Search results for: complex perovskite

Authors: Christian Angerer, Markus Lienkamp

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Electric vehicles offer a high variety of possible drivetrain topologies with up to 4 motors. Multi-motor-designs can have several advantages regarding traction, vehicle dynamics, safety and even efficiency. With a rising number of motors, the whole drivetrain becomes more complex. All permutations of gearings, drivetrain-layouts, motor-types and –sizes lead up in a very large solution space. Single elements of this solution space can be analyzed by simulation methods. In addition to longitudinal vehicle behavior, which most optimization-approaches are restricted to, also lateral dynamics are important for vehicle dynamics, stability and efficiency. In order to compete large solution spaces and to find an optimal result, genetic algorithm based optimization is state-of-the-art. As lateral dynamics simulation is way more CPU-intensive, optimization takes much more time than in case of longitudinal-only simulation. Therefore, this paper shows an approach how to create meta-models from a 14-degree of freedom vehicle model in order to enable a numerically efficient drivetrain-layout optimization process under consideration of lateral dynamics. Different meta-modelling approaches such as neural networks or DoE are implemented and comparatively discussed.

Keywords: driving dynamics, drivetrain layout, genetic optimization, meta-modeling, lateral dynamicx

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Authors: Zuhairah Abdul Hadi, Mohd Nazir bin Md. Zabit, Zuriadah Ismail

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Metacognitive has been empirically evidenced to be one important element influencing learning outcomes. Expert learners engage in metacognition by monitoring and controlling their thinking, and listing, considering and selecting the best strategies to achieve desired goals. Studies also found that good critical thinkers engage in more metacognition and people tend to activate more metacognition when solving complex problems. This study extends past studies by performing a qualitative analysis to understand metacognitive patterns among two high and two low performing groups by carefully examining video and audio records taken during Problem-based learning activities. High performing groups are groups with majority members scored well in Watson Glaser II Critical Thinking Appraisal (WGCTA II) and academic achievement tests. Low performing groups are groups with majority members fail to perform in the two tests. Audio records are transcribed and analyzed using schemas adopted from past studies. Metacognitive statements are analyzed using three stages model and patterns of metacognitive are described by contexts, components, and levels for each high and low performing groups.

Keywords: academic achievement, critical thinking, metacognitive, problem-based learning

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Authors: Aftab Khan, Ashfaq Khan

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The research paper focuses on an interesting challenge faced in Blind Image Deblurring (BID). It relates to the estimation of arbitrarily shaped or non-parametric Point Spread Functions (PSFs) of motion blur caused by camera handshake. These PSFs exhibit much more complex shapes than their parametric counterparts and deblurring in this case requires intricate ways to estimate the blur and effectively remove it. This research work introduces a novel blind deblurring scheme visualized for deblurring images corrupted by arbitrarily shaped PSFs. It is based on Genetic Algorithm (GA) and utilises the Blind/Reference-less Image Spatial QUality Evaluator (BRISQUE) measure as the fitness function for arbitrarily shaped PSF estimation. The proposed BID scheme has been compared with other single image motion deblurring schemes as benchmark. Validation has been carried out on various blurred images. Results of both benchmark and real images are presented. Non-reference image quality measures were used to quantify the deblurring results. For benchmark images, the proposed BID scheme using BRISQUE converges in close vicinity of the original blurring functions.

Keywords: blind deconvolution, blind image deblurring, genetic algorithm, image restoration, image quality measures

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Authors: Diemas Purnama Muhammad Firman Pratama, Denny Maulana Malik

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Development of Jatigede Dam that was the mega project in Indonesia, since 1963. Area of around Jatigede Dam is complex, it has structural geology active fault, and as possible can occur landslide. This research focus on soil test. The purpose of this research to know soil quality Jatigede Dam which caused by water seepage of Jatigede Dam, then can be made seepage modelling around Jatigede Dam including Cisampih Village. Method of this research is SRW (Soil Reaction to Water). There are three samples are taken nearby Jatigede Dam. Four paramaters to determine water seepage such as : V ( velocity of soil to release water), Dl (Ability of soil to release water), Ds (Ability of soil to absorb water), Dt (Ability of soil to hold water). meanwhile, another proscess of interaction beetween water and soil are produced angle, which is made of water flow and vertikal line. Called name SIAT. SIAT has two type is na1 and na2. Each samples has a value from the first sample is 280,333(degree), the second 270 (degree) and the third 270 (degree). The difference na1 is, water interaction towards Dt value angle, while na2 is water interaction towards Dl and Ds value angle. Result of calculating SRW method, first till third sample has a value 7, 11,5 and 9. Based on data, interpreted in around teritory of Jatigede Dam, will get easier impact from water seepage because, condition soil reaction too bad so, it can not hold water.

