Search results for: content based image retrieval (CBIR)

Authors: Ahmet E. Osmanlioglu

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In this study, natural bentonite was used as natural clay material and samples were taken from the Kalecik district in Ankara. In this research, bentonite is the subject of an analysis from standpoint of assessing the basic properties of engineered barriers with respect to the buffer material. Bentonite and sand mixtures were prepared for tests. Some of clay minerals give relatively higher hydraulic conductivity and lower swelling pressure. Generally, hydraulic conductivity of these type clays is lower than <10-12 m/s. The hydraulic properties of clay-sand mixtures are evaluated to design engineered barrier specifications. Hydraulic conductivities of bentonite-sand mixture were found in the range of 1.2x10-10 to 9.3x10-10 m/s. Optimum B/S mixture ratio was determined as 35% in terms of hydraulic conductivity and mechanical stability. At the second stage of this study, all samples were compacted into cylindrical shape molds (diameter: 50 mm and length: 120 mm). The strength properties of compacted mixtures were better than the compacted bentonite. In addition, the larger content of the quartz sand in the mixture has the greater thermal conductivity.

Keywords: engineered barriers, mechanical stability, clay, nuclear waste disposal

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Authors: Meng Su

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High-dimensional data analysis often presents challenges in capturing the complex, nonlinear relationships and manifold structures inherent to the data. This article presents a novel approach that leverages the strengths of two powerful techniques, Diffusion Maps and Diffusion Probabilistic Models (DPMs), to address these challenges. By integrating the dimensionality reduction capability of Diffusion Maps with the data modeling ability of DPMs, the proposed method aims to provide a comprehensive solution for analyzing and generating high-dimensional data. The Diffusion Map technique preserves the nonlinear relationships and manifold structure of the data by mapping it to a lower-dimensional space using the eigenvectors of the graph Laplacian matrix. Meanwhile, DPMs capture the dependencies within the data, enabling effective modeling and generation of new data points in the low-dimensional space. The generated data points can then be mapped back to the original high-dimensional space, ensuring consistency with the underlying manifold structure. Through a detailed example implementation, the article demonstrates the potential of the proposed hybrid approach to achieve more accurate and effective modeling and generation of complex, high-dimensional data. Furthermore, it discusses possible applications in various domains, such as image synthesis, time-series forecasting, and anomaly detection, and outlines future research directions for enhancing the scalability, performance, and integration with other machine learning techniques. By combining the strengths of Diffusion Maps and DPMs, this work paves the way for more advanced and robust data analysis methods.

Keywords: diffusion maps, diffusion probabilistic models (DPMs), manifold learning, high-dimensional data analysis

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Authors: S. Shamohammadi, L. Razavi

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This paper based on the principle concepts of SCS-CN model, a new mathematical model for computation of retention potential (S) presented. In the mathematical model, not only precipitation-runoff concepts in SCS-CN model are precisely represented in a mathematical form, but also new concepts, called “maximum retention” and “total retention” is introduced, and concepts of potential retention capacity, maximum retention, and total retention have been separated from each other. In the proposed model, actual retention (F), maximum actual retention (Fmax), total retention (S), maximum retention (Smax), and potential retention (Sp), for the first time clearly defined, so that Sp is not variable, but a function of morphological characteristics of the watershed. Indeed, based on the mathematical relation of the conceptual curve of SCS-CN model, the proposed model provides a new method for the computation of actual retention in watershed and it simply determined runoff based on. In the corresponding relations, in addition to Precipitation (P), Initial retention (Ia), cumulative values of actual retention capacity (F), total retention (S), runoff (Q), antecedent moisture (M), potential retention (Sp), total retention (S), we introduced Fmax and Fmin referring to maximum and minimum actual retention, respectively. As well as, ksh is a coefficient which depends on morphological characteristics of the watershed. Advantages of the modified version versus the original model include a better precision, higher performance, easier calibration and speed computing.

Keywords: model, mathematical, retention, watershed, SCS

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Authors: Kwok W. Mui, Ling T. Wong, Chin T. Cheung, Ho C. Yu

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Based on an indoor environmental quality (IEQ) index established by previous work that indicates the overall IEQ acceptance from the prospect of an occupant in residential buildings in terms of four IEQ factors - thermal comfort, indoor air quality, visual and aural comforts, this study develops a user-friendly IEQ calculator for iOS and Android users to calculate the occupant acceptance and compare the relative performance of IEQ in apartments. The calculator allows the prediction of the best IEQ scenario on a quantitative scale. Any indoor environments under the specific IEQ conditions can be benchmarked against the predicted IEQ acceptance range. This calculator can also suggest how to achieve the best IEQ acceptance among a group of residents.

