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Authors: Georgia Kremmyda, Angelos Georgoulas, Yiannis Koumpouros, James T. Mottram

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There is a growing interest in enhancing the creativity and problem-solving ability of engineering students by expanding their engagement to complex, interdisciplinary problems such as environmental issues, resilience to man-made and natural disasters, global health matters, water needs, increased energy demands, and other global humanitarian challenges. Tackling societal challenges requires knowledgeable and erudite engineers who can handle, combine, transform and create innovative, affordable and sustainable solutions. This view simultaneously complements and challenges current conceptions of an emerging educational movement that, almost without exception, are underpinned by calls for competitive economic growth and technological development. This article reveals a taxonomy of humanitarian attributes to be enabled to professional engineers, through reformed curricula and innovative pedagogies, which once implemented and integrated efficiently in higher engineering education, they will provide students and educators with opportunities to explore interdependencies and connections between resources, sustainable design, societal needs, and the natural environment and to critically engage with implicit and explicit facets of disciplinary identity. The research involves carrying out a study on (a) current practices, best practices and barriers in knowledge organisation, content, and hierarchy in graduate engineering programmes, (b) best practices associated with teaching and research in engineering education around the world, (c) opportunities inherent in general reforms of graduate engineering education and inherent in integrating the humanitarian context throughout engineering education programmes, and, (d) an overarching taxonomy of professional attributes for tackling humanitarian challenges. Research methods involve state-of-the-art literature review on engineering education and pedagogy to resource thematic findings on current status in engineering education worldwide, and qualitative research through three practice dialogue workshops, run in Asia (Vietnam, Indonesia and Bangladesh) involving a variety of national, international and local stakeholders (industries; NGOs, governmental organisations). Findings from this study provide evidence on: (a) what are the professional engineering attributes (skills, experience, knowledge) needed for tackling humanitarian challenges; (b) how we can integrate other disciplines and professions to engineering while defining the professional attributes of engineers who are capable of tackling humanitarian challenges. The attributes will be linked to those discipline(s) and profession(s) that are more likely to enforce the attributes (removing the assumption that engineering education as it stands at the moment can provide all attributes), and; (c) how these attributes shall be supplied; what kind of pedagogies or training shall take place beyond current practices. Acknowledgment: The study is currently in progress and is being undertaken in the framework of the project ENHANCE - ENabling Humanitarian Attributes for Nurturing Community-based Engineering (project No: 598502-EEP-1-2018-1-UK-EPPKA2-CBHE-JP (2018-2582/001-001), funded by the Erasmus + KA2 Cooperation for innovation and the exchange of good practices – Capacity building in the field of Higher Education.

Keywords: professional engineering attributes, engineering education, taxonomy, humanitarian challenges, humanitarian engineering

Procedia PDF Downloads 191

Authors: Mabel Y. C. Yau, Roy C. F. Lai, Hugo Y. H. Or

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This study is a pilot surveillance of hygiene compliance and food microbial safety of both licensed and mobile vendors selling Chinese ready–to-eat snack foods in Hong Kong. The study reflects similar situations in running mobile food vending business on trucks. Hong Kong is about to launch the Food Truck Pilot Scheme by the end of 2016 or early 2017. Technically, selling food on the vehicle is no different from hawking food on the street or vending food on the street. Each type of business bears similar food safety issues and cast the same impact on public health. Present findings demonstrate exemplarily situations that also apply to food trucks. 9 types of Cantonese style snacks of 32 samples in total were selected for microbial screening. A total of 16 vending sites including supermarkets, street markets, and snack stores were visited. The study finally focused on a traditional snack, the steamed rice cake with red beans called Put Chai Ko (PCK). PCK is a type of classical Cantonese pastry sold on push carts on the street. It used to be sold at room temperature and served with bamboo sticks in the old days. Some shops would have them sold steam fresh. Microbial examinations on aerobic counts, yeast, and mould, coliform, salmonella as well as Staphylococcus aureus detections were carried out. Salmonella was not detected in all samples. Since PCK does not contain ingredients of beef, poultry, eggs or dairy products, the risk of the presence of Salmonella in PCK was relatively lower although other source of contamination might be possible. Coagulase positive Staphylococcus aureus was found in 6 of the 14 samples sold at room temperature. Among these 6 samples, 3 were PCK. One of the samples was in an unacceptable range of total colony forming units higher than 105. The rest were only satisfactory. Observational evaluations were made with checklists on personal hygiene, premises hygiene, food safety control, food storage, cleaning and sanitization as well as waste disposals. The maximum score was 25 if total compliance were obtained. The highest score among vendors was 20. Three stores were below average, and two of these stores were selling PCK. Most of the non-compliances were on food processing facilities, sanitization conditions and waste disposal. In conclusion, although no food poisoning outbreaks happened during the time of the investigation, the risk of food hazard existed in these stores, especially among street vendors. Attention is needed in the traditional practice of food selling, and that food handlers might not have sufficient knowledge to properly handle food products. Variations in food qualities existed among supply chains or franchise eateries or shops. It was commonly observed that packaging and storage conditions are not properly enforced in the retails. The same situation could be reflected across the food business. It did indicate need of food safety training in the industry and loopholes in quality control among business.

Keywords: cantonese snacks, food safety, microbial, hygiene, street food

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Authors: Riadh Zorgati, Thomas Triboulet

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In quite diverse application areas such as astronomy, medical imaging, geophysics or nondestructive evaluation, many problems related to calibration, fitting or estimation of a large number of input parameters of a model from a small amount of output noisy data, can be cast as inverse problems. Due to noisy data corruption, insufficient data and model errors, most inverse problems are ill-posed in a Hadamard sense, i.e. existence, uniqueness and stability of the solution are not guaranteed. A wide class of inverse problems in physics relates to the Fredholm equation of the first kind. The ill-posedness of such inverse problem results, after discretization, in a very ill-conditioned linear system of equations, the condition number of the associated matrix can typically range from 109 to 1018. This condition number plays the role of an amplifier of uncertainties on data during inversion and then, renders the inverse problem difficult to handle numerically. Similar problems appear in other areas such as numerical optimization when using interior points algorithms for solving linear programs leads to face ill-conditioned systems of linear equations. Devising efficient solution approaches for such system of equations is therefore of great practical interest. Efficient iterative algorithms are proposed for solving a system of linear equations. The approach is based on a preconditioning of the initial matrix of the system with an approximation of a generalized inverse leading to a stochastic preconditioned matrix. This approach, valid for non-negative matrices, is first extended to hermitian, semi-definite positive matrices and then generalized to any complex rectangular matrices. The main results obtained are as follows: 1) We are able to build a generalized inverse of any complex rectangular matrix which satisfies the convergence condition requested in iterative algorithms for solving a system of linear equations. This completes the (short) list of generalized inverse having this property, after Kaczmarz and Cimmino matrices. Theoretical results on both the characterization of the type of generalized inverse obtained and the convergence are derived. 2) Thanks to its properties, this matrix can be efficiently used in different solving schemes as Richardson-Tanabe or preconditioned conjugate gradients. 3) By using Lp norms, we propose generalized Kaczmarz’s type matrices. We also show how Cimmino's matrix can be considered as a particular case consisting in choosing the Euclidian norm in an asymmetrical structure. 4) Regarding numerical results obtained on some pathological well-known test-cases (Hilbert, Nakasaka, …), some of the proposed algorithms are empirically shown to be more efficient on ill-conditioned problems and more robust to error propagation than the known classical techniques we have tested (Gauss, Moore-Penrose inverse, minimum residue, conjugate gradients, Kaczmarz, Cimmino). We end on a very early prospective application of our approach based on stochastic matrices aiming at computing some parameters (such as the extreme values, the mean, the variance, …) of the solution of a linear system prior to its resolution. Such an approach, if it were to be efficient, would be a source of information on the solution of a system of linear equations.

