. Among other uses, these characteristics have been using to develop many sensors, biosensors and actuators, and PCB-based lab-on chips; for example, deoxyribonucleic acid (DNA) amplification devices for Polymerase Chain Reaction (PCR). In addition, several applications of these devices are going to be noted in this paper, and two tables summarizing the layers’ functions are included in the discussion: the first one for metallic layers, and the second one for the vias, solder mask, flexible and rigid substrate functions.

This paper presents the design of a safety system based on controlled electromagnetic field (CEMF) sensing technology to prevent accidents caused by power tools, especially related to handheld circular saws. The safety system creates an invisible protection bubble of electromagnetic field around the cutting edge. The system can provide early warning or critical warning when a person penetrates the safety bubble. This paper covers how the CEMF technology has been adapted to add value within this application where it needs to coexist with a difficult environment of metallic parts turning thousands of times per minute, strong vibrations, and different ranges of materials to be processed. The proposed contactless solution successfully detects the user, providing enough time for the power tool to totally stop its movement before touching and harming the user. This key property has required a careful optimization of the electromagnetic field generation, the design of a shield circuitry capable of operating properly in a large metal device, and the development of a multi-frame algorithm to address the stringent requirements related to the ability of the system to react to both very fast and very slow events. The feasibility of the system has been validated by a virtual testbench.

This paper set out to explore the precision agriculture (PA)-training needs of students studying in agricultural universities in the Euro-Mediterranean region (Greece, Italy, Portugal and Spain). SPARKLE is a Knowledge Alliance Project, funded by the European Union (EU), and one of its main goals is to narrow the innovation divide between entrepreneurship and the effective application of sustainable PA. During the project, the research conducted in all countries in the Euro-Mediterranean region revealed differences in the PA-training needs of university students. Additionally, this paper set out to explore the socioeconomic characteristics of students that affect their interest and knowledge towards PA. Finally, this paper aimed to understand the scope, present status and strategies for improving PA training in agricultural universities in the Euro-Mediterranean region. The following descriptive statistics and two multivariate analysis techniques were used: Two-Step Cluster Analysis (TSCA) and Categorical Regression (CATREG). Results support the notion that the lack of “PA knowledge/interest” adds to the technological gap amongst university students, slow adoption of PA and lower levels of overall rural economic development. These findings will be used as the fundamental cognition for the development of a joint action plan and several other national plans in the selected regions.

In this paper, we aim to open up new perspectives in the field of autonomous aerial surveillance and target tracking systems, by exploring an alternative that, surprisingly, and to the best of the authors’ knowledge, has not been addressed in that context by the research community thus far. It can be summarized by the following two questions. Under the scope of such applications, what are the implications and possibilities offered by mounting several steerable cameras onboard of each aerial agent? Second, how can optimization algorithms benefit from this new framework, in their attempt to provide more efficient and cost-effective solutions on these areas? The paper presents the idea as an additional degree of freedom to be exploited, which can enable more efficient alternatives in the deployment of such applications. As an initial approach, the problem of the optimal positioning with respect to a set of targets of one single agent, equipped with several onboard tracking cameras with different or variable focal lengths, is addressed. As a consequence of this allowed heterogeneity in focal lengths, the notion of distance needs to be adapted into a notion of optical range, as the agent can trade longer Euclidean distances for correspondingly longer focal lengths. Moreover, the proposed optimization indices try to balance, in an optimal way, the verticality of the viewpoints along with the optical range to the targets. Under these premises, several positioning strategies are proposed and comparatively evaluated.

This paper presents a method for switching reduction in cascaded H-bridge converters. Given the wide applicability of this topology, it would be especially desirable to increase its efficiency with switching losses reduction techniques. Since this type of converter requires voltage balancing methods, several modulation methods consider the possibility of combining the balancing and switching reduction goals together. In this paper, a previously disclosed optimization-based balance method was modified further to consider the switching losses in its objective function. Each commutation was penalized in proportion to the phase current and the module voltage, thus avoiding commutations that would produce the most losses but tolerating low-losses commutations. The structure of the original method was maintained so that the algorithm could be applied with minimal change. The results show that it is possible to reduce the switching up to 14% without any noticeable drawback and up to 22% at the cost of a greater DC-link ripple. It is also possible to selectively reduce the effective switching frequency of only some modules, making it significantly low. This extends the adaptability of the converter, possibly allowing hybrid converters with modules of different transistor technologies.

