Search results for: driven%20pendulum

Authors: Lalit Ahuja, Nancy Das, Yashas Shetty

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LED lighting has been increasingly adopted for vehicles in both domestic and foreign automotive markets. Although this miniaturized technology gives the best light output, low energy consumption, and cost-efficient solutions for driving, the same is the need of the hour. In this paper, we present a methodology for driving the highest class two-wheeler headlamp with regulator and rectifier (RR) output. Unlike usual LED headlamps, which are driven by a battery, regulator, and rectifier (RR) driven, a low-cost and highly efficient LED Driver Module (LDM) is proposed. The positive half of magneto output is regulated and used to charge batteries used for various peripherals. While conventionally, the negative half was used for operating bulb-based exterior lamps. But with advancements in LED-based headlamps, which are driven by a battery, this negative half pulse remained unused in most of the vehicles. Our system uses negative half-wave rectified DC output from RR to provide constant light output at all RPMs of the vehicle. With the negative rectified DC output of RR, we have the advantage of pulsating DC input which periodically goes to zero, thus helping us to generate a constant DC output equivalent to the required LED load, and with a change in RPM, additional active thermal bypass circuit help us to maintain the efficiency and thermal rise. The methodology uses the negative half wave output of the RR along with a linear constant current driver with significantly higher efficiency. Although RR output has varied frequency and duty cycles at different engine RPMs, the driver is designed such that it provides constant current to LEDs with minimal ripple. In LED Headlamps, a DC-DC switching regulator is usually used, which is usually bulky. But with linear regulators, we’re eliminating bulky components and improving the form factor. Hence, this is both cost-efficient and compact. Presently, output ripple-free amplitude drivers with fewer components and less complexity are limited to lower-power LED Lamps. The focus of current high-efficiency research is often on high LED power applications. This paper presents a method of driving LED load at both High Beam and Low Beam using the negative half wave rectified pulsating DC from RR with minimum components, maintaining high efficiency within the thermal limitations. Linear regulators are significantly inefficient, with efficiencies typically about 40% and reaching as low as 14%. This leads to poor thermal performance. Although they don’t require complex and bulky circuitry, powering high-power devices is difficult to realise with the same. But with the input being negative half wave rectified pulsating DC, this efficiency can be improved as this helps us to generate constant DC output equivalent to LED load minimising the voltage drop on the linear regulator. Hence, losses are significantly reduced, and efficiency as high as 75% is achieved. With a change in RPM, DC voltage increases, which can be managed by active thermal bypass circuitry, thus resulting in better thermal performance. Hence, the use of bulky and expensive heat sinks can be avoided. Hence, the methodology to utilize the unused negative pulsating DC output of RR to optimize the utilization of RR output power and provide a cost-efficient solution as compared to costly DC-DC drivers.

Keywords: class D LED headlamp, regulator and rectifier, pulsating DC, low cost and highly efficient, LED driver module

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Authors: Mohammad Ehson Rangiha, Bill Karakostas

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Social Business Process Management (SBPM) promises to overcome limitations of traditional BPM by allowing flexible process design and enactment through the involvement of users from a social community. This paper proposes a meta-model and architecture for socially driven business process management systems. It discusses the main facets of the architecture such as goal-based role assignment that combines social recommendations with user profile, and process recommendation, through a real example of a charity organization.

Keywords: business process management, goal-based modelling, process recommendation social collaboration, social BPM

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Authors: Meenal Badki

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We address the issue of active feature determination, where the objective is to determine the set of examples on which additional data (such as lab tests) needs to be gathered, given a large number of examples with some features (such as demographics) and some examples with all the features (such as the complete Electronic Health Record). We note that certain features may be more costly, unique, or laborious to gather. Our proposal is a general active learning approach that is independent of classifiers and similarity metrics. It allows us to identify examples that differ from the full data set and obtain all the features for the examples that match. Our comprehensive evaluation shows the efficacy of this approach, which is driven by four authentic clinical tasks.

Keywords: feature determination, classification, active learning, sample-efficiency

