Search results for: psychophysiological adaptive automation

Authors: Mahima Shrivastava, Soumya Kar, B. Swetha Malika, Lalu Saheb, M. Muthu Kumar, P. V. Ponambala Moorthi

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Natural hazards and manmade destruction causes both economic and societal losses. Generalized pre-mitigation strategies introduced and adopted for prevention of disaster all over the world are capable of augmenting the resiliency and optimizing the life-cycle cost of facilities. In countries like India where varied topographical feature exists requires location specific mitigation measures and strategies to be followed for better enhancement by event-driven and code-driven approaches. Present state of vindication measures followed and adopted, lags dominance in accomplishing the required development. In addition, serious concern and debate over climate change plays a vital role in enhancing the need and requirement for the development of time bound adaptive mitigation measures. For the development of long-term sustainable policies incorporation of future climatic variation is inevitable. This will further assist in assessing the impact brought about by the climate change on life-cycle cost of facilities. This paper develops more definite region specific and time bound pre-mitigation measures, by reviewing the present state of mitigation measures in India and all over the world for improving life-cycle cost of facilities. For the development of region specific adoptive measures, Indian regions were divided based on multiple-calamity prone regions and geo-referencing tools were used to incorporate the effect of climate changes on life-cycle cost assessment. This study puts forward significant effort in establishing sustainable policies and helps decision makers in planning for pre-mitigation measures for different regions. It will further contribute towards evaluating the life cycle cost of facilities by adopting the developed measures.

Keywords: climate change, geo-referencing tools, life-cycle cost, multiple-calamity prone regions, pre-mitigation strategies, sustainable policies

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Authors: Safaa H. Sindi, Michael Roe

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This project divides supply chain (SC) models into seven Eras, according to the evolution of the market’s needs throughout time. The five earliest Eras describe the emergence of supply chains, while the last two Eras are to be created. Research objectives: The aim is to generate the two latest Eras with their respective models that focus on the consumable goods. Era Six contains the Optimal Multidimensional Matrix (OMM) that incorporates most characteristics of the SC and allocates them into four quarters (Agile, Lean, Leagile, and Basic SC). This will help companies, especially (SMEs) plan their optimal SC route. Era Seven creates an Automated Multidimensional Model (AMM) which upgrades the matrix of Era six, as it accounts for all the supply chain factors (i.e. Offshoring, sourcing, risk) into an interactive system with Heuristic Learning that helps larger companies and industries to select the best SC model for their market. Methodologies: The data collection is based on a Fuzzy-Delphi study that analyses statements using Fuzzy Logic. The first round of Delphi study will contain statements (fuzzy rules) about the matrix of Era six. The second round of Delphi contains the feedback given from the first round and so on. Preliminary findings: both models are applicable, Matrix of Era six reduces the complexity of choosing the best SC model for SMEs by helping them identify the best strategy of Basic SC, Lean, Agile and Leagile SC; that’s tailored to their needs. The interactive heuristic learning in the AMM of Era seven will help mitigate error and aid large companies to identify and re-strategize the best SC model and distribution system for their market and commodity, hence increasing efficiency. Potential contributions to the literature: The problematic issue facing many companies is to decide which SC model or strategy to incorporate, due to the many models and definitions developed over the years. This research simplifies this by putting most definition in a template and most models in the Matrix of era six. This research is original as the division of SC into Eras, the Matrix of Era six (OMM) with Fuzzy-Delphi and Heuristic Learning in the AMM of Era seven provides a synergy of tools that were not combined before in the area of SC. Additionally the OMM of Era six is unique as it combines most characteristics of the SC, which is an original concept in itself.

Keywords: Leagile, automation, heuristic learning, supply chain models

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Authors: Ignatius Madu

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The study aims at assessing the environmental and socioeconomic determinants of climate change resilience in rural Nigeria. This is necessary because researches and development efforts on building climate change resilience of rural areas in developing countries are usually made without the knowledge of the impacts of the inherent rural characteristics that determine resilient capacities of the households. This has, in many cases, led to costly mistakes, delayed responses, inaccurate outcomes, and other difficulties. Consequently, this assessment becomes crucial not only to policymakers and people living in risk-prone environments in rural areas but also to fill the research gap. To achieve the aim, secondary data were obtained from the Annual Abstract of Statistics 2017, LSMS-Integrated Surveys on Agriculture and General Household Survey Panel 2015/2016, and National Agriculture Sample Survey (NASS), 2010/2011.Resilience was calculated by weighting and adding the adaptive, absorptive and anticipatory measures of households variables aggregated at state levels and then regressed against rural environmental and socioeconomic characteristics influencing it. From the regression, the coefficients of the variables were used to compute the impacts of the variables using the Stochastic Regression of Impacts on Population, Affluence and Technology (STIRPAT) Model. The results showed that the northern States are generally low in resilient indices and are impacted less by the development indicators. The major determining factors are percentage of non-poor, environmental protection, road transport development, landholding, agricultural input, population density, dependency ratio (inverse), household asserts, education and maternal care. The paper concludes that any effort to a successful resilient building in rural areas of the country should first address these key factors that enhance rural development and wellbeing since it is better to take action before shocks take place.

Keywords: climate change resilience; spatial impacts; STIRPAT model; Nigeria

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Authors: Chenhao Zhu

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Quantitative mapping is playing a growing role in guiding urban planning, such as using a heat map created by CFX, CFD2000, or Envi-met, to adjust the master plan. However, there is no effective quantitative link between the mappings and planning formation. So, in many cases, the decision-making is still based on the planner's subjective interpretation and understanding of these mappings, which limits the improvement of scientific and accuracy brought by the quantitative mapping. Therefore, in this paper, an effort has been made to give a methodology of building a parametric link between the mapping and planning formation. A parametric planning process based on radiant mapping has been proposed for creating an urban green system. In the first step, a script is written in Grasshopper to build a road network and form the block, while the Ladybug Plug-in is used to conduct a radiant analysis in the form of mapping. Then, the research creatively transforms the radiant mapping from a polygon into a data point matrix, because polygon is hard to engage in the design formation. Next, another script is created to select the main green spaces from the road network based on the criteria of radiant intensity and connect the green spaces' central points to generate a green corridor. After that, a control parameter is introduced to adjust the corridor's form based on the radiant intensity. Finally, a green system containing greenspace and green corridor is generated under the quantitative control of the data matrix. The designer only needs to modify the control parameter according to the relevant research results and actual conditions to realize the optimization of the green system. This method can also be applied to much other mapping-based analysis, such as wind environment analysis, thermal environment analysis, and even environmental sensitivity analysis. The parameterized link between the mapping and planning will bring about a more accurate, objective, and scientific planning.

