Search results for: Learning materials

Authors: Ahmed Slami, Med El Amine Brixi Nigassa, Nassima Labdelli, Sofiane Soulimane, Arnaud Pothier

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Many people suffer from diabetes, a disease marked by abnormal levels of sugar in the blood; 285 million people have diabetes, 6.6% of the world adult population (in 2010), according to the International Diabetes Federation. Insulin medicament is invented to be injected into the body. Generally, the injection requires the patient to do it manually. However, in many cases he will be unable to inject the drug, saw that among the side effects of hyperglycemia is the weakness of the whole body. The researchers designed a medical device that injects insulin too autonomously by using micro-pumps. Many micro-pumps of concepts have been investigated during the last two decades for injecting molecules in blood or in the body. However, all these micro-pumps are intended for slow infusion of drug (injection of few microliters by minute). Now, the challenge is to develop micro-pumps for fast injections (1 microliter in 10 seconds) with accuracy of the order of microliter. Recently, studies have shown that only piezoelectric actuators can achieve this performance, knowing that few systems at the microscopic level were presented. These reasons lead us to design new smart microsystems injection drugs. Therefore, many technological advances are still to achieve the improvement of materials to their uses, while going through their characterization and modeling action mechanisms themselves. Moreover, it remains to study the integration of the piezoelectric micro-pump in the microfluidic platform features to explore and evaluate the performance of these new micro devices. In this work, we propose a new micro-pump model based on piezoelectric actuation with a new design. Here, we use a finite element model with Comsol software. Our device is composed of two pumping chambers, two diaphragms and two actuators (piezoelectric disks). The latter parts will apply a mechanical force on the membrane in a periodic manner. The membrane deformation allows the fluid pumping, the suction and discharge of the liquid. In this study, we present the modeling results as function as device geometry properties, films thickness, and materials properties. Here, we demonstrate that we can achieve fast injection. The results of these simulations will provide quantitative performance of our micro-pumps. Concern the spatial actuation, fluid rate and allows optimization of the fabrication process in terms of materials and integration steps.

Keywords: COMSOL software, piezoelectric, micro-pump, microfluidic

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Authors: N. Jena, Nitin Seth

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Globalization and free trade has forced the organizations to continuously rethink and rework on the increasing cost of logistics. World wide, it is visualized that on one side the steel sector is witnessing rapid growth and on the other side it is facing huge challenges in terms of availability of raw materials for uninterrupted production. Inbound logistics also gains significant importance for ensuring the timely availability of raw materials. It is seen that in Indian steel sector logistic cost is still very large and challenging. Effectively managing the inbound logistics in steel decides the profitability and serviceability of the organization. Effective management of inbound logistics also has a major role on the inventory of the organization. Since, the logistics for the steel industry in India is evolving rapidly and it is the interplay of infrastructure, technology and new types of service providers that will define whether the industry is able to help its customers to reduce their logistics costs. Integration of Logistics has been treated as one of the most potential area for the companies to provide a base for cost reduction. In spite of the proven area for benefits for the industry, it is very surprising that none of the researchers have explored this area. Although, many researchers explored the subject of logistics in steel industry, but their perspective varied from exploring and understanding the associated cost and finding out the relations between them. Visualizing a potential gap, the present research is under taken to explore the integration opportunities in inbound logistics for steel sector. Typically in Indian steel sector where in most of the manufacturers depend on imported materials for processing the logistics is very challenging and accounts for transactions at supplier – who is situated in different country, shipper- who is transporting the material to the host country, regulators in both countries-that include customs and various clearing agents, local logistics service providers and local transporters/handlers. It is seen that In bound logistics cost in the steel sector is very high and accounts for about 15-16% of the turn over, integration of information across different channels provides and opportunity for improvements and growth of the organization. In the present paper, a case of leading steel manufacturer has been taken and the potentials for integration of information across various partners have been identified. The paper provides the identification of grey area in steel sector for major improvements in cycle time and lowering the inventories by integration of information. Finally, based on integration of information, the paper presents a business information framework for steel sector.