Keywords: Jatigede Dam, Cisampih village, water seepage, soil quality

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Authors: Surendra Kumar Patel

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Disability is not just a health problem; it is a complex phenomenon, reflecting the interaction between features of a person’s age and physiology. Population ageing is a major demographic issue for India in the 21st century. Older population of India constituted 8% of total population, while 5.19% has affected by disability of older age group. Objective of the present research paper is to examine the state wise differential in disability among 60+ population and to access the health care of disabled population especially the 60+ disabled persons. The data sources of the present paper are census 2001 and 2011. For analyzing the state wise differentials by disability types and comparative advantage of data, rate, ratio, and percentage have been used. The Standardized Index of Diversity of Disability (SIDD) studies differential and diversity in disability. The results show that there are 5.19% persons have disability among 60+ population and sex differential not very significant, as it is 5.3 % of male and 5.05% in female in India but place of residence shows significant variation from 2001 to 2011 census. There is huge diversity in disability prevalence among 60+ in India, highest in Sikkim followed by Rajasthan, approximately, they comprise 11%, and the lowest found in Tamil Nadu as 2.53%. This huge gap in prevalence percentage shows the health care needs of highly prevailing states.

Keywords: disability, Standardized Index of Diversity of Disability (SIDD), differential and diversity in disability, 60+ population

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Authors: Ghazi Chabchoub, Mouna Feki, Mohamed Abid, Hammadi Ayadi

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Autoimmune thyroid diseases (AITDs), including Graves’ disease (GD) and Hashimoto’s thyroiditis (HT), are inherited as complex traits. Genetic factors associated with AITDs have been tentatively identified by candidate gene and genome scanning approaches. We analysed three intragenic microsatellite markers in the thyroid hormone receptor associated protein 2 gene (THRAP2), mapped near D12S79 marker, which have a potential role in immune function and inflammation [THRAP2-1(TG)n, THRAP2-2 (AC)n and THRAP2-3 (AC)n]. Our study population concerned 12 patients affected with AITDs belonging to a multiplex Tunisian family with high prevalence of AITDs. Fluorescent genotyping was carried out on ABI 3100 sequencers (Applied Biosystems USA) with the use of GENESCAN for semi-automated fragment sizing and GENOTYPER peak-calling software. Statistical analysis was performed using the non parametric Lod score (NPL) by Merlin software. Merlin outputs non-parametric NPLall (Z) and LOD scores and their corresponding asymptotic P values. The analysis for three intragenic markers in the THRAP2 gene revealed strong evidence for linkage (NPL=3.68, P=0.00012). Our results suggested the possible role of THRAP2 gene in AITDs susceptibility in this family.

Keywords: autoimmunity, autoimmune disease, genetic, linkage analysis

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Authors: Zahra Abdolkarimi, Naser Zouri

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Nowadays, there is unbelievable growing of Robots created a collection of complex and motivate subject in robotic and intellectual ornate, also it made a mechatronics style base of theoretical and technical way in Robocop. Additionally, robotics system recommended RoboCup factor as a provider of some standardization and testing method in case of computer discussion widely. The actual purpose of RoboCup is creating independent team of robots in 2050 based of FiFa roles to bring the victory in compare of world star team. In addition, decision making of robots depends to environment reaction, self-player and rival player with using inductive Fuzzy system valuation subsidiary to solve issue of robots in land game. The measure of selection in compare with other methods depends to amount of victories percentage in the same team that plays accidently. Consequences, shows method of our discussion is the best way for Particle Swarm Optimization and Fuzzy system compare to other decision of robotics algorithmic.

Keywords: PSO algorithm, inference fuzzy system, chaos theory, soccer robot league

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Authors: Lokes Parvatha Kumaran S., Sakthi Jay Mahenthar C., Sathyaprakash P., Jayakumar V., Shobanadevi A.

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With the evolution of technology, the need to solve complex computational problems like machine learning and deep learning has shot up. But even the most powerful classical supercomputers find it difficult to execute these tasks. With the recent development of quantum computing, researchers and tech-giants strive for new quantum circuits for machine learning tasks, as present works on Quantum Machine Learning (QML) ensure less memory consumption and reduced model parameters. But it is strenuous to simulate classical deep learning models on existing quantum computing platforms due to the inflexibility of deep quantum circuits. As a consequence, it is essential to design viable quantum algorithms for QML for noisy intermediate-scale quantum (NISQ) devices. The proposed work aims to explore Variational Quantum Circuits (VQC) for Deep Reinforcement Learning by remodeling the experience replay and target network into a representation of VQC. In addition, to reduce the number of model parameters, quantum information encoding schemes are used to achieve better results than the classical neural networks. VQCs are employed to approximate the deep Q-value function for decision-making and policy-selection reinforcement learning with experience replay and the target network.