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Authors: Ahmad Haidar

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Modern economic systems are characterized by growing complexity, and addressing their challenges requires innovative approaches. This study examines the implications of artificial intelligence (AI) on unemployment in Europe from a macroeconomic perspective, employing data modeling techniques to understand the relationship between AI integration and labor market dynamics. To understand the AI-unemployment nexus comprehensively, this research considers factors such as sector-specific AI adoption, skill requirements, workforce demographics, and geographical disparities. The study utilizes a panel data model, incorporating data from European countries over the last two decades, to explore the potential short-term and long-term effects of AI implementation on unemployment rates. In addition to investigating the direct impact of AI on unemployment, the study also delves into the potential indirect effects and spillover consequences. It considers how AI-driven productivity improvements and cost reductions might influence economic growth and, in turn, labor market outcomes. Furthermore, it assesses the potential for AI-induced changes in industrial structures to affect job displacement and creation. The research also highlights the importance of policy responses in mitigating potential negative consequences of AI adoption on unemployment. It emphasizes the need for targeted interventions such as skill development programs, labor market regulations, and social safety nets to enable a smooth transition for workers affected by AI-related job displacement. Additionally, the study explores the potential role of AI in informing and transforming policy-making to ensure more effective and agile responses to labor market challenges. In conclusion, this study provides a comprehensive analysis of the macroeconomic implications of AI on unemployment in Europe, highlighting the importance of understanding the nuanced relationships between AI adoption, economic growth, and labor market outcomes. By shedding light on these relationships, the study contributes valuable insights for policymakers, educators, and researchers, enabling them to make informed decisions in navigating the complex landscape of AI-driven economic transformation.

Keywords: artificial intelligence, unemployment, macroeconomic analysis, european labor market

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Authors: L. Richter, J. Lübkemann, P. Nyhuis

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In order to remain competitive in what is a turbulent environment; businesses must be able to react rapidly to change. The past response to volatile market conditions was to introduce an element of flexibility to production. Nowadays, what is often required is a redesign of factory structures in order to cope with the state of constant flux. The Institute of Production Systems and Logistics is currently developing a descriptive and causal model for the redesign of plant structures as part of an ongoing research project. This article presents the first research findings attained in devising this model.

Keywords: change driven factory redesign, factory planning, plant structure, flexibility

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Authors: R. Benelmir, M. El Kadri, A. Donnot, D. Descieux

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HVAC represents a significant part of energy needs in buildings. Integrating renewable energy in cooling processes contributes to reducing primary energy consumption. Sorption refrigeration allows cold production through the use of solar/biomass/geothermal energy or even valuation of waste heat. This work presents an analysis of an experimental bench incorporating an adsorption chiller driven by hybrid energy resources associating solar thermal collectors with a cogeneration gas engine and a geothermal heat pump.

Keywords: solar cooling, cogeneration, geothermal heat pump, hybrid energy resources

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Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

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The increasing use of deep learning applications in production is becoming a competitive advantage. Predictive quality enables the assurance of product quality by using data-driven forecasts via machine learning models as a basis for decisions on test results. The use of real Bosch production data along the value chain of hydraulic valves is a promising approach to classifying the leakage of directional valves.

Keywords: artificial neural networks, classification, hydraulics, predictive quality, deep learning

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Authors: Shafiq ur Rehman, Zubair Ahmed Shaikh

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This research provides the comparative study of different mobile payment system and proposes an efficient solution of mobile payment system. The research involves discovering how the mobile payment methods can be used and implemented keeping user and system interaction under consideration. The implementation of Nielsen’s heuristic and universal design principles enhanced the user’s interaction design and made the system more appropriate, understandable and visible to the end user. The design of application is greatly affected by the user driven factors. These factors help in the efficiency of the application usage.

Keywords: mobile payment system, m-commerce, usability, near field communication

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Authors: Rituraj Deka, Nomi Baruah

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The development of information technology during the past few years resulted in designing of more and more complex software. The outsourcing of software development makes a higher requirement for the management of software development project. Various software enterprises follow various paths in their pursuit of excellence, applying various principles, methods and techniques along the way. The new research is proving that CMMI and Agile methodologies can benefit from using both methods within organizations with the potential to dramatically improve business performance. The paper describes a mapping between CMMI key process areas (KPAs) and Feature-Driven Development (FDD) communication perspective, so as to increase the understanding of how improvements can be made in the software development process.

Keywords: Agile, CMMI, FDD, KPAs

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Authors: Soojin Kim, Jiwon Yang, Sungzoon Cho

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As a seasonal product is only in demand for a short time, inventory management is critical to profits. Both markdowns and stockouts decrease the return on perishable products; therefore, researchers have been interested in the distribution of seasonal products with the aim of maximizing profits. In this study, we propose a data-driven seasonal product sales pattern analysis method for individual retail outlets based on observed sales data clustering; the proposed method helps in determining distribution strategies.