Keywords: calculator, indoor environmental quality (IEQ), residential buildings, 5-star benchmarks

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Authors: Gabrielle Robertson, Matthew Downs, Joseph Dagher

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Iron deposition in the brain has been linked with a host of neurological disorders such as Alzheimer’s, Parkinson’s, and Multiple Sclerosis. While some treatment options exist, there are no objective measurement tools that allow for the monitoring of iron levels in the brain in vivo. An emerging Magnetic Resonance Imaging (MRI) method has been recently proposed to deduce iron concentration through quantitative measurement of magnetic susceptibility. This is a multi-step process that involves repeated modeling of physical processes via approximate numerical solutions. For example, the last two steps of this Quantitative Susceptibility Mapping (QSM) method involve I) mapping magnetic field into magnetic susceptibility and II) mapping magnetic susceptibility into iron concentration. Process I involves solving an ill-posed inverse problem by using regularization via injection of prior belief. The end result from Process II highly depends on the model used to describe the molecular content of each voxel (type of iron, water fraction, etc.) Due to these factors, the accuracy and repeatability of QSM have been an active area of research in the MRI and medical imaging community. This work aims to estimate iron concentration in the brain via a single step. A synthetic numerical model of the human head was created by automatically and manually segmenting the human head on a high-resolution grid (640x640x640, 0.4mm³) yielding detailed structures such as microvasculature and subcortical regions as well as bone, soft tissue, Cerebral Spinal Fluid, sinuses, arteries, and eyes. Each segmented region was then assigned tissue properties such as relaxation rates, proton density, electromagnetic tissue properties and iron concentration. These tissue property values were randomly selected from a Probability Distribution Function derived from a thorough literature review. In addition to having unique tissue property values, different synthetic head realizations also possess unique structural geometry created by morphing the boundary regions of different areas within normal physical constraints. This model of the human brain is then used to create synthetic MRI measurements. This is repeated thousands of times, for different head shapes, volume, tissue properties and noise realizations. Collectively, this constitutes a training-set that is similar to in vivo data, but larger than datasets available from clinical measurements. This 3D convolutional U-Net neural network architecture was used to train data-driven Deep Learning models to solve for iron concentrations from raw MRI measurements. The performance was then tested on both synthetic data not used in training as well as real in vivo data. Results showed that the model trained on synthetic MRI measurements is able to directly learn iron concentrations in areas of interest more effectively than other existing QSM reconstruction methods. For comparison, models trained on random geometric shapes (as proposed in the Deep QSM method) are less effective than models trained on realistic synthetic head models. Such an accurate method for the quantitative measurement of iron deposits in the brain would be of important value in clinical studies aiming to understand the role of iron in neurological disease.

Keywords: magnetic resonance imaging, MRI, iron deposition, machine learning, quantitative susceptibility mapping

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Authors: Gamze Uslu, Sebnem Baydere, Alper K. Demir

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In this study, data loss tolerance of Support Vector Machines (SVM) based activity recognition model and multi activity classification performance when data are received over a lossy wireless sensor network is examined. Initially, the classification algorithm we use is evaluated in terms of resilience to random data loss with 3D acceleration sensor data for sitting, lying, walking and standing actions. The results show that the proposed classification method can recognize these activities successfully despite high data loss. Secondly, the effect of differentiated quality of service performance on activity recognition success is measured with activity data acquired from a multi hop wireless sensor network, which introduces high data loss. The effect of number of nodes on the reliability and multi activity classification success is demonstrated in simulation environment. To the best of our knowledge, the effect of data loss in a wireless sensor network on activity detection success rate of an SVM based classification algorithm has not been studied before.

Keywords: activity recognition, support vector machines, acceleration sensor, wireless sensor networks, packet loss

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Authors: Jian-Jun Gao

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Repetition is used for a variety of functions in conversation. When young children first learn to speak, they often repeat words from the adult’s recent utterance with the learning and social function. The objective of this study was to ascertain whether the repetitions are equivalent in indicating attention to new words and the initial repeat of information in conversation. Based on the observation of naturally occurring language use in Taiwan Corpus of Child Mandarin (TCCM), the results in this study provided empirical support to the previous findings that children are more likely to repeat new words they are offered than to repeat new information. When children get older, there would be a drop in the repetition of both new words and new information.

Keywords: acquisition, corpus, mandarin, new words, new information, repetition

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Authors: Kamyar Kildashti, Rasoul Mirghaderi

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This paper describes the three-dimensional seismic performance assessment of a high-rise steel moment-frame setback tower, designed and detailed per the 2010 ASCE7, under multiple support excitations. The vulnerability analyses are conducted based on nonlinear history analyses under a set of multi-directional strong ground motion records which are scaled to design-based site-specific spectrum in accordance with ASCE41-13. Spatial variation of input motions between far distant supports of each part of the tower is considered by defining time lag. Plastic hinge monotonic and cyclic behavior for prequalified steel connections, panel zones, as well as steel columns is obtained from predefined values presented in TBI Guidelines, PEER/ATC72 and FEMA P440A to include stiffness and strength degradation. Inter-story drift ratios, residual drift ratios, as well as plastic hinge rotation demands under multiple support excitations, are compared to those obtained from uniform support excitations. Performance objectives based on acceptance criteria declared by TBI Guidelines are compared between uniform and multiple support excitations. The results demonstrate that input motion discrepancy results in detrimental effects on the local and global response of the tower.