Keywords: conditioning, generalized inverse, linear system, norms, stochastic matrix

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Authors: Hongmei Wang, Ziyun Xiang, Ying liu, Li Yu, Dongsheng Yue

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Intro: The COVID-19 (Corona Virus Disease 2019) has greatly changed the global economic, political and financial ecology. The mutation of the coronavirus in the UK in December 2020 has brought new panic to the world. Deep learning was performed on Chest Computed tomography (CT) of COVID-19 and Influenza and describes their characteristics. The predominant features of COVID-19 pneumonia was ground-glass opacification, followed by consolidation. Lesion density: most lesions appear as ground-glass shadows, and some lesions coexist with solid lesions. Lesion distribution: the focus is mainly on the dorsal side of the periphery of the lung, with the lower lobe of the lungs as the focus, and it is often close to the pleura. Other features it has are grid-like shadows in ground glass lesions, thickening signs of diseased vessels, air bronchi signs and halo signs. The severe disease involves whole bilateral lungs, showing white lung signs, air bronchograms can be seen, and there can be a small amount of pleural effusion in the bilateral chest cavity. At the same time, this year's flu season could be near its peak after surging throughout the United States for months. Chest CT for Influenza infection is characterized by focal ground glass shadows in the lungs, with or without patchy consolidation, and bronchiole air bronchograms are visible in the concentration. There are patchy ground-glass shadows, consolidation, air bronchus signs, mosaic lung perfusion, etc. The lesions are mostly fused, which is prominent near the hilar and two lungs. Grid-like shadows and small patchy ground-glass shadows are visible. Deep neural networks have great potential in image analysis and diagnosis that traditional machine learning algorithms do not. Method: Aiming at the two major infectious diseases COVID-19 and influenza, which are currently circulating in the world, the chest CT of patients with two infectious diseases is classified and diagnosed using deep learning algorithms. The residual network is proposed to solve the problem of network degradation when there are too many hidden layers in a deep neural network (DNN). The proposed deep residual system (ResNet) is a milestone in the history of the Convolutional neural network (CNN) images, which solves the problem of difficult training of deep CNN models. Many visual tasks can get excellent results through fine-tuning ResNet. The pre-trained convolutional neural network ResNet is introduced as a feature extractor, eliminating the need to design complex models and time-consuming training. Fastai is based on Pytorch, packaging best practices for in-depth learning strategies, and finding the best way to handle diagnoses issues. Based on the one-cycle approach of the Fastai algorithm, the classification diagnosis of lung CT for two infectious diseases is realized, and a higher recognition rate is obtained. Results: A deep learning model was developed to efficiently identify the differences between COVID-19 and influenza using chest CT.

Keywords: COVID-19, Fastai, influenza, transfer network

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Authors: Salima Bijapuri, Shweta Bhatbolan, Sejalben Patel

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Ergonomics concerns the fitting of the environment and the equipment to the worker. Ergonomic principles can be employed in different dimensions of the industrial sector. Participation of all the stakeholders is the key to the formulation of a multifaceted and comprehensive approach to lessen the burden of occupational hazards. Taking responsibility for one’s own work activities by acquiring sufficient knowledge and potential to influence the practices and outcomes is the basis of participatory ergonomics and even hastens the process to identify workplace hazards. The study was aimed to check how participatory ergonomics can be effective in the management of work-related musculoskeletal disorders. Method: A mega kitchen was identified in a twin city of Karnataka, India. Consent was taken, and the screening of workers was done using observation methods. Kitchen work was structured to include different tasks, which included preparation, cooking, distributing, and serving food, packing food to be delivered to schools, dishwashing, cleaning and maintenance of kitchen and equipment, and receiving and storing raw material. Total 100 workers attended the education session on participatory ergonomics and its role in implementing the correct ergonomic practices, thus preventing WRMSDs. Demographic details and baseline data on related musculoskeletal pain and discomfort were collected using the Nordic pain questionnaire and VAS score pre- and post-study. Monthly visits were made, and the education sessions were reiterated on each visit, thus reminding, correcting, and problem-solving of each worker. After 9 months with a total of 4 such education session, the post education data was collected. The software SPSS 20 was used to analyse the collected data. Results: The majority of them (78%), depending on the availability and feasibility, participated in the intervention workshops were arranged four times. The average age of the participants was 39 years. The percentage of female participants was 79.49%, and 20.51% of participants comprised of males. The Nordic Musculoskeletal Questionnaire (NMQ) showed that knee pain was the most commonly reported complaint (62%) from the last 12 months with a mean VAS of 6.27, followed by low back pain. Post intervention, the mean VAS Score was reduced significantly to 2.38. The comparison of pre-post scores was made using Wilcoxon matched pairs test. Upon enquiring, it was found that, the participants learned the importance of applying ergonomics at their workplace which inturn was beneficial for them to handle any problems arising at their workplace on their own with self confidence. Conclusion: The participatory ergonomics proved effective with workers of mega kitchen, and it is a feasible and practical approach. The advantage of the given study area was that it had a sophisticated and ergonomically designed workstation; thus it was the lack of education and practical knowledge to use these stations was of utmost need. There was a significant reduction in VAS scores with the implementation of changes in the working style, and the knowledge of ergonomics helped to decrease physical load and improve musculoskeletal health.

Keywords: ergonomic awareness session, mega kitchen, participatory ergonomics, work related musculoskeletal disorders

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Authors: Huseyin Sinan Gunesli

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Process Safety Management is a disciplined framework for managing the integrity of systems and processes that handle hazardous substances. It relies on good design principles, well-implemented automation systems, and operating and maintenance practices. Alarm Management Systems play a critically important role in the safe and efficient operation of modern industrial plants. In that respect, Alarm Management is one of the critical factors feeding the safe operations of the plants in the manner of applying effective process safety principles. Trans Anatolian Natural Gas Pipeline (TANAP) is part of the Southern Gas Corridor, which extends from the Caspian Sea to Italy. TANAP transports Natural Gas from the Shah Deniz gas field of Azerbaijan, and possibly from other neighboring countries, to Turkey and through Trans Adriatic Pipeline (TAP) Pipeline to Europe. TANAP plays a crucial role in maintaining Energy Security for the region and Europe. In that respect, the application of Process Safety principles is vital to deliver safe, reliable and efficient Natural Gas delivery to Shippers both in the region and Europe. Effective Alarm Management is one of those Process Safety principles which feeds safe operations of the TANAP pipeline. Alarm Philosophy was designed and implemented in TANAP Pipeline according to the relevant standards. However, it is essential to manage the alarms received in the control room effectively to maintain safe operations. In that respect, TANAP has commenced Alarm Management & Rationalization program as of February 2022 after transferring to Plateau Regime, reaching the design parameters. While Alarm Rationalization started, there were more than circa 2300 alarms received per hour from one of the compressor stations. After applying alarm management principles such as reviewing and removal of bad actors, standing, stale, chattering, fleeting alarms, comprehensive review and revision of alarm set points through a change management principle, conducting alarm audits/design verification and etc., it has been achieved to reduce down to circa 40 alarms per hour. After the successful implementation of alarm management principles as specified above, the number of alarms has been reduced to industry standards. That significantly improved operator vigilance to focus on mainly important and critical alarms to avoid any excursion beyond safe operating limits leading to any potential process safety events. Following the ‟What Gets Measured, Gets Managed” principle, TANAP has identified key Performance Indicators (KPIs) to manage Process Safety principles effectively, where Alarm Management has formed one of the key parameters of those KPIs. However, review and analysis of the alarms were performed manually. Without utilizing Alarm Management Software, achieving full compliance with international standards is almost infeasible. In that respect, TANAP has started using one of the industry-wide known Alarm Management Applications to maintain full review and analysis of alarms and define actions as required. That actually significantly empowered TANAP’s process safety principles in terms of Alarm Management.

Keywords: process safety principles, energy security, natural gas pipeline operations, alarm rationalization, alarm management, alarm management application

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Authors: Miriam I. Jimenez-Perez, Mariana C. Orellana-Haro, Carolina Guzman-Brambila

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As part of microbiology and dietetics courses, students of medicine and nutrition analyze the main pathogenic microorganisms and perform dietary analyzes. The course of microbiology describes in a general way the main pathogens including bacteria, viruses, fungi, and parasites, as well as their interaction with the human species. We hypothesize that lack of practical application of the course causes the students not to find the value and the clinical application of it when in reality it is a matter of great importance for healthcare in our country. The courses of the medical microbiology and dietetics are mostly theoretical and only a few hours of laboratory practices. Therefore, it is necessary the incorporation of new innovative techniques that involve more practices and community fieldwork, real cases analysis and real-life situations. The purpose of this intervention was to incorporate real-world learning experiences in the instruction of medical microbiology and dietetics courses, in order to improve the learning process, understanding and the application in the field. During a period of 6 months, medicine and nutrition students worked in a community of urban poverty. We worked with 90 children between 4 and 6 years of age from low-income families with no access to medical services, to give an infectious diagnosis related to nutritional status in these children. We expect that this intervention would give a different kind of context to medical microbiology and dietetics students improving their learning process, applying their knowledge and laboratory practices to help a needed community. First, students learned basic skills in microbiology diagnosis test during laboratory sessions. Once, students acquired abilities to make biochemical probes and handle biological samples, they went to the community and took stool samples from children (with the corresponding informed consent). Students processed the samples in the laboratory, searching for enteropathogenic microorganism with RapID™ ONE system (Thermo Scientific™) and parasites using Willis and Malloy modified technique. Finally, they compared the results with the nutritional status of the children, previously measured by anthropometric indicators. The anthropometric results were interpreted by the OMS Anthro software (WHO, 2011). The microbiological result was interpreted by ERIC® Electronic RapID™ Code Compendium software and validated by a physician. The results were analyses of infectious outcomes and nutritional status. Related to fieldwork community learning experiences, our students improved their knowledge in microbiology and were capable of applying this knowledge in a real-life situation. They found this kind of learning useful when they translate theory to a real-life situation. For most of our students, this is their first contact as health caregivers with real population, and this contact is very important to help them understand the reality of many people in Mexico. In conclusion, real-world or fieldwork learning experiences empower our students to have a real and better understanding of how they can apply their knowledge in microbiology and dietetics and help a much- needed population, this is the kind of reality that many people live in our country.