Keywords: parametric link, mapping, urban green system, radiant intensity, planning strategy, grasshopper

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Authors: Rajkumar Ghosh

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India faces a critical task of water shortage, specifically during dry seasons, which adversely impacts agricultural productivity and food protection. Natural farming, specializing in sustainable practices, demands green water management in smart cities in India. This paper examines how rooftop rainwater harvesting (RRWH) can alleviate water scarcity and support sustainable organic farming practices in India. RRWH emerges as a promising way to increase water availability for the duration of dry intervals and decrease reliance on traditional water sources in smart cities. The look at explores the capacity of RRWH to enhance water use performance, help crop growth, enhance soil health, and promote ecological stability inside the farming ecosystem. The medical paper delves into the advantages, challenges, and implementation techniques of RRWH in organic farming. It addresses demanding situations, including seasonal variability of rainfall, limited rooftop vicinity, and monetary concerns. Moreover, it analyses broader environmental and socio-economic implications of RRWH for sustainable agriculture, emphasizing water conservation, biodiversity protection, and the social properly-being of farming communities. The belief underscores the importance of RRWH as a sustainable solution for reaching the aim of sustainable agriculture in natural farming in India. It emphasizes the want for further studies, policy advocacy, and capacity-building initiatives to promote RRWH adoption and assist the transformation in the direction of sustainable organic farming systems. The paper proposes adaptive strategies to triumph over demanding situations and optimize the advantages of RRWH in organic farming. By way of doing so, India can make vast development in addressing water scarcity issues and making sure a greater resilient and sustainable agricultural future in smart cities.

Keywords: rooftop rainwater harvesting, organic farming, green water management, food protection, ecological stabilty

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Authors: Naznine Anwar, Kim Cornish, Izelle Labuschagne, Nellie Georgiou-Karistianis

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Falls and subsequent injuries are common features in symptomatic Huntington’s disease (symp-HD) individuals. As part of daily walking, navigating around obstacles may incur a greater risk of falls in symp-HD. We designed obstacle-crossing experiment to examine adaptive gait dynamics and to identify underlying spatiotemporal gait characteristics that could increase the risk of falling in symp-HD. This experiment involved navigating around one or two ground-based obstacles under two conditions (walking while navigating around one obstacle, and walking while navigating around two obstacles). A total of 32 participants were included, 16 symp-HD and 16 healthy controls with age and sex matched. We used a GAITRite electronic walkway to examine the spatiotemporal gait characteristics and inter-trail gait variability when participants walked at their preferable speed. A minimum of six trials were completed which were performed for baseline free walk and also for each and every condition during navigating around the obstacles. For analysis, we separated all walking steps into three phases as approach steps, navigating steps and recovery steps. The mean and inter-trail variability (within participant standard deviation) for each step gait variable was calculated across the six trails. We found symp-HD individuals significantly decreased their gait velocity and step length and increased step duration variability during the navigating steps and recovery steps compared with approach steps. In contrast, HC individuals showed less difference in gait velocity, step time and step length variability from baseline in both respective conditions as well as all three approaches. These findings indicate that increasing spatiotemporal gait variability may be a possible compensatory strategy that is adopted by symp-HD individuals to effectively navigate obstacles during walking. Such findings may offer benefit to clinicians in the development of strategies for HD individuals to improve functional outcomes in the home and hospital based rehabilitation program.

Keywords: Huntington’s disease, gait variables, navigating around obstacle, basal ganglia dysfunction

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Authors: Taha Benarbia

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The advent of automated and connected vehicles has revolutionized the transportation industry, presenting new opportunities for enhancing the efficiency, safety, and sustainability of our transportation networks. This paper explores the integration of automated and connected vehicles into a smart transportation framework, leveraging the power of deep learning techniques to optimize the overall network performance. The first aspect addressed in this paper is the deployment of automated vehicles (AVs) within the transportation system. AVs offer numerous advantages, such as reduced congestion, improved fuel efficiency, and increased safety through advanced sensing and decisionmaking capabilities. The paper delves into the technical aspects of AVs, including their perception, planning, and control systems, highlighting the role of deep learning algorithms in enabling intelligent and reliable AV operations. Furthermore, the paper investigates the potential of connected vehicles (CVs) in creating a seamless communication network between vehicles, infrastructure, and traffic management systems. By harnessing real-time data exchange, CVs enable proactive traffic management, adaptive signal control, and effective route planning. Deep learning techniques play a pivotal role in extracting meaningful insights from the vast amount of data generated by CVs, empowering transportation authorities to make informed decisions for optimizing network performance. The integration of deep learning with automated and connected vehicles paves the way for advanced transportation network optimization. Deep learning algorithms can analyze complex transportation data, including traffic patterns, demand forecasting, and dynamic congestion scenarios, to optimize routing, reduce travel times, and enhance overall system efficiency. The paper presents case studies and simulations demonstrating the effectiveness of deep learning-based approaches in achieving significant improvements in network performance metrics

Keywords: automated vehicles, connected vehicles, deep learning, smart transportation network

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Authors: K. R. Roopesh Bharatwaj, Avinash Maharana, Favour Tobi Aborisade, Roger Young

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Presently, there are few cases of complete automation of drones and its allied intelligence capabilities. In essence, the potential of the drone has not yet been fully utilized. This paper presents feasible methods to build an intelligent drone with smart capabilities such as self-driving, and obstacle avoidance. It does this through advanced Reinforcement Learning Techniques and performs object detection using latest advanced algorithms, which are capable of processing light weight models with fast training in real time instances. For the scope of this paper, after researching on the various algorithms and comparing them, we finally implemented the Deep-Q-Networks (DQN) algorithm in the AirSim Simulator. In future works, we plan to implement further advanced self-driving and object detection algorithms, we also plan to implement voice-based speech recognition for the entire drone operation which would provide an option of speech communication between users (People) and the drone in the time of unavoidable circumstances. Thus, making drones an interactive intelligent Robotic Voice Enabled Service Assistant. This proposed drone has a wide scope of usability and is applicable in scenarios such as Disaster management, Air Transport of essentials, Agriculture, Manufacturing, Monitoring people movements in public area, and Defense. Also discussed, is the entire drone communication based on the satellite broadband Internet technology for faster computation and seamless communication service for uninterrupted network during disasters and remote location operations. This paper will explain the feasible algorithms required to go about achieving this goal and is more of a reference paper for future researchers going down this path.