Keywords: quantum computing, quantum machine learning, variational quantum circuit, deep reinforcement learning, quantum information encoding scheme

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Authors: Wipada Chaiwchan, Patcharee Klinhom

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This research is aimed to develop the online-class scheduling management system and improve as a complex problem solution, this must take into consideration in various conditions and factors. In addition to the number of courses, the number of students and a timetable to study, the physical characteristics of each class room and regulations used in the class scheduling must also be taken into consideration. This system is developed to assist management in the class scheduling for convenience and efficiency. It can provide several instructors to schedule simultaneously. Both lecturers and students can check and publish a timetable and other documents associated with the system online immediately. It is developed in a web-based application. PHP is used as a developing tool. The database management system was MySQL. The tool that is used for efficiency testing of the system is questionnaire. The system was evaluated by using a Black-Box testing. The sample was composed of 2 groups: 5 experts and 100 general users. The average and the standard deviation of results from the experts were 3.50 and 0.67. The average and the standard deviation of results from the general users were 3.54 and 0.54. In summary, the results from the research indicated that the satisfaction of users was in a good level. Therefore, this system could be implemented in an actual workplace and satisfy the users’ requirement effectively

Keywords: timetable, schedule, management system, online

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Authors: Samina Khalid, Tehmina Khalil, Smeea Arshad

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Knowledge management is essential ingredient of successful coordination in globally distributed software engineering. Various frameworks, KMSs, and tools have been proposed to foster coordination and communication between virtual teams but practical implementation of these solutions has not been found. Organizations have to face challenges to implement knowledge management system. For this purpose at first, a literature review is arranged to investigate about challenges that restrict organizations to implement KMS and then by taking in account these challenges a problem of need of integrated solution in the form of standardized KMS that can easily store tacit and explicit knowledge, has traced down to facilitate coordination and collaboration among virtual teams. Literature review has been already shown that knowledge is a complex perception with profound meanings, and one of the most important resources that contributes to the competitive advantage of an organization. In order to meet the different challenges caused by not properly managing knowledge related to projects among virtual teams in GSE, we suggest making use of the cloud computing model. In this research a distributed architecture to support KM storage is proposed called conceptual framework of KM as a service in cloud. Framework presented is enhanced and conceptual framework of KM is embedded into that framework to store projects related knowledge for future use.

Keywords: management, Globsl software development, global software engineering

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Authors: Doki Naomi Onyeje, Doki Gowon Ama

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The past 4 years have been traumatic for Nigerians, having to deal with a number of complex economic issues with dire consequences for the economy. Households have had to respond variously to some of these problems in peculiar ways, depending, of course, on the nature and character of a particular shock. The type, magnitude, intensity and duration of a particular shock might be the determinant of different household responses. While households’ responses to the Global Financial Crisis and Covid 19 Pandemic have been documented by researchers, other economic shocks have continued to emerge in Nigeria. The dramatic turn of events since coming on board of the new government on May 29th 2023, has introduced a new economic twist that households will have to adjust to. This study, therefore, sets out to examine household responses by disaggregating them by their livelihood sources. A survey of 420 households across North Central Nigeria will be done to generate information on the respective responses. A Multinomial logit regression analysis will be employed to test the hypothesis that livelihood source(s) influences household responses to economic shocks. Consequently, responses from public and private households will be examined. The expected results should be that household responses might have some similarities, but it is expected that some peculiar responses across groups will emerge and these differences will guide for group-specific interventions. The Theatre for Development (TfD) approach will be used to disseminate and propagate results from this study to and among stakeholders for effective policy frameworks.

Keywords: drama, dynamics, economic shocks, household responses, Nigeria

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Authors: M. Karaman, H. Catalkaya

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Due to the complex nature of cyber attacks and their effects ranging from personal to governmental level, it becomes one of the priority tasks for operation planners to take into account the risks, influences and effects of cyber attacks. However it can also be embedded or integrated technically with electronic warfare planning, cyber operation planning is needed to have a sole and broadened perspective. This perspective embodies itself firstly in operational design and then military decision making process. In order to find out the ill-structured problems, understand or visualize the operational environment and frame the problem, operational design can help support cyber operation planners and commanders. After having a broadened and conceptual startup with cyber operational design, military decision making process will follow the principles of design into more concrete elements like reaching results after risk management and center of gravity analysis of our and the enemy. In this paper we tried to emphasize the importance of cyber operational design, cyber operation planning and its integration to military decision making problem. In this foggy, uncertain and unaccountable cyber security environment, it is inevitable to stay away from cyber attacks. Therefore, a cyber operational design should be formed with line of operations, decisive points and end states in cyber then a tactical military decision making process should be followed with cyber security focus in order to support the whole operation.