Keywords: real-world learning experiences, medical microbiology, dietetics, nutritional status, infectious status.

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Authors: Andreas Lind, Aitor Iriondo Pascual, Dan Hogberg, Lars Hanson

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Factory setup lifecycles are most often described and prepared in CAD environments; the preparation is based on experience and inputs from several cross-disciplinary processes. Early in the factory setup preparation, a so-called block layout is created. The intention is to describe a high-level view of the intended factory setup and to claim area reservations and allocations. Factory areas are then blocked, i.e., targeted to be used for specific intended resources and processes, later redefined with detailed factory setup layouts. Each detailed layout is based on the block layout and inputs from cross-disciplinary preparation processes, such as manufacturing sequence, productivity, workers’ workplace requirements, and resource setup preparation. However, this activity is often not carried out with all variables considered simultaneously, which might entail a risk of sub-optimizing the detailed layout based on manual decisions. Therefore, this work aims to realize a digital method for assembly manufacturing layout planning where productivity, area utilization, and ergonomics can be considered simultaneously in a cross-disciplinary manner. The purpose of the digital method is to support engineers in finding optimized designs of detailed layouts for assembly manufacturing factories, thereby facilitating better decisions regarding setups of future factories. Input datasets are company-specific descriptions of required dimensions for specific area reservations, such as defined dimensions of a worker’s workplace, material façades, aisles, and the sequence to realize the product assembly manufacturing process. To test and iteratively develop the digital method, a demonstrator has been developed with an adaptation of existing software that simulates and proposes optimized designs of detailed layouts. Since the method is to consider productivity, ergonomics, area utilization, and constraints from the automatically generated block layout, a multi-objective optimization approach is utilized. In the demonstrator, the input data are sent to the simulation software industrial path solutions (IPS). Based on the input and Lua scripts, the IPS software generates a block layout in compliance with the company’s defined dimensions of area reservations. Communication is then established between the IPS and the software EPP (Ergonomics in Productivity Platform), including intended resource descriptions, assembly manufacturing process, and manikin (digital human) resources. Using multi-objective optimization approaches, the EPP software then calculates layout proposals that are sent iteratively and simulated and rendered in IPS, following the rules and regulations defined in the block layout as well as productivity and ergonomics constraints and objectives. The software demonstrator is promising. The software can handle several parameters to optimize the detailed layout simultaneously and can put forward several proposals. It can optimize multiple parameters or weight the parameters to fine-tune the optimal result of the detailed layout. The intention of the demonstrator is to make the preparation between cross-disciplinary silos transparent and achieve a common preparation of the assembly manufacturing factory setup, thereby facilitating better decisions.

Keywords: factory setup, multi-objective, optimization, simulation

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Authors: Ashish Kumar Dwivedi

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Uttar Pradesh is largest part of Indian Federal system encapsulating twenty two million populations and has huge cultural, economic and religious diversity. The newly elected 18 months old state leadership of Uttar Pradesh has envisaged and initiated various proactive strides for the public grievance redressal and inclusive development schemes for all the sections of population from its very day of assumption of the office by Hon’ble Chief Minster Shri Yogi Adtiyanath. These initiatives also include Departmental responses via social media handles as Twitter, Facebook Page, and Web interaction. In the same course, every department of state government has been guided for the correct usage of verified social media handle separately and in co-ordination with other departments. These guidelines included making new WhatsApp groups to connect technocrats and politicians to communicate on common platform. Minister for Department of Infrastructure and Industrial Development, Shri Satish Mahana is a very popular leader and very intuitive statesman, has thousands of followers on social media and his accounts receive almost three hundred individually mentioned notifications from the various parts of Uttar Pradesh. These notifications primarily include problems related to livelihood and grievances concerned to department. To address these communications, a body of five experts has been set who are actively responding on various levels and increase bureaucratic engagements with marginalized sections of society. With reference to above background, this piece of research was conducted to analyze, categorize and derive effective implementation of public policies via social media platforms. This act of responsiveness has brought positive change in the mindset of population for the government, which was missed earlier. Department of Industrial Development in the Government is also inclined to attract investors aiming to become first trillion-dollar economy of India henceforth department also organized two major successful events in last one year. These events were also frame worked on social media platform to update 2.5 million population of state who is actively using social media in many ways. To analyze change scientifically, this study has been conducted and big data has been collected from October 2017 to September 2018 from the departmental social media handles as Twitter, Facebook, and emails. For this data, a statistical study has been conducted to analyze sentiments and expectations, specific and common requirement of communities, nature of grievances and their effective elucidation fitted into government policies. The control sample has also been taken from previous government activities to analyze the change. The statistical study used tools such as correlation study and principal component analysis. Also in this research communication, the modus operandi of grievance redressal, proliferation of government policies, connections to their beneficiaries and quick response procedure will be discussed.

Keywords: correlation study, principal component analysis, bureaucratic engagements, social media

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Authors: Andreas Schweiger, Matthias Gnigler, Elisabeth Wieder, Michael Grobbauer

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Especially in the alpine region, available areas for new residential development are limited. One possible solution is to exploit the potential of existing settlements. Urban redensification, especially the addition of floors to existing buildings, requires efficient, lightweight constructions with short construction times. This topic is being addressed in the five-year Alpine Building Centre. The focus of this cooperation between Salzburg University of Applied Sciences and RSA GH Studio iSPACE is on transdisciplinary research in the fields of building and energy technology, building envelopes and geoinformation, as well as the transfer of research results to industry. One development objective is a system of wood panel system construction with a high degree of prefabrication to optimize the construction quality, the construction time and the applicability for small and medium-sized enterprises. The system serves as a reliable working basis for mastering the complex building task of redensification. The technical solution is the development of an open system in timber frame and solid wood construction, which is suitable for a maximum two-story addition of residential buildings. The applicability of the system is mainly influenced by the existing building stock. Therefore, timber frame and solid timber construction are combined where necessary to bridge large spans of the existing structure while keeping the dead weight as low as possible. Escape routes are usually constructed in reinforced concrete and are located outside the system boundary. Thus, within the framework of the legal and normative requirements of timber construction, a hybrid construction method for redensification created. Component structure, load-bearing structure and detail constructions are developed in accordance with the relevant requirements. The results are directly applicable in individual cases, with the exception of the required verifications. In order to verify the practical suitability of the developed system, stakeholder workshops are held on the one hand, and the system is applied in the planning of a two-storey extension on the other hand. A company-independent construction standard offers the possibility of cooperation and bundling of capacities in order to be able to handle larger construction volumes in collaboration with several companies. Numerous further developments can take place on the basis of the system, which is under open license. The construction system will support planners and contractors from design to execution. In this context, open means publicly published and freely usable and modifiable for own use as long as the authorship and deviations are mentioned. The companies are provided with a system manual, which contains the system description and an application manual. This manual will facilitate the selection of the correct component cross-sections for the specific construction projects by means of all component and detail specifications. This presentation highlights the initial situation, the motivation, the approach, but especially the technical solution as well as the possibilities for the application. After an explanation of the objectives and working methods, the component and detail specifications are presented as work results and their application.

Keywords: redensification, SME, urban development, wood building system

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Authors: Abderrahim El Maslouhi

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The paper aims to analyze an often-overlooked dimension of global constitutionalism, which is the rise of the regulatory state and its impact on parliamentary dynamics in transition regimes. In contrast to Majone’s technocratic vision of convergence towards a single regulatory system based on competence and efficiency, national transpositions of regulatory governance and, in general, the relationship to global standards primarily depend upon a number of distinctive parameters. These include policy formation process, speed of change, depth of parliamentary tradition and greater or lesser vulnerability to the normative conditionality of donors, interstate groupings and transnational regulatory bodies. Based on a comparison between three post-Arab Spring countries -Morocco, Tunisia, and Egypt, whose constitutions have undergone substantive review in the period 2011-2014- and some European Union state members, the paper intends, first, to assess the degree of permeability to global constitutionalism in different contexts. A noteworthy divide emerges from this comparison. Whereas European constitutions still seem impervious to the lexicon of global constitutionalism, the influence of the latter is obvious in the recently drafted constitutions in Morocco, Tunisia, and Egypt. This is evidenced by their reference to notions such as ‘governance’, ‘regulators’, ‘accountability’, ‘transparency’, ‘civil society’, and ‘participatory democracy’. Second, the study will provide a contextual account of internal and external rationales underlying the constitutionalization of regulatory governance in the cases examined. Unlike European constitutionalism, where parliamentarism and the tradition of representative government function as a structural mechanism that moderates the de-parliamentarization effect induced by global constitutionalism, Arab constitutional transitions have led to a paradoxical situation; contrary to the public demands for further parliamentarization, the 2011 constitution-makers have opted for a de-parliamentarization pattern. This is particularly reflected in the procedures established by constitutions and regular legislation, to handle the interaction between lawmakers and regulatory bodies. Once the ‘constitutional’ and ‘independent’ nature of these agencies is formally endorsed, the birth of these ‘fourth power’ entities, which are neither elected nor directly responsible to elected officials, will raise the question of their accountability. Third, the paper shows that, even in the three selected countries, the de-parliamentarization intensity is significantly variable. By contrast to the radical stance of the Moroccan and Egyptian constituents who have shown greater concern to shield regulatory bodies from legislatures’ scrutiny, the Tunisian case indicates a certain tendency to provide lawmakers with some essential control instruments (e. g. exclusive appointment power, adversarial discussion of regulators’ annual reports, dismissal power, later held unconstitutional). In sum, the comparison reveals that the transposition of the regulatory state model and, more generally, sensitivity to the legal implications of global conditionality essentially relies on the evolution of real-world power relations at both national and international levels.