Thermal energy storage (TES) allows the existing mismatch between supply and demand in energy systems to be overcome. Considering temperatures above 150 °C, there are major potential benefits for applications, such as process heat and electricity production, where TES coupled with concentrating solar power (CSP) plants can increase the penetration of renewable energies. To this end, this paper performs a critical analysis of the literature on the current and most promising concrete energy storage technologies, identifying five challenges that must be overcome for the successful exploitation of this technology. With these five challenges in mind, this paper proposes an approach that uses a new modular design of concrete-based TES. A preliminary study of the feasibility of the proposed system was performed using computational fluid dynamics (CFD) techniques, showing promising results.

Improving energy efficiency in buildings has a key role to play in achieving the ambitious goal of EU-wide climate neutrality by 2050, set out in the European Green Deal. This paper describes a cost-optimal analysis of residential buildings of Valencian Community, Spain. Thus, an assessment of the contribution of total primary energy savings per year (MW/h) of the social dwellings managed by EVha, Entitat Valenciana d’Habitatge i Sòl (eng. Valencian entity for dwelling and ground) towards the national contribution is presented in this paper. To assess it, the MedZEB cost-optimal methodology has been applied to optimise the performance of the building’s envelope. This means that Optimal Renovation Strategies through Life-Cycle Analysis have been applied to obtain the Packages of Optimal Solutions of the different reference buildings in a reference climate. First, the renovation scenario with 100% of the building stock being renovated has been calculated. Then, the renovation scenario of 1%, being the current European rate of renovation and, finally the renovation scenario of 2%, given that the objective of the Renovation Wave is to at least double the annual energy renovation rate of residential and non-residential buildings by 2030 and to foster deep energy renovations.

In this paper, we show how volume rendering with a Programmable Transfer Function can be used for the effective and comprehensible visualization of WiFi signals. A traditional transfer function uses a low-dimensional lookup table to map the volumetric scalar field to color and opacity. In this paper, we present the concept of a Programmable Transfer Function. We then show how generalizing traditional lookup-based transfer functions to Programmable Transfer Functions enables us to leverage view-dependent and real-time attributes of a volumetric field to depict the data variations of WiFi surfaces with low and high-frequency components. Our Programmable Transfer Functions facilitate interactive knowledge discovery and produce meaningful visualizations.

Nowadays, digital transformation (DX) is the key concept to change and improve the operations in governments, companies, and schools. Therefore, any data should be digitized for processing by computers. Unfortunately, a lot of data and information are printed and handled on paper, although they may originally come from digital sources. Data on paper can be digitized using an optical character recognition (OCR) software. However, if the paper contains a table, it becomes difficult because of the separated characters by rows and columns there. It is necessary to solve the research question of "how to convert a printed table on paper into an Excel table while keeping the relationships between the cells?" In this paper, we propose a printed table digitization algorithm using image processing techniques and OCR software for it. First, the target paper is scanned into an image file. Second, each table is divided into a collection of cells where the topology information is obtained. Third, the characters in each cell are digitized by OCR software. Finally, the digitalized data are arranged in an Excel file using the topology information. We implement the algorithm on Python using OpenCV for the image processing library and Tesseract for the OCR software. For evaluations, we applied the proposal to 19 scanned and 17 screenshotted table images. The results show that for any image, the Excel file is generated with the correct structure, and some characters are misrecognized by OCR software. The improvement will be in future works.

Information on congestion of buses, which are one of the major public transportation modes, can be very useful in light of the current COVID-19 pandemic. Because it is unrealistic to manually monitor the number of riders on all buses in operation, a system that can automatically monitor congestion is necessary. The main goal of this paper’s work is to automatically estimate the congestion level on a bus route with acceptable performance. For practical operation, it is necessary to design a system that does not infringe on the privacy of passengers and ensures the safety of passengers and the installation sites. In this paper, we propose a congestion estimation system that protects passengers’ privacy and reduces the installation cost by using Bluetooth low-energy (BLE) signals as sensing data. The proposed system consists of (1) a sensing mechanism that acquires BLE signals emitted from passengers’ mobile terminals in the bus and (2) a mechanism that estimates the degree of congestion in the bus from the data obtained by the sensing mechanism. To evaluate the effectiveness of the proposed system, we conducted a data collection experiment on an actual bus route in cooperation with Nara Kotsu Co., Ltd. The results showed that the proposed system could estimate the number of passengers with a mean absolute error of 2.49 passengers (error rate of 38.8%)