Keywords: cyber operational design, military decision making process (MDMP), operation planning, end state

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Authors: Emilia-Gheorghina Negru

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As an EU goal, gender diversity in early year’s education aims and promotes equality of chances and respect for gender peculiarities of the pupils which are involved in formal educational activities. Early year’s education, as the first step to the Curriculum, prints to teachers the need to identify the role of the gender dimension on this stage, depending on the age level of preschool children through effective, complex, innovative and analytical awareness of gender diversity teaching and management strategies. Through gender educational work we, as teachers, will examine the effectiveness of the PATHS (Promoting Alternative Thinking Strategies) curriculum the gender development of school-aged children. PATHS and a school-based preventive intervention model are necessary to be designed to improve children's ability to discuss and understand equality and gender concepts. Our teachers must create an intervention model and provide PATHS lessons during the school year. Results of the intervention will be effective for both low- and high-risk children in improving their range of math’s skills for girls and vocabulary, fluency and emotional part for boys in discussing gender experiences, their efficacy beliefs regarding the management of equality in gender area, and their developmental understanding of some aspects of gender.

Keywords: gender, gender differences, gender equality, gender role, gender stereotypes

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Authors: Shuofeng Yuan, Bojian Zheng

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Assembly of the heterotrimeric polymerase complex of influenza virus from the individual subunits PB1, PA, and PB2 is a prerequisite for viral replication, in which the interaction between the N-terminal of PB1 (PB1N) and the C terminal of PA (PAC) may be a desired target for antiviral development. In this study, we first compared the feasibility of high throughput screening by enzyme-linked immunosorbent assay (ELISA) and fluorescence polarization (FP) assay. Among the two, ELISA was demonstrated to own broader dynamic range so that it was used for screening inhibitors, which blocked PA and PB1 interaction. Several binding inhibitors of PAC-PB1N were identified and subsequently tested for the antiviral efficacy. Apparently, 3-(2-chlorophenyl)-6-ethyl-7-methyl[1,2,4]triazolo[4,3-a]pyrimidin-5-ol, designated ANA-1, was found to be a strong inhibitor of PAC-PB1N interaction and act as a potent antiviral agent against the infections of multiple subtypes of influenza A virus, including H1N1, H3N2, H5N1, H7N7, H7N9 and H9N2 subtypes, in cell cultures. Intranasal administration of ANA-1 protected mice from lethal challenge and reduced lung viral loads in H1N1 virus infected BALB/c mice. Docking analyses predicted that ANA-1 bound to an allosteric site of PAC, which would cause conformational changes thereby disrupting the PAC-PB1N interaction. Overall, our study has identified a novel compound with potential to be developed as an anti-influenza drug.

Keywords: influenza, antiviral, viral polymerase, compounds

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Authors: Sofiane Bendoukha, Daniel Moldt, Hayat Bendoukha

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Workflow concepts are essential for the development of remote sensing applications. They can help users to manage and process satellite data and execute scientific experiments on distributed resources. The objective of this paper is to introduce an approach for the specification and the execution of complex scientific workflows in Cloud-like environments. The approach strives to support scientists during the modeling, the deployment and the monitoring of their workflows. This work takes advantage from Petri nets and more pointedly the so-called reference nets formalism, which provides a robust modeling/implementation technique. RENEWGRASS is a tool that we implemented and integrated into the Petri nets editor and simulator RENEW. It provides an easy way to support not experienced scientists during the specification of their workflows. It allows both modeling and enactment of image processing workflows from the remote sensing domain. Our case study is related to the implementation of vegetation indecies. We have implemented the Normalized Differences Vegetation Index (NDVI) workflow. Additionally, we explore the integration possibilities of the Cloud technology as a supplementary layer for the deployment of the current implementation. For this purpose, we discuss migration patterns of data and applications and propose an architecture.

Keywords: cloud computing, scientific workflows, petri nets, RENEWGRASS

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Authors: Steffy Maria Joseph, Abdu Rahiman V, Abdul Hameed K. M.

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Online handwritten character recognition is a challenging field in Artificial Intelligence. The classification success rate of current techniques decreases when the dataset involves similarity and complexity in stroke styles, number of strokes and stroke characteristics variations. Malayalam is a complex south indian language spoken by about 35 million people especially in Kerala and Lakshadweep islands. In this paper, we consider the significant feature extraction for the similar stroke styles of Malayalam. This extracted feature set are suitable for the recognition of other handwritten south indian languages like Tamil, Telugu and Kannada. A classification scheme based on support vector machines (SVM) is proposed to improve the accuracy in classification and recognition of online malayalam handwritten characters. SVM Classifiers are the best for real world applications. The contribution of various features towards the accuracy in recognition is analysed. Performance for different kernels of SVM are also studied. A graphical user interface has developed for reading and displaying the character. Different writing styles are taken for each of the 44 alphabets. Various features are extracted and used for classification after the preprocessing of input data samples. Highest recognition accuracy of 97% is obtained experimentally at the best feature combination with polynomial kernel in SVM.