Keywords: integration, steel sectors, suppliers, shippers, customs and cargo agents, transporters

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

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

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

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Authors: Victoria L. Nkosi, Parvaneh Farhangpour

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Often a Grade 12 certificate is perceived as a passport to tertiary education and the minimum requirement to enter the world of work. In spite of its importance, many students do not make this milestone in South Africa. It is important to find out why so many students still fail in spite of transformation in the education system in the post-apartheid era. Given the complexity of education and its context, this study adopted a case study design to examine one historically underperforming high school in Bushbuckridge, Mpumalanga Province, South Africa in 2013. The aim was to gain a understanding of the inner and outer school contextual factors associated with the high failure rate among Grade 12 students.  Government documents and reports were consulted to identify factors in the district and the village surrounding the school and a student survey was conducted to identify school, home and student factors. The randomly-sampled half of the population of Grade 12 students (53) participated in the survey and quantitative data are analyzed using descriptive statistical methods. The findings showed that a host of factors is at play. The school is located in a village within a municipality which has been one of the poorest three municipalities in South Africa and the lowest Grade 12 pass rate in the Mpumalanga province.   Moreover, over half of the families of the students are single parents, 43% are unemployed and the majority has a low level of education. In addition, most families (83%) do not have basic study materials such as a dictionary, books, tables, and chairs. A significant number of students (70%) are over-aged (+19 years old); close to half of them (49%) are grade repeaters. The school itself lacks essential resources, namely computers, science laboratories, library, and enough furniture and textbooks. Moreover, teaching and learning are negatively affected by the teachers’ occasional absenteeism, inadequate lesson preparation, and poor communication skills. Overall, the continuous low performance of students in this school mirrors the vicious circle of multiple negative conditions present within and outside of the school. The complexity of factors associated with the underperformance of Grade 12 students in this school calls for a multi-dimensional intervention from government and stakeholders. One important intervention should be the placement of over-aged students and grade-repeaters in suitable educational institutions for the benefit of other students.

Keywords: inner context, outer context, over-aged students, vicious cycle

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Authors: Mariia Zhuldybina, Ahmed Moulay, Mirko Torres, Mike Rozel, Ngoc-Duc Trinh, Chloé Bois

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To reduce the global waste of perishable goods, a solution for monitoring and traceability of their environmental conditions is needed. Temperature is the most controllable environmental parameter determining the kinetics of physical, chemical, and microbial spoilage in food products. To store the time-temperature information, time-temperature indicator (TTI) is a promising solution. Printed electronics (PE) has shown a great potential to produce customized electronic devices using flexible substrates and inks with different functionalities. We propose to fabricate a hybrid printed TTI using environmentally friendly materials. The real-time TTI profile can be stored and transmitted to the smartphone via Near Field Communication (NFC). To ensure environmental performance, Canadian Green Electronics NSERC Network is developing green materials for the ink formulation with different functionalities. In terms of substrate, paper-based electronics has gained the great interest for utilization in a wide area of electronic systems because of their low costs in setup and methodology, as well as their eco-friendly fabrication technologies. The main objective is to deliver a prototype of TTI using small-scale printed techniques under typical printing conditions. All sub-components of the smart labels, including a memristor, a battery, an antenna compatible with NFC protocol, and a circuit compatible with integration performed by an offsite supplier will be fully printed with flexography or flat-bed screen printing.