Keywords: convolution neural network, natural language processing, obstacle avoidance, satellite broadband technology, self-driving

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Authors: Talal Alsulaiman, Khaldoun Khashanah

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In this paper, we provided a literature survey on the artificial stock problem (ASM). The paper began by exploring the complexity of the stock market and the needs for ASM. ASM aims to investigate the link between individual behaviors (micro level) and financial market dynamics (macro level). The variety of patterns at the macro level is a function of the AFM complexity. The financial market system is a complex system where the relationship between the micro and macro level cannot be captured analytically. Computational approaches, such as simulation, are expected to comprehend this connection. Agent-based simulation is a simulation technique commonly used to build AFMs. The paper proceeds by discussing the components of the ASM. We consider the roles of behavioral finance (BF) alongside the traditionally risk-averse assumption in the construction of agent's attributes. Also, the influence of social networks in the developing of agents’ interactions is addressed. Network topologies such as a small world, distance-based, and scale-free networks may be utilized to outline economic collaborations. In addition, the primary methods for developing agents learning and adaptive abilities have been summarized. These incorporated approach such as Genetic Algorithm, Genetic Programming, Artificial neural network and Reinforcement Learning. In addition, the most common statistical properties (the stylized facts) of stock that are used for calibration and validation of ASM are discussed. Besides, we have reviewed the major related previous studies and categorize the utilized approaches as a part of these studies. Finally, research directions and potential research questions are argued. The research directions of ASM may focus on the macro level by analyzing the market dynamic or on the micro level by investigating the wealth distributions of the agents.

Keywords: artificial stock markets, market dynamics, bounded rationality, agent based simulation, learning, interaction, social networks

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Authors: Francesca Nicolosi, Teresa Cosola

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Climate changes in Mediterranean areas, such as the increase of average seasonal temperatures, the urban heat island phenomenon, the intensification of solar radiation and the extreme weather threats, cause disruption events, so that climate adaptation has become a pressing issue. Due to the strategic role that the built heritage holds in terms of environmental impact and energy waste and its potentiality, it is necessary to assess the vulnerability and the adaptive capacity of the existing building to climate change, in order to define different mitigation scenarios. The aim of this research work is to define an optimized and integrated methodology for the assessment of resilience levels and adaptation scenarios for existing buildings in Mediterranean urban areas. Moreover, the study of resilience indicators allows us to define building environmental and energy performance in order to identify the design and technological solutions for the improvement of the building and its urban area potentialities. The methodology identifies step-by-step different phases, starting from the detailed study of characteristic elements of urban system: climatic, natural, human, typological and functional components are analyzed in their critical factors and their potential. Through the individuation of the main perturbing factors and the vulnerability degree of the system to the risks linked to climate change, it is possible to define mitigation and adaptation scenarios. They can be different, according to the typological, functional and constructive features of the analyzed system, divided into categories of intervention, and characterized by different analysis levels (from the single building to the urban area). The use of software simulations allows obtaining information on the overall behavior of the building and the urban system, to generate predictive models in the medium and long-term environmental and energy retrofit and to make a comparative study of the mitigation scenarios identified. The studied methodology is validated on a case study.

Keywords: climate impact mitigation, energy efficiency, existing building heritage, resilience

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Authors: Xiaowei Zhang, Min Xu, Saeid Habibi, Fengjun Yan, Ryan Ahmed

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Recently, Electric Vehicles (EVs) have received extensive consideration since they offer a more sustainable and greener transportation alternative compared to fossil-fuel propelled vehicles. Lithium-Ion (Li-ion) batteries are increasingly being deployed in EVs because of their high energy density, high cell-level voltage, and low rate of self-discharge. Since Li-ion batteries represent the most expensive component in the EV powertrain, accurate monitoring and control strategies must be executed to ensure their prolonged lifespan. The Battery Management System (BMS) has to accurately estimate parameters such as the battery State-of-Charge (SOC), State-of-Health (SOH), and Remaining Useful Life (RUL). In order for the BMS to estimate these parameters, an accurate and control-oriented battery model has to work collaboratively with a robust state and parameter estimation strategy. Since battery physical parameters, such as the internal resistance and diffusion coefficient change depending on the battery state-of-life (SOL), the BMS has to be adaptive to accommodate for this change. In this paper, an extensive battery aging study has been conducted over 12-months period on 5.4 Ah, 3.7 V Lithium polymer cells. Instead of using fixed charging/discharging aging cycles at fixed C-rate, a set of real-world driving scenarios have been used to age the cells. The test has been interrupted every 5% capacity degradation by a set of reference performance tests to assess the battery degradation and track model parameters. As battery ages, the combined model parameters are optimized and tracked in an offline mode over the entire batteries lifespan. Based on the optimized model, a state and parameter estimation strategy based on the Extended Kalman Filter (EKF) and the relatively new Smooth Variable Structure Filter (SVSF) have been applied to estimate the SOC at various states of life.

Keywords: lithium-ion batteries, genetic algorithm optimization, battery aging test, parameter identification

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Authors: Rahul Paul, Peter Mctaggart, Luke Skinner

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Maintaining public safety and network reliability are the core objectives of all electricity distributors globally. For many electricity distributors, managing vegetation clearances from their above ground assets (poles and conductors) is the most important and costly risk mitigation control employed to meet these objectives. Light Detection And Ranging (LiDAR) is widely used by utilities as a cost-effective method to inspect their spatially-distributed assets at scale, often captured using high powered LiDAR scanners attached to fixed wing or rotary aircraft. The resulting 3D point cloud model is used by these utilities to perform engineering grade measurements that guide the prioritisation of vegetation cutting programs. Advances in computer vision and machine-learning approaches are increasingly applied to increase automation and reduce inspection costs and time; however, real-world LiDAR capture variables (e.g., aircraft speed and height) create complexity, noise, and missing data, reducing the effectiveness of these approaches. This paper proposes a method for identifying each conductor from LiDAR data via clustering methods that can precisely reconstruct conductors in complex real-world configurations in the presence of high levels of noise. It proposes 3D catenary models for individual clusters fitted to the captured LiDAR data points using a least square method. An iterative learning process is used to identify potential conductor models between pole pairs. The proposed method identifies the optimum parameters of the catenary function and then fits the LiDAR points to reconstruct the conductors.