Keywords: clustering, distribution, sales pattern, seasonal product

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Authors: Olia Kanevskaia

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Standardization has been in the limelight of numerous academic studies. Typically described as ‘any set of technical specifications that either provides or is intended to provide a common design for a product or process’, standards do not only set quality benchmarks for products and services, but also spur competition and innovation, resulting in advantages for manufacturers and consumers. Their contribution to globalization and technology advancement is especially crucial in the Information and Communication Technology (ICT) and telecommunications sector, which is also characterized by a weaker state-regulation and expert-based rule-making. Most of the standards developed in that area are interoperability standards, which allow technological devices to establish ‘invisible communications’ and to ensure their compatibility and proper functioning. This type of standard supports a large share of our daily activities, ranging from traffic coordination by traffic lights to the connection to Wi-Fi networks, transmission of data via Bluetooth or USB and building the network architecture for the Internet of Things (IoT). A large share of ICT standards is developed in the specialized voluntary platforms, commonly referred to as Standards Development Organizations (SDOs), which gather experts from various industry sectors, private enterprises, governmental agencies and academia. The institutional architecture of these bodies can vary from semi-public bodies, such as European Telecommunications Standards Institute (ETSI), to industry-driven consortia, such as the Internet Engineering Task Force (IETF). The past decades witnessed a significant shift of standard setting to those institutions: while operating independently from the states regulation, they offer a rather informal setting, which enables fast-paced standardization and places technical supremacy and flexibility of standards above other considerations. Although technical norms and specifications developed by such nongovernmental platforms are not binding, they appear to create significant regulatory impact. In the United States (US), private voluntary standards can be used by regulators to achieve their policy objectives; in the European Union (EU), compliance with harmonized standards developed by voluntary European Standards Organizations (ESOs) can grant a product a free-movement pass. Moreover, standards can de facto manage the functioning of the market when other regulative alternatives are not available. Hence, by establishing (potentially) mandatory norms, SDOs assume regulatory functions commonly exercised by States and shape their own legal order. The purpose of this paper is threefold: First, it attempts to shed some light on SDOs’ institutional architecture, focusing on private, industry-driven platforms and comparing their regulatory frameworks with those of formal organizations. Drawing upon the relevant scholarship, the paper then discusses the extent to which the formulation of technological standards within SDOs constitutes a private legal order, operating in the shadow of governmental regulation. Ultimately, this contribution seeks to advise whether a state-intervention in industry-driven standard setting is desirable, and whether the increasing regulatory importance of SDOs should be addressed in legislation on standardization.

Keywords: private order, standardization, standard-setting organizations, transnational law

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Authors: Stefanie J. Huber, Tobias Schmidt

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Cross-country differences in homeownership rates are large and very persistent over time, ranging between 35% in Switzerland to 80% in Spain. In this project, we test the hypothesis that these cross-country differences are driven by cultural tastes. To isolate the effect of culture from the effects of institutions and economic factors, we investigate the homeownership attitudes of second-generation immigrants in the United States. We find robust evidence that cross-country differences in cultural preferences are an important explanatory factor for the observed persistent differences in homeownership rates across countries.

Keywords: housing markets, homeownership rates, country heterogeneity, preferences, cultural transmission, migration

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Authors: Jocelyn Jones, Louise Southalan, Lindey Andrews, Mandy Wilson, Emma Vieira, Jackie Oakley, Dorothy Bagshaw, Alice V. Brown, Patrick Egan, Duc Dau, Lucy Spanswick

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Working with people experiencing homelessness requires careful use of methods that support them to comfortably share their experiences. This is particularly important for Aboriginal and Torres Strait Islander peoples, the traditional owners of Australia, who have experienced intergenerational and compounding trauma since colonisation. Aboriginal cultures regularly experience research fatigue and distrust in research’s potential for impact. They often view research as an extraction -a process of taking the knowledge that empowers the research team and its institution, rather than benefiting those being researched. Through a partnership between an Aboriginal Community Controlled Organisation and a university research institute, we conducted a community-driven research project with 70-90 Aboriginal people experiencing homelessness in Perth, Western Australia. The project aimed to listen to and advocate for the voices of those who are experiencing homelessness, guided by the Aboriginal community. In consultation with Aboriginal Elders, we selected methods that are considered culturally safe, including those who would prefer to express their experiences creatively. This led us to run a series of Photovoice workshops -an established method that supports people to share their experiences through photography. This method treats participants as experts and is regularly used with marginalised groups across the world. We detail our experience and lessons in using Photovoice with Aboriginal community members experiencing homelessness. This includes the ways the method needed to be moulded to community needs and driven by their individual choices, such as being dynamic in the length of time participants would spend with us, how we would introduce the method to them, and providing support workers for participants when taking photos. We also discuss lessons in establishing and retaining engagement and how the method was successful in supporting participants to comfortably share their stories. Finally, we outline the insights into homelessness that the method offered, including highlighting the difficulty experienced by participants in transitioning from homelessness to accommodation and the diversity of hopes people who have experienced homelessness have for the future.

