Search results for: neural style transfer

Authors: Fatemeh Jannesarvatan, Ghazaal Parastooei, Jimmy frerejan, Saedeh Mokhtari, Peter Van Rosmalen

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Medical and dental education increasingly emphasizes the acquisition, integration, and coordination of complex knowledge, skills, and attitudes that can be applied in practical situations. Instructional design approaches have focused on using real-life tasks in order to facilitate complex learning in both real and simulated environments. The Four component instructional design (4C/ID) model has become a useful guideline for designing instructional materials that improve learning transfer, especially in health profession education. The objective of this study was to apply the 4C/ID model in the creation of virtual patients (VPs) that dental students can use to practice their clinical management and clinical reasoning skills. The study first explored the context and concept of complication factors and common errors for novices and how they can affect the design of a virtual patient program. The study then selected key dental information and considered the content needs of dental students. The design of virtual patients was based on the 4C/ID model's fundamental principles, which included: Designing learning tasks that reflect real patient scenarios and applying different levels of task complexity to challenge students to apply their knowledge and skills in different contexts. Creating varied learning materials that support students during the VP program and are closely integrated with the learning tasks and students' curricula. Cognitive feedback was provided at different levels of the program. Providing procedural information where students followed a step-by-step process from history taking to writing a comprehensive treatment plan. Four virtual patients were designed using the 4C/ID model's principles, and an experimental design was used to test the effectiveness of the principles in achieving the intended educational outcomes. The 4C/ID model provides an effective framework for designing engaging and successful virtual patients that support the transfer of knowledge and skills for dental students. However, there are some challenges and pitfalls that instructional designers should take into account when developing these educational tools.

Keywords: 4C/ID model, virtual patients, education, dental, instructional design

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Authors: P. W. Tsai, W. L. Hong, C. W. Chen, C. Y. Chen

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In this paper, we present a neural network (NN) based approach represent a nonlinear Tagagi-Sugeno (T-S) system. A linear differential inclusion (LDI) state-space representation is utilized to deal with the NN models. Taking advantage of the LDI representation, the stability conditions and controller design are derived for a class of nonlinear structural systems. Moreover, the concept of utilizing the Parallel Particle Swarm Optimization (PPSO) algorithm to solve the common P matrix under the stability criteria is given in this paper.

Keywords: Lyapunov stability, parallel particle swarm optimization, linear differential inclusion, artificial intelligence

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Authors: Uwalomwa Uwuigbe, Olubukola Ranti Uwuigbe, Jinadu Olugbenga, Otekunrin Adegbola

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Corporate reporting has evolved over the years resulting from criticisms of the precedent by shareholders, stakeholders and other relevant financial institutions. Integrated reporting has become a globalized corporate reporting style, with its adoption around the world occurring rapidly to bring about an improvement in the quality of corporate reporting. While some countries have swiftly clinched into reporting in an integrated manner, others have not. In addition, there are ample research that has been conducted on the benefits of adopting integrated reporting, however, the same is not true in developing economies like Nigeria. Hence, this study basically examined the factors determining the adoption of integrated reporting in Nigeria. One hundred (100) copies of questionnaire was administered to financial managers of 20 selected listed companies in the Nigeria stock exchange market. The data obtained was analysed using the Spearman Rank Order Correlation via the Statistical Package for Social Science. This study observed that there is a significant relationship between the social pressures of isomorphic changes and integrated reporting adoption in Nigeria. The study recommends the need for an enforcement mechanism to be put in place while considering the adoption of integrated reporting in Nigeria, enforcement mechanisms should put into consideration the investors demand, the level of economic development, and the degree of corporate social responsibility.

Keywords: corporate social responsibility, isomorphic, integrated reporting, Nigeria, sustainability

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Authors: Nihan Akdemir

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Clothes are more than a piece of fabric, and the most visible material item of the fashion symbol is the garment, which carries multiple and various meanings. The dynamism of the clothing symbol can carry open or closed codes depending on culture, gender, and social location. And each one can be the expression of social identity over ethnicity, religious beliefs, age, education and social class. Through observation of clothing styles over these items, the assumptions could be made about a person’s identity. A distinctive and typical style, form or character of the clothing such as ‘zoot suits’, ‘ao dai’, removes the garment from functional and ordinary element to the symbolic area. Clothing is an 'identification' tool that functions in determining the symbolic boundaries between people in a sense. And this paper includes the investigation of the relation between social identity and clothing and also fashion. And this relationship has been taken into consideration over the visual expression because even during the ancient times, the clothes were the basic and simple way of representing the identity and social classes. The visible expression of identity over clothing from Ancient Egypt to today’s clothing and fashion has been researched in this article. And all these items have been explained with visual images and supported by the literature investigations. Then the results have shown that every piece of clothing from fabric to coloring have visual significations about social identity.