Keywords: high-rise building, nonlinear time history analysis, multiple support excitation, performance-based design

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Authors: Z. Wang, F. Pashaei Kamali, J. A. Posada Duque, P. Osseweijer

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Globally, the aviation sector is seeking for sustainable solutions to comply with the pressure to reduce greenhouse gas emissions. Jet fuels derived from biomass are generally perceived as a sustainable alternative compared with their fossil counterparts. However, the establishment of jet biofuels supply chains will have impacts on environment, economy, and society. While existing studies predominantly evaluated environmental impacts and techno-economic feasibility of jet biofuels, very few studies took the social / socioeconomic aspect into consideration. Therefore, this study aims to provide a focused evaluation of social sustainability for aviation biofuels with a supply chain perspective. Three potential jet biofuel supply chains based on different feedstocks, i.e. sugarcane, eucalyptus, and macauba were analyzed in the context of Brazil. The assessment of social sustainability is performed with a process-based approach combined with input-output analysis. Over the supply chains, a set of social sustainability issues including employment, working condition (occupational accident and wage level), labour right, education, equity, social development (GDP and trade balance) and food security were evaluated in a (semi)quantitative manner. The selection of these social issues is based on two criteria: (1) the issues are highly relevant and important to jet biofuel production; (2) methodologies are available for assessing these issues. The results show that the three jet biofuel supply chains lead to a differentiated level of social effects. The sugarcane-based supply chain creates the highest number of jobs whereas the biggest contributor of GDP turns out to be the macauba-based supply chain. In comparison, the eucalyptus-based supply chain stands out regarding working condition. It is also worth noting that biojet fuel supply chain with high level of social benefits could result in high level of social concerns (such as occupational accident, violation of labour right and trade imbalance). Further research is suggested to investigate the possible interactions between different social issues. In addition, the exploration of a wider range of social effects is needed to expand the comprehension of social sustainability for biofuel supply chains.

Keywords: biobased supply chain, jet biofuel, social assessment, social sustainability, socio-economic impacts

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Authors: Zumra Mehmedovic, Susan Luhrmann

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Treatment-resistant depression (TRD) is a debilitating mental health disorder for which there are very few available treatment options. Current research suggests that ketamine may be a safe and effective option for the treatment of TRD. Research utilizing a review of the literature was conducted to determine if ketamine in conjunction with antidepressants is more effective than antidepressants alone in the treatment of TRD. The literature consists of ten journal articles which include quantitative studies based on primary research. A critique of the literature was done to determine whether the findings are reliable, critiquing elements influencing the believability and robustness of the research. The research was based on the neuroplasticity theory of depression, hypothesizing that ketamine, in conjunction with antidepressants, will be more effective than antidepressants alone as they have different mechanisms of action. All the studies except one found ketamine in conjunction with antidepressants to be a more effective treatment than antidepressants alone in the treatment of TRD. Results of the studies indicate that ketamine is effective in treating TRD at various doses, settings, and routes of administration. Further research is necessary, though, to further explore and confirm the findings. Several gaps in literature were identified, including the optimal dose of ketamine, its long-term efficacy and safety, and effects of ketamine in repeated doses. The research topic is highly significant to advanced practice nursing, as based on the findings, ketamine can be utilized as a safe and effective treatment for TRD.

Keywords: ketamine, major depressive disorder, treatment-resistant depression, treatment

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Authors: Ogola Lois Kange

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The study looked at the role technology had previously played and now plays in small and medium scale women-owned businesses starting up in Kaduna, which is an emerging entrepreneurship hub state in Nigeria. The study selected a random population of 20 businesses drawn from the north and south of Kaduna. The selection was based on a survey administered to 100 Women-owned businesses that had started up within the last 3-5years. Questionnaires were administered and analyzed based on the participants’ backgrounds, upbringing, exposure and access to technology. One of the key findings is that women-owned businesses can no longer thrive without the application of basic technology.