Keywords: NFC, printed electronics, time-temperature indicator, hybrid electronics

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Authors: M. Vassou, A. Karasimos

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A primary concern in the field of Second Language Acquisition (SLA) research is to determine the innate mechanisms of second language learning and acquisition through the systematic study of a learner's interlanguage. Errors emerge while a learner attempts to communicate using the target-language and can be seen either as the observable linguistic product of the latent cognitive and language process of mental representations or as an indispensable learning mechanism. Therefore, the study of the learner’s erroneous forms may depict the various strategies and mechanisms that take place during the language acquisition process resulting in deviations from the target-language norms and difficulties in communication. Mapping the erroneous utterances of a late adult learner in the process of acquiring Greek as a second language constitutes one of the main aims of this study. For our research purposes, we created an error-tagged learner corpus composed of the participant’s written texts produced throughout a period of a 4- year instructed language acquisition. Error analysis and interlanguage theory constitute the methodological and theoretical framework, respectively. The research questions pertain to the learner's most frequent errors per linguistic category and per year as well as his choices concerning the Greek Article System. According to the quantitative analysis of the data, the most frequent errors are observed in the categories of the stress system and syntax, whereas a significant fluctuation and/or gradual reduction throughout the 4 years of instructed acquisition indicate the emergence of developmental stages. The findings with regard to the article usage bespeak fossilization of erroneous structures in certain contexts. In general, our results point towards the existence and further development of an established learner’s (inter-) language system governed not only by mother- tongue and target-language influences but also by the learner’s assumptions and set of rules as the result of a complex cognitive process. It is expected that this study will contribute not only to the knowledge in the field of Greek as a second language and SLA generally, but it will also provide an insight into the cognitive mechanisms and strategies developed by multilingual learners of late adulthood.

Keywords: Greek as a second language, error analysis, interlanguage, late adult learner

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Authors: Patrick Ebong Ebewo

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The trend of high unemployment levels globally is a growing concern, which suggests that university students especially those studying the creative industries are most likely to face unemployment upon completion of their studies. Therefore the effort of university in fostering entrepreneurial knowledge is equally important to the development of student’s soft skill. The purpose of this paper is to assess the significance of perceived university environment and perceived educational support that influencing University students’ intention in starting their own business in the future. Thus, attempting to answer the question 'How does perceived university environment affect students’ attitude towards entrepreneurship as a career option, perceived entrepreneurial abilities, subjective norm and entrepreneurial intentions?' The study is based on the Theory of Planned Behaviour model adapted from previous studies and empirically tested on graduates at the Tshwane University of Technology. A sample of 150 graduates from the Arts and Design graduates took part in the study and data collected were analysed using structural equation modelling (SEM). Our findings seem to suggest the indirect impact of perceived university environment on entrepreneurial intention through perceived environment support and perceived entrepreneurial abilities. Thus, any increase in perceived university environment might influence students to become entrepreneurs. Based on these results, it is recommended that: (a) Tshwane University of Technology and other universities of technology should establish an ‘Entrepreneurship Internship Programme’ as a tool for stimulated work integrated learning. Post-graduation intervention could be implemented by the development of a ‘Graduate Entrepreneurship Program’ which should be embedded in the Bachelor of Technology (B-Tech now Advance Diploma) and Postgraduate courses; (b) Policymakers should consider the development of a coherent national policy framework that addresses entrepreneurship for the Arts/creative industries sector. This would create the enabling environment for the evolution of Higher Education Institutions from merely Teaching, Learning & Research to becoming drivers for creative entrepreneurship.

Keywords: business venture, entrepreneurship education, entrepreneurial intent, university environment