Keywords: Arab legislatures, de-parliamentarization, global constitutionalism, normative conditionality, regulatory state

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Authors: Sarah Mueller-Saegebrecht, André Brendler

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Business model innovation (BMI) as an intentional change of an existing business model (BM) or the design of a new BM is essential to a firm's development in dynamic markets. The relevance of BMI is also evident in the ongoing COVID-19 pandemic, in which start-ups, in particular, are affected by limited access to resources. However, first studies also show that they react faster to the pandemic than established firms. A strategy to successfully handle such threatening dynamic changes represents BMI. Entrepreneurship literature shows how and when firms should utilize BMI in times of crisis and which barriers one can expect during the BMI process. Nevertheless, research merging BMI barriers and crises is still underexplored. Specifically, further knowledge about antecedents and the effect of moderators on the BMI process is necessary for advancing BMI research. The addressed research gap of this study is two-folded: First, foundations to the subject on how different crises impact BM change intention exist, yet their analysis lacks the inclusion of barriers. Especially, entrepreneurship literature lacks knowledge about the individual perception of BMI barriers, which is essential to predict managerial reactions. Moreover, internal BMI barriers have been the focal point of current research, while external BMI barriers remain virtually understudied. Second, to date, BMI research is based on qualitative methodologies. Thus, a lack of quantitative work can specify and confirm these qualitative findings. By focusing on the crisis context, this study contributes to BMI literature by offering a first quantitative attempt to embed BMI barriers into a structural equation model. It measures managers' perception of BMI development and implementation barriers in the BMI process, asking the following research question: How does a manager's perception of BMI barriers influence BMI development and implementation in times of crisis? Two distinct research streams in economic literature explain how individuals react when perceiving a threat. "Prospect Theory" claims that managers demonstrate risk-seeking tendencies when facing a potential loss, and opposing "Threat-Rigidity Theory" suggests that managers demonstrate risk-averse behavior when facing a potential loss. This study quantitively tests which theory can best predict managers' BM reaction to a perceived crisis. Out of three in-depth interviews in the German chemical industry, 60 past BMIs were identified. The participating start-up managers gave insights into their start-up's strategic and operational functioning. After, each interviewee described crises that had already affected their BM. The participants explained how they conducted BMI to overcome these crises, which development and implementation barriers they faced, and how severe they perceived them, assessed on a 5-point Likert scale. In contrast to current research, results reveal that a higher perceived threat level of a crisis harms BM experimentation. Managers seem to conduct less BMI in times of crisis, whereby BMI development barriers dampen this relation. The structural equation model unveils a mediating role of BMI implementation barriers on the link between the intention to change a BM and the concrete BMI implementation. In conclusion, this study confirms the threat-rigidity theory.

Keywords: barrier perception, business model innovation, business model innovation barriers, crises, prospect theory, start-ups, structural equation model, threat-rigidity theory

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Authors: Solanki Ravirajsinh, Kudo Kuniaki, Sharma Ankit, Devi Sherine, Kuboshima Misaki, Tachi Shuntaro

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In software development life cycles, the absence of scalable CI/CD significantly impacts organizations, leading to increased overall maintenance costs, prolonged release delivery times, heightened manual efforts, and difficulties in meeting tight deadlines. Implementing CI/CD with standard serverless technologies using cloud services overcomes all the above-mentioned issues and helps organizations improve efficiency and faster delivery without the need to manage server maintenance and capacity. By integrating scalable CI/CD with scalable automation testing, productivity, quality, and agility are enhanced while reducing the need for repetitive work and manual efforts. Implementing scalable CI/CD for development using cloud services like ECS (Container Management Service), AWS Fargate, ECR (to store Docker images with all dependencies), Serverless Computing (serverless virtual machines), Cloud Log (for monitoring errors and logs), Security Groups (for inside/outside access to the application), Docker Containerization (Docker-based images and container techniques), Jenkins (CI/CD build management tool), and code management tools (GitHub, Bitbucket, AWS CodeCommit) can efficiently handle the demands of diverse development environments and are capable of accommodating dynamic workloads, increasing efficiency for faster delivery with good quality. CI/CD pipelines encourage collaboration among development, operations, and quality assurance teams by providing a centralized platform for automated testing, deployment, and monitoring. Scalable CI/CD streamlines the development process by automatically fetching the latest code from the repository every time the process starts, building the application based on the branches, testing the application using a scalable automation testing framework, and deploying the builds. Developers can focus more on writing code and less on managing infrastructure as it scales based on the need. Serverless CI/CD eliminates the need to manage and maintain traditional CI/CD infrastructure, such as servers and build agents, reducing operational overhead and allowing teams to allocate resources more efficiently. Scalable CI/CD adjusts the application's scale according to usage, thereby alleviating concerns about scalability, maintenance costs, and resource needs. Creating scalable automation testing using cloud services (ECR, ECS Fargate, Docker, EFS, Serverless Computing) helps organizations run more than 500 test cases in parallel, aiding in the detection of race conditions, performance issues, and reducing execution time. Scalable CI/CD offers flexibility, dynamically adjusting to varying workloads and demands, allowing teams to scale resources up or down as needed. It optimizes costs by only paying for the resources as they are used and increases reliability. Scalable CI/CD pipelines employ automated testing and validation processes to detect and prevent errors early in the development cycle.

Keywords: achieve parallel execution, cloud services, scalable automation testing, scalable continuous integration and deployment

Procedia PDF Downloads 43

Authors: Monica Arnaudo, Monika Topel, Bjorn Laumert

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Within the Swedish context, the current trend of relatively low electricity prices promotes the electrification of the energy infrastructure. The residential heating sector takes part in this transition by proposing a switch from a centralized district heating system towards a distributed heat pumps-based setting. When it comes to urban environments, two issues arise. The first, seen from an electricity-sector perspective, is related to the fact that existing networks are limited with regards to their installed capacities. Additional electric loads, such as heat pumps, can cause severe overloads on crucial network elements. The second, seen from a heating-sector perspective, has to do with the fact that the indoor comfort conditions can become difficult to handle when the operation of the heat pumps is limited by a risk of overloading on the distribution grid. Furthermore, the uncertainty of the electricity market prices in the future introduces an additional variable. This study aims at assessing the extent to which distributed heat pumps can penetrate an existing heat energy network while respecting the technical limitations of the electricity grid and the thermal comfort levels in the buildings. In order to account for the multi-disciplinary nature of this research question, a cosimulation modeling approach was adopted. In this way, each energy technology is modeled in its customized simulation environment. As part of the cosimulation methodology: a steady-state power flow analysis in pandapower was used for modeling the electrical distribution grid, a thermal balance model of a reference building was implemented in EnergyPlus to account for space heating and a fluid-cycle model of a heat pump was implemented in JModelica to account for the actual heating technology. With the models set in place, different scenarios based on forecasted electricity market prices were developed both for present and future conditions of Hammarby Sjöstad, a neighborhood located in the south-east of Stockholm (Sweden). For each scenario, the technical and the comfort conditions were assessed. Additionally, the average cost of heat generation was estimated in terms of levelized cost of heat. This indicator enables a techno-economic comparison study among the different scenarios. In order to evaluate the levelized cost of heat, a yearly performance simulation of the energy infrastructure was implemented. The scenarios related to the current electricity prices show that distributed heat pumps can replace the district heating system by covering up to 30% of the heating demand. By lowering of 2°C, the minimum accepted indoor temperature of the apartments, this level of penetration can increase up to 40%. Within the future scenarios, if the electricity prices will increase, as most likely expected within the next decade, the penetration of distributed heat pumps can be limited to 15%. In terms of levelized cost of heat, a residential heat pump technology becomes competitive only within a scenario of decreasing electricity prices. In this case, a district heating system is characterized by an average cost of heat generation 7% higher compared to a distributed heat pumps option.