Keywords: business, entrepreneurship, start-up, technology, women

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Authors: Santanu Chattopadhyay, Gautam Sarkar, Arabinda Das

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This paper presents wavelet based classification of various heart diseases. Electrocardiogram signals of different heart patients have been studied. Statistical natures of electrocardiogram signals for different heart diseases have been compared with the statistical nature of electrocardiograms for normal persons. Under this study four different heart diseases have been considered as follows: Myocardial Ischemia (MI), Congestive Heart Failure (CHF), Arrhythmia and Sleep Apnea. Statistical nature of electrocardiograms for each case has been considered in terms of kurtosis values of two types of wavelet coefficients: approximate and detail. Nine wavelet decomposition levels have been considered in each case. Kurtosis corresponding to both approximate and detail coefficients has been considered for decomposition level one to decomposition level nine. Based on significant difference, few decomposition levels have been chosen and then used for classification.

Keywords: arrhythmia, congestive heart failure, discrete wavelet transform, electrocardiogram, myocardial ischemia, sleep apnea

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Authors: Kharisma Utomo Mulyodinoto, Suwarno, Ahmed Abu-Siada

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Transformer insulating oil is a key component that can be utilized to detect incipient faults within operating transformers without taking them out of service. Dissolved gas-in-oil analysis has been widely accepted as a powerful technique to detect such incipient faults. While the measurement of dissolved gases within transformer oil samples has been standardized over the past two decades, analysis of the results is not always straightforward as it depends on personnel expertise more than mathematical formulas. In analyzing such data, the generation rate of each dissolved gas is of more concern than the absolute value of the gas. As such, history of dissolved gases within a particular transformer should be archived for future comparison. Lack of such history may lead to misinterpretation of the obtained results. IEEE C57.104-2008 standards have classified the health condition of the transformer based on the absolute value of individual dissolved gases along with the total dissolved combustible gas (TDCG) within transformer oil into 4 conditions. While the technique is easy to implement, it is considered as a very conservative technique and is not widely accepted as a reliable interpretation tool. Moreover, measured gases for the same oil sample can be within various conditions limits and hence, misinterpretation of the data is expected. To overcome this limitation, this paper introduces a fuzzy logic approach to predict the health condition of the transformer oil based on IEEE C57.104-2008 standards along with Roger ratio and IEC ratio-based methods. DGA results of 31 chosen oil samples from 469 transformer oil samples of normal transformers and pre-known fault-type transformers that were collected from Indonesia Electrical Utility Company, PT. PLN (Persero), from different voltage rating: 500/150 kV, 150/20 kV, and 70/20 kV; different capacity: 500 MVA, 60 MVA, 50 MVA, 30 MVA, 20 MVA, 15 MVA, and 10 MVA; and different lifespan, are used to test and establish the fuzzy logic model. Results show that the proposed approach is of good accuracy and can be considered as a platform toward the standardization of the dissolved gas interpretation process.

Keywords: dissolved gas analysis, fuzzy logic, health index, IEEE C57.104-2008, IEC ratio method, Roger ratio method

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Authors: Ola A. Younis, Said Ghoul

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Systems running these days are huge, complex and exist in many versions. Controlling these versions and tracking their changes became a very hard process as some versions are created using meaningless names or specifications. Many versions of a system are created with no clear difference between them. This leads to mismatching between a user’s request and the version he gets. In this paper, we present a system versions meta-modeling approach that produces versions based on system’s features. This model reduced the number of steps needed to configure a release and gave each version its unique specifications. This approach is applicable for systems that use features in its specification.

Keywords: features, meta-modeling, semantic modeling, SPL, VCS, versioning

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Authors: Damilola Mofikoya

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Developed countries account for a large proportion of greenhouse gas emissions. In the last decade, countries including the United States and China have made a commitment to cut down carbon emissions by signing the Paris Climate Agreement. However, carbon neutrality is a challenging issue to tackle at the country level because of the scale of the problem. To overcome this challenge, cities are at the forefront of these efforts. Many cities in the United States are taking strategic actions and proposing programs and initiatives focused on renewable energy, green transportation, less use of fossil fuel vehicles, etc. There have been concerns about the implications of those strategies and a lack of community engagement. This paper is focused on community-based efforts that help actualize the reduction of carbon footprint through sustained and inclusive action. Existing zero-carbon assessment tools are examined to understand variables and indicators associated with the zero-carbon goals. Based on a broad, systematic review of literature on community strategies, and existing zero-carbon assessment tools, a dashboard was developed to help simplify and demystify carbon neutrality goals at a community level. The literature was able to shed light on the key contributing factors responsible for the success of community efforts in carbon neutrality. Stakeholder education is discussed as one of the strategies to help communities take action and generate momentum. The community-based efforts involving individuals and residents, such as reduction of food wastages, shopping preferences, transit mode choices, and healthy diets, play an important role in the context of zero-carbon initiatives. The proposed community-based dashboard will emphasize the importance of sustained, structured, and collective efforts at a communal scale. Finally, the present study discusses the relationship between life expectancy and quality of life and how it affects carbon neutrality in communities.