Keywords: point cloud, LİDAR data, machine learning, computer vision, catenary curve, vegetation management, utility industry

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Authors: Peiming Li

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This paper presents an innovative blockchain-based approach to enhance the reliability and efficiency of federated learning systems. By integrating a decentralized oracle consensus mechanism into the federated learning framework, we address key challenges of data and model integrity. Our approach utilizes a network of redundant oracles, functioning as independent validators within an epoch-based training system in the federated learning model. In federated learning, data is decentralized, residing on various participants' devices. This scenario often leads to concerns about data integrity and model quality. Our solution employs blockchain technology to establish a transparent and tamper-proof environment, ensuring secure data sharing and aggregation. The decentralized oracles, a concept borrowed from blockchain systems, act as unbiased validators. They assess the contributions of each participant using a Hidden Markov Model (HMM), which is crucial for evaluating the consistency of participant inputs and safeguarding against model poisoning and malicious activities. Our methodology's distinct feature is its epoch-based training. An epoch here refers to a specific training phase where data is updated and assessed for quality and relevance. The redundant oracles work in concert to validate data updates during these epochs, enhancing the system's resilience to security threats and data corruption. The effectiveness of this system was tested using the Mnist dataset, a standard in machine learning for benchmarking. Results demonstrate that our blockchain-oriented federated learning approach significantly boosts system resilience, addressing the common challenges of federated environments. This paper aims to make these advanced concepts accessible, even to those with a limited background in blockchain or federated learning. We provide a foundational understanding of how blockchain technology can revolutionize data integrity in decentralized systems and explain the role of oracles in maintaining model accuracy and reliability.

Keywords: federated learning system, block chain, decentralized oracles, hidden markov model

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Authors: Nurul Aliaa Idris, David A. Collings

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Phi thickenings are specialized secondary cell wall thickenings that are found in the cortex of the roots in a wide range of plant species, including orchids. The role of phi thickenings in the root is still under debate through research have linked environmental conditions, particularly abiotic stresses such as water stress, heavy metal stress and salinity to their induction in the roots. It has also been suggested that phi thickenings may act as a barrier to regulate solute uptake, act as a physical barrier against fungal hyphal penetration due to its resemblance to the Casparian strip and play a mechanical role to support cortical cells. We have investigated phi thickening function in epiphytic orchids of the genus Miltoniopsis through induction experiment against factors such as soil compaction and water stress. The permeability of the phi thickenings in Miltoniopsis was tested through uptake experiments using the fluorescent tracer dyes Calcofluor white, Lucifer yellow and Propidium iodide then viewed with wide-field or confocal microscopy. To test whether phi thickening may prevent fungal colonization in the root cell, fungal re-infection experiment was conducted by inoculating isolated symbiotic fungus to sterile in vitro Miltoniopsis explants. As the movement of fluorescent tracers through the apoplast was not blocked by phi thickenings, and as phi thickenings developed in the roots of sterile cultures in the absence of fungus and did not prevent fungal colonization of cortical cells, the phi thickenings in Miltoniopsis do not function as a barrier. Phi thickenings were found to be absent in roots grown on agar and remained absent when plants were transplanted to moist soil. However, phi thickenings were induced when plants were transplanted to well-drained media, and by the application of water stress in all soils tested. It is likely that phi thickenings stabilize the root cortex during dehydration. Nevertheless, the varied induction responses present in different plant species suggest that the phi thickenings may play several adaptive roles, instead of just one, depending on species.

Keywords: abiotic stress, Miltoniopsis, orchid, phi thickening

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Authors: Pranay Mathur, Carlo Michelassi, Simi Karatha, Gilda Pedoto

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Industrial plant uptime is top most importance for reliable, profitable & sustainable operation. Trip and failed start has major impact on plant reliability and all plant operators focussed on efforts required to minimise the trips & failed starts. The performance of these CTQs are measured with 2 metrics, MTBT(Mean time between trips) and SR (Starting reliability). These metrics helps to identify top failure modes and identify units need more effort to improve plant reliability. Baker Hughes Trip reduction program structured to reduce these unwanted trip 1. Real time machine operational parameters remotely available and capturing the signature of malfunction including related boundary condition. 2. Real time alerting system based on analytics available remotely. 3. Remote access to trip logs and alarms from control system to identify the cause of events. 4. Continuous support to field engineers by remotely connecting with subject matter expert. 5. Live tracking of key CTQs 6. Benchmark against fleet 7. Break down to the cause of failure to component level 8. Investigate top contributor, identify design and operational root cause 9. Implement corrective and preventive action 10. Assessing effectiveness of implemented solution using reliability growth models. 11. Develop analytics for predictive maintenance With this approach , Baker Hughes team is able to support customer in achieving their Reliability Key performance Indicators for monitored units, huge cost savings for plant operators. This Presentation explains these approach while providing successful case studies, in particular where 12nos. of LNG and Pipeline operators with about 140 gas compressing line-ups has adopted these techniques and significantly reduce the number of trips and improved MTBT

Keywords: reliability, availability, sustainability, digital infrastructure, weibull, effectiveness, automation, trips, fail start

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Authors: Anna Siegler

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Bullying among peers is not uncommon; however, adults can notice only a fragment of the cases of harassment during everyday life. The systemic approaches of bullying investigation put the whole school community in the focus of attention and propose that the solution should emerge from the culture of the school. Bystanders are essential in the prevention and intervention processes as an active agent rather than passive. For combating exclusion, stigmatization and harassment, it is important that the bystanders have to realize they have the power to take action. To prevent the escalation of violence, victims must believe that students and teachers will help them and their environment is able to provide safety. The study based on scientific narrative psychological approach, and focuses on the examination of the different perspectives of students, how peers are mentalizing with each other in case of bullying. The data collection contained responses of students (N = 138) from three schools in Hungary, and from three different area of the country (Budapest, Martfű and Barcs). The test battery include Bullying Prevalence Questionnaire, Interpersonal Reactivity Index and an instruction to get narratives about bullying, which effectiveness was tested during a pilot test. The obtained results are in line with the findings of previous bullying research: the victims are mentalizing less with their peers and experience greater personal distress when they are in identity threatening situations, thus focusing on their own difficulties rather than social signals. This isolation is an adaptive response in short-term although it seems to lead to a deficit in social skills later in life and makes it difficult for students to become socially integrated to society. In addition the results also show that students use more mental state attribution when they report verbal bullying than in case of physical abuse. Those who witness physical harassment also witness concrete answers to the problem from teachers, in contrast verbal abuse often stays without consequences. According to the results students mentalizing more in these stories because they have less normative explanation to what happened. To expanding bullying literature, this research helps to find ways to reduce school violence through community development.