Keywords: cosimulation, distributed heat pumps, district heating, electrical distribution grid, integrated energy systems

Procedia PDF Downloads 150

Authors: Caspar Goeke, Holger Finger, Dorena Diekamp, Peter König

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Online-based research has recently gained increasing attention from various fields of research in the cognitive sciences. Technological advances in the form of online crowdsourcing (Amazon Mechanical Turk), open data repositories (Open Science Framework), and online analysis (Ipython notebook) offer rich possibilities to improve, validate, and speed up research. However, until today there is no cross-platform integration of these subsystems. Furthermore, implementation of online studies still suffers from the complex implementation (server infrastructure, database programming, security considerations etc.). Here we propose and test a new JavaScript framework that enables researchers to conduct any kind of behavioral research in the browser without the need to program a single line of code. In particular our framework offers the possibility to manipulate and combine the experimental stimuli via a graphical editor, directly in the browser. Moreover, we included an action-event system that can be used to handle user interactions, interactively change stimuli properties or store participants’ responses. Besides traditional recordings such as reaction time, mouse and keyboard presses, the tool offers webcam based eye and face-tracking. On top of these features our framework also takes care about the participant recruitment, via crowdsourcing platforms such as Amazon Mechanical Turk. Furthermore, the build in functionality of google translate will ensure automatic text translations of the experimental content. Thereby, thousands of participants from different cultures and nationalities can be recruited literally within hours. Finally, the recorded data can be visualized and cleaned online, and then exported into the desired formats (csv, xls, sav, mat) for statistical analysis. Alternatively, the data can also be analyzed online within our framework using the integrated Ipython notebook. The framework was designed such that studies can be used interchangeably between researchers. This will support not only the idea of open data repositories but also constitutes the possibility to share and reuse the experimental designs and analyses such that the validity of the paradigms will be improved. Particularly, sharing and integrating the experimental designs and analysis will lead to an increased consistency of experimental paradigms. To demonstrate the functionality of the framework we present the results of a pilot study in the field of spatial navigation that was conducted using the framework. Specifically, we recruited over 2000 subjects with various cultural backgrounds and consequently analyzed performance difference in dependence on the factors culture, gender and age. Overall, our results demonstrate a strong influence of cultural factors in spatial cognition. Such an influence has not yet been reported before and would not have been possible to show without the massive amount of data collected via our framework. In fact, these findings shed new lights on cultural differences in spatial navigation. As a consequence we conclude that our new framework constitutes a wide range of advantages for online research and a methodological innovation, by which new insights can be revealed on the basis of massive data collection.

Keywords: cultural differences, crowdsourcing, JavaScript framework, methodological innovation, online data collection, online study, spatial cognition

Procedia PDF Downloads 257

Authors: Mohammadreza Nematollahi, Bahareh Mosadegh Sedghy, Alireza Tajbakhsh

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The last two decades have witnessed substantial attention to organic and sustainable agricultural supply chains. Motivated by real-world practices, this paper aims to address two main challenges observed in organic product supply chains: decentralized decision-making process between farmers and their retailers, and competition between organic products and their conventional counterparts. To this aim, an agricultural supply chain consisting of two farmers, a conventional farmer and an organic farmer who offers an organic version of the same product, is considered. Both farmers distribute their products through a single retailer, where there exists competition between the organic and the conventional product. The retailer, as the market leader, sets the wholesale price, and afterward, the farmers set their production quantity decisions. This paper first models the demand functions of the conventional and organic products by incorporating the effect of asymmetric brand equity, which captures the fact that consumers usually pay a premium for organic due to positive perceptions regarding their health and environmental benefits. Then, profit functions with consideration of some characteristics of organic farming, including crop yield gap and organic cost factor, are modeled. Our research also considers both economies and diseconomies of scale in farming production as well as the effects of organic subsidy paid by the government to support organic farming. This paper explores the investigated supply chain in three scenarios: decentralized, centralized, and coordinated decision-making structures. In the decentralized scenario, the conventional and organic farmers and the retailer maximize their own profits individually. In this case, the interaction between the farmers is modeled under the Bertrand competition, while analyzing the interaction between the retailer and farmers under the Stackelberg game structure. In the centralized model, the optimal production strategies are obtained from the entire supply chain perspective. Analytical models are developed to derive closed-form optimal solutions. Moreover, analytical sensitivity analyses are conducted to explore the effects of main parameters like the crop yield gap, organic cost factor, organic subsidy, and percent price premium of the organic product on the farmers’ and retailer’s optimal strategies. Afterward, a coordination scenario is proposed to convince the three supply chain members to shift from the decentralized to centralized decision-making structure. The results indicate that the proposed coordination scenario provides a win-win-win situation for all three members compared to the decentralized model. Moreover, our paper demonstrates that the coordinated model respectively increases and decreases the production and price of organic produce, which in turn motivates the consumption of organic products in the market. Moreover, the proposed coordination model helps the organic farmer better handle the challenges of organic farming, including the additional cost and crop yield gap. Last but not least, our results highlight the active role of the organic subsidy paid by the government as a means of promoting sustainable organic product supply chains. Our paper shows that although the amount of organic subsidy plays a significant role in the production and sales price of organic products, the allocation method of subsidy between the organic farmer and retailer is not of that importance.

Keywords: analytical game-theoretic model, product competition, supply chain coordination, sustainable organic supply chain

Procedia PDF Downloads 111

Authors: Kanokwan Chancharoenchai

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Economic growth can be considered as an important element of countries’ development process. For developing countries, like Thailand, to ensure the continuous growth of the economy, the Thai government usually implements various policies to stimulate economic growth. They may take the form of fiscal, monetary, trade, and other policies. Because of these different aspects, understanding factors relating to economic growth could allow the government to introduce the proper plan for the future economic stimulating scheme. Consequently, this issue has caught interest of not only policymakers but also academics. This study, therefore, investigates explanatory variables for economic growth in Thailand from 2005 to 2017 with a total of 52 quarters. The findings would contribute to the field of economic growth and become helpful information to policymakers. The investigation is estimated throughout the production function with non-linear Cobb-Douglas equation. The rate of growth is indicated by the change of GDP in the natural logarithmic form. The relevant factors included in the estimation cover three traditional means of production and implicit effects, such as human capital, international activity and technological transfer from developed countries. Besides, this investigation takes the internal and external instabilities into account as proxied by the unobserved inflation estimation and the real effective exchange rate (REER) of the Thai baht, respectively. The unobserved inflation series are obtained from the AR(1)-ARCH(1) model, while the unobserved REER of Thai baht is gathered from naive OLS-GARCH(1,1) model. According to empirical results, the AR(|2|) equation which includes seven significant variables, namely capital stock, labor, the imports of capital goods, trade openness, the REER of Thai baht uncertainty, one previous GDP, and the world financial crisis in 2009 dummy, presents the most suitable model. The autoregressive model is assumed constant estimator that would somehow cause the unbias. However, this is not the case of the recursive coefficient model from the state space model that allows the transition of coefficients. With the powerful state space model, it provides the productivity or effect of each significant factor more in detail. The state coefficients are estimated based on the AR(|2|) with the exception of the one previous GDP and the 2009 world financial crisis dummy. The findings shed the light that those factors seem to be stable through time since the occurrence of the world financial crisis together with the political situation in Thailand. These two events could lower the confidence in the Thai economy. Moreover, state coefficients highlight the sluggish rate of machinery replacement and quite low technology of capital goods imported from abroad. The Thai government should apply proactive policies via taxation and specific credit policy to improve technological advancement, for instance. Another interesting evidence is the issue of trade openness which shows the negative transition effect along the sample period. This could be explained by the loss of price competitiveness to imported goods, especially under the widespread implementation of free trade agreement. The Thai government should carefully handle with regulations and the investment incentive policy by focusing on strengthening small and medium enterprises.