Keywords: social identity, clothing, fashion, visual expression, visual signification

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Authors: Bharath R., Tharun Sai N., Bhuvan G.

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This project focuses on developing a Parallel Computing method aimed at optimizing matrix multiplication through GPU acceleration. Addressing algorithmic challenges, GPU programming intricacies, and integration issues, the project aims to enhance efficiency and scalability. The methodology involves algorithm design, GPU programming, and optimization techniques. Future plans include advanced optimizations, extended functionality, and integration with high-level frameworks. User engagement is emphasized through user-friendly interfaces, open- source collaboration, and continuous refinement based on feedback. The project's impact extends to significantly improving matrix multiplication performance in scientific computing and machine learning applications.

Keywords: matrix multiplication, parallel processing, cuda, performance boost, neural networks

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Authors: Vidhi Jain

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Communication between speakers and non-speakers of American Sign Language (ASL) can be problematic, inconvenient, and expensive. This project attempts to bridge the communication gap by designing a portable glove that captures the user’s ASL gestures and outputs the translated text on a smartphone. The glove is equipped with flex sensors, contact sensors, and a gyroscope to measure the flexion of the fingers, the contact between fingers, and the rotation of the hand. The glove’s Arduino UNO microcontroller analyzes the sensor readings to identify the gesture from a library of learned gestures. The Bluetooth module transmits the gesture to a smartphone. Using this device, one day speakers of ASL may be able to communicate with others in an affordable and convenient way.

Keywords: sign language, morse code, convolutional neural network, American sign language, gesture recognition

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Authors: Sushil Kumar Gupta, Atharva Joshi, Ayush Sonawale, Sachin Naik, Rajshree Khande

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The usage of artificially created videos and audio by deep learning is a major problem of the current media landscape, as it pursues the goal of misinformation and distrust. In conclusion, the objective of this work targets generating a reliable deepfake detection model using deep learning that will help detect forged videos accurately. In this work, CelebDF v1, one of the largest deepfake benchmark datasets in the literature, is adopted to train and test the proposed models. The data includes authentic and synthetic videos of high quality, therefore allowing an assessment of the model’s performance against realistic distortions.

Keywords: deepfake detection, CelebDF v1, convolutional neural network (CNN), xception model, data augmentation, media manipulation

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Authors: Ardiansyah I. Ryan, Ashsholih K. R., Fathurrohman G. R., Kurniadi M. R., Huda P. A

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The burden of brain-related disease is very high. There are a lot of brain-related diseases with limited treatment result and thus raise the burden more. The Parkinson Disease (PD), Mental Health Problem, or Paralysis of extremities treatments had risen concern, as the patients for those diseases usually had a low quality of life and low chance to recover fully. There are also many other brain or related neural diseases with the similar condition, mainly the treatments for those conditions are still limited as our understanding of the brain function is insufficient. Brain Implant Technology had given hope to help in treating this condition. In this paper, we examine the current update of the brain implant technology. Neurotechnology is growing very rapidly worldwide. The United States Food and Drug Administration (FDA) has approved the use of Deep Brain Stimulation (DBS) as a brain implant in humans. As for neural implant both the cochlear implant and retinal implant are approved by FDA too. All of them had shown a promising result. DBS worked by stimulating a specific region in the brain with electricity. This device is planted surgically into a very specific region of the brain. This device consists of 3 main parts: Lead (thin wire inserted into the brain), neurostimulator (pacemaker-like device, planted surgically in the chest) and an external controller (to turn on/off the device by patient/programmer). FDA had approved DBS for the treatment of PD, Pain Management, Epilepsy and Obsessive Compulsive Disorder (OCD). The target treatment of DBS in PD is to reduce the tremor and dystonia symptoms. DBS has been showing the promising result in animal and limited human trial for other conditions such as Alzheimer, Mental Health Problem (Major Depression, Tourette Syndrome), etc. Every surgery has risks of complications, although in DBS the chance is very low. DBS itself had a very satisfying result as long as the subject criteria to be implanted this device based on indication and strictly selection. Other than DBS, there are several brain implant devices that still under development. It was included (not limited to) implant to treat paralysis (In Spinal Cord Injury/Amyotrophic Lateral Sclerosis), enhance brain memory, reduce obesity, treat mental health problem and treat epilepsy. The potential of neurotechnology is unlimited. When brain function and brain implant were fully developed, it may be one of the major breakthroughs in human history like when human find ‘fire’ for the first time. Support from every sector for further research is very needed to develop and unveil the true potential of this technology.