Keywords: SVM, matlab, malayalam, South Indian scripts, onlinehandwritten character recognition

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Authors: Maha Salah, Hanaa Hashem, Mahmoud M. Alsagheir, Mohammed Salah

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Acute respiratory distress syndrome (ARDS) represents a complex clinical syndrome and carries a high risk for mortality. The severity of the clinical course, the uncertainty of the outcome, and the reliance on the full spectrum of critical care resources for treatment mean that the entire health care team is challenged. Researchers and clinicians have investigated the nature of the pathological process and explored treatment options with the goal of improving outcome. Through this application of research to practice, we know that some previous strategies have been ineffective, and innovations in mechanical ventilation, sedation, nutrition, and pharmacological intervention remain important research initiatives. Developed Clinical pathway is multidisciplinary plans of best clinical practice for this specified groups of patients that aid in the coordination and delivery of high quality care. They are a documented sequence of clinical interventions that help a patient to move, progressively through a clinical experience to a desired outcome. Although there is a lot of heterogeneity in patients with ARDS, this suggested developed clinical pathway with alternatives was built depended on a lot of researches and evidence based medicine and nursing practices which may be helping these patients to improve outcomes, quality of life and decrease mortality.

Keywords: acute respiratory distress syndrome (ARDS), clinical pathway, clinical syndrome

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Authors: Rudolf Egger

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This paper explores the relationships between the basic learning processes of leading trade union workers and their methods for coping with the changes in the life-courses of societies today. It will discuss the fragile discourse on lifelong learning in trade unions and the “production of self-techniques” to get in touch with the new economic forms. On the basis of an empirical project, different processes of the socialization of leading trade union workers will be analysed to discover the consequences of the lifelong learning discourse. The results show what competences they need to develop for the “wider benefits of negotiations”. The main challenge remains to make visible how deeply intertwined trade union learning and education are with development in an ongoing dynamic economic process, rather than a quick-fix injection of skills and information. There is a complex relationship existing between the three ‘partners’, work, learning and society forming. The author suggests that contemporary trade unions could be trendsetters who make their own learning agendas by drawing less on formal education and more on informal and non-formal learning contexts. This is in parallel with growing political and scientific consciousness of the need to arrive at new educational/vocational policies and practices.

Keywords: trade union workers, educational leadership, learning societies, social acting

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Authors: Ahmed Jarray, Vanessa Magnanimo, Stefan Luding

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Granular avalanches are ubiquitous in nature and occur in numerous industrial processes associated with particulate systems. When a small amount of liquid is added to a pile of particles, pendular bridges form and the particles are attracted by capillary forces, creating complex structure and flow behavior. We have performed an extensive series of experiments to investigate the effect of capillary force and particle size on wet granular avalanches, and we established a methodology that ensures the control of the granular flow in a rotating drum. The velocity of the free surface and the angle of repose of the particles in the rotating drum are determined using particle tracking method. The capillary force between the particles is significantly reduced by making the glass beads hydrophobic via chemical silanization. We show that the strength of the capillary forces between two adjacent particles can be deliberately manipulated through surface modification of the glass beads, thus, under the right conditions; we demonstrate that the avalanche dynamics can be controlled. The results show that the avalanche amplitude decreases when increasing the capillary force. We also find that liquid-induced cohesion increases the width of the gliding layer and the dynamic angle of repose, however, it decreases the velocity of the free surface.

Keywords: avalanche dynamics, capillary force, granular material, granular flow

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Authors: Bipasha Sen, Aditya Agarwal

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Multilingual automatic speech recognition (ASR) system is a single entity capable of transcribing multiple languages sharing a common phone space. Performance of such a system is highly dependent on the compatibility of the languages. State of the art speech recognition systems are built using sequential architectures based on recurrent neural networks (RNN) limiting the computational parallelization in training. This poses a significant challenge in terms of time taken to bootstrap and validate the compatibility of multiple languages for building a robust multilingual system. Complex architectural choices based on self-attention networks are made to improve the parallelization thereby reducing the training time. In this work, we propose Reed, a simple system based on 1D convolutions which uses very short context to improve the training time. To improve the performance of our system, we use raw time-domain speech signals directly as input. This enables the convolutional layers to learn feature representations rather than relying on handcrafted features such as MFCC. We report improvement on training and inference times by atleast a factor of 4x and 7.4x respectively with comparable WERs against standard RNN based baseline systems on SpeechOcean's multilingual low resource dataset.