Keywords: carbon footprint, communities, life expectancy, quality of life

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Authors: Cheyenne Johnson, Samantha Robinson, Christina Chant, Ann M. Mitchell, Carol Price, Carmel Clancy, Adam Searby, Deborah S. Finnell

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Introduction: Substance use along the continuum from at-risk use to a substance use disorder (SUD) contributes substantially to the burden of disease and related harms worldwide. There is a growing body of literature that highlights the lack of substance use related content in nursing curricula. Furthermore, there is also a lack of consensus on key competencies necessary for entry-level nurses. Globally, there is a lack of established nursing competencies related to prevention, health promotion, harm reduction and treatment of at-risk substance use and SUDs. At a critical time in public health, this gap in nursing curricula contributes to a lack of preparation for entry-level nurses to support people along the continuum of substance use. Thus, in practice, early opportunities for screening, support, and interventions may be missed. To address this gap, an international committee was convened to develop international entry-level nursing competencies specifying the knowledge, skills, and abilities that all nurses should possess in order to address the continuum of substance use. Methodology: An international steering committee, including representation from Canada, United States, United Kingdom, and Australia was established to lead this work over a one-year time period. The steering committee conducted a scoping review, undertaken to examine nursing competency frameworks, and to inform a competency structure that would guide this work. The next steps were to outline key competency areas and establish leaders for working groups to develop the competencies. In addition, a larger international committee was gathered to contribute to competency working groups, review the collective work and concur on the final document. Findings: A comprehensive framework was developed with competencies covering a wide spectrum of substance use across the lifespan and in the context of prevention, health promotion, harm reduction and treatment, including special populations. The development of this competency-based framework meets an identified need to provide guidance for universities, health authorities, policy makers, nursing regulators and other organizations that provide and support nursing education which focuses on care for patients and families with at-risk substance use and SUDs. Conclusion: Utilizing these global competencies as expected outcomes of an educational and skill building curricula for entry-level nurses holds great promise for incorporating evidence-informed training in the care and management of people across the continuum of substance use.

Keywords: addiction nursing, addiction nursing curriculum, competencies, substance use

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Authors: José Carlos Bronze, Carlinda Leite, Angélica Monteiro

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The creation of the Erasmus Program in 1987 represented a milestone in promoting and funding international mobility in higher education in Europe. Its effects were so significant that they influenced the creation of the European Higher Education Area through the Bologna Process and ensured the program’s continuation and maintenance. Over the last decades, the escalating figures of participants and funds instigated significant scientific studies on the program's effects on higher education. More recently, in 2014, the program was renamed “Erasmus+” when it expanded into other fields of education, namely Vocational Education and Training (VET). Despite being now running in this field of education for a decade (2014-2024), its effects on VET remain less studied and less known, while the higher education field keeps attracting researchers’ attention. Given this gap, it becomes relevant to study the effects of E+ on VET, particularly in the priority domains of the Program: “Inclusion and Diversity,” “Participation in Democratic Life, Common Values and Civic Engagement,” “Environment and Fight Against Climate Change,” and “Digital Transformation.” This latter has been recently emphasized due to the COVID-19 pandemic that forced the so-called emergency remote teaching, leading schools to quickly transform and adapt to a new reality regardless of the preparedness levels of teachers and students. Together with the remaining E+ priorities, they directly relate to an emancipatory perspective of education sustained in soft skills such as critical thinking, intercultural awareness, autonomy, active citizenship, teamwork, and problem-solving, among others. Based on this situation, it is relevant to know the effects of E+ on the VET field, namely questioning how international mobility instigates digitalization processes and supports emancipatory queries therein. As an education field that more directly connects to hard skills and an instrumental approach oriented to the labor market’s needs, a study was conducted to determine the effects of international mobility on developing digital literacy and soft skills in the VET field. In methodological terms, the study used semi-structured interviews with teaching and non-teaching staff from three VET schools who are strongly active in the E+ Program. The interviewees were three headmasters, four mobility project managers, and eight teachers experienced in international mobility. The data was subjected to qualitative content analysis using the NVivo 14 application. The results show that E+ international mobility promotes and facilitates the use of digital technologies as a pedagogical resource at VET schools and enhances and generates students’ soft skills. In conclusion, E+ mobility in the VET field supports adopting the program’s priorities by increasing the teachers’ knowledge and use of digital resources and amplifying and generating participants’ soft skills.