Keywords: Aboriginal and Torres Strait Islander peoples, photovoice, homelessness, community-led research

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Authors: Fatimah AlSaiari

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In recent years, newspapers in the United Kingdom have been no longer just a means of sharing news about what happens in the world; they are also used to influence target readers by having them become more up-to-date, well-informed, entertained, exasperated, delighted, and infuriated. To achieve these objectives and maintain influence on public opinion, journalists use a particular language in which they can convey emotions and opinions, organize their discourse, and establish solidarity with their audience. This type of language has been widely analyzed under different labels, such as evaluation, appraisal, and stance. There is a considerable amount of linguistic and non-linguistic research devoted to analyzing this type of interpersonal language in journalistic discourse, and most of these studies were carried out to challenge the traditional assumptions of the objectivity and impartiality of news reporting. However, very little research has been undertaken on evaluative language in newspaper institutional editorials, and there is hardly any systematic or exhaustive analysis of this type of language in British tabloid and broadsheet newspapers. This study will attempt to provide new insights into the nature of authorial and non-authorial evaluation in leading articles in popular and quality British newspapers, along with their targets, sources, and discourse functions. The study will also attempt to develop a framework of evaluation that can be applied to evaluative lexical items in newspaper opinion texts. The framework is both theory-driven (i.e., it builds on and modifies previous frameworks of evaluation such as appraisal theory and parameter-based approach) and data-driven (i.e., it elicits the evaluative categories from the analysis of the corpus, which helps in the development of the current framework). To achieve this aim, a corpus of 140 leading articles were selected. The findings revealed that the tabloids tended to express their stance through explicitness, dramatization, frequent reference to social actors’ emotions and beliefs, and exaggeration in negativity, while the broadsheets preferred to express their stance through mitigation ambiguity and implicitness. conceptual themes and propositions were more preferable targets for expressing stance in the broadsheets while human behavior and characters were preferable targets for the tabloids.

Keywords: appraisal theory, evaluative language, British newspapers, broadsheets & tabloids, evaluative adjectives

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Authors: Shruti Kohli

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The sophistication and pervasiveness of cyber-attacks are constantly growing, driven partly by technological progress, profitable applications in organized crime and state-sponsored innovation. The modernization of rail control systems has resulted in an increasing reliance on digital technology and increased the potential for security breaches and cyber-attacks. This research track showcases the need for developing a secure reusable scalable framework for enhancing cyber security of rail assets. A cyber security framework has been proposed that is being developed to detect the tell-tale signs of cyber-attacks against industrial assets.

Keywords: cyber security, rail asset, security threat, cyber ontology

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Authors: N. H. Z. Abidin, N. F. M. Mokhtar, S. S. A. Gani

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The influence of diffusion of the thermal or known as Soret effect in a heated Binary fluid model with Coriolis force is investigated theoretically. The linear stability analysis is used, and the eigenvalue is obtained using the Galerkin method. The impact of the Soret and Coriolis force on the onset of stationary convection in a system is analysed with respect to various Binary fluid parameters and presented graphically. It is found that an increase of the Soret values, destabilize the Binary fluid layer system. However, elevating the values of the Coriolis force helps to lag the onset of convection in a system.

Keywords: Benard convection, binary fluid, Coriolis, Soret

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Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

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Due to increasing cost pressure in global markets, artificial intelligence is becoming a technology that is decisive for competition. Predictive quality enables machinery and plant manufacturers to ensure product quality by using data-driven forecasts via machine learning models as a decision-making basis for test results. The use of cross-process Bosch production data along the value chain of hydraulic valves is a promising approach to classifying the quality characteristics of workpieces.

Keywords: predictive quality, hydraulics, machine learning, classification, supervised learning

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Authors: Sidong Zhao, Xingping Wang

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Recently, the government of China has provided strong support the developments of overseas industrial parks. The global distribution of China overseas industrial parks has gradually moved from the 'sparks of fire' to the 'prairie fires.' The support and distribution have promoted developing overseas industrial parks to a strategy of constructing a China's new open economic system and a typical representative of the 'Chinese wisdom' and the 'China's plans' that China has contributed to the globalization of the new era under the initiative of the Belt and Road. As the industrial parks are the basis of 'work/employment', a basic function of a city (Athens Constitution), planning for developments of industrial parks has become a long-term focus of urban planning. Based on the research of the planning and the analysis of the present developments of some typical China overseas industrial parks, we found some interesting rules: First, large numbers of the China overseas industrial parks are located in less developed countries. These industrial parks have become significant drives of the developments of the host cities and even the regions in those countries, especially in investment, employment and paid tax fee for the local, etc. so, the planning and development of overseas industrial parks have received extensive attention. Second, there are some problems in the small part of the overseas Park, such as the planning of the park not following the planning of the host city and lack of implementation of the park planning, etc. These problems have led to the difficulties of the implementation of the planning and the sustainable developments of the parks. Third, a unique pattern of space development has been formed. in the dimension of the patterns of regional spatial distribution, there are five characteristics - along with the coast, along the river, along with the main traffic lines and hubs, along with the central urban area and along the connections of regions economic. In the dimension of the spatial relationships between the industrial park and the city, there is a growing and evolving trend as 'separation – integration - union'. In the dimension of spatial mode of the industrial parks, there are different patterns of development, such as a specialized industrial park, complex industrial park, characteristic town and new urban area of industry, etc. From the perspective of the trends of the developments and spatial modes, in the future, the planning of China overseas industrial parks should emphasize the idea of 'building a city based on the industrial park'. In other words, it's making the developments of China overseas industrial parks move from 'driven by policy' to 'driven by the functions of the city', accelerating forming the system of China overseas industrial parks and integrating the industrial parks and the cities.