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Authors: Tiantian Feng

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There is a dearth of research on the literary circle as a teaching strategy in English as a Foreign Language (EFL) classes in Chinese colleges and universities and even fewer empirical studies on its impacts. In this one-quarter, design-based project, the researcher aims to increase students’ engagement, cooperation, and, on top of that, reading comprehension performance by utilizing a researcher-developed, adapted reading circle model in an EFL reading course at a Chinese college. The model also integrated team-based learning and portfolio assessment, with an emphasis on the specialization of individual responsibilities, contributions, and outcomes in reading projects, with the goal of addressing current issues in EFL classes at Chinese colleges, such as passive learning, test orientation, ineffective and uncooperative teamwork, and lack of dynamics. In this quasi-experimental research, two groups of students enrolled in the course were invited to participate in four in-class team projects, with the intervention class following the adapted literature circle model and team members rotating as Leader, Coordinator, Brain trust, and Reporter. The researcher/instructor used a sequential explanatory mixed-methods approach to quantitatively analyze the final grades for the pre-and post-tests, as well as individual scores for team projects and will code students' artifacts in the next step, with the results to be reported in a subsequent paper(s). Initial analysis showed that both groups saw an increase in final grades, but the intervention group enjoyed a more significant boost, suggesting that the adapted reading circle model is effective in improving students’ reading comprehension performance. This research not only closes the empirical research gap of literature circles in college EFL classes in China but also adds to the pool of effective ways to optimize reading comprehension performance and class performance in college EFL classes.

Keywords: literature circle, EFL teaching, college english reading, reading comprehension

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Authors: Ram Prasad Baral

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A large number of herb materials contain Essential Oils with extensive bioactivities. Acknowledging the importance of plants and its medicinal value, extraction of Essential Oil had been done using Steam Distillation method. In this project, Steam Distillation was used to extract oil from different plant materials like Chamomilla recutita (L.) Rauschert, Artemisia Vulgaris L, Rhododendron anthopogon D. Don, Cymbopogon nardus L, Andropogon nardus, Cinnamomum tamala, Juniperus spp, Cymbopohonflexuosus flexuous, Mantha Arvensia, Nardostachys Jatamansi, Wintergreen Essential Oil, and Valeriana Officinalis. Research has confirmed centuries of practical use of essential oils, and we now know that the 'fragrant pharmacy' contains compounds with an extremely broad range of biochemical effects. Essential oils are so termed as they are believed to represent the very essence of odor and flavor. The recovery of Essential Oil from the raw botanical starting material is very important since the quality of the oil is greatly influenced during this step. There is a variety of methods for obtaining volatile oils from plants. Steam distillation method was found to be one of the promising techniques for the extraction of essential oil from plants as reputable distiller will preserve the original qualities of the plant. The distillation was conducted in Clevenger apparatus in which boiling, condensing, and decantation was done. Analysis of essential oil was done using Gas Chromatography-Mass Spectrometer apparatus, which gives evaluates essential oil qualitatively and quantitatively. The volume of essential oil obtained was changing with respect to temperature and time of heating.

Keywords: Chamomilla recutita (L.) Rauschert, Artemisia Vulgaris L, Rhododendron anthopogon D. Don, Cymbopogon nardus L, Andropogon nardus, Cinnamomum tamala, Juniperus spp, Cymbopohonflexuosus flexuous, Mantha

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Authors: Ebipatei Victoria Tunyan, T. A. Cao, Cheol Young Ock

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Detecting subjectively biased statements is a vital task. This is because this kind of bias, when present in the text or other forms of information dissemination media such as news, social media, scientific texts, and encyclopedias, can weaken trust in the information and stir conflicts amongst consumers. Subjective bias detection is also critical for many Natural Language Processing (NLP) tasks like sentiment analysis, opinion identification, and bias neutralization. Having a system that can adequately detect subjectivity in text will boost research in the above-mentioned areas significantly. It can also come in handy for platforms like Wikipedia, where the use of neutral language is of importance. The goal of this work is to identify the subjectively biased language in text on a sentence level. With machine learning, we can solve complex AI problems, making it a good fit for the problem of subjective bias detection. A key step in this approach is to train a classifier based on BERT (Bidirectional Encoder Representations from Transformers) as upstream model. BERT by itself can be used as a classifier; however, in this study, we use BERT as data preprocessor as well as an embedding generator for a Bi-LSTM (Bidirectional Long Short-Term Memory) network incorporated with attention mechanism. This approach produces a deeper and better classifier. We evaluate the effectiveness of our model using the Wiki Neutrality Corpus (WNC), which was compiled from Wikipedia edits that removed various biased instances from sentences as a benchmark dataset, with which we also compare our model to existing approaches. Experimental analysis indicates an improved performance, as our model achieved state-of-the-art accuracy in detecting subjective bias. This study focuses on the English language, but the model can be fine-tuned to accommodate other languages.