Keywords: autoregressive model, economic growth, state space model, Thailand

Procedia PDF Downloads 151

Authors: Eleonora Carloni, Michela Arnaboldi

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In academia, the investigation of the relationship between cultural heritage and corporations is ubiquitous in several fields of studies. In practice corporations are more and more integrating arts and cultural heritage in their strategies for disparate benefits, such as: to foster customer’s purchase intention with authentic and aesthetic experiences, to improve their reputation towards local communities, and to motivate employees with creative thinking. There are diverse forms under which corporations set these artistic interventions, from sponsorships to arts-based training centers for employees, but scholars agree that the maximum expression of this cultural trend are corporate museums, growing in number and relevance. Corporate museums are museum-like settings, hosting artworks of corporations’ history and interests. In academia they have been ascribed as strategic asset and they have been associated with diverse uses for corporations’ benefits, from place for preservation of cultural heritage, to tools for public relations and cultural flagship stores. Previous studies have thus extensively but fragmentally studied the diverse benefits of corporate museum opening to corporations, with a lack of comprehensive approach and a digression on how to evaluate and report corporate museum’s performances. Stepping forward, the present study aims to investigate: 1) what are the key performance measures corporate museums need to report to the associated corporations; 2) how are the key performance measures reported to the concerned corporations. This direction of study is not only suggested as future direction in academia but it has solid basis in practice, aiming to answer to the need of corporate museums’ directors to account for corporate museum’s activities to the concerned corporation. Coherently, at an empirical level the study relies on action research method, whose distinctive feature is to develop practical knowledge through a participatory process. This paper indeed relies on the experience of a collaborative project between the researchers and a set of corporate museums in Italy, aimed at co-developing a performance measurement system. The project involved two steps: a first step, in which researchers derived the potential performance measures from literature along with exploratory interviews; a second step, in which researchers supported the pool of corporate museums’ directors in co-developing a set of key performance indicators for reporting. Preliminary empirical findings show that while scholars insist on corporate museums’ capability to develop networking relations, directors insist on the role of museums as internal supplier of knowledge for innovation goals. Moreover, directors stress museums’ cultural mission and outcomes as potential benefits for corporation, by remarking to include both cultural and business measures in the final tool. In addition, they give relevant attention to the wording used in humanistic terms while struggling to express all measures in economic terms. The paper aims to contribute to corporate museums’ and more broadly to arts-based initiatives’ literature in two directions. Firstly, it elaborates key performance measures with related indicators to report on cultural initiatives for corporations. Secondly, it provides evidence of challenges and practices to handle reporting on these initiatives, because of tensions arising from the co-existence of diverse perspectives, namely arts and business worlds.

Keywords: arts-based initiative, corporate museum, hybrid organization, performance measurement

Procedia PDF Downloads 176

Authors: Miguel A. Figueroa, José A. Lara-Ramos, Miguel A. Mueses

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Pharmaceutical residues are a section of emerging contaminants of anthropogenic origin that are present in a myriad of waters with which human beings interact daily and are starting to affect the ecosystem directly. Conventional waste-water treatment systems are not capable of degrading these pharmaceutical effluents because their designs cannot handle the intermediate products and biological effects occurring during its treatment. That is why it is necessary to hybridize conventional waste-water systems with non-conventional processes. In the specific case of an ozonation process, its efficiency highly depends on a perfect dispersion of ozone, long times of interaction of the gas-liquid phases and the size of the ozone bubbles formed through-out the reaction system. In order to increase the efficiency of these parameters, the use of a modified flotation cell has been proposed recently as a reactive system, which is used at an industrial level to facilitate the suspension of particles and spreading gas bubbles through the reactor volume at a high rate. The objective of the present work is the development of a mathematical model that can closely predict the kinetic rates of reactions taking place in the flotation cell at an experimental scale by means of identifying proper reaction mechanisms that take into account the modified chemical and hydrodynamic factors in the FeO-catalyzed Ozonation of Diclofenac aqueous solutions in a flotation cell. The methodology is comprised of three steps: an experimental phase where a modified flotation cell reactor is used to analyze the effects of ozone concentration and loading catalyst over the degradation of Diclofenac aqueous solutions. The performance is evaluated through an index of utilized ozone, which relates the amount of ozone supplied to the system per milligram of degraded pollutant. Next, a theoretical phase where the reaction mechanisms taking place during the experiments must be identified and proposed that details the multiple direct and indirect reactions the system goes through. Finally, a kinetic model is obtained that can mathematically represent the reaction mechanisms with adjustable parameters that can be fitted to the experimental results and give the model a proper physical meaning. The expected results are a robust reaction rate law that can simulate the improved results of Diclofenac mineralization on water using the modified flotation cell reactor. By means of this methodology, the following results were obtained: A robust reaction pathways mechanism showcasing the intermediates, free-radicals and products of the reaction, Optimal values of reaction rate constants that simulated Hatta numbers lower than 3 for the system modeled, degradation percentages of 100%, TOC (Total organic carbon) removal percentage of 69.9 only requiring an optimal value of FeO catalyst of 0.3 g/L. These results showed that a flotation cell could be used as a reactor in ozonation, catalytic ozonation and photocatalytic ozonation processes, since it produces high reaction rate constants and reduces mass transfer limitations (Ha > 3) by producing microbubbles and maintaining a good catalyst distribution.

Keywords: advanced oxidation technologies, iron oxide, emergent contaminants, AOTS intensification

Procedia PDF Downloads 112

Authors: Swati Bhomia, C. M. Kishtawal, Neeru Jaiswal

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Traditionally, monsoon forecasts have encountered many difficulties that stem from numerous issues such as lack of adequate upper air observations, mesoscale nature of convection, proper resolution, radiative interactions, planetary boundary layer physics, mesoscale air-sea fluxes, representation of orography, etc. Uncertainties in any of these areas lead to large systematic errors. Global circulation models (GCMs), which are developed independently at different institutes, each of which carries somewhat different representation of the above processes, can be combined to reduce the collective local biases in space, time, and for different variables from different models. This is the basic concept behind the multi-model superensemble and comprises of a training and a forecast phase. The training phase learns from the recent past performances of models and is used to determine statistical weights from a least square minimization via a simple multiple regression. These weights are then used in the forecast phase. The superensemble forecasts carry the highest skill compared to simple ensemble mean, bias corrected ensemble mean and the best model out of the participating member models. This approach is a powerful post-processing method for the estimation of weather forecast parameters reducing the direct model output errors. Although it can be applied successfully to the continuous parameters like temperature, humidity, wind speed, mean sea level pressure etc., in this paper, this approach is applied to rainfall, a parameter quite difficult to handle with standard post-processing methods, due to its high temporal and spatial variability. The present study aims at the development of advanced superensemble schemes comprising of 1-5 day daily precipitation forecasts from five state-of-the-art global circulation models (GCMs), i.e., European Centre for Medium Range Weather Forecasts (Europe), National Center for Environmental Prediction (USA), China Meteorological Administration (China), Canadian Meteorological Centre (Canada) and U.K. Meteorological Office (U.K.) obtained from THORPEX Interactive Grand Global Ensemble (TIGGE), which is one of the most complete data set available. The novel approaches include the dynamical model selection approach in which the selection of the superior models from the participating member models at each grid and for each forecast step in the training period is carried out. Multi-model superensemble based on the training using similar conditions is also discussed in the present study, which is based on the assumption that training with the similar type of conditions may provide the better forecasts in spite of the sequential training which is being used in the conventional multi-model ensemble (MME) approaches. Further, a variety of methods that incorporate a 'neighborhood' around each grid point which is available in literature to allow for spatial error or uncertainty, have also been experimented with the above mentioned approaches. The comparison of these schemes with respect to the observations verifies that the newly developed approaches provide more unified and skillful prediction of the summer monsoon (viz. June to September) rainfall compared to the conventional multi-model approach and the member models.

Keywords: multi-model superensemble, dynamical model selection, similarity criteria, neighborhood technique, rainfall prediction

Procedia PDF Downloads 139

Authors: Jose Neri, Fabrice Canto, Alastair Magnaldo, Laurent Guillerme, Vincent Dugas

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A miniaturized and automated approach for the volumetric titration of free nitric acid in U(VI) solutions is presented. Free acidity measurement refers to the acidity quantification in solutions containing hydrolysable heavy metal ions such as U(VI), U(IV) or Pu(IV) without taking into account the acidity contribution from the hydrolysis of such metal ions. It is, in fact, an operation having an essential role for the control of the nuclear fuel recycling process. The main objective behind the technical optimization of the actual ‘beaker’ method was to reduce the amount of radioactive substance to be handled by the laboratory personnel, to ease the instrumentation adjustability within a glove-box environment and to allow a high-throughput analysis for conducting more cost-effective operations. The measurement technique is based on the concept of the Taylor-Aris dispersion in order to create inside of a 200 μm x 5cm circular cylindrical micro-channel a linear concentration gradient in less than a second. The proposed analytical methodology relies on the actinide complexation using pH 5.6 sodium oxalate solution and subsequent alkalimetric titration of nitric acid with sodium hydroxide. The titration process is followed with a CCD camera for fluorescence detection; the neutralization boundary can be visualized in a detection range of 500nm- 600nm thanks to the addition of a pH sensitive fluorophore. The operating principle of the developed device allows the active generation of linear concentration gradients using a single cylindrical micro channel. This feature simplifies the fabrication and ease of use of the micro device, as it does not need a complex micro channel network or passive mixers to generate the chemical gradient. Moreover, since the linear gradient is determined by the liquid reagents input pressure, its generation can be fully achieved in faster intervals than one second, being a more timely-efficient gradient generation process compared to other source-sink passive diffusion devices. The resulting linear gradient generator device was therefore adapted to perform for the first time, a volumetric titration on a chip where the amount of reagents used is fixed to the total volume of the micro channel, avoiding an important waste generation like in other flow-based titration techniques. The associated analytical method is automated and its linearity has been proven for the free acidity determination of U(VI) samples containing up to 0.5M of actinide ion and nitric acid in a concentration range of 0.5M to 3M. In addition to automation, the developed analytical methodology and technique greatly improves the standard off-line oxalate complexation and alkalimetric titration method by reducing a thousand fold the required sample volume, forty times the nuclear waste per analysis as well as the analysis time by eight-fold. The developed device represents, therefore, a great step towards an easy-to-handle nuclear-related application, which in the short term could be used to improve laboratory safety as much as to reduce the environmental impact of the radioanalytical chain.