The automatic classification of aluminum profile surface defects is of great significance in improving the surface quality of aluminum profiles in practical production. This classification is influenced by the small and unbalanced number of samples and lack of uniformity in the size and spatial distribution of aluminum profile surface defects. It is difficult to achieve high classification accuracy by directly using the current advanced classification algorithms. In this paper, digital image processing methods such as rotation, flipping, contrast, and luminance transformation were used to augment the number of samples and imitate the complex imaging environment in actual practice. A RepVGG with CBAM attention mechanism (RepVGG-CBAM) model was proposed and applied to classify ten types of aluminum profile surface defects. The classification accuracy reached 99.41%, in particular, the proposed method can perfectly classify six types of defects: concave line (cl), exposed bottom (eb), exposed corner bottom (ecb), mixed color (mc), non-conductivity (nc) and orange peel (op), with 100% precision, recall, and F1. Compared with the existing advanced classification algorithms VGG16, VGG19, ResNet34, ResNet50, ShuffleNet_v2, and basic RepVGG, our model is the best in terms of accuracy, macro precision, macro recall and macro F1, and the accuracy was improved by 4.85% over basic RepVGG. Finally, an ablation experiment proved that the classification ability was strongest when the CBAM attention mechanism was added following Stage 1 to Stage 4 of RepVGG. Overall, the method we proposed in this paper has a significant reference value for classifying aluminum profile surface defects.

Information on congestion of buses, which are one of the major public transportation modes, can be very useful in light of the current COVID-19 pandemic. Because it is unrealistic to manually monitor the number of riders on all buses in operation, a system that can automatically monitor congestion is necessary. The main goal of this paper’s work is to automatically estimate the congestion level on a bus route with acceptable performance. For practical operation, it is necessary to design a system that does not infringe on the privacy of passengers and ensures the safety of passengers and the installation sites. In this paper, we propose a congestion estimation system that protects passengers’ privacy and reduces the installation cost by using Bluetooth low-energy (BLE) signals as sensing data. The proposed system consists of (1) a sensing mechanism that acquires BLE signals emitted from passengers’ mobile terminals in the bus and (2) a mechanism that estimates the degree of congestion in the bus from the data obtained by the sensing mechanism. To evaluate the effectiveness of the proposed system, we conducted a data collection experiment on an actual bus route in cooperation with Nara Kotsu Co., Ltd. The results showed that the proposed system could estimate the number of passengers with a mean absolute error of 2.49 passengers (error rate of 38.8%), journal article

This paper set out to explore the precision agriculture (PA)-training needs of students studying in agricultural universities in the Euro-Mediterranean region (Greece, Italy, Portugal and Spain). SPARKLE is a Knowledge Alliance Project, funded by the European Union (EU), and one of its main goals is to narrow the innovation divide between entrepreneurship and the effective application of sustainable PA. During the project, the research conducted in all countries in the Euro-Mediterranean region revealed differences in the PA-training needs of university students. Additionally, this paper set out to explore the socioeconomic characteristics of students that affect their interest and knowledge towards PA. Finally, this paper aimed to understand the scope, present status and strategies for improving PA training in agricultural universities in the Euro-Mediterranean region. The following descriptive statistics and two multivariate analysis techniques were used: Two-Step Cluster Analysis (TSCA) and Categorical Regression (CATREG). Results support the notion that the lack of “PA knowledge/interest” adds to the technological gap amongst university students, slow adoption of PA and lower levels of overall rural economic development. These findings will be used as the fundamental cognition for the development of a joint action plan and several other national plans in the selected regions.