Keywords: overseas industrial park, spatial mode, planning, China

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Authors: Amela Ajanovic, Reinhard Haas

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Electric vehicles (EVs) are considered as an important means to cope with current environmental problems in transport. However, their high capital costs and limited driving ranges state major barriers to a broader market penetration. The core objective of this paper is to investigate the future market prospects of various types of EVs from an economic and ecological point of view. Our method of approach is based on the calculation of total cost of ownership of EVs in comparison to conventional cars and a life-cycle approach to assess the environmental benignity. The most crucial parameters in this context are km driven per year, depreciation time of the car and interest rate. The analysis of future prospects it is based on technological learning regarding investment costs of batteries. The major results are the major disadvantages of battery electric vehicles (BEVs) are the high capital costs, mainly due to the battery, and a low driving range in comparison to conventional vehicles. These problems could be reduced with plug-in hybrids (PHEV) and range extenders (REXs). However, these technologies have lower CO₂ emissions in the whole energy supply chain than conventional vehicles, but unlike BEV they are not zero-emission vehicles at the point of use. The number of km driven has a higher impact on total mobility costs than the learning rate. Hence, the use of EVs as taxis and in car-sharing leads to the best economic performance. The most popular EVs are currently full hybrid EVs. They have only slightly higher costs and similar operating ranges as conventional vehicles. But since they are dependent on fossil fuels, they can only be seen as energy efficiency measure. However, they can serve as a bridging technology, as long as BEVs and fuel cell vehicle do not gain high popularity, and together with PHEVs and REX contribute to faster technological learning and reduction in battery costs. Regarding the promotion of EVs, the best results could be reached with a combination of monetary and non-monetary incentives, as in Norway for example. The major conclusion is that to harvest the full environmental benefits of EVs a very important aspect is the introduction of CO₂-based fuel taxes. This should ensure that the electricity for EVs is generated from renewable energy sources; otherwise, total CO₂ emissions are likely higher than those of conventional cars.

Keywords: costs, mobility, policy, sustainability,

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Authors: Jiaqi Yin, Baofeng Liang

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The rapid development in the fields of computer science and information technology presents new challenges and opportunities for foundational programming education. Traditional programming courses often focus heavily on theoretical knowledge while neglecting students’ practical programming and problem-solving abilities. This paper delves into the significance of programming education based on application abilities and provides a detailed explanation of a reform approach that incorporates project-driven teaching to nurture students with more comprehensive computer science skills.

Keywords: fundamentals of programming, application abilities, pedagogical reform, program design

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Authors: Jingwen Ou

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Writing for academic purposes in a second or foreign language poses a significant challenge for non-native speakers, particularly at the tertiary level, where English academic writing for L2 students is often hindered by difficulties in academic discourse, including vocabulary, academic register, and organization. The past two decades have witnessed a rising popularity in the application of the data-driven learning (DDL) approach in EAP writing instruction. In light of such a trend, this study aims to enhance the integration of DDL into English for academic purposes (EAP) writing classrooms by investigating the perception of Chinese college students regarding the use of corpus tools for improving EAP writing. Additionally, the research explores their corpus consultation behaviors during training to provide insights into corpus-assisted EAP instruction for DDL practitioners. Given the uprising popularity of DDL, this research aims to investigate Chinese university students’ use of corpus tools with three main foci: 1) the influence of corpus tools on learning behaviours, 2) the influence of corpus tools on students’ academic writing performance outcomes, and 3) students’ perceptions and potential perceptional changes towards the use of such tools. Three corpus tools, CQPWeb, Sketch Engine, and LancsBox X, are selected for investigation due to the scarcity of empirical research on patterns of learners’ engagement with a combination of multiple corpora. The research adopts a pre-test / post-test design for the evaluation of students’ academic writing performance before and after the intervention. Twenty participants will be divided into two groups: an intervention and a non-intervention group. Three corpus training workshops will be delivered at the beginning, middle, and end of a semester. An online survey and three separate focus group interviews are designed to investigate students’ perceptions of the use of corpus tools for improving academic writing skills, particularly the rhetorical functions in different essay sections. Insights from students’ consultation sessions indicated difficulties with DDL practice, including insufficiency of time to complete all tasks, struggle with technical set-up, unfamiliarity with the DDL approach and difficulty with some advanced corpus functions. Findings from the main study aim to provide pedagogical insights and training resources for EAP practitioners and learners.