Keywords: Erasmus international mobility, digital literacy, soft skills, vocational education and training

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Authors: Laila Mahtout, Kerami Ahmed, Rabhi Souhila

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The objective of this work is to reduce the impact on the environment of an acid dye (Black Eriochrome T) using catalytic photo-degradation in the presence of the semiconductor powder (TiO₂) previously characterized. A series of tests have been carried out in order to demonstrate the influence of certain parameters on the degree of dye degradation by titanium dioxide in the presence of UV rays, such as contact time, the powder mass and the pH of the solution. X-ray diffraction analysis of the powder showed that the anatase structure is predominant and the rutile phase is presented by peaks of low intensity. The various chemical groups which characterize the presence of the bands corresponding to the anatase and rutile form and other chemical functions have been detected by the Fourier Transform Infrared spectroscopy. The photo degradation of the NET by TiO₂ is very interesting because it gives encouraging results. The study of photo-degradation at different concentrations of the dye showed that the lower concentrations give better removal rates. The degree of degradation of the dye increases with increasing pH; it reaches the maximum value at pH = 9. The ideal mass of TiO₂ which gives the high removal rate is 1.2 g/l. Thermal treatment of TiO₂ with the addition of CuO with contents of 5%, 10%, and 15% respectively gives better results of degradation of the NET dye. The high percentage of elimination is observed at a CuO content of 15%.

Keywords: acid dye, ultraviolet rays, degradation, photocatalyse

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Authors: Reza Behboodian

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Monitoring the structural health and diagnosing their damage in the early stages has always been one of the topics of concern. Nowadays, research on structural damage detection methods based on vibration analysis is very extensive. Moreover, these methods can be used as methods of permanent and timely inspection of structures and prevent further damage to structures. Non-destructive methods are the low-cost and economical methods for determining the damage of structures. In this research, a non-destructive method for detecting and identifying the failure location in structures based on dynamic responses resulting from time history analysis is proposed. When the structure is damaged due to the reduction of stiffness, and due to the applied loads, the displacements in different parts of the structure were increased. In the proposed method, the damage position is determined based on the calculation of the strain energy difference in each member of the damaged structure and the healthy structure at any time. Defective members of the structure are indicated by the amount of strain energy relative to the healthy state. The results indicated that the proper accuracy and performance of the proposed method for identifying failure in structures.

Keywords: failure, time history analysis, dynamic response, strain energy

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Authors: Safa Abusara Mohammed Ali, Mohammed Khair Abdallah, Gurdon A. Brockmann, M. Reissmann

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The aim of the study was the characterization of DGAT1 variants in Sudanese dairy cattle breeds. In this study, we examined 94 Kenana and 91 Butana dairy cattle from two regions of Sudan. We genotyped the DGAT1 sequence variant AJ318490.1:g.10433/10434 AA>GC that leads to the Lysine – Alanine substitution at position 232 (K232A) in the protein and the VNTR polymorphism in the promoter region. Genotyping was performed by allele specific PCR and PCR fragment lengths determination, respectively. In both breeds, the DGAT1 Lysine variant (232K) that is associated with high fat and protein content as well as high fat yield in other breeds is the high frequent allele. The frequencies of the 232K allele were 96.3% and 84.6% in Kenana and Butana breeds, respectively. At the DGAT1 promoter VNTR locus, four alleles containing four to seven repeats of the 18 bp motif were found in both breeds. The highest frequent allele was the VNTR allele 3 containing five repeats with 60.4 % and 57.5 % in Kenana and Butana breeds, respectively. In conclusion, the two examined Sudanese dairy cattle breeds do not differ in allele frequencies at the DGAT1 locus.

Keywords: dairy cattle, DGAT1, Kenana, Butana.

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Authors: Jens Friedrich, Matthias A. Gebele, Armin Lechler, Alexander Verl

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Chatter vibrations and process instabilities are the most important factors limiting the productivity of the milling process. Chatter can leads to damage of the tool, the part or the machine tool. Therefore, the estimation and prediction of the process stability is very important. The process stability depends on the spindle speed, the depth of cut and the width of cut. In milling, the process conditions are defined in the NC-program. While the spindle speed is directly coded in the NC-program, the depth and width of cut are unknown. This paper presents a new simulation based approach for the prediction of the depth and width of cut of a milling process. The prediction is based on a material removal simulation with an analytically represented tool shape and a multi-dexel approach for the work piece. The new calculation method allows the direct estimation of the depth and width of cut, which are the influencing parameters of the process stability, instead of the removed volume as existing approaches do. The knowledge can be used to predict the stability of new, unknown parts. Moreover with an additional vibration sensor, the stability lobe diagram of a milling process can be estimated and improved based on the estimated depth and width of cut.

Keywords: dexel, process stability, material removal, milling

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Authors: Hongkui Li, Tongli Lu , Jianwu Zhang

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This paper focuses on developing an estimation method of clutch drag torque in wet DCT. The modelling of clutch drag torque is investigated. As the main factor affecting the clutch drag torque, dynamic viscosity of oil is discussed. The paper proposes an estimation method of clutch drag torque based on recursive least squares by utilizing the dynamic equations of gear shifting synchronization process. The results demonstrate that the estimation method has good accuracy and efficiency.