Producción Científica, This paper reviews different existing systems of seedling microirrigation in afforestation. These systems differ from agricultural irrigation methods since they only pursue the establishment of the planted seedlings instead of achieving good agricultural yields. They, therefore, involve very low irrigation doses compared to the usual irrigation doses found in the agricultural sector. These approaches are nonconventional localized irrigation systems with high efficiency in water application. Based on the water discharge equations they use, these methods can be classified into four groups: direct deep irrigation, irrigation through porous walls, irrigation with wicks, and irrigation with solar distillers. This paper describes a total of sixteen different systems suitable for afforestation. All the systems are compared with each other. To make the comparisons, four key parameters are considered: the cost of acquiring and installing the system, the water application efficiency, the maintenance of the system, and the possibility of irrigating several plants at the same time. The irrigation systems described in this review represent an important technical advance not only for dryland forestry but also for rainfed arboriculture, xeriscaping, and xerogardening. These systems make it possible to widely extend the planting period to almost throughout the year, not only in arid regions but also in less dry or even humid climates, especially when critical areas have to be afforested, including shallow, sandy, saline, or gypseous soils, suntraps, windy and desertified areas, open pit mines, and other areas. Seedling microirrigation is an emerging sector of the irrigation industry that is rapidly developing with new devices and patents. Two foreseeable future trends can be identified: the growing use of new permeable materials and the possibility of connecting individual emitters to irrigation lines.

Producción Científica, This paper analyzes the direct influence of CSR educational actions on business confidence in the context of the banking sector in an emerging country (Peru). A mediating effect through corporate reputation is also analyzed. To test the hypotheses presented in this paper, we have sent a survey to 1745 executive officers of the branches of the banks. These key individuals were selected as the target population of the study because the authors sought to study the management’s perception of CSR and business confidence. From the data obtained from the survey, it has been tested that educational CSR actions in Peruvian banks directly influences the perception of business confidence. Secondly, this relationship is partially mediated by the effect of CSR educational actions on corporate reputation.

Producción Científica, Tuber melanosporum (Ascomycota, Pezizales) is an ectomycorrhizal fungus that produces highly appreciated hypogeous fruiting bodies called black truffles. The aim of this paper was to research the composition of ectomycorrhiza-associated fungal and bacterial communities in T. melanosporum oak plantations. Results of this paper showed the competitive effect of T. melanosporum on other fungal species, especially other mycorrhizal and pathogenic species. T. melanosporum was shown to be associated mainly with bacteria, some of them important for their properties as mycorrhizal helper bacteria. A dendrogram analysis of co-occurrence showed that T. melanosporum tended to co-occur with the following bacteria species: Singulisphaera limicola, Nannocistis excedens and Sporosarcina globispora. In addition, it was linked to fungal species such as Mortierella elongata, M. minutissima, Cryptococcus uzbekistanensis, C. chernovii and C. aerius. This study provides an exhaustive analysis of the diversity, structure and composition of fungal and bacterial communities associated with T. melanosporum to enhance understanding of the biology, composition and role of these communities in truffle plantations., Junta de Castilla y León y Fondo Europeo de Desarrollo Regional (FEDER) - (Project CLU-2019-01-iuFOR), European Union’s Horizon 2020 - (Grant 734907), Junta de Castilla y León - (Project 04/16/PA/0001)

Producción Científica, There is an increasing interest in improving energy efficiency and reducing operational costs of induction motors in the industry. These costs can be significantly reduced, and the efficiency of the motor can be improved if the condition of the machine is monitored regularly and if monitoring techniques are able to detect failures at an incipient stage. An early fault detection makes the elimination of costly standstills, unscheduled downtime, unplanned breakdowns, and industrial injuries possible. Furthermore, maintaining a proper motor operation by reducing incipient failures can reduce motor losses and extend its operating life. There are many review papers in which analyses of fault detection techniques in induction motors can be found. However, all these reviewed techniques can detect failures only at developed or advanced stages. To our knowledge, no review exists that assesses works able to detect failures at incipient stages. This paper presents a review of techniques and methodologies that can detect faults at early stages. The review presents an analysis of the existing techniques focusing on the following principal motor components: stator, rotor, and rolling bearings. For steady-state and transient operating modes of the motor, the methodologies are discussed and recommendations for future research in this area are also presented.