Keywords: corpus linguistics, data-driven learning, English for academic purposes, tertiary education in China

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Authors: Patrick Innocenti, Elias Montini, Silvia Menato, Marzio Sorlini

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Documented experiences of industrial symbiosis are always triggered and driven only by economic goals: environmental and (even rarely) social results are sometimes assessed and declared as effects of virtuous behaviours, but are merely casual and un-pursued side externalities. Even worse: all the symbiotic project candidates entailing economic loss for just one of the (also dozen) partners are simply stopped without considering the overall benefit for the whole partnership. The here-presented approach aims at providing methodologies and tools to effectively manage these situations and fostering the implementation of virtuous symbiotic investments in manufacturing aggregations for a more sustainable production.

Keywords: business model, industrial symbiosis, industrial agglomerations, sustainability

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Authors: Ahmed Soltan, Ahmed G. Radwan, Ahmed M. Soliman

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This work aims to generalize the integer order Sallen-Key filters into the fractional-order domain. The analysis in the case of two different fractional-order elements introduced where the general transfer function becomes four terms which are unusual in the conventional case. In addition, the effect of the transfer function parameters on the filter poles and hence the stability is introduced and closed forms for the filter critical frequencies are driven. Finally, different examples of the fractional order Sallen-Key filter design are presented with circuit simulations using ADS where a great matching between the numerical and simulation results is obtained.

Keywords: Sallen-Key, fractance, stability, low-pass filter, analog filter

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Authors: Amit R. Bhende, G. K. Awari

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Remaining useful life (RUL) prediction is one of key technologies to realize prognostics and health management that is being widely applied in many industrial systems to ensure high system availability over their life cycles. The present work proposes a data-driven method of RUL prediction based on multiple health state assessment for rolling element bearings. Bearing degradation data at three different conditions from run to failure is used. A RUL prediction model is separately built in each condition. Feed forward back propagation neural network models are developed for prediction modeling.

Keywords: bearing degradation data, remaining useful life (RUL), back propagation, prognosis

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Authors: Lev Idels, Arcady Ponosov

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Stochastic fractional differential equations have recently attracted considerable attention, as they have been used to model real-world processes, which are subject to natural memory effects and measurement uncertainties. Compared to conventional hereditary differential equations, one of the advantages of fractional differential equations is related to more realistic geometric properties of their trajectories that do not intersect in the phase space. In this report, a Peano-like existence theorem for nonlinear stochastic fractional differential equations is proven under very general hypotheses. Several specific classes of equations are checked to satisfy these hypotheses, including delay equations driven by the fractional Brownian motion, stochastic fractional neutral equations and many others.

Keywords: delay equations, operator methods, stochastic noise, weak solutions

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Authors: Wenhao Li, Shijun Guo

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Carbon fibre reinforced composites are progressively replacing metal structures in modern civil aircraft. This is because composite materials have large potential of weight saving compared with metal. However, the achievement to date of weight saving in composite structure is far less than the theoretical potential due to many uncertainties in structural integrity and safety concern. Unlike the conventional metallic structure, composite components are bonded together along the joints where structural integrity is a major concern. To ensure the safety, metal fasteners are used to reinforce the composite bonded joints. One of the solutions for a significant weight saving of composite structure is to develop an effective technology of on-board Structural Health Monitoring (SHM) System. By monitoring the real-life stress status of composite structures during service, the safety margin set in the structure design can be reduced with confidence. It provides a means of safeguard to minimize the need for programmed inspections and allow for maintenance to be need-driven, rather than usage-driven. The aim of this paper is to develop smart composite joint. The key technology is a multifunctional thermoplastic composite fastener (MTCF). The MTCF will replace some of the existing metallic fasteners in the most concerned locations distributed over the aircraft composite structures to reinforce the joints and form an on-board SHM network system. Each of the MTCFs will work as a unit of the AU and AE technology. The proposed MTCF technology has been patented and developed by Prof. Guo in Cranfield University, UK in the past a few years. The manufactured MTCF has been successfully employed in the composite SLJ (Single-Lap Joint). In terms of the structure integrity, the hybrid SLJ reinforced by MTCF achieves 19.1% improvement in the ultimate failure strength in comparison to the bonded SLJ. By increasing the diameter or rearranging the lay-up sequence of MTCF, the hybrid SLJ reinforced by MTCF is able to achieve the equivalent ultimate strength as that reinforced by titanium fastener. The predicted ultimate strength in simulation is in good agreement with the test results. In terms of the structural health monitoring, a signal from the MTCF was measured well before the load of mechanical failure. This signal provides a warning of initial crack in the joint which could not be detected by the strain gauge until the final failure.