Keywords: bullying, mentalization, narrative, school culture

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Authors: Mohammad Syed Ali Molla, Mohammed Azim, Mohammad Esharuzzaman

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Centrifugal-casting machine is used in manufacturing special machine components like multi-layer journal bearing used in all internal combustion engine, steam, gas turbine and air craft turboengine where isotropic properties and high precisions are desired. Moreover, this machine can be used in manufacturing thin wall hightech machine components like cylinder liners and piston rings of IC engine and other machine parts like sleeves, and bushes. Heavy-duty machine component like railway wheel can also be prepared by centrifugal casting. A lot of technological developments are required in casting process for production of good casted machine body and machine parts. Usually defects like blowholes, surface roughness, chilled surface etc. are found in sand casted machine parts. But these can be removed by centrifugal casting machine using rotating metallic die. Moreover, die rotation, its temperature control, and good pouring practice can contribute to the quality of casting because of the fact that the soundness of a casting in large part depends upon how the metal enters into the mold or dies and solidifies. Poor pouring practice leads to variety of casting defects such as temperature loss, low quality casting, excessive turbulence, over pouring etc. Besides these, handling of molten metal is very unsecured and dangerous for the workers. In order to get rid of all these problems, the need of an automatic pouring device arises. In this research work, a robot assisted pouring device and a centrifugal casting machine are designed, developed constructed and tested experimentally which are found to work satisfactorily. The robot assisted pouring device is further modified and developed for using it in actual metal casting process. Lot of settings and tests are required to control the system and ultimately it can be used in automation of centrifugal casting machine to produce high-tech machine parts with desired precision.

Keywords: bearing, centrifugal casting, cylinder liners, robot

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Authors: S. K. Thind, Aparjot Kaur

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Heat stress is one of the major environmental factors drastically reducing wheat production. Crop heat tolerance can be enhanced by preconditioning of plants by exogenous application of osmoprotectants. Presently, the effect of trehalose pretreatment (at 1 mM, and 1.5 nM) under heat stress of 35±2˚C (moderate) and 40±2˚ (severe) for four and eight hour was conducted in wheat (Tricticum aestivum L.) genotypes viz. HD2967, PBW 175, PBW 343, PBW 621, and PBW 590. Heat stress affects wide spectrum of physiological processes within plants that are irreversibly damaged by stress. Membrane thermal stability (MTS) and cell viability was significantly decreased under heat stress for eight hours. Pretreatment with trehalose improved MTS and cell viability under stress and this effect was more promotory with higher concentration. Thermal stability of photosynthetic apparatus differed markedly between genotypes and Hill reaction activity was recorded more in PBW621 followed by C306 as compared with others. In all genotypes photolysis of water showed decline with increase in temperature stress. Trehalose pretreatment helped in sustaining Hill reaction activity probably by stabilizing the photosynthetic apparatus against heat-induced photo inhibition. Both plant growth and development were affected by temperature in both shoot and root under heat stress. The reduction was compensated partially by trehalose (1.5 mM) application. Adaption to heat stress is associated with the metabolic adjustment which led to accumulation of soluble sugars including non-reducing and reducing for their role in adaptive mechanism. Higher acid invertase activity in shoot of tolerant genotypes appeared to be a characteristic for stress tolerance. As sucrose synthase play central role in sink strength and in studied wheat genotype was positively related to dry matter accumulation. The duration of heat stress for eight hours had more severe effect on these parameters and trehalose application at 1.5 mM ameliorated it to certain extent.

Keywords: heat stress, Triticum aestivum, trehalose, membrane thermal stability, triphenyl tetrazolium chloride, reduction test, growth, sugar metabolism

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Authors: Sungho Kim, Jaechoul Shin, Yujin Baek, Nakseok Kim, Kyungnam Kim, Shinhaeng Jo

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The climate change and increase in heavy traffic have been accelerating damages that cause the problems such as pothole on asphalt pavement. Pothole causes traffic accidents, vehicle damages, road casualties and traffic congestion. A quick and efficient maintenance method is needed because pothole is caused by stripping and accelerates pavement distress. In this study, we propose a rapid and systematic pothole management by developing a pothole automated repairing equipment including a volume measurement system of pothole. Three kinds of cold mix asphalt mixture were investigated to select repair materials. The materials were evaluated for satisfaction with quality standard and applicability to automated equipment. The volume measurement system of potholes was composed of multi-sensor that are combined with laser sensor and ultrasonic sensor and installed in front and side of the automated repair equipment. An algorithm was proposed to calculate the amount of repair material according to the measured pothole volume, and the system for releasing the correct amount of material was developed. Field test results showed that the loss of repair material amount could be reduced from approximately 20% to 6% per one point of pothole. Pothole rapid automated repair equipment will contribute to improvement on quality and efficient and economical maintenance by not only reducing materials and resources but also calculating appropriate materials. Through field application, it is possible to improve the accuracy of pothole volume measurement, to correct the calculation of material amount, and to manage the pothole data of roads, thereby enabling more efficient pavement maintenance management. Acknowledgment: The author would like to thank the MOLIT(Ministry of Land, Infrastructure, and Transport). This work was carried out through the project funded by the MOLIT. The project name is 'development of 20mm grade for road surface detecting roadway condition and rapid detection automation system for removal of pothole'.

Keywords: automated equipment, management, multi-beam sensor, pothole

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Authors: Sakshi Chopra, Harsimarpreet Kaur, Ashima Nehra

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Objectives: Malingering is fabricating or exaggerating the symptoms of mental or physical disorders for a variety of secondary gains or motives, which may include financial compensation; avoiding work; getting lighter criminal sentences; or simply to attract attention or sympathy. Malingering is different from somatization disorder and factitious disorder. The prevalence of malingering is unknown and difficult to determine. In an estimated study in forensic population, it can reach up to 17% cases. But the accuracy of such estimates is questionable as successful malingerers are not detected and thus, not included. Methods: The case study of a 58 years old, right handed, graduate, pre-morbidly working in a national company with reported history of stroke leading to head injury; cerebral infarction/facial palsy and dementia. He was referred for disability certification so that his job position can be transferred to his son as he could not work anymore. A series of Neuropsychological tests were administered. Results: With a mental age of < 2.5 years; social adaptive functioning was overall < 20 showing profound Mental Retardation, less than 1 year social age in abilities of self-help, eating, dressing, locomotion, occupation, communication, self-direction, and socialization; severely impaired verbal and performance ability, 96% impairment in Activities of Daily Living, with an indication of very severe depression. With inconsistent and fluctuating medical findings and problem descriptions to different health professionals forming the board for his disability, it was concluded that this patient was malingering. Conclusions: Even though it can be easily defined, malingering can be very challenging to diagnosis. Cases of malingering impose a substantial economic burden on the health care system and false attribution of malingering imposes a substantial burden of suffering on a significant proportion of the patient population. Timely, tactful diagnosis and management can help ease this patient burden on the healthcare system. Malingering can be detected by only trained mental health professionals in the clinical setting.