Keywords: subjective bias detection, machine learning, BERT–BiLSTM–Attention, text classification, natural language processing

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Authors: Kai Warsoenke, Maik Mackiewicz

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To achieve a high quality of assembled car body structures, tolerancing is used to ensure a geometric accuracy of the single car body parts. There are two main techniques to determine the required tolerances. The first is tolerance analysis which describes the influence of individually tolerated input values on a required target value. Second is tolerance synthesis to determine the location of individual tolerances to achieve a target value. Both techniques are based on classical statistical methods, which assume certain probability distributions. To ensure competitiveness in both saturated and dynamic markets, production processes in vehicle manufacturing must be flexible and efficient. The dimensional specifications selected for the individual body components and the resulting assemblies have a major influence of the quality of the process. For example, in the manufacturing of forming tools as operating equipment or in the higher level of car body assembly. As part of the metrological process monitoring, manufactured individual parts and assemblies are recorded and the measurement results are stored in databases. They serve as information for the temporary adjustment of the production processes and are interpreted by experts in order to derive suitable adjustments measures. In the production of forming tools, this means that time-consuming and costly changes of the tool surface have to be made, while in the body shop, uncertainties that are difficult to control result in cost-intensive rework. The stored measurement results are not used to intelligently design tolerances in future processes or to support temporary decisions based on real-world geometric data. They offer potential to extend the tolerancing methods through data analysis and machine learning models. The purpose of this paper is to examine real-world measurement data from individual car body components, as well as assemblies, in order to develop an approach for using the data in short-term actions and future projects. For this reason, the measurement data will be analyzed descriptively in the first step in order to characterize their behavior and to determine possible correlations. In the following, a database is created that is suitable for developing machine learning models. The objective is to create an intelligent way to determine the position and number of measurement points as well as the local tolerance range. For this a number of different model types are compared and evaluated. The models with the best result are used to optimize equally distributed measuring points on unknown car body part geometries and to assign tolerance ranges to them. The current results of this investigation are still in progress. However, there are areas of the car body parts which behave more sensitively compared to the overall part and indicate that intelligent tolerancing is useful here in order to design and control preceding and succeeding processes more efficiently.

Keywords: automotive production, machine learning, process optimization, smart tolerancing

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Authors: Rasha F. Sharaf

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Treatment of dental caries in young children is considered a great challenge for all dentists, especially with uncooperative children. Recently non-invasive techniques have been highlighted as they alleviate the need for local anesthesia and other painful procedures during management of carious teeth and, at the same time, increase the success rate of the treatment done. Silver Diamine Fluoride (SDF) is one of the most effective cariostatic materials that arrest the progression of carious lesions and aid in remineralizing the demineralized tooth structure. Both fluoride and silver ions proved to have an antibacterial action and aid in the precipitation of an insoluble layer that prevents further decay. At the same time, Moringa proved to have an effective antibacterial action against different types of bacteria, therefore, it can be used as a non-invasive technique for the management of caries in children. One of the important theories for the control of caries is by depriving the cariogenic bacteria from nutrients causing their starvation and death, which can be achieved by applying stainless steel crown on primary molars with carious lesions which are not involving the pulp, and this technique is known as Hall technique. The success rate of the Hall technique can be increased by arresting the carious lesion using either SDF or Moringa and gaining the benefit of their antibacterial action. Multiple clinical cases with 1 year follow up will be presented, comparing different treatment options, and using various materials and techniques for non-invasive and non-painful management of carious primary teeth.