Producción Científica, In this paper, a technique that integrates methods of dynamic economic optimization and real-time control by including economic model predictive control and closed-loop predictive control has been developed, using a two-layer structure. The upper layer, which consists of an economic nonlinear MPC (NMPC), makes use of the updated state information to optimize some economic cost indices and calculates in real time the economically optimal trajectories for the process states. The lower layer uses a closed-loop nonlinear GPC (NCLGPC) to calculate the control actions that allow for the outputs of the process to follow the trajectories received from the upper layer. This paper also includes the theoretical demonstration proving that the deviation between the state of the closed-loop system and the economically time varying trajectory provided by the upper layer is bounded, thus guaranteeing stability. The proposed approach is based on the use of nonlinear models to describe all the relevant process dynamics and cover a wide operating range, providing accurate predictions and guaranteeing the performance of the control systems. In particular, the methodology is implemented in the N-Removal process of a WWTP and the results demonstrate that the method is effective and can be used profitably in practical cases such as the chemical, refinery and petrochemical process industries., Ministerio de Economía y Competitividad - (project DPI2015- 67341C21R), Junta de Castilla y Leon y Fondo Europeo de Desarrollo Regional (FEDER) - (grants CLU 2017-09 and UIC 233)

Background: Pediatric minimally invasive surgery (MIS) is a standard technique worldwide. We aimed to analyze the research activity in this field. Methods: Articles on pediatric MIS (1991–2020) were analyzed from the Web of Science™ for the total number of publications, citations, journals, and impact factors (IF). Of these, the 50 most cited publications were evaluated in detail and classified according to the level of evidence (i.e., study design) and topic (i.e., surgical procedure). Results: In total, 4464 publications and 53,111 citations from 684 journals on pediatric MIS were identified. The 50 most cited papers were published from 32 institutions in the USA/Canada (n = 28), Europe (n = 19), and Asia (n = 3) in 12 journals. Four authors (USA/Europe) contributed to 26% of the 50 most cited papers as first/senior author. Hot topics were laparoscopic pyeloplasty (n = 9), inguinal hernia repair (n = 7), appendectomy, and pyloromyotomy (n = 4 each). The majority of publications were retrospective studies (n = 33) and case reports (n = 6) (IF 5.2 ± 3.2; impact index 16.5 ± 6.4; citations 125 ± 39.4). They were cited as often as articles with high evidence levels (meta-analyses, n = 2; randomized controlled trials, n = 7; prospective studies, n = 2) (IF 12.9 ± 22.5; impact index 14.0 ± 6.5; citations 125 ± 34.7; p > 0.05). Conclusions: Publications on laparoscopic pyeloplasty, inguinal hernia repair, appendectomy, and pyloromyotomy are cited most often in pediatric MIS. However, the relevant number of studies with strong evidence for the advantages of MIS in pediatric surgery is missing.

Climate change-related hazards will aggravate and impact differently on urban societies. Although early warning systems will be important for reducing the hazard risks in cities, the nature of early warning systems that are available to residents of informal settlements remains less understood. This paper aimed to assess the early warning systems through which informal dwellers reduce their hazard risks in an African city. Using Accra as the case, data were collected from 582 households using a structured questionnaire along with 25 institutional key informant interviews and 14 focus discussions with state and settlement actors in this study. Findings of the paper show that a mix of formal and informal early warning systems are utilized by residents of informal settlements, but the majority of them perceived state disaster management institutions as not performing optimally in their resident settlements. The nature of land ownership in the informal settlements influenced their political exclusion and state institutions’ decisions not to locate weather monitoring equipment in their settlements. Respondents without the security of land tenure perceived state disaster management institutions as not performing optimally, which negatively affects their capacity to respond to climate change-related hazards. The paper thus recommends the incorporation of informal early warning systems into city-wide hazard early warning systems through participatory planning in Accra and similar contexts. Future scholars may extend this discourse by examining the effect of the use of informal early warning systems on the uptake of formal hazard early warning sources in informal settlements.

Pterygium is an eye condition that causes the fibrovascular tissues to grow towards the corneal region. At the early stage, it is not a harmful condition, except for slight discomfort for the patients. However, it will start to affect the eyesight of the patient once the tissues encroach towards the corneal region, with a more serious impact if it has grown into the pupil region. Therefore, this condition needs to be identified as early as possible to halt its growth, with the use of simple eye drops and sunglasses. One of the associated risk factors for this condition is a low educational level, which explains the reason that the majority of the patients are not aware of this condition. Hence, it is important to develop an automated pterygium screening system based on simple imaging modalities such as a mobile phone camera so that it can be assessed by many people. During the early stage of automated pterygium screening system development, conventional machine learning techniques such as support vector machines and artificial neural networks are the de facto algorithms to detect the presence of pterygium tissues. However, with the arrival of the deep learning era, coupled with the availability of large training data, deep learning networks have replaced the conventional networks in screening for the pterygium condition. The deep learning networks have been successfully implemented for three major purposes, which are to classify an image regarding whether there is the presence of pterygium tissues or not, to localize the lesion tissues through object detection methodology, and to semantically segment the lesion tissues at the pixel level. This review paper summarizes the type, severity, risk factors, and existing state-of-the-art technology in automated pterygium screening systems. A few available datasets are also discussed in this paper for both classification and segmentation tasks. In conclusion, a computer-assisted pterygium screening system will benefit many p