Keywords: composite single-lap joint, crack propagation, multifunctional composite fastener, structural health monitoring

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Authors: Theoktisti Makridou, Konstantinos Tsaprailis, George Arvanitakis, Charalampos Kontoes

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In the literature, the data-driven approaches for mosquito abundance prediction relaying on supervised machine learning models that get trained with historical in-situ measurements. The counterpart of this approach is once the model gets trained on pointlevel (specific x,y coordinates) measurements, the predictions of the model refer again to point-level. These point-level predictions reduce the applicability of those solutions once a lot of early warning and mitigation actions applications need predictions for an area level, such as a municipality, village, etc... In this study, we apply a data-driven predictive model, which relies on public-open satellite Earth Observation and geospatial data and gets trained with historical point-level in-Situ measurements of mosquito abundance. Then we propose a methodology to extract information from a point-level predictive model to a broader area-level prediction. Our methodology relies on the randomly spatial sampling of the area of interest (similar to the Poisson hardcore process), obtaining the EO and geomorphological information for each sample, doing the point-wise prediction for each sample, and aggregating the predictions to represent the average mosquito abundance of the area. We quantify the performance of the transformation from the pointlevel to the area-level predictions, and we analyze it in order to understand which parameters have a positive or negative impact on it. The goal of this study is to propose a methodology that predicts the mosquito abundance of a given area by relying on point-level prediction and to provide qualitative insights regarding the expected performance of the area-level prediction. We applied our methodology to historical data (of Culex pipiens) of two areas of interest (Veneto region of Italy and Central Macedonia of Greece). In both cases, the results were consistent. The mean mosquito abundance of a given area can be estimated with similar accuracy to the point-level predictor, sometimes even better. The density of the samples that we use to represent one area has a positive effect on the performance in contrast to the actual number of sampling points which is not informative at all regarding the performance without the size of the area. Additionally, we saw that the distance between the sampling points and the real in-situ measurements that were used for training did not strongly affect the performance.

Keywords: mosquito abundance, supervised machine learning, culex pipiens, spatial sampling, west nile virus, earth observation data

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Authors: Abraham Castellanos, Christophe Durville, Sophie Echenim

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In this article, a portfolio optimization problem is performed in a Solvency II context: it illustrates how advanced optimization techniques can help to tackle complex operational pain points around the monitoring, control, and stability of Solvency Capital Requirement (SCR). The market SCR of a portfolio is calculated as a combination of SCR sub-modules. These sub-modules are the results of stress-tests on interest rate, equity, property, credit and FX factors, as well as concentration on counter-parties. The market SCR is non convex and non differentiable, which does not make it a natural optimization criteria candidate. In the SCR formulation, correlations between sub-modules are fixed, whereas risk-driven portfolio allocation is usually driven by the dynamics of the actual correlations. Implementing a portfolio construction approach that is efficient on both a regulatory and economic standpoint is not straightforward. Moreover, the challenge for insurance portfolio managers is not only to achieve a minimal SCR to reduce non-invested capital but also to ensure stability of the SCR. Some optimizations have already been performed in the literature, simplifying the standard formula into a quadratic function. But to our knowledge, it is the first time that the standard formula of the market SCR is used in an optimization problem. Two solvers are combined: a bundle algorithm for convex non- differentiable problems, and a BFGS (Broyden-Fletcher-Goldfarb- Shanno)-SQP (Sequential Quadratic Programming) algorithm, to cope with non-convex cases. A market SCR minimization is then performed with historical data. This approach results in significant reduction of the capital requirement, compared to a classical Markowitz approach based on the historical volatility. A comparative analysis of different optimization models (equi-risk-contribution portfolio, minimizing volatility portfolio and minimizing value-at-risk portfolio) is performed and the impact of these strategies on risk measures including market SCR and its sub-modules is evaluated. A lack of diversification of market SCR is observed, specially for equities. This was expected since the market SCR strongly penalizes this type of financial instrument. It was shown that this direct effect of the regulation can be attenuated by implementing constraints in the optimization process or minimizing the market SCR together with the historical volatility, proving the interest of having a portfolio construction approach that can incorporate such features. The present results are further explained by the Market SCR modelling.