Keywords: clutch drag torque, wet DCT, dynamic viscosity, recursive least squares

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Authors: Charmi Chande, Ravindra Phadke

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Microfluidics devices are fabricated by using multiple fabrication methods. Photolithography is one of the common methods wherein SU8 is widely used for making master which in turn is used for making working chip by the process of soft lithography. The high-aspect ratio features of SU-8 makes it suitable to be used as micro moulds for injection moulding, hot embossing, and moulds to form polydimethylsiloxane (PDMS) structures for bioMEMS (Microelectromechanical systems) applications. But due to high cost, difficulty in procuring and need for clean room, restricts the use of this polymer especially in developing countries and small research labs. ‘Bisphenol –A’ based polymers in mixture with curing agent are used in various industries like Paints and coatings, Adhesives, Electrical systems and electronics, Industrial tooling and composites. We present the novel use of ‘Bisphenol – A’ based polymer in fabricating micro channels for Lab On Chip(LOC) devices. The present paper describes the prototype for production of microfluidics chips using range of ‘Bisphenol-A’ based polymers viz. GY 250, ATUL B11, DER 331, DER 330 in mixture with cationic photo initiators. All the steps of chip production were carried out using an inexpensive approach that uses low cost chemicals and equipment. This even excludes the need of clean room. The produced chips using all above mentioned polymers were validated with respect to height and the chip giving least height was selected for further experimentation. The lowest height achieved was 7 micrometers by GY250. The cost of the master fabricated was $ 0.20 and working chip was $. 0.22. The best working chip was used for morphological identification and profiling of microorganisms from environmental samples like soil, marine water and salt water pan sites. The current chip can be adapted for various microbiological screening experiments like biochemical based microbial identification, studying uncultivable microorganisms at single cell/community level.

Keywords: bisphenol–A based epoxy, cationic photoinitiators, microfabrication, photolithography

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Authors: Simiao Ren, En Wei

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Drowning is a significant safety issue worldwide, and a robust computer vision-based alert system can easily prevent such tragedies in swimming pools. However, due to domain shift caused by the visual gap (potentially due to lighting, indoor scene change, pool floor color etc.) between the training swimming pool and the test swimming pool, the robustness of such algorithms has been questionable. The annotation cost for labeling each new swimming pool is too expensive for mass adoption of such a technique. To address this issue, we propose a domain-aware data augmentation pipeline based on Gaussian Poisson Generative Adversarial Network (GP-GAN). Combined with YOLOv8, we demonstrate that such a domain adaptation technique can significantly improve the model performance (from 0.24 mAP to 0.82 mAP) on new test scenes. As the augmentation method only require background imagery from the new domain (no annotation needed), we believe this is a promising, practical route for preventing swimming pool drowning.

Keywords: computer vision, deep learning, YOLOv8, detection, swimming pool, drowning, domain adaptation, generative adversarial network, GAN, GP-GAN

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Authors: Philomena Ibuh Adzongo, Margaret U. Oluwole, Justina Nguveren Jor.

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This paper investigated the need for the development of entrepreneurial skills for Benue State University students. The population consisted of all 1,500 final year students in Benue State University. A sample of 100 students was selected using simple random sampling. A 12-item self-constructed and content validated questionnaire by research experts titled, the Need for the Development of Entrepreneurial Skills in Benue State University Students (NDECBSUS) was used to collect the data. The questionnaire items were rated using a 4-point modified rating scale of Strongly Agree, Agree, Disagree and Strongly Disagree, assigned the following scores of 4,3,2 and 1, respectively. The questionnaire was administered by the researcher with the help of two research assistants through the primary source. Simple percentages and chi-square were used to answer the research questions and test the hypotheses, respectively. The findings revealed that in business management, business management skills, personal skills, and technical skills need to be developed in students for them to become effective and efficient entrepreneurs and concluded that the acquisition of these skills will reduce the challenge of unemployment. The study recommended that funds should be made available by all education stakeholders for such programmes to remain functional.

Keywords: entrepreneurial skill, entrepreneurship, need for development, university students

Procedia PDF Downloads 345

Authors: A. Achour L. Chekour, A. Mekroud

Abstract:

Tribology, the science of lubrication, friction and wear, plays an important role in science "crossroads" initiated by the recent developments in the industry. Its multidisciplinary nature reinforces its scientific interest. It covers all the sciences that deal with the contact between two solids loaded and relative motion. It is thus one of the many intersections more clearly established disciplines such as solid mechanics and the fluids, rheological, thermal, materials science and chemistry. As for his experimental approach, it is based on the physical and processing signals and images. The optimization of operating conditions by cutting tool must contribute significantly to the development and productivity of advanced automation of machining techniques because their implementation requires sufficient knowledge of how the process and in particular the evolution of tool wear. In addition, technological advances have developed the use of very hard materials, refractory difficult machinability, requiring highly resistant materials tools. In this study, we present the behavior wear a machining tool during the roughing operation according to the cutting parameters. The interpretation of the experimental results is based mainly on observations and analyzes of sharp edges e tool using the latest techniques: scanning electron microscopy (SEM) and optical rugosimetry laser beam.