Keywords: brain implant, deep brain stimulation (DBS), deep brain stimulation, Parkinson

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Authors: Bagher Bayat, Wouter Verhoef, Behnaz Arabi, Christiaan Van der Tol

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The aim of this study was to follow the canopy reflectance patterns in response to soil water deficit and to detect trends of changes in biophysical and biochemical parameters of grass (Poa pratensis species). We used visual interpretation, imaging spectroscopy and radiative transfer model inversion to monitor the gradual manifestation of water stress effects in a laboratory setting. Plots of 21 cm x 14.5 cm surface area with Poa pratensis plants that formed a closed canopy were subjected to water stress for 50 days. In a regular weekly schedule, canopy reflectance was measured. In addition, Leaf Area Index (LAI), Chlorophyll (a+b) content (Cab) and Leaf Water Content (Cw) were measured at regular time intervals. The 1-D bidirectional canopy reflectance model SAIL, coupled with the leaf optical properties model PROSPECT, was inverted using hyperspectral measurements by means of an iterative optimization method to retrieve vegetation biophysical and biochemical parameters. The relationships between retrieved LAI, Cab, Cw, and Cs (Senescent material) with soil moisture content were established in two separated groups; stress and non-stressed. To differentiate the water stress condition from the non-stressed condition, a threshold was defined that was based on the laboratory produced Soil Water Characteristic (SWC) curve. All parameters retrieved by model inversion using canopy spectral data showed good correlation with soil water content in the water stress condition. These parameters co-varied with soil moisture content under the stress condition (Chl: R2= 0.91, Cw: R2= 0.97, Cs: R2= 0.88 and LAI: R2=0.48) at the canopy level. To validate the results, the relationship between vegetation parameters that were measured in the laboratory and soil moisture content was established. The results were totally in agreement with the modeling outputs and confirmed the results produced by radiative transfer model inversion and spectroscopy. Since water stress changes all parts of the spectrum, we concluded that analysis of the reflectance spectrum in the VIS-NIR-MIR region is a promising tool for monitoring water stress impacts on vegetation.

Keywords: hyperspectral remote sensing, model inversion, vegetation responses, water stress

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Authors: C. Mayr, J. Periya, A. Kariminezhad

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In this paper, we developed a learning framework for the classification of vulnerable road users (VRU) by their range-Doppler signatures. The frequency-modulated continuous-wave (FMCW) radar raw data is first pre-processed to obtain robust object range-Doppler maps per coherent time interval. The complex-valued range-Doppler maps captured from our outdoor measurements are further fed into a convolutional neural network (CNN) to learn the classification. This CNN has gone through a hyperparameter optimization process for improved learning. By learning VRU range-Doppler signatures, the three classes 'pedestrian', 'dog', and 'noise' are classified with an average accuracy of almost 95%. Interestingly, this classification accuracy holds for a combined longitudinal and lateral object trajectories.

Keywords: machine learning, radar, signal processing, autonomous driving

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Authors: Seung Ho Park, Young Su Moon, Nam Ik Cho

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We propose a convolution neural network (CNN) for quality adaptive compression artifact reduction named QCARNet. The proposed method is different from the existing discriminative models that learn a specific model at a certain quality level. The method is composed of a quality estimation CNN (QECNN) and a compression artifact reduction CNN (CARCNN), which are two functionally separate CNNs. By connecting the QECNN and CARCNN, each CARCNN layer is able to adaptively reduce compression artifacts and preserve details depending on the estimated quality level map generated by the QECNN. We experimentally demonstrate that the proposed method achieves better performance compared to other state-of-the-art blind compression artifact reduction methods.

Keywords: compression artifact reduction, deblocking, image denoising, image restoration

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Authors: Ebru Thwaites Diken

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This article analyzes the works of certain directors in Danish cinema, namely Susanne Bier and Lone Sherfig, in the context of transnationalisation of Danish cinema. It looks at how the films' narratives negotiate and reconstruct the local / national / regional and the global. Scholars such as Nestingen & Elkington (2005), Hjort (2010), Higbee and Lim (2010), Bondebjerg and Redvall (2011) address transnationalism of Danish cinema in terms of production and distribution processes and how film making trascends national boundaries. This paper employs a particular understanding of transnationalism - in terms of how ideas and characters travel - to analyze how the storytelling and style has evolved to connect the national, the regional and the global on the basis of the works of these two directors. Strategies such as Hollywoodization - i.e. focus on stardom and classical narration, adhering to conventional European genre formulas, producing Danish films in English language have been identifiable strategies in Danish cinema in the period after the 2000s. Susanne Bier and Lone Scherfig are significant for employing some of these strategies simultaneously. For this reason, this article will look at how these two directors have employed these strategies and negotiated the cultural boundaries and exchanges.