Keywords: free acidity, lab-on-a-chip, linear concentration gradient, Taylor-Aris dispersion, volumetric titration

Procedia PDF Downloads 387

Authors: Shreyas Kumar, Mili Shangari

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Integrating artificial intelligence (AI) in the cyber insurance sector represents a significant advancement, offering the potential to revolutionize risk assessment, fraud detection, and claims processing. However, this integration introduces a range of regulatory and economic challenges that must be addressed to ensure responsible and effective deployment of AI technologies. This paper examines the multifaceted regulatory landscape governing AI in cyber insurance and explores the economic implications of compliance, innovation, and market dynamics. AI's capabilities in processing vast amounts of data and identifying patterns make it an invaluable tool for insurers in managing cyber risks. Yet, the application of AI in this domain is subject to stringent regulatory scrutiny aimed at safeguarding data privacy, ensuring algorithmic transparency, and preventing biases. Regulatory bodies, such as the European Union with its General Data Protection Regulation (GDPR), mandate strict compliance requirements that can significantly impact the deployment of AI systems. These regulations necessitate robust data protection measures, ethical AI practices, and clear accountability frameworks, all of which entail substantial compliance costs for insurers. The economic implications of these regulatory requirements are profound. Insurers must invest heavily in upgrading their IT infrastructure, implementing robust data governance frameworks, and training personnel to handle AI systems ethically and effectively. These investments, while essential for regulatory compliance, can strain financial resources, particularly for smaller insurers, potentially leading to market consolidation. Furthermore, the cost of regulatory compliance can translate into higher premiums for policyholders, affecting the overall affordability and accessibility of cyber insurance. Despite these challenges, the potential economic benefits of AI integration in cyber insurance are significant. AI-enhanced risk assessment models can provide more accurate pricing, reduce the incidence of fraudulent claims, and expedite claims processing, leading to overall cost savings and increased efficiency. These efficiencies can improve the competitiveness of insurers and drive innovation in product offerings. However, balancing these benefits with regulatory compliance is crucial to avoid legal penalties and reputational damage. The paper also explores the potential risks associated with AI integration, such as algorithmic biases that could lead to unfair discrimination in policy underwriting and claims adjudication. Regulatory frameworks need to evolve to address these issues, promoting fairness and transparency in AI applications. Policymakers play a critical role in creating a balanced regulatory environment that fosters innovation while protecting consumer rights and ensuring market stability. In conclusion, the integration of AI in cyber insurance presents both regulatory and economic challenges that require a coordinated approach involving regulators, insurers, and other stakeholders. By navigating these challenges effectively, the industry can harness the transformative potential of AI, driving advancements in risk management and enhancing the resilience of the cyber insurance market. This paper provides insights and recommendations for policymakers and industry leaders to achieve a balanced and sustainable integration of AI technologies in cyber insurance.

Keywords: artificial intelligence (AI), cyber insurance, regulatory compliance, economic impact, risk assessment, fraud detection, cyber liability insurance, risk management, ransomware

Procedia PDF Downloads 33

Authors: Stefan K. Behfar

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The rapid growth of the Ethereum network has brought forth the urgent need for scalable analysis methods to handle the increasing volume of blockchain data. In this research, we propose efficient methodologies for making Ethereum network analysis scalable. Our approach leverages a combination of graph-based data representation, probabilistic sampling, and parallel processing techniques to achieve unprecedented scalability while preserving critical network insights. Data Representation: We develop a graph-based data representation that captures the underlying structure of the Ethereum network. Each block transaction is represented as a node in the graph, while the edges signify temporal relationships. This representation ensures efficient querying and traversal of the blockchain data. Probabilistic Sampling: To cope with the vastness of the Ethereum blockchain, we introduce a probabilistic sampling technique. This method strategically selects a representative subset of transactions and blocks, allowing for concise yet statistically significant analysis. The sampling approach maintains the integrity of the network properties while significantly reducing the computational burden. Graph Convolutional Networks (GCNs): We incorporate GCNs to process the graph-based data representation efficiently. The GCN architecture enables the extraction of complex spatial and temporal patterns from the sampled data. This combination of graph representation and GCNs facilitates parallel processing and scalable analysis. Distributed Computing: To further enhance scalability, we adopt distributed computing frameworks such as Apache Hadoop and Apache Spark. By distributing computation across multiple nodes, we achieve a significant reduction in processing time and enhanced memory utilization. Our methodology harnesses the power of parallelism, making it well-suited for large-scale Ethereum network analysis. Evaluation and Results: We extensively evaluate our methodology on real-world Ethereum datasets covering diverse time periods and transaction volumes. The results demonstrate its superior scalability, outperforming traditional analysis methods. Our approach successfully handles the ever-growing Ethereum data, empowering researchers and developers with actionable insights from the blockchain. Case Studies: We apply our methodology to real-world Ethereum use cases, including detecting transaction patterns, analyzing smart contract interactions, and predicting network congestion. The results showcase the accuracy and efficiency of our approach, emphasizing its practical applicability in real-world scenarios. Security and Robustness: To ensure the reliability of our methodology, we conduct thorough security and robustness evaluations. Our approach demonstrates high resilience against adversarial attacks and perturbations, reaffirming its suitability for security-critical blockchain applications. Conclusion: By integrating graph-based data representation, GCNs, probabilistic sampling, and distributed computing, we achieve network scalability without compromising analytical precision. This approach addresses the pressing challenges posed by the expanding Ethereum network, opening new avenues for research and enabling real-time insights into decentralized ecosystems. Our work contributes to the development of scalable blockchain analytics, laying the foundation for sustainable growth and advancement in the domain of blockchain research and application.

Keywords: Ethereum, scalable network, GCN, probabilistic sampling, distributed computing

Procedia PDF Downloads 76

Authors: Mohiuddin Ahsanul Kabir Chowdhury, Nafisa Lira Huq, Afroza Khanom, Rafiqul Islam, Abdullah Nurus Salam Khan, Farhana Karim, Nabila Zaka, Shams El Arifeen, Sk. Masum Billah

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After having astounding achievements in reducing maternal mortality and achieving the target for Millennium Development Goal (MDG) 5, the Government of Bangladesh has set new target to reduce Maternal Mortality Ratio (MMR) to 70 per 100,000 live births aligning with targets of Sustainable Development Goals (SDGs). Aversion of deaths from maternal complication by ensuring quality health care could be an important path to accelerate the rate of reduction of MMR. This formative research was aimed at exploring the provision of quality maternal health services at different level of health facilities. The study was conducted in 1 district hospital (DH) and 4 Upazila health complexes (UHC) of Kurigram district of Bangladesh, utilizing both quantitative and qualitative research methods. We conducted 14 key informant interviews with facility managers and 20 in-depth interviews with health care providers and support staff. Besides, we observed 387 normal deliveries from which we found 17 cases of post partum haemorrhage (PPH) and 2 cases of eclampsia during the data collection period extended from July-September 2016. The quantitative data were analyzed by using descriptive statistics, and the qualitative component underwent thematic analysis with the broad themes of facility readiness for maternal complication management, and management of complications. Inadequacy in human resources has been identified as the most important bottleneck to provide quality care to manage maternal complications. The DH had a particular paucity of human resources in medical officer cadre where about 61% posts were unfilled. On the other hand, in the UHCs the positions mostly empty were obstetricians (75%, paediatricians (75%), staff nurses (65%), and anaesthetists (100%). The workload on the existing staff is increased because of the persistence of vacant posts. Unavailability of anesthetists and consultants does not permit the health care providers (HCP) of lower cadres to perform emergency operative procedures and forces them to refer the patients although referral system is not well organized in rural Bangladesh. Insufficient bed capacity, inadequate training, shortage of emergency medicines etc. are other hindrance factors for facility readiness. Among the 387 observed delivery case, 17 (4.4%) were identified as PPH cases, and only 2 cases were found as eclampsia/pre-eclampsia. The majority of the patients were treated with uterine message (16 out of 17, 94.1%) and injectable Oxytocin (14 out of 17, 82.4%). The providers of DH mentioned that they can manage the PPH because of having provision for diagnostic and blood transfusion services, although not as 24/7 services. Regarding management of eclampsia/pre-eclampsia, HCPs provided Diazepam, MgSO4, and other anti-hypertensives. The UHCs did not have MgSO4 at stock even, and one facility manager admitted that they treat eclampsia with Diazepam only. The nurses of the UHCs were found to be afraid to handle eclampsia cases. The upcoming interventions must ensure refresher training of service providers, continuous availability of essential medicine and equipment needed for complication management, availability of skilled health workforce, availability of functioning blood transfusion unit and pairing of consultants and anaesthetists to reach the newly set targets altogether.