Keywords: financial risk, numerical optimization, portfolio management, solvency capital requirement

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Authors: Hoora Beheshti Haradasht, Abooali Golzary

Abstract:

Environmental education plays a pivotal role in shaping the future stewards of our planet. Leveraging the power of artificial intelligence (AI) in this endeavor presents an innovative approach to captivate and educate elementary school children about environmental sustainability. This paper explores the application of AI technologies in designing interactive and personalized learning experiences that foster curiosity, critical thinking, and a deep connection to nature. By harnessing AI-driven tools, virtual simulations, and personalized content delivery, educators can create engaging platforms that empower children to comprehend complex environmental concepts while nurturing a lifelong commitment to protecting the Earth. With the pressing challenges of climate change and biodiversity loss, cultivating an environmentally conscious generation is imperative. Integrating AI in environmental education revolutionizes traditional teaching methods by tailoring content, adapting to individual learning styles, and immersing students in interactive scenarios. This paper delves into the potential of AI technologies to enhance engagement, comprehension, and pro-environmental behaviors among elementary school children. Modern AI technologies, including natural language processing, machine learning, and virtual reality, offer unique tools to craft immersive learning experiences. Adaptive platforms can analyze individual learning patterns and preferences, enabling real-time adjustments in content delivery. Virtual simulations, powered by AI, transport students into dynamic ecosystems, fostering experiential learning that goes beyond textbooks. AI-driven educational platforms provide tailored content, ensuring that environmental lessons resonate with each child's interests and cognitive level. By recognizing patterns in students' interactions, AI algorithms curate customized learning pathways, enhancing comprehension and knowledge retention. Utilizing AI, educators can develop virtual field trips and interactive nature explorations. Children can navigate virtual ecosystems, analyze real-time data, and make informed decisions, cultivating an understanding of the delicate balance between human actions and the environment. While AI offers promising educational opportunities, ethical concerns must be addressed. Safeguarding children's data privacy, ensuring content accuracy, and avoiding biases in AI algorithms are paramount to building a trustworthy learning environment. By merging AI with environmental education, educators can empower children not only with knowledge but also with the tools to become advocates for sustainable practices. As children engage in AI-enhanced learning, they develop a sense of agency and responsibility to address environmental challenges. The application of artificial intelligence in elementary environmental education presents a groundbreaking avenue to cultivate environmentally conscious citizens. By embracing AI-driven tools, educators can create transformative learning experiences that empower children to grasp intricate ecological concepts, forge an intimate connection with nature, and develop a strong commitment to safeguarding our planet for generations to come.

Keywords: artificial intelligence, environmental education, elementary children, personalized learning, sustainability

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Authors: Kriti Jain, Sucha Singh Gill

Abstract:

Subsidies have been a major part of agricultural policies around the world, and more extensively since the green revolution in developing countries, for the sake of attaining higher agricultural productivity and achieving food security. But entrenched subsidies lead to distorted incentives and promote inefficiencies in the agricultural sector, threatening the viability of these very subsidies and sustainability of the agricultural production systems, posing a threat to the livelihood of farmers and laborers dependent on it. This paper analyzes the economic and ecological sustainability implications of prolonged input and output subsidies in agriculture by studying the case of Indian Punjab, an agriculturally developed state responsible for ensuring food security in the country when it was facing a major food crisis. The paper focuses specifically on the environmentally unsustainable cropping pattern changes as a result of Minimum Support Price (MSP) and assured procurement and on the resource use efficiency and cost implications of power subsidy for irrigation in Punjab. The study is based on an analysis of both secondary and primary data sources. Using secondary data, a time series analysis was done to capture the changes in Punjab’s cropping pattern, water table depth, fertilizer consumption, and electrification of agriculture. This has been done to examine the role of price and output support adopted to encourage the adoption of green revolution technology in changing the cropping structure of the state, resulting in increased input use intensities (especially groundwater and fertilizers), which harms the ecological balance and decreases factor productivity. Evaluation of electrification of Punjab agriculture helped evaluate the trend in electricity productivity of agriculture and how free power imposed further pressure on the extant agricultural ecosystem. Using data collected from a primary survey of 320 farmers in Punjab, the extent of wasteful application of groundwater irrigation, water productivity of output, electricity usage, and cost of irrigation driven electricity subsidy to the exchequer were estimated for the dominant cropping pattern amongst farmers. The main findings of the study revealed how because of a subsidy has driven agricultural framework, Punjab has lost area under agro climatically suitable and staple crops and moved towards a paddy-wheat cropping system, that is gnawing away the state’s natural resources like water table has been declining at a significant rate of 25 cms per year since 1975-76, and excessive and imbalanced fertilizer usage has led to declining soil fertility in the state. With electricity-driven tubewells as the major source of irrigation within a regime of free electricity and water-intensive crop cultivation, there is both wasteful application of irrigation water and electricity in the cultivation of paddy crops, burning an unproductive hole in the exchequer’s pocket. There is limited access to both agricultural extension services and water-conserving technology, along with policy imbalance, keeping farmers in an intensive and unsustainable production system. Punjab agriculture is witnessing diminishing returns to factor, which under the business-as-usual scenario, will soon enter the phase of negative returns to factor.

Keywords: cropping pattern, electrification, subsidy, sustainability

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