Corporate identity has played a vital role in the Halal industry to create a strong foundation for its reputation in the long run. This paper used two modeling analyses for two different data. The first analysis aims to predict the relationship between Corporate Identity Management between Internal Brand and Employee Brand Support (consequence) mediated by CIM using partial-least squares-structural equation modeling (PLS-SEM). A total of 206 employees from Malaysia’s Halal food SMEs took part in the survey. The second analysis to identify topic proportions patterns using the topic modeling approach on Halal brand identity Machine learning approach of knowledge mining was applied for this analysis. Metadata of 1,091 articles were mined from the Scopus database on Halal studies across all social sciences fields. The result revealed that there was a partial relationship between Internal Brand (antecedent) and Employee Brand Support (consequence) mediated by CIM. This finding was supported by the identified topic proportions patterns from the topic modeling approach that pointed out a weak topic proportion on the Halal brand identity discussion globally, interestingly the result also found that the Halal brand identity discussion involving the Halal food industry is almost non-existed in Malaysia’s Halal food SMEs. The contributions of this paper were apparent in three major areas which are methodology, theoretical and future suggestions. The utilization of two different model analyses was able to confirm the consistency of the major findings with the literature review which opens up more possibilities for future researchers.

The food delivery service is the most typical and visible example of online-to-offline (O2O) commerce. More consumers are using food delivery services for various reasons during the COVID-19 pandemic, making this business model viral worldwide. In the post-pandemic era, offering food delivery services will become the new normal for restaurants. Although a growing number of publications have focused on consumer behavior in this issue, no review paper has addressed current research and industry trends. Thus, this paper aims to review the literature published from 2020 to the present (October 2022) on consumers’ use of food delivery services during the pandemic. A thematic review was conducted, with 40 articles searched from Scopus and Web of Science being included. Quantitative findings showed current research trends, and thematic analyses formed eight themes of factors influencing consumer behavior: (1) technical and utilitarian factors, (2) system-related attributes, (3) emotional and hedonic factors, (4) individual characteristics, (5) service quality, (6) risk-related factors, (7) social factors, and (8) food-related attributes. The paper also emphasizes COVID-19-related influences and suggests promising future research directions. The results offer insights into industry practices and starting points for future research.

Pterygium is an eye condition that causes the fibrovascular tissues to grow towards the corneal region. At the early stage, it is not a harmful condition, except for slight discomfort for the patients. However, it will start to affect the eyesight of the patient once the tissues encroach towards the corneal region, with a more serious impact if it has grown into the pupil region. Therefore, this condition needs to be identified as early as possible to halt its growth, with the use of simple eye drops and sunglasses. One of the associated risk factors for this condition is a low educational level, which explains the reason that the majority of the patients are not aware of this condition. Hence, it is important to develop an automated pterygium screening system based on simple imaging modalities such as a mobile phone camera so that it can be assessed by many people. During the early stage of automated pterygium screening system development, conventional machine learning techniques such as support vector machines and artificial neural networks are the de facto algorithms to detect the presence of pterygium tissues. However, with the arrival of the deep learning era, coupled with the availability of large training data, deep learning networks have replaced the conventional networks in screening for the pterygium condition. The deep learning networks have been successfully implemented for three major purposes, which are to classify an image regarding whether there is the presence of pterygium tissues or not, to localize the lesion tissues through object detection methodology, and to semantically segment the lesion tissues at the pixel level. This review paper summarizes the type, severity, risk factors, and existing state-of-the-art technology in automated pterygium screening systems. A few available datasets are also discussed in this paper for both classification and segmentation tasks. In conclusion, a computer-assisted pterygium screening system will benefit many p