Keywords: Bangladesh, health facilities, maternal complications, quality of care

Procedia PDF Downloads 235

Authors: Asma Omri, Iheb Sifaoui, Sofiane Sayahi, Hichem Besbes

Abstract:

Future vehicle systems demand advanced capabilities, notably in-cabin life detection and driver monitoring systems, with a particular emphasis on drowsiness detection. To meet these requirements, several techniques employ artificial intelligence methods based on real-time vital sign measurements. In parallel, Frequency-Modulated Continuous-Wave (FMCW) radar technology has garnered considerable attention in the domains of healthcare and biomedical engineering for non-invasive vital sign monitoring. FMCW radar offers a multitude of advantages, including its non-intrusive nature, continuous monitoring capacity, and its ability to penetrate through clothing. In this paper, we propose a system utilizing the AWR6843AOP radar from Texas Instruments (TI) to extract precise vital sign information. The radar allows us to estimate Ballistocardiogram (BCG) signals, which capture the mechanical movements of the body, particularly the ballistic forces generated by heartbeats and respiration. These signals are rich sources of information about the cardiac cycle, rendering them suitable for heart rate estimation. The process begins with real-time subject positioning, followed by clutter removal, computation of Doppler phase differences, and the use of various filtering methods to accurately capture subtle physiological movements. To address the challenges associated with FMCW radar-based vital sign monitoring, including motion artifacts due to subjects' movement or radar micro-vibrations, Long Short-Term Memory (LSTM) networks are implemented. LSTM's adaptability to different heart rate patterns and ability to handle real-time data make it suitable for continuous monitoring applications. Several crucial steps were taken, including feature extraction (involving amplitude, time intervals, and signal morphology), sequence modeling, heart rate estimation through the analysis of detected cardiac cycles and their temporal relationships, and performance evaluation using metrics such as Root Mean Square Error (RMSE) and correlation with reference heart rate measurements. For dataset construction and LSTM training, a comprehensive data collection system was established, integrating the AWR6843AOP radar, a Heart Rate Belt, and a smart watch for ground truth measurements. Rigorous synchronization of these devices ensured data accuracy. Twenty participants engaged in various scenarios, encompassing indoor and real-world conditions within a moving vehicle equipped with the radar system. Static and dynamic subject’s conditions were considered. The heart rate estimation through LSTM outperforms traditional signal processing techniques that rely on filtering, Fast Fourier Transform (FFT), and thresholding. It delivers an average accuracy of approximately 91% with an RMSE of 1.01 beat per minute (bpm). In conclusion, this paper underscores the promising potential of FMCW radar technology integrated with artificial intelligence algorithms in the context of automotive applications. This innovation not only enhances road safety but also paves the way for its integration into the automotive ecosystem to improve driver well-being and overall vehicular safety.

Keywords: ballistocardiogram, FMCW Radar, vital sign monitoring, LSTM

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Authors: Rajkumar Ghosh, Ananya Mukhopadhyay

Abstract:

This scientific paper presents a thorough investigation into the integration of roof-mounted photovoltaic (PV) array systems and home rooftop rainwater collection systems in a remote community in Himachal Pradesh, India, with the goal of optimum utilization of natural resources for attaining sustainable living conditions by 2030. The study looks into the technical feasibility, environmental benefits, and socioeconomic impacts of this integrated method, emphasizing its ability to handle energy and water concerns in remote rural regions. This comprehensive method not only provides a sustainable source of electricity but also ensures a steady supply of clean water, promoting resilience and improving the quality of life for the village's residents. This research highlights the potential of such integrated systems in supporting sustainable conditions in rural areas through a combination of technical feasibility studies, economic analysis, and community interaction. There would be 20690 villages and 1.48 million homes (23.79% annual growth rate) in Himachal Pradesh if all residential buildings in the state had roof-mounted photovoltaic arrays to capture solar energy for power generation. The energy produced is utilized to power homes, lessening dependency on traditional fossil fuels. The same residential buildings housed domestic rooftop rainwater collection systems. Rainwater runoff from rooftops is collected and stored in tanks for use in a number of residential purposes, such as drinking, cooking, and irrigation. The gathered rainfall enhances the region's limited groundwater resources, easing the strain on local wells and aquifers. Although Himachal Pradesh of India is a Power state, the PV arrays have reduced the reliance of village on grid power and diesel generators by providing a steady source of electricity. Rooftop rainwater gathering has not only increased residential water supply but it has also lessened the burden on local groundwater resources. This helps to replenish groundwater and offers a more sustainable water supply for the town. The neighbourhood has saved money by utilizing renewable energy and rainwater gathering. Furthermore, lower fossil fuel consumption reduces greenhouse gas emissions, which helps to mitigate the effects of climate change. The integrated strategy of installing grid connected rooftop photovoltaic arrays and home rooftop rainwater collecting systems in Himachal Pradesh rural community demonstrates a feasible model for sustainable development. According to “Swaran Jayanti Energy Policy of Himachal Pradesh”, Himachal Pradesh is planned 10 GW from rooftop mode from Solar Power. Government of India provides 40% subsidy on solar panel of 1-3 kw and subsidy of Rs 6,000 per kw per year to encourage domestic consumers of Himachal Pradesh. This effort solves energy and water concerns, improves economic well-being, and helps to conserve the environment. Such integrated systems can serve as a model for sustainable development in rural areas not only in Himachal Pradesh, but also in other parts of the world where resource scarcity is a major concern. Long-term performance and scalability of such integrated systems should be the focus of future study. Efforts should also be made to duplicate this approach in other rural areas and examine its socioeconomic and environmental implications over time.

Keywords: renewable energy, photovoltaic arrays, rainwater harvesting, sustainability, rural development, Himachal Pradesh, India

Procedia PDF Downloads 100

Authors: Suparna Bagchi

Abstract:

Education as a discipline will probably be shaped by the importance it places on a conceptual, curricular, and pedagogical need to shift the emphasis toward transformative classrooms working for positive change through cultural diversity. Awareness of cultural diversity and race equality has heightened following George Floyd’s killing in the USA in 2020. This increasing awareness is particularly relevant in areas of historically low ethnic diversity which have lately experienced a rise in ethnic minority populations and where inclusive growth is a challenge. This research study aims to explore the perspectives of practitioners, students, and parents towards multiculturalism in four South West England primary schools. A qualitative case study methodology has been adopted framed by sociocultural theory. Data were collected through virtually conducted semi-structured interviews with school practitioners and parents, observation of students’ classroom activities, and documentary analysis of classroom displays. Although one-third of the school population includes ethnically diverse children, BAME (Black, Asian, and Minority Ethnic) characters featured in children's books published in Britain in 2019 were almost invisible, let alone a BAME main character. The Office for Standards in Education, Children's Services and Skills (Ofsted) are vocal about extending the Curriculum beyond the academic and technical arenas for pupils’ broader development and creation of an understanding and appreciation of cultural diversity. However, race equality and community cohesion which could help in the students’ broader development are not Ofsted’s school inspection criteria. The absence of culturally diverse content in the school curriculum highlighted by the 1985 Swann Report and 2007 Ajegbo Report makes England’s National Curriculum look like a Brexit policy three decades before Brexit. A revised National Curriculum may be the starting point with the teachers as curriculum framers playing a significant part. The task design is crucial where teachers can place equal importance on the interwoven elements of “how”, “what” and “why” the task is taught. Teachers need to build confidence in encouraging difficult conversations around racism, fear, indifference, and ignorance breaking the stereotypical barriers, thus helping to create students’ conception of a multicultural Britain. Research showed that trainee teachers in predominantly White areas often exhibit confined perspectives while educating children. Irrespective of the geographical location, school teachers can be equipped with culturally responsive initial and continuous professional development necessary to impart multicultural education. This may aid in the reduction of employees’ unconscious bias. This becomes distinctly pertinent to avoid horrific cases in the future like the recent one in Hackney where a Black teenager was strip-searched during period wrongly suspected of cannabis possession. Early research findings show participants’ eagerness for more ethnic diversity content incorporated in teaching and learning. However, schools are considerably dependent on the knowledge-focused Primary National Curriculum in England. Moreover, they handle issues around the intersectionality of disability, poverty, and gender. Teachers were trained in times when foregrounding ethnicity matters was not happening. Therefore, preoccupied with Curriculum requirements, intersectionality issues, and teacher preparations, schools exhibit an incapacity due to which keeping momentum on ethnic diversity is somewhat endangered.

Keywords: case study, curriculum decolonisation, inclusive education, multiculturalism, qualitative research in Covid19 times

Procedia PDF Downloads 118