Keywords: transnational cinema, danish cinema, susanne bier, lone scherfig

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Authors: Obafemi Richard Jegede

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The relationship between adults and children is pivotal for the social, emotional, and cognitive development of the latter. This paper explores the multifaceted dynamics of adult-child relationships, emphasizing their significance in fostering positive outcomes for children's well-being. It delves into dimensions such as attachment, communication, and parenting styles, addressing their impact on children's mental health and development. Furthermore, the role of supportive environments and interventions in enhancing adult-child relationships is examined. Understanding the complexities of these relationships is crucial for promoting healthy and nurturing interactions that contribute to children's holistic development. Positive interactions with caring adults promote children's self-regulation, empathy, and resilience, while negative or inconsistent relationships can lead to emotional distress and impaired social skills. Creating supportive environments that prioritize positive adult-child relationships is essential for promoting children's well-being. By comprehensively understanding the factors that shape adult-child relationships, we can better support children's development and well-being. This paper aims to provide insights into the complexities of adult-child relationships and their profound impact on children's development and overall well-being.

Keywords: impact on children's development, supportive environments and interventions, parenting style, communication between adult and children

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Authors: Devatha Kalyan Kumar, Aravindraj D., Sadathulla A.

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Big data are now rapidly expanding in all engineering and science and many other domains. The potential of large or massive data is undoubtedly significant, make sense to require new ways of thinking and learning techniques to address the various big data challenges. Machine learning is continuously unleashing its power in a wide range of applications. In this paper, the latest advances and advancements in the researches on machine learning for big data processing. First, the machine learning techniques methods in recent studies, such as deep learning, representation learning, transfer learning, active learning and distributed and parallel learning. Then focus on the challenges and possible solutions of machine learning for big data.

Keywords: active learning, big data, deep learning, machine learning

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Authors: Rosa Hendijani, Amir Ghadimi Herfeh

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Nutrition labels are diet-related health policies. They help individuals improve food-choice decisions and reduce intake of calories and unhealthy food elements, like cholesterol. However, many individuals do not pay attention to nutrition labels or fail to appropriately understand them. According to the literature, thinking and cognitive styles can have significant effects on attention to nutrition labels. According to the author's knowledge, the effect of global/local processing on attention to nutrition labels have not been previously studied. Global/local processing encourages individuals to attend to the whole/specific parts of an object and can have a significant impact on people's visual attention. In this study, this effect was examined with an experimental design using the eye-tracking technique. The research hypothesis was that individuals with local processing would pay more attention to nutrition labels, including nutrition tables and traffic lights. An experiment was designed with two conditions: global and local information processing. Forty participants were randomly assigned to either global or local conditions, and their processing style was manipulated accordingly. Results supported the hypothesis for nutrition tables but not for traffic lights.

Keywords: eye-tracking, nutrition labelling, global/local information processing, individual differences

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Authors: Parvaneh Ziviyar, Simin Armaghan

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Traditional house in Rasht contains monuments and heritage of ancestors who once lived in these houses. These houses represent the customs, culture and lifestyle of the people of Rasht and bridge the gap between modern people and their past that is being forgotten. Maintenance of the buildings and architectural heritage together with their unique architecture and climatic related construction has an important role in tourism attraction and sustainable development. The purpose of this study was to develop a new definition of vacation shacks that is different with the definition of Cultural Heritage Organization. The place to stay and visit that is rebuilt or renovated based on traditional architectural style of Rasht and yet provides modern amenities so that it would not undermine indigenous traditional sense of the house. Data collection for this study is based on review of literature and field study. Results and the statistics of this study will prove that the research hypothesis is supported and there is a correlation between traditional houses of Rasht, as tourism–accommodation place and tourist attraction. It also indicates the capability and potential of these ancient monuments in the introduction of the culture of this land, and calling people and many tourists come to visit and stay in such places.

Keywords: architecture, traditional houses, vacation shacks, tourism

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Authors: Jeh Patel, Chandrahas Paidi, Ahmed Hambaba