Keywords: disability, India, malingering, neuropsychological assessment

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Authors: Il Ho Park, Joong Seob Lee, Sung Hun Kang, Jae-Min Shin, Il Seok Park, Seok Min Hong, Seok Jin Hong

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Introduction: The human microbiota is the aggregate of microorganisms, and the bacterial microbiome of the human digestive tract contributes to both health and disease. In health, bacteria are key components in the development of mucosal barrier function and in innate and adaptive immune responses, and they also work to suppress the establishment of pathogens. In human upper airway, the sinonasal microbiota might play an important role in chronic rhinosinusitis (CRS). The purpose of this study is to investigate the human upper airway microbiome in CRS patients and to compare the sinonasal microbiome of adults with children. Materials and methods: A total of 19 samples from 19 patients (Group1; 9 CRS in children, aged 5 to 14 years versus Group 2; 10 CRS in adults aged 21 to 59 years) were examined. Swabs were collected from the middle meatus and/or anterior ethmoid region under general anesthesia during endoscopic sinus surgery or tonsillectomy. After DNA extraction from swab samples, we analysed bacterial microbiome consortia using 16s rRNA gene sequencing approach (the Illumina MiSeq platform). Results: In this study, relatively abundance of the six bacterial phyla and tremendous genus and species found in substantial amounts in the individual sinus swab samples, include Corynebacterium, Hemophilus, Moraxella, and Streptococcus species. Anaerobes like Fusobacterium and Bacteroides were abundantly present in the children group, Bacteroides and Propionibacterium were present in adults group. In genus, Haemophilus was the most common CRS microbiome in children and Corynebacterium was the most common CRS microbiome in adults. Conclusions: Our results show the diversity of human upper airway microbiome, and the findings will suggest that CRS is a polymicrobial infection. The Corynebacterium and Hemophilus may live as commensals on mucosal surfaces of sinus in the upper respiratory tract. The further study will be needed for analysis of microbiome-human interactions in upper airway and CRS.

Keywords: microbiome, upper airway, chronic rhinosinusitis, adult and children

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Authors: Luisa Cabezas, Karol Leal, Harold Mendoza, Fabio Trochez, Angel Lozada

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According to the 2030 Agenda for Sustainable Development Goals (SDG) in which equal importance is given to economic, social, and environmental dimensions where the equality and dignity of each human person is placed at the center of discussion, changing the development concept for one with more responsibility with the environment. It can be found that the energy and food systems are deeply entangled, and they are transversal to the 17 proposed SDG. In this order of ideas, a research project is carried out at Unidad Central del Valle del Cauca (UCEVA) with these two systems in mind, on one hand the energy transition and, on the other hand the transformation of agri-food systems. This project it could be achieved by automation and control irrigation system of medicinal, aromatic, and condimentary plants (MACP) area within the UCEVA Agroecological Farm and located in rural area of Tulua municipality (Valle del Cauca Department, Colombia). This system have allowed to stablish a remote monitoring of MACP area, including MACP moisture measurement, and execute the required system actions. In addition, the electrical system of irrigation control system is powered by a scalable photovoltaic solar energy system based on its specifications. Thus, the developed system automates and control de irrigation system, which is energetically self-sustainable and allows to satisfy the MACP area requirements. Is important to highlight that at MACP area, several medicinal, aromatic, and condimentary plants species are preserved to become primary sources for the pharmaceutical industry and, in many occasions, the only medicines for many communities. Therefore, preserve medicinal plants area would generates medicinal security and preserve cultural heritage as these plants are part of ancestral knowledge that penetrate academic and research communities at UCEVA campus to other society sectors.

Keywords: ancestral knowledge, climate change, medicinal plants, solar energy

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Authors: Dylan Santos De Pinho, Arnaud Gay De Combes, Matthieu Steuhlet, Claude Jeannerat, Nabil Ouerhani

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The Industry 4.0 initiative has been launched to address huge challenges related to ever-smaller batch sizes. The end-user need for highly customized products requires highly adaptive production systems in order to keep the same efficiency of shop floors. Most of the classical Software solutions that operate the manufacturing processes in a shop floor are based on rigid Manufacturing Execution Systems (MES), which are not capable to adapt the production order on the fly depending on changing demands and or conditions. In this paper, we present a highly modular and flexible solution to orchestrate a set of production systems composed of a micro-milling machine-tool, a polishing station, a cleaning station, a part inspection station, and a rough material store. The different stations are installed according to a novel matrix configuration of a 3x3 vertical shelf. The different cells of the shelf are connected through horizontal and vertical rails on which a set of shuttles circulate to transport the machined parts from a station to another. Our software solution for orchestrating the tasks of each station is based on a Multi-Agent System. Each station and each shuttle is operated by an autonomous agent. All agents communicate with a central agent that holds all the information about the manufacturing order. The core innovation of this paper lies in the path planning of the different shuttles with two major objectives: 1) reduce the waiting time of stations and thus reduce the cycle time of the entire part, and 2) reduce the disturbances like vibration generated by the shuttles, which highly impacts the manufacturing process and thus the quality of the final part. Simulation results show that the cycle time of the parts is reduced by up to 50% compared with MES operated linear production lines while the disturbance is systematically avoided for the critical stations like the milling machine-tool.