Keywords: convolutional neural networks, language compatibility, low resource languages, multilingual automatic speech recognition

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Authors: Chad A. Long

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The United States military is now commonly responding to complex humanitarian emergencies and natural disasters around the world. From catastrophic earthquakes in Haiti to typhoons devastating the Philippines, U.S. military assistance is requested when the event exceeds the local government's ability to assist the population. This study assesses the characteristics of catastrophes that surpass a nation’s individual ability to respond and recover from the event. The paper begins with a historical summary of military aid and then analyzes over 40 years of the United States military humanitarian response. Over 300 military operations were reviewed and coded based on the nature of the disaster. This in-depth study reviewed the U.S. military’s deployment events for cyclones and earthquakes to determine the strength of the natural disaster requiring external assistance. The climatological data for cyclone landfall and magnitude data for earthquake epicenters were identified, grouped into regions and analyzed for time-based trends. The results showed that foreign countries will likely request the U.S. military for cyclones with speeds greater or equal to 125 miles an hour and earthquakes at the magnitude of 7.4 or higher. These results of this study will assist the geographic combatant commands in determining future military response requirements.

Keywords: military, natural disasters, earthquakes, cyclone

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Authors: Francisca Margarita Ocran

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Underwear, and more particularly bras and panties, are defined as intimate clothing. Strictly speaking, they enhance the place of women in the public or private satchel. Therefore, women's lingerie is a complex garment with a high involvement profile, motivating consumers to buy it not only by its functional utility but also by the multisensory experience it provides them. Customer behavior models are generally based on customer data mining, and each model is designed to answer questions at a specific time. Predicting the customer experience is uncertain and difficult. Thus, knowledge of consumers' tastes in lingerie deserves to be treated as an experiential product, where the dimensions of the experience motivating consumers to buy a lingerie product and to remain faithful to it must be analyzed in detail by the manufacturers and retailers to engage and retain consumers, which is why this research aims to identify the variables that push consumers to choose their lingerie product, based on an in-depth analysis of the types of fabrics used to make lingerie. The data used in this study comes from online purchases. Machine learning approach with the use of Python programming language and Pycaret gives us a precision of 86.34%, 85.98%, and 84.55% for the three algorithms to use concerning the preference of a buyer in front of a range of lingerie. Gradient Boosting, random forest, and K Neighbors were used in this study; they are very promising and rich in the classification of preference in the textile industry.

Keywords: consumer behavior, data mining, lingerie, machine learning, preference

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Authors: Adela Diepoltova, Klara Konecna, Ondrej Jandourek, Petr Nachtigal

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A loss of control over antibiotic-resistant pathogens has become a global issue due to severe and often untreatable infections. This state is reflected in complicated treatment, health costs, and higher mortality. All these factors emphasize the urgent need for the discovery and development of new anti-infectives. One of the most common pathogens mentioned in the phenomenon of antibiotic resistance are bacteria of the genus Staphylococcus. These bacterial agents have developed several mechanisms against the effect of antibiotics. One of them is biofilm formation. In staphylococci, biofilms are associated with infections such as endocarditis, osteomyelitis, catheter-related bloodstream infections, etc. To author's best knowledge, no validated and standardized methodology evaluating candidate compound activity against staphylococcal biofilms exists. However, a variety of protocols for in vitro drug activity testing has been suggested, yet there are often fundamental differences. Based on our experience, a key methodological step that leads to credible results is to form a robust biofilm with appropriate attributes such as firm adherence to the substrate, a complex arrangement in layers, and the presence of extracellular polysaccharide matrix. At first, for the purpose of drug antibiofilm activity evaluation, the focus was put on various conditions (supplementation of cultivation media by human plasma/fetal bovine serum, shaking mode, the density of initial inoculum) that should lead to reproducible and robust in vitro staphylococcal biofilm formation in microtiter plate model. Three model staphylococcal reference strains were included in the study: Staphylococcus aureus (ATCC 29213), methicillin-resistant Staphylococcus aureus (ATCC 43300), and Staphylococcus epidermidis (ATCC 35983). The total biofilm biomass was quantified using the Christensen method with crystal violet, and results obtained from at least three independent experiments were statistically processed. Attention was also paid to the viability of the biofilm-forming staphylococcal cells and the presence of extracellular polysaccharide matrix. The conditions that led to robust biofilm biomass formation with attributes for biofilms mentioned above were then applied by introducing an alternative method analogous to the commercially available test system, the Calgary Biofilm Device. In this test system, biofilms are formed on pegs that are incorporated into the lid of the microtiter plate. This system provides several advantages (in situ detection and quantification of biofilm microbial cells that have retained their viability after drug exposure). Based on our preliminary studies, it was found that the attention to the peg surface and substrate on which the bacterial biofilms are formed should also be paid to. Therefore, further steps leading to the optimization were introduced. The surface of pegs was coated by human plasma, fetal bovine serum, and L-polylysine. Subsequently, the willingness of bacteria to adhere and form biofilm was monitored. In conclusion, suitable conditions were revealed, leading to the formation of reproducible, robust staphylococcal biofilms in vitro for the microtiter model and the system analogous to the Calgary biofilm device, as well. The robustness and typical slime texture could be detected visually. Likewise, an analysis by confocal laser scanning microscopy revealed a complex three-dimensional arrangement of biofilm forming organisms surrounded by an extracellular polysaccharide matrix.