Keywords: friction, wear, tool, cutting

Procedia PDF Downloads 321

Authors: Kailen Krame

Abstract:

This paper presents a review of the literature on the efficacy of mindfulness-based interventions for reducing occupational stress and burnout among K-12 educators. An in-depth discussion of the incidence and impact of teacher stress and burnout is provided, as a wealth of literature indicates that this issue is of growing concern and has important implications not only for individual educators but also for students and the school as an organization. Given the evidence of a link between teacher wellbeing and student outcomes, this topic is worth further investigation in order to better understand sources of stress and burnout and propose adequate coping strategies for today’s educators. As a potential solution to teacher stress and burnout, mindfulness-based interventions are reviewed in-depth, and an overview of the history, diverse application, and effects of mindfulness practice are provided. Relevant outcomes of educator mindfulness training presented in the literature include increased emotional regulation, self-efficacy, and personal wellbeing, among several others. Lastly, additional implications and benefits of educator mindfulness training are explored, limitations of the current research are reviewed, and apparent best practices are proposed.

Keywords: educator burnout, emotional regulation, mindfulness, self-efficacy, stress-reduction

Procedia PDF Downloads 133

Authors: Diqin Qi, Jiaming Li, Siman Li

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Based on the use of the three-point smoothing method for selectively processing original data columns, this paper establishes a group of grey GM(1,1) models to predict the concentration ranges of four major air pollutants in Shanghai from 2023 to 2024. The results indicate that PM₁₀, SO₂, and NO₂ maintain the national Grade I standards, while the concentration of PM₂.₅ has decreased but still remains within the national Grade II standards. Combining the forecast results, recommendations are provided for the Shanghai municipal government's efforts in air pollution prevention and control.

Keywords: atmospheric pollutant prediction, Grey GM(1, 1), model group, three-point smoothing method

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Authors: Maryam Atapour

Abstract:

Chemical pesticides, which are widely used in agriculture, cause problems such as soil and water pollution, reducing biodiversity and creating pest resistance. These problems have led to increased attention to alternative and more sustainable methods such as natural-based pesticides. Herbal pesticides have been developed based on essential oils or extracts from different parts of plants, such as leaves, roots, and flowers. Herbal pesticides are compatible with the environment and can be used in integrated pest management programs. Despite the many benefits, herbal pesticides, especially essential oil-based compounds, have low durability in the environment, and their production costs are high, so the use of herbal extracts with appropriate formulations is more justified in all aspects. In the current study and based on the results of previous studies, aqueous and 70% ethanolic extract of Artemisia absinthium L. was prepared by the percolation method and formulated as an emulsion and water-soluble powder. To produce powder formulation, 20% maltodextrin was used with the spray-dryer method. Different concentrations of these compounds were sprayed on bushes infected with rose aphid Macrosiphum rosae (L.). Sampling was done randomly and the percentage of aphids’ mortality was checked. The results showed that the use of different concentrations of ethanolic extracts created a significant difference in the mortality rate of aphids, while water-soluble powder formulation caused less mortality. The current results showed that the extract of this plant has practical usability to control aphids, and with the appropriate formulation, it can be used as a good alternative to chemical pesticides.

Keywords: contact toxicity, formulation, extract, aphid, Artemisia absinthium.

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Authors: Minho Kwon, Jeonghee Lim, Yeongseok Jeong, Jongyoon Moon, Donghoon Shin, Kiyoung Kim

Abstract:

In the past, the criteria and procedures for the design of concrete structures were mainly based on the stresses allowed for structural components. However, although the frequency of earthquakes has increased and the risk has increased recently, it has been difficult to determine the safety factor for earthquakes in the safety assessment of structures based on allowable stresses. Recently, limit state design method has been introduced for reinforced concrete structures, and limit state-based approach has been recognized as a more effective technique for seismic design. Therefore, in this study, the limit state of the bridge, which is a structure requiring higher stability against earthquakes, was evaluated. The finite element program LS-DYNA and twenty ground motion were used for time history analysis. The fracture caused by tensile and compression of the pier were set to the limit state. In the concrete tensile fracture, the limit state arrival rate was 100% at peak ground acceleration 0.4g. In the concrete compression fracture, the limit state arrival rate was 100% at peak ground acceleration 0.2g.

Keywords: allowable stress, limit state, safety factor, peak ground acceleration

Procedia PDF Downloads 203