Keywords: multi-agent systems, micro-manufacturing, flexible manufacturing, transfer systems

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Authors: Muhammad Awais Afzal, Lorena Tuchscherr De Hauschopp, Christian Hübner

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Introduction: Autophagy is an evolutionarily conserved lysosome-dependent degradation pathway, which can be induced by extrinsic and intrinsic stressors in living systems to adapt to fluctuating environmental conditions. In the context of inflammatory stress, autophagy contributes to the elimination of invading pathogens, the regulation of innate and adaptive immune mechanisms, and regulation of inflammasome activity as well as tissue damage repair. Lysosomes can be recycled from autolysosomes by the process of autophagic lysosome reformation (ALR), which depends on the presence of several proteins including Spatacsin. Thus ALR contributes to the replenishment of lysosomes that are available for fusion with autophagosomes in situations of increased autophagic turnover, e.g., during bacterial infections, inflammatory stress or sepsis. Objectives: We aimed to assess whether ALR plays a role for cell survival in an in-vitro bacterial infection model. Methods: Mouse embryonic fibroblasts (MEFs) were isolated from wild-type mice and Spatacsin (Spg11-/-) knockout mice. Wild-type MEFs and Spg11-/- MEFs were infected with Staphylococcus aureus (multiplication of infection (MOI) used was 10). After 8 and 16 hours of infection, cell viability was assessed on BD flow cytometer through propidium iodide intake. Bacterial intake by cells was also calculated by plating cell lysates on blood agar plates. Results: in-vitro infection of MEFs with Staphylococcus aureus showed a marked decrease of cell viability in ALR deficient Spatacsin knockout (Spg11-/-) MEFs after 16 hours of infection as compared to wild-type MEFs (n=3 independent experiments; p < 0.0001) although no difference was observed for bacterial intake by both genotypes. Conclusion: Suggesting that ALR is important for the defense of invading pathogens e.g. S. aureus, we observed a marked increase of cell death in an in-vitro infection model in cells with compromised ALR.

Keywords: autophagy, autophagic lysosome reformation, bacterial infections, Staphylococcus aureus

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Authors: G. Lambe, D. Mansukhani, A. Shetty, S. Khodaiji, C. Rodrigues, F. Kapadia

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Introduction: Sepsis is known to cause impairment of both innate and adaptive immunity and involves an early uncontrolled inflammatory response, followed by a protracting immunosuppression phase, which includes decreased expression of cell receptors, T cell anergy and exhaustion, impaired cytokine production, which may cause high risk for secondary infections due to reduced response to antigens. Although human cytomegalovirus (CMV) is widely recognized as a serious viral pathogen in sepsis and immunocompromised patients, the incidence of CMV reactivation in patients with sepsis lacking strong evidence of immunosuppression is not well defined. Therefore, it is important to determine an association between CMV reactivation and sepsis-induced immunosuppression. Aim: To determine the association between incidence of CMV reactivation and immune modulation in sepsis-induced immunosuppression with time. Material and Methods: Ten CMV-seropositive adult patients with severe sepsis were included in this study. Blood samples were collected on Day 0, and further weekly up to 21 days. CMV load was quantified by real-time PCR using plasma. The expression of immunosuppression markers, namely, HLA-DR, PD-1, and regulatory T cells, were determined by flow cytometry using whole blood. Results: At Day 0, no CMV reactivation was observed in 6/10 patients. In these patients, the median length for reactivation was 14 days (range, 7-14 days). The remaining four patients, at Day 0, had a mean viral load of 1802+2599 copies/ml, which increased with time. At Day 21, the mean viral load for all 10 patients was 60949+179700 copies/ml, indicating that viremia increased with the length of stay in the hospital. HLA-DR expression on monocytes significantly increased from Day 0 to Day 7 (p = 0.001), following which no significant change was observed until Day 21, for all patients except 3. In these three patients, HLA-DR expression on monocytes showed a decrease at elevated viral load (>5000 copies/ml), indicating immune suppression. However, the other markers, PD-1 and regulatory T cells, did not show any significant changes. Conclusion: These preliminary findings suggest that CMV reactivation can occur in patients with severe sepsis. In fact, the viral load continued to increase with the length of stay in the hospital. Immune suppression, indicated by decreased expression of HLA-DR alone, was observed in three patients with elevated viral load.

Keywords: CMV reactivation, immune suppression, sepsis immune modulation, CMV viral load

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Authors: Dorottya Horváth, Andras Lang, Diana Varro-Horvath

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This research activity and study is part of a major research effort to gain an integrative, neuropsychological, and personality psychological understanding of Attention Deficit Hyperactivity Disorder (ADHD) and thus improve the specification of diagnostic and therapeutic care. In the past, the neuropsychology section has investigated working memory, executive function, attention, and behavioural manifestations in children. Currently, we are looking for personality psychological protective factors for ADHD and its symptomatic exacerbation. We hypothesise that secure attachment, adaptive emotion regulation, and high resilience are protective factors. The aim of this study is to measure and report the results of a Hungarian sample of the Cognitive Emotion Regulation Questionnaire for Children (CERQ-k) because before studying groups with different developmental differences, it is essential to know the average scores of groups with neurotypical devel-opment. Until now, there was no Hungarian version of the above test, so we used our own translation. This questionnaire has been developed to assess children's thoughts after experiencing negative life events. It consists of 4-4 items per subscale, for a total of 36 items. The response categories for each item range from 1 (almost never) to 5 (almost always). The subscales were self-blame, blaming others, acceptance, planning, positive refocusing, rumination or thought-focusing, positive reappraisal, putting into perspective, and catastrophizing. The data for this study were collected from 120 children aged 9-14 years. It was analysed using descriptive statistical analysis, where the mean and standard deviation values for each age group, as well as the Cronbach's alpha value, were significant in testing the reliability of the questionnaire. The results showed that the questionnaire is a reliable and valid measuring instrument also on a Hungarian sample. These developments and results will allow the use of a version of the Cognitive Emotion Regulation Questionnaire for children in Hungarian and pave the way for the study of different developmental groups such as children with learning disabilities and/or with ADHD.