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Traditional methods for analyzing athlete movement often lack the detail and immediacy required for optimal training. This project aims to address this limitation by developing a Real-time human pose estimation system specifically designed to enhance athlete training across various sports. This system leverages the power of convolutional neural networks (CNNs) to provide a comprehensive and immediate analysis of an athlete’s movement patterns during training sessions. The core architecture utilizes dilated convolutions to capture crucial long-range dependencies within video frames. Combining this with the robust encoder-decoder architecture to further refine pose estimation accuracy. This capability is essential for precise joint localization across the diverse range of athletic poses encountered in different sports. Furthermore, by quantifying movement efficiency, power output, and range of motion, the system provides data-driven insights that can be used to optimize training programs. Pose estimation data analysis can also be used to develop personalized training plans that target specific weaknesses identified in an athlete’s movement patterns. To overcome the limitations posed by outdoor environments, the project employs strategies such as multi-camera configurations or depth sensing techniques. These approaches can enhance pose estimation accuracy in challenging lighting and occlusion scenarios, where pose estimation accuracy in challenging lighting and occlusion scenarios. A dataset is collected From the labs of Martin Luther King at San Jose State University. The system is evaluated through a series of tests that measure its efficiency and accuracy in real-world scenarios. Results indicate a high level of precision in recognizing different poses, substantiating the potential of this technology in practical applications. Challenges such as enhancing the system’s ability to operate in varied environmental conditions and further expanding the dataset for training were identified and discussed. Future work will refine the model’s adaptability and incorporate haptic feedback to enhance the interactivity and richness of the user experience. This project demonstrates the feasibility of an advanced pose detection model and lays the groundwork for future innovations in assistive enhancement technologies.

Keywords: computer vision, deep learning, human pose estimation, U-NET, CNN

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Authors: Nana Weng

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From 2008, Chinese Foreign Direct Investment flows to the European Union continued its rapid rise. Currently, the industrial structure adjustment in developing countries has also been placed on the international movement of factors of production. Now China economy is in an important period of transformation on industrial structure adjustment. Under the international transfer of industry background, the adjustment of industrial structure upgrading and sophistication are the key elements of a successful economic transformation. In order to achieve a virtuous cycle of foreign investment patterns and optimize the industrial structure of foreign direct investment as well, the research on the positive the role of the EU direct investment and how it impact China’s industrial structure optimization and upgrading is of great significance. In this paper, the author explained how the EU as an investment destination is different with the United States and ASEAN. Then, based on the theory of FDI and industrial structure and combining the four kinds of motives of China’s ODI in EU, this paper explained the impact mechanism which has influenced China domestic industrial structure primarily through the Transfer effect, Correlation effect and Competitive effect. On the premise that FDI activities do affect the home country’s domestic industrial structure, this paper made empirical analysis with industrial panel data. With the help of Gray Correlation Method and Limited Distributed Lags, this paper found that China/s ODI in the EU impacted the tertiary industry strongly and had a significant positive impact, particularly the manufacturing industry and the financial industry. This paper also pointed out that Chinese MNEs should realize several issues, such as pay more attention to high-tech industries so that they can make the best use of reverse technology spillover. When Chinese enterprises ‘go out,' they ought to keep in mind that domestic research and development capital contribution can make greater economic growth. Finally, based on theoretical and empirical analysis results, this paper presents the industry choice recommendations in the future of the EU direct investment, particularly through the development of the proper rational industrial policy and industrial development strategic to guide the industrial restructuring and upgrading.

Keywords: china ODI in european union, industrial structure optimization, impact mechanism, empirical analysis

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Authors: Siddhi Pedamkar, Reenu Singh

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This report is based on how a culture transforms from one era to another era in commercial space. This transformation is observed in commercial as well as residential spaces. The spaces have specific color concepts, surface detailing furniture, and function-specific layouts. But the cultural impact is very rarely seen in commercial spaces, mostly because the interior is divine by function to a large extent. Information was collected from books and research papers. A quantitative survey was conducted to understand people's perceptions about the impact of culture on design entities and how culture dictates the different types of space and their character. The survey also highlights the impact of types of interior lighting, colour schemes, and furniture types on the interior environment. The questionnaire survey helped in framing design parameters for contemporary interior design. The design parameters are used to propose design options for new-age furniture that can be used in co-working spaces. For the new and contemporary working spaces, new age design furniture, interior elements such as visual partition, semi-visual partition, lighting, and layout can be transformed by cultural changes in the working style of people and organization.

Keywords: commercial space, culture, environment, furniture, interior

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Authors: Guanqun Shi, Xueqing Zhang

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The frequent occurrence of failures in PPP projects which caused great loss has raised attention from the government as well as the concessionaire. PPPs are complex arrangements for its long operation period and multiple players. Many types of risks in PPP projects may cause the project fail. The insurance is an important tool to transfer the risks. Through a comparison and analysis of international government PPP guidelines and contracts as well as the case studies worldwide, we have identified eight main insurance principles, discussed thirteen insurance types in different stages. An overall procedure would be established to improve the practices in PPP projects.