Keywords: anti-biofilm drug activity screening, in vitro biofilm formation, microtiter plate model, the Calgary biofilm device, staphylococcal infections, substrate modification, surface coating

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Authors: Sina Mahdavi

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Background and Objective: Multiple sclerosis (MS) is the most common inflammatory autoimmune disease of the central nervous system (CNS) that affects the myelination process in the CNS. Complex interactions of various "environmental or infectious" factors may act as triggers in autoimmunity and disease progression. The association between viral infections, especially the John Cunningham virus (JCV) and MS is one potential cause that is not well understood. This study aims to summarize the available data on JCV infection in MS disease progression. Materials and Methods: For this study, the keywords "Multiple sclerosis", " John Cunningham virus ", and "central nervous system" in the databases PubMed, Google Scholar, Sid, and MagIran between 2019 and 2022 were searched, and 12 articles were chosen, studied, and analyzed. Results: MS patients are candidates for natalizumab therapy, which inhibits lymphocyte migration and increases the risk of progressive multifocal leukoencephalopathy (PML), a rare lytic infection of glial cells caused by JCV. Oligodendrocytes may be the target of JCV infection in the central nervous system (CNS). Conclusion: There is a high expression of JCV during the natalizumab treatment period for MS patients, suggesting that the virus may play a role in the development of MS by inducing an inflammatory state. Therefore, it is necessary to evaluate anti-JCV antibody serum as an important risk factor for the development of PML before deciding on the treatment course for these patients.

Keywords: multiple sclerosis, John Cunningham virus, central nervous system, autoimmunity

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Authors: L. Grinis

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Turbulent flow in complex geometries receives considerable attention due to its importance in many engineering applications. It has been the subject of interest for many researchers. Some of these interests include the design of storm water channels. The design of these channels requires testing through physical models. The main practical limitation of physical models is the so called “scale effect”, that is, the fact that in many cases only primary physical mechanisms can be correctly represented, while secondary mechanisms are often distorted. These observations form the basis of our study, which centered on problems associated with the design of storm water channels near the Dead Sea, in Israel. To help reach a final design decision we used different physical models. Our research showed good coincidence with the results of laboratory tests and theoretical calculations, and allowed us to study different effects of fluid flow in an open channel. We determined that problems of this nature cannot be solved only by means of theoretical calculation and computer simulation. This study demonstrates the use of physical models to help resolve very complicated problems of fluid flow through baffles and similar structures. The study applies these models and observations to different construction and multiphase water flows, among them, those that include sand and stone particles, a significant attempt to bring to the testing laboratory a closer association with reality.

Keywords: open channel, physical modeling, baffles, turbulent flow

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Authors: Åse Nygren, Linda du Plessis

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Academic leadership has traditionally been associated with collegiality, consensus and a limitation in time. These factors alone have resulted in a complex and fuzzy leadership culture in academia, combined with a strong sense of autonomy among researchers and teachers. A more competitive educational market have resulted in increased audit as well as recent autonomy reforms with higher demands on effectiveness, cost awareness and accountability in higher education. In recent years, with the introduction of new public management, academic leadership has been in a state of transition moving from collegiality towards manergerialism. University reforms and changes, which have gradually taken place in most western countries in the past decade, including Sweden and South-Africa, have contributed to the notion that collegial academic leadership is questioned. Academic leadership is traditionally associated with vice-chancellors, deans and heads of departments. This paper will focus on “outer circle” of academic leaders, consisting of, for example, program directors, directors of disciplines, course coordinators and research leaders. We investigate the meaning of collegiality for these groups of academic leaders in Sweden and South-Africa. The paper rests on a comparative study made on universities both in Sweden and in South-Africa. The aim of the comparison is to achieve a wider scope and to investigate perspectives from both inside and outside of Bologna.