Keywords: neurotypical development, emotion regulation, negative life events, CERQ-k, Hungarian average scores

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Authors: Jolanta Uszko, Tomasz Wloch, Aneta Pirowska, Roman Nowobilski

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Introduction: Phantom phenomena are often reported by subjects who have undergone limb amputation. Mostly, patients feel the amputated part of the limb as if it was still attached to the body. Two types of phantom phenomena: painless (phantom sensation) and painful (phantom pain) were described. Triggers of phantom sensations and phantom pain, as well as fully effective treatment, have not been clearly described yet. Purpose: To assess the influence of psychosocial factors and some clinical conditions on the occurrence of phantom phenomena in amputee athletes. Subjects: 21 men (age: 31 years, SD = 7.5 years) after lower or upper extremity amputation, who regularly performed high-intensity sports (Amp Football Team Players) were included to the study. Method and equipment: In the research, the following method and tools were used: Questionnaire [Pirowska] adapted for athletes with disabilities, Numerical Rating Scale (NRS) - for phantom pain assessment, McGill Pain Assessment Questionnaire (short version), Beck's Depression Inventory (BDI), State Trait Anxiety Inventory (STAI): X-1 and X-2, shortened version of The World Health Organization Quality of Life (WHOQOLBREFF). Results: In the study group, the lower leg amputations with traumatic etiology were predominant. Phantom sensations were present in all subjects. Half of the respondents claimed to experience phantom sensations at least once a day, paroxysmally. There was a prevalence of phantom sensations characterized as incomplete, immobile limb. Phantom pain was reported by over 85% of respondents. The nature of phantom pain was frequently described as stabbing, squeezing, shooting, pulsing, tiring. There was a significant correlation between phantom pain intensity and anxiety, quality of life, depressive tendencies, perception of phantom pain as the obstacle in daily functioning and intensity of the limb pain before amputation. Conclusions: The etiology of phantom phenomena is complex. Psychological factors seem to have a significant influence on the intensity of the phantom pain. Particular attention should be paid to patients who complain about persistent limb pain before the amputation. These are patients with an increased risk of the phantom pain of relatively high intensity.

Keywords: amputation, phantom pain, phantom sensations, adaptive sports

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Authors: Balkibekova Venera Serikpaevna

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Background: Autism Spectrum Disorder (ASD) poses significant challenges in both diagnosis and treatment. Existing therapeutic interventions often target specific symptoms, necessitating the exploration of alternative approaches. This study investigates the RITM (Rhythm Integration Tapping Music) developed by Balkibekova, aiming to create imitation, social engagement and a wide range of emotions through brain development. Methods: A randomized controlled trial was conducted with 100 participants diagnosed with ASD, aged 1 to 4 years. Participants were randomly assigned to either the RITM therapy group or a control group receiving standard care. The RITM therapy, rooted in tapping rhythm to music such as: marche on the drums, waltz on bells, lullaby on musical triangle, dancing on tambourine, polka on wooden spoons. Therapy sessions were conducted over a 3 year period, with assessments at baseline, midpoint, and post-intervention. Results: Preliminary analyses reveal promising outcomes in the RITM therapy group. Participants demonstrated significant improvements in social interactions, speech understanding, birth of speech, and adaptive behaviors compared to the control group. Careful examination of subgroup analyses provides insights into the differential effectiveness of the RITM approach across various ASD profiles. Conclusions: The findings suggest that RITM therapy, as developed by Balkibekova, holds promise as intervention for ASD. The integrative nature of the approach, addressing multiple domains simultaneously, may contribute to its efficacy. Further research is warranted to validate these preliminary results and explore the long-term impact of RITM therapy on individuals with ASD. This abstract presents a snapshot of the research, emphasizing the significance, methodology, key findings, and implications of the RITM therapy method for consideration in an autism conference.

Keywords: RITM therapy, tapping rhythm, autism, mirror neurons, bright emotions, social interactions, communications

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Authors: Thapa M., J.P. Dutta, K.R. Pandey, R.R. Kattel

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Nepal is extremely vulnerable to the impact of climate change. To mitigate the climate change effects on agricultural production and productivity a range of adaptive strategies needs to be considered. The study was conducted to assess organic paddy production as a coping strategy to the adverse impact of climate change in Phulbari, VDC of Chitwan district. Altogether, 120 respondents (60 adopters of organic farming and 60 from non adopter) were selected using snowball technique of sampling. Pre- tested interview schedule, direct observation, focus group discussion, key informant interview as well as secondary data were used to collect the required information. Factors determining the adoption of organic farming were found to be age, year of schooling, training, frequency of extension contact, perception about climate change, economically active members and poor. A unit increase in these factors except poor would increase the probability of adoption by 4.1%, 7.5%, 7.8%, 43.1%, 41.8% and 7% respectively. However, for poor, it would decrease the probability of adoption of organic farming by 5.1%. Average organic matter content in the adopters' field was higher (2.7%) than the non-adopters' field (2.5%). The regression result showed that type of farmer, price and area under rice cultivation had positive and significant relationship with income; however dependency ratio had negative relationship. As the year of adoption of organic farming increases, the production of rice decline in the first two years then after goes on increasing but the cost of production goes on decreasing with the year of adoption. The respondents adapted to the changing climate through diversification of crops, use of resistance varieties and following good cropping pattern. Gradually growing consumers' awareness about health, preference towards quality food products are the strong points behind organic farming, whereas lacks of bio-fertilizers, lack of effective extension services, no price differentiation between organic and inorganic products were the weak points. There is need for more training and education to change the attitude of farmers and enhance their confidence about the role of organic farming to cope with climate change impact.

Keywords: Organic farming, climate change, sustainable development

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Authors: Amna Khaliq

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In this research paper, a comparison study has been undertaken between Canada and Denmark to analyze the education system between the countries in entrepreneurship. Denmark, a land of high wages and high taxes, and Canada, a land of immigrants and opportunities, have seen a positive relationship in entrepreneurs' growth. They are both considered one of the top ten countries to start a business and to have government support globally. However, education is entirely free to Danish students, including university degrees, compared to Canadians, which can further hurdle for Canadian millennials to grow in the business world—the business experience more growth with educated entrepreneurs with international backgrounds in new immigrants. Denmark has seen a gradual increase in female entrepreneurs over the decade but is still lower than OECD countries. Compassionate management and work-life balance are prioritized in Denmark, unlike in Canada. Danish are early adopters of technology and have excellent infrastructure to support the technology industry, whereas Canada is still a service-oriented and manufacturer-based country. 2018 has been the highest number of opening businesses for Canada and Denmark. Some companies offer high wages, hiring bonuses, flexible working hours, wellness, and mental health benefits during Pandemic to keep the companies running and keep their workers' morale high. Pandemic has taught consumers new patterns to shop online. It is essential now to use technology and automation to increase productivity in businesses. Only those companies will survive that are applying this strategy. The Pandemic has ultimately changed entrepreneurs' and employees' behavior in the business world. Along with Ph.D. professors, entrepreneurs should be allowed to teach at learning intuitions. Millennials turn out to be the most entrepreneurial generation in both countries. Entrepreneurship education will only be beneficial when students create businesses and learn from real-life experiences. Managing physical, mental, emotional, and psychological health while dealing with high pressure in entrepreneurship are soft skills learned through practical work.

Keywords: entrepreneurship education, millennials, pandemic, Denmark, Canada

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