Keywords: public private partnerships, insurance, contract, risk

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Authors: Shubham Gogri, Lucia Florescu

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Medical diagnosis and radiotherapy treatment planning using Computed Tomography (CT) rely on the quantitative accuracy and quality of the CT images. At the same time, requirements for CT imaging include reducing the radiation dose exposure to patients and minimizing scanning time. A solution to this is the sparse-view CT technique, based on a reduced number of projection views. This, however, introduces a new problem— the incomplete projection data results in lower quality of the reconstructed images. To tackle this issue, deep learning methods have been applied to enhance the quality of the sparse-view CT images. A first approach involved employing Mir-Net, a dedicated deep neural network designed for image enhancement. This showed promise, utilizing an intricate architecture comprising encoder and decoder networks, along with the incorporation of the Charbonnier Loss. However, this approach was computationally demanding. Subsequently, a specialized Generative Adversarial Network (GAN) architecture, rooted in the Pix2Pix framework, was implemented. This GAN framework involves a U-Net-based Generator and a Discriminator based on Convolutional Neural Networks. To bolster the GAN's performance, both Charbonnier and Wasserstein loss functions were introduced, collectively focusing on capturing minute details while ensuring training stability. The integration of the perceptual loss, calculated based on feature vectors extracted from the VGG16 network pretrained on the ImageNet dataset, further enhanced the network's ability to synthesize relevant images. A series of comprehensive experiments with clinical CT data were conducted, exploring various GAN loss functions, including Wasserstein, Charbonnier, and perceptual loss. The outcomes demonstrated significant image quality improvements, confirmed through pertinent metrics such as Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM) between the corrected images and the ground truth. Furthermore, learning curves and qualitative comparisons added evidence of the enhanced image quality and the network's increased stability, while preserving pixel value intensity. The experiments underscored the potential of deep learning frameworks in enhancing the visual interpretation of CT scans, achieving outcomes with SSIM values close to one and PSNR values reaching up to 76.

Keywords: generative adversarial networks, sparse view computed tomography, CT image correction, Mir-Net

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Authors: N. Zerzouri, N. Benalia, N. Bensiali

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This work is devoted to an analysis of the operation of a doubly fed induction generator (DFIG) integrated with a wind system. The power transfer between the stator and the network is carried out by acting on the rotor via a bidirectional signal converter. The analysis is devoted to the study of a fault in the converter due to an interruption of the control of a semiconductor. Simulation results obtained by the MATLAB/Simulink software illustrate the quality of the power generated at the default.

Keywords: doubly fed induction generator (DFIG), wind energy, PWM inverter, modeling

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Authors: Bert Seither

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Entrepreneurship is a critical driver of economic growth, especially in emerging regions such as Latin America. This study investigates how parental influences, particularly parental individual entrepreneurial orientation (IEO), shape the entrepreneurial traits of Latin American entrepreneurs. By examining key factors like parental IEO, work ethic, parenting style, and family support, this research assesses how much of an entrepreneur's own IEO can be attributed to parental influence. The study also explores how socio-economic status and cultural context moderate the relationship between parental traits and entrepreneurial orientation. Data will be collected from 600 Latin American entrepreneurs via an online survey. This research aims to provide a comprehensive understanding of the intergenerational transmission of entrepreneurial traits and the broader socio-cultural factors that contribute to entrepreneurial success in diverse contexts. Findings from this study will offer valuable insights for policymakers, educators, and business leaders on fostering entrepreneurship across Latin America, providing practical applications for shaping entrepreneurial behavior through family influences.

Keywords: entrepreneurial orientation, parental influence, Latin American entrepreneurs, socio-economic status, cultural context

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Authors: Tara Chanady

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Through 21 walking interviews with women from various backgrounds and positionalities, this study examines issues of identity politics in Montreal’s sociocultural space. The research looks at the social, political and economical implications of claiming or refusing identifications amongst women of sexual diversity (e.g. defining as lesbian, queer, bi, pan, fluid or not wanting to identity). The results are analysed from a phenomenological perspective, paying attention to the participants personal interpretations and perspectives, as well as contextualising the interviews in time and space. Using intersectional insights, this study pays attention to varying social positions, including immigration status (newly immigrated, rural to city immigration, Montreal-born, seeking asylum), age (20 to 80), gender (cis, trans and intersex women), relationship style (monogamous and polyamorous) and class. Preliminary findings include a generational shift in issues (e.g. community politics within lesbian communities in the 1980s), varying perspectives on the need of exclusive and safe spaces, shifts in issues of racism and transphobia and identifying points of tensions within conceptualisations of queer and lesbian positionalities.