The food delivery service is the most typical and visible example of online-to-offline (O2O) commerce. More consumers are using food delivery services for various reasons during the COVID-19 pandemic, making this business model viral worldwide. In the post-pandemic era, offering food delivery services will become the new normal for restaurants. Although a growing number of publications have focused on consumer behavior in this issue, no review paper has addressed current research and industry trends. Thus, this paper aims to review the literature published from 2020 to the present (October 2022) on consumers’ use of food delivery services during the pandemic. A thematic review was conducted, with 40 articles searched from Scopus and Web of Science being included. Quantitative findings showed current research trends, and thematic analyses formed eight themes of factors influencing consumer behavior: (1) technical and utilitarian factors, (2) system-related attributes, (3) emotional and hedonic factors, (4) individual characteristics, (5) service quality, (6) risk-related factors, (7) social factors, and (8) food-related attributes. The paper also emphasizes COVID-19-related influences and suggests promising future research directions. The results offer insights into industry practices and starting points for future research.

Corporate identity has played a vital role in the Halal industry to create a strong foundation for its reputation in the long run. This paper used two modeling analyses for two different data. The first analysis aims to predict the relationship between Corporate Identity Management between Internal Brand and Employee Brand Support (consequence) mediated by CIM using partial-least squares-structural equation modeling (PLS-SEM). A total of 206 employees from Malaysia’s Halal food SMEs took part in the survey. The second analysis to identify topic proportions patterns using the topic modeling approach on Halal brand identity Machine learning approach of knowledge mining was applied for this analysis. Metadata of 1,091 articles were mined from the Scopus database on Halal studies across all social sciences fields. The result revealed that there was a partial relationship between Internal Brand (antecedent) and Employee Brand Support (consequence) mediated by CIM. This finding was supported by the identified topic proportions patterns from the topic modeling approach that pointed out a weak topic proportion on the Halal brand identity discussion globally, interestingly the result also found that the Halal brand identity discussion involving the Halal food industry is almost non-existed in Malaysia’s Halal food SMEs. The contributions of this paper were apparent in three major areas which are methodology, theoretical and future suggestions. The utilization of two different model analyses was able to confirm the consistency of the major findings with the literature review which opens up more possibilities for future researchers.

Diesel generators (DGs) are set to work as a backup during power outages or support the load in remote areas not connected to the national grid. These DGs are working at a constant speed to produce reliable AC power, while electrical energy demand fluctuates according to instantaneous needs. High electric loads occur only for a few hours a day in remote areas, resulting in oversizing DGs. During a low load operation, DGs face poor fuel efficiency and condensation of fuel residues on the walls of engine cylinders that increase friction and premature wear. One solution to increase combustion efficiency at low electric loads is to reduce diesel engine (DE) speed to its ideal regime according to the mechanical torque required by the electrical generator. Therefore, Variable Speed Diesel Generators (VSDGs) allow the operation of the diesel engine at an optimal speed according to the electrical load but require additional electrical equipment and control to maintain the power output to electrical standards. Variable speed technology has shown a significant reduction of up to 40% fuel consumption, resulting in low GHG emissions and operating costs compared to a conventional diesel generator. This technology also eliminates engine idle time during a low load regime to have a longer engine lifetime. The main objective of this survey paper is to present the state of the art of the VSDG technologies and compare their performance in terms of fuel savings, increased engine lifetime, and reduced greenhouse gases (GHG) emissions. Various concepts and the latest VSDG technologies have been evaluated in this paper based on their performance appraisal and degree of innovation.

This paper presents deterioration level estimation based on convolutional neural networks using a confidence-aware attention mechanism for infrastructure inspection. Spatial attention mechanisms try to highlight the important regions in feature maps for estimation by using an attention map. The attention mechanism using an effective attention map can improve feature maps. However, the conventional attention mechanisms have a problem as they fail to highlight important regions for estimation when an ineffective attention map is mistakenly used. To solve the above problem, this paper introduces the confidence-aware attention mechanism that reduces the effect of ineffective attention maps by considering the confidence corresponding to the attention map. The confidence is calculated from the entropy of the estimated class probabilities when generating the attention map. Because the proposed method can effectively utilize the attention map by considering the confidence, it can focus more on the important regions in the final estimation. This is the most significant contribution of this paper. The experimental results using images from actual infrastructure inspections confirm the performance improvement of the proposed method in estimating the deterioration level.