Keywords: academic leadership, new public management, collegiality, consensus

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Authors: Seyed Hossein Iranmanesh, Hassan Nouri, Seyed Reza Iranmanesh

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In the dynamic and complex landscape of today’s business, organizations often face challenges in impactful decision-making across multi-project settings. To efficiently allocate resources, coordinate tasks, and optimize project outcomes, establishing robust decision-making processes is essential. Furthermore, the increasing importance of information systems and their integration within organizational workflows introduces an additional layer of complexity. This research proposes the use of blockchain technology as a suitable solution to enhance decision-making in multi-project environments, particularly within the realm of information systems. The conceptual framework in this study comprises four independent variables and one dependent variable. The identified independent variables for the targeted research include: Blockchain Layer in Integrated Systems, Quality of Generated Information ,User Satisfaction with Integrated Systems and Utilization of Integrated Systems. The project’s performance, considered as the dependent variable and moderated by organizational policies and procedures, reflects the impact of blockchain technology adoption on organizational effectiveness1. The results highlight the significant influence of blockchain implementation on organizational performance.

Keywords: multi-project environments, decision support systems, information systems, blockchain technology, decentralized systems.

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Authors: Abdullah Alhajoj, Bassam Alowaiesh

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This work aims to reduce the risks of discharging olive mill waste directly to the environment without treatment in Sakaka City, KSA. The organic loads expressed by chemical oxygen demand (COD) and biological oxygen demand (BOD) of the produced wastewater (OMWW) as well as the solid waste (OMW) were evaluated. The wastes emitted from the three-phase centrifuge decanters was found to be higher than that emitted from the two-phase centrifuge decanters. The olive mill wastewater (OMWW) was treated using advanced oxidation combined with filtration treatment. The results indicated that the concentration of COD, BOD, TSS, oil and grease and phenol was reduced by using complex sand filtration from 72150, 21660 10256, 36430, and 1470 mg/l to 980, 421, 58, 68, and 0.35 mg/l for three-phase OMWW and from 150562, 17955, 15325, 19658 and 2153 mg/l to 1050, 501, 29, 0.75, and 0.29 mg/l, respectively. While, by using modified trickling filter (packed with the neck of waste plastic bottles the concentration of the previously mentioned parameters was reduced to 1190, 570, 55, 0.85, and 0.3 mg/l, respectively. This work supports the application of such treatment technique for reducing the environmental threats of olive mill waste effluents in Saudi Arabia.

Keywords: two-phase, three-phase, olive mill, olive oil, waste treatment, filtration, advanced oxidation, waste plastic bottles

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Authors: Ahmed O. Babaleye, Rafet E. Kurt

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The global oil and gas industry is beginning to witness an increase in the number of installations moving towards decommissioning. Decommissioning of offshore installations is a complex, costly and hazardous activity, making safety one of the major concerns. Among existing removal options, complete and partial removal options pose the highest risks. Therefore, a dynamic risk model of the accidents from the two options is important to assess the risks on an overall basis. In this study, a risk-based safety model is developed to conduct quantitative risk analysis (QRA) for jacket structure systems failure. Firstly, bow-tie (BT) technique is utilised to model the causal relationship between the system failure and potential accident scenarios. Subsequently, to relax the shortcomings of BT, Bayesian Belief Networks (BBNs) were established to dynamically assess associated uncertainties and conditional dependencies. The BBN is developed through a similitude mapping of the developed bow-tie. The BBN is used to update the failure probabilities of the contributing elements through diagnostic analysis, thus, providing a case-specific and realistic safety analysis method when compared to a bow-tie. This paper presents the application of dynamic safety analysis to guide the allocation of risk control measures and consequently, drive down the avoidable cost of remediation.

Keywords: Bayesian belief network, offshore decommissioning, dynamic safety model, quantitative risk analysis

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Authors: H. Soltani, Kevin Laugero

Abstract:

Obesity is becoming an increasingly critical issue in the United States due to the steady and substantial increase in prevalence over the last 30 years. Existing interventions have been able to help participants achieve short-term weight loss, but have failed to show long-term results. The complex nature of behavioral change remains one of the most difficult barriers in promoting sustainable weight-loss in overweight individuals. Research suggests that the 'intention-behavior gap' can be explained by a person’s ability to regulate higher-order thinking, or Executive Function (EF). A review of 63 research articles was completed in fall of 2017 to identify the role of EF in regulating eating behavior and to identify whether there is a potential for improving dietary quality by enhancing EF. Results showed that poor EF is positively associated with obesogenic behavior, namely increased consumption of highly palatable foods, eating in the absence of hunger, high saturated fat intake and low fruit and vegetable consumption. Recent research has indicated that interventions targeting an improvement in EF can be successful in helping promote healthy behaviors. Furthermore, interventions of longer duration have a more lasting and versatile effect on weight loss and maintenance. This may present an opportunity for the increasingly ubiquitous use of mobile application technology.

Keywords: eating behavior, executive function, nutrition, obesity, weight-loss

Procedia PDF Downloads 153