Keywords: identifications, lesbian, queer, sexual orientation

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Authors: François Chiocchio, Mahshid Gharibpour

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Regardless of the extent to which succession management is implemented in the private sector, it is still overlooked in the public sector. Traditional succession management is evolving providing a better alignment between business strategies and HR strategies. Succession management brings sustainable effectiveness for succession programs through career path development, knowledge and skill transfer, job retention, as well as high-potential candidates’ empowerment for upcoming vacancies. By way of a systematic literature review, we bring into focus strategic succession management in public organizations and discuss best ways of implementation. 

Keywords: succession management, strategic succession management, public organization, succession management model

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Authors: Dorith Tavor, Adi Wolfson

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In the past two decades a variety of green solvents have been proposed, including water, ionic liquids, fluorous solvents, and supercritical fluids. However, their implementation in industrial processes is still limited due to their tedious and non-sustainable synthesis, lack of experimental data and familiarity, as well as operational restrictions and high cost. Several years ago we presented, for the first time, the use of glycerol-based solvents as alternative sustainable reaction mediums in both catalytic and non-catalytic organic synthesis. Glycerol is the main by-product from the conversion of oils and fats in oleochemical production. Moreover, in the past decade, its price has substantially decreased due to an increase in supply from the production and use of fatty acid derivatives in the food, cosmetics, and drugs industries and in biofuel synthesis, i.e., biodiesel. The renewable origin, beneficial physicochemical properties and reusability of glycerol-based solvents, enabled improved product yield and selectivity as well as easy product separation and catalyst recycling. Furthermore, their high boiling point and polarity make them perfect candidates for non-conventional heating and mixing techniques such as ultrasound- and microwave-assisted reactions. Finally, in some reactions, such as catalytic transfer-hydrogenation or transesterification, they can also be used simultaneously as both solvent and reactant. In our ongoing efforts to design a viable protocol that will facilitate the acceptance of glycerol and its derivatives as sustainable solvents, pure glycerol and glycerol triacetate (triacetin) as well as various glycerol-triacetin mixtures were tested as sustainable solvents in several representative organic reactions, such as nucleophilic substitution of benzyl chloride to benzyl acetate, Suzuki-Miyaura cross-coupling of iodobenzene and phenylboronic acid, baker’s yeast reduction of ketones, and transfer hydrogenation of olefins. It was found that reaction performance was affected by the glycerol to triacetin ratio, as the solubility of the substrates in the solvent determined product yield. Thereby, employing optimal glycerol to triacetin ratio resulted in maximum product yield. In addition, using glycerol-based solvents enabled easy and successful separation of the products and recycling of the catalysts.

Keywords: glycerol, green chemistry, sustainability, catalysis

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Authors: Yazhou Zhou, Yong Huang, Guoqin Ge

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In the process of human social development, the coupling and coordinated development among the ecological environment(E), production(P), and living functions(L) is of great significance for sustainable development. This study uses an improved coupling coordination degree model (CCDM) to discover the coordination conflict between E and human settlement environment. The main work of this study is as follows: (1) It is found that in the process of urbanization development of Ya 'an city from 2014 to 2018, the degree of coupling (DOC) value between E, P, and L is high, but the coupling coordination degree (CCD) of the three is low, especially the DOC value of E and the other two has the biggest decline. (2) A more objective weight value is obtained, which can avoid the analysis error caused by subjective judgment weight value.

Keywords: ecological environment, coupling coordination degree, neural network, sustainable development

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Authors: Amani Tahat, Serdal Kirmizialtin

Abstract:

Trajectory fragment methods such as Markov State Models (MSM), Milestoning (MS) and Transition Path sampling are the prime choice of extending the timescale of all atom Molecular Dynamics simulations. In these approaches, a set of structures that covers the accessible phase space has to be chosen a priori using cluster analysis. Structural clustering serves to partition the conformational state into natural subgroups based on their similarity, an essential statistical methodology that is used for analyzing numerous sets of empirical data produced by Molecular Dynamics (MD) simulations. Local transition kernel among these clusters later used to connect the metastable states using a Markovian kinetic model in MSM and a non-Markovian model in MS. The choice of clustering approach in constructing such kernel is crucial since the high dimensionality of the biomolecular structures might easily confuse the identification of clusters when using the traditional hierarchical clustering methodology. Of particular interest, in the case of MS where the milestones are very close to each other, accurate determination of the milestone identity of the trajectory becomes a challenging issue. Throughout this work we present two cluster analysis methods applied to the cis–trans isomerism of dinucleotide AA. The choice of nucleic acids to commonly used proteins to study the cluster analysis is two fold: i) the energy landscape is rugged; hence transitions are more complex, enabling a more realistic model to study conformational transitions, ii) Nucleic acids conformational space is high dimensional. A diverse set of internal coordinates is necessary to describe the metastable states in nucleic acids, posing a challenge in studying the conformational transitions. Herein, we need improved clustering methods that accurately identify the AA structure in its metastable states in a robust way for a wide range of confused data conditions. The single linkage approach of the hierarchical clustering available in GROMACS MD-package is the first clustering methodology applied to our data. Self Organizing Map (SOM) neural network, that also known as a Kohonen network, is the second data clustering methodology. The performance comparison of the neural network as well as hierarchical clustering method is studied by means of computing the mean first passage times for the cis-trans conformational rates. Our hope is that this study provides insight into the complexities and need in determining the appropriate clustering algorithm for kinetic analysis. Our results can improve the effectiveness of decisions based on clustering confused empirical data in studying conformational transitions in biomolecules.

Keywords: milestoning, self organizing map, single linkage, structure clustering

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Authors: Ochuko K. Overen, Edson L. Meyer

Abstract:

Uncontrolled heat transfer between the inner and outer space of low-cost housings through the thermal envelope result in indoor thermal discomfort. As a result, an excessive amount of energy is consumed for space heating and cooling. Thermo-optical properties are the ability of paints to reduce the rate of heat transfer through the thermal envelope. The aim of this study is to analyze the thermal performance of a low-cost house with its walls inner surface coated with transparent infrared reflective paint. The thermo-optical properties of the paint were analyzed using Scanning Electron Microscopy/ Energy Dispersive X-ray spectroscopy (SEM/EDX), Fourier Transform Infra-Red (FTIR) and thermal photographic technique. Meteorological indoor and ambient parameters such as; air temperature, relative humidity, solar radiation, wind speed and direction of a low-cost house in Golf-course settlement, South Africa were monitored. The monitoring period covers both winter and summer period before and after coating. The thermal performance of the coated walls was evaluated using time lag and decrement factor. The SEM image shows that the coat is transparent to light. The presence of Al as Al2O and other elements were revealed by the EDX spectrum. Before coating, the average decrement factor of the walls in summer was found to be 0.773 with a corresponding time lag of 1.3 hours. In winter, the average decrement factor and corresponding time lag were 0.467 and 1.6 hours, respectively. After coating, the average decrement factor and corresponding time lag were 0.533 and 2.3 hour, respectively in summer. In winter, an average decrement factor of 1.120 and corresponding time lag of 3 hours was observed. The findings show that the performance of the coats is influenced by the seasons. With a 74% reduction in decrement factor and 1.4 time lag increase in winter, it implies that the coatings have more ability to retain heat within the inner space of the house than preventing heat flow into the house. In conclusion, the results have shown that transparent infrared reflective paint has the ability to reduce the propagation of heat flux through building walls. Hence, it can serve as a remedy to the poor thermal performance of low-cost housings in South Africa.

Keywords: energy efficiency, decrement factor, low-cost housing, paints, rural development, thermal comfort, time lag

Procedia PDF Downloads 283

Authors: Rafal Bryk, Holger Schmidt, Thomas Mull, Ingo Ganzmann, Oliver Herbst

Abstract:

Prediction of the two-phase water mixture level during fast depressurization of the Reactor Pressure Vessel (RPV) resulting from an accident scenario is an important issue from the view point of the reactor safety. Since the level swell may influence the behavior of some passive safety systems, it has been recognized that an assumption which at the beginning may be considered as a conservative one, not necessary leads to a conservative result. This paper discusses outcomes obtained during simulations of the water dynamics and heat transfer during sudden depressurization of a vessel filled up to a certain level with liquid water under saturation conditions and with the rest of the vessel occupied by saturated steam. In case of the pressure decrease e.g. due to the main steam line break, the liquid water evaporates abruptly, being a reason thereby, of strong transients in the vessel. These transients and the sudden emergence of void in the region occupied at the beginning by liquid, cause elevation of the two-phase mixture. In this work, several models calculating the water collapse and swell levels are presented and validated against experimental data. Each of the models uses different approach to calculate void fraction. The object-oriented models were developed with the Modelica modelling language and the OpenModelica environment. The models represent the RPV of the Integral Test Facility Karlstein (INKA) – a dedicated test rig for simulation of KERENA – a new Boiling Water Reactor design of Framatome. The models are based on dynamic mass and energy equations. They are divided into several dynamic volumes in each of which, the fluid may be single-phase liquid, steam or a two-phase mixture. The heat transfer between the wall of the vessel and the fluid is taken into account. Additional heat flow rate may be applied to the first volume of the vessel in order to simulate the decay heat of the reactor core in a similar manner as it is simulated at INKA. The comparison of the simulations results against the reference data shows a good agreement.

Keywords: boiling water reactor, level swell, Modelica, RPV depressurization, thermal-hydraulics

Procedia PDF Downloads 210