Keywords: SDF, hall technique, carious primary teeth, moringa extract

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Authors: Tanveer Iqbal, Saima Yasin, Muhammad Zafar, Ahmad Shakeel, Fahad Nazir, Paul F. Luckham

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The contact performance of polymeric composites is dependent on the localized mechanical properties of materials. This is particularly important for fiber oriented polymeric materials where self-lubrication from top layers has been the basic requirement. The nanoindentation response of fiber reinforced poly(etheretherketone), PEEK, composites have been evaluated to determine the near-surface mechanical characteristics. Load-displacement compliance, hardness and elastic modulus data based on contact compliance mode (CSM) indentation of carbon fiber oriented and glass fiber oriented PEEK composites are reported as a function of indentation contact displacement. The composite surfaces were indented to a maximum penetration depth of 5µm using Berkovich tip indenter. A typical multiphase response of the composite surface is depicted from analysis of the indentation data for the composites, showing presence of polymer matrix, fibers, and interphase regions. The observed experimental results show that although the surface mechanical properties of carbon fiber based PEEK composite were comparatively higher, the properties of matrix material were seen to be increased in the presence of glass fibers. The experimental methodology may provide a convenient means to understand morphological description of the multimodal polymeric composites.

Keywords: nanoindentation, PEEK, modulus, hardness, plasticization

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Authors: Dmitriy Babenko, Sergey Yegorov, Ilya Korshukov, Aidana Sultanbekova, Valentina Barkhanskaya, Tatiana Bashirova, Yerzhan Zhunusov, Yevgeniya Li, Viktoriya Parakhina, Svetlana Kolesnichenko, Yeldar Baiken, Aruzhan Pralieva, Zhibek Zhumadilova, Matthew S. Miller, Gonzalo H. Hortelano, Anar Turmuhambetova, Antonella E. Chesca, Irina Kadyrova

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Introduction: The rapidly evolving COVID-19 pandemic, along with the re-emergence of pathogens causing acute respiratory infections (ARI), has necessitated the development of novel diagnostic tools to differentiate various causes of ARI. MALDI-MS, due to its wide usage and affordability, has been proposed as a potential instrument for diagnosing SARS-CoV-2 versus non-SARS-CoV-2 ARI. The aim of this study was to investigate the potential of MALDI-MS in conjunction with a machine learning model to accurately distinguish between symptomatic infections caused by SARS-CoV-2 and non-SARS-CoV-2 during both the early and later phases of the pandemic. Furthermore, this study aimed to analyze mass spectrometry (MS) data obtained from nasal swabs of healthy individuals. Methods: We gathered mass spectra from 252 samples, comprising 108 SARS-CoV-2-positive samples obtained in 2020 (Covid 2020), 7 SARS-CoV- 2-positive samples obtained in 2023 (Covid 2023), 71 samples from symptomatic individuals without SARS-CoV-2 (Control non-Covid ARVI), and 66 samples from healthy individuals (Control healthy). All the samples were subjected to RT-PCR testing. For data analysis, we employed the caret R package to train and test seven machine-learning algorithms: C5.0, KNN, NB, RF, SVM-L, SVM-R, and XGBoost. We conducted a training process using a five-fold (outer) nested repeated (five times) ten-fold (inner) cross-validation with a randomized stratified splitting approach. Results: In this study, we utilized the Covid 2020 dataset as a case group and the non-Covid ARVI dataset as a control group to train and test various machine learning (ML) models. Among these models, XGBoost and SVM-R demonstrated the highest performance, with accuracy values of 0.97 [0.93, 0.97] and 0.95 [0.95; 0.97], specificity values of 0.86 [0.71; 0.93] and 0.86 [0.79; 0.87], and sensitivity values of 0.984 [0.984; 1.000] and 1.000 [0.968; 1.000], respectively. When examining the Covid 2023 dataset, the Naive Bayes model achieved the highest classification accuracy of 43%, while XGBoost and SVM-R achieved accuracies of 14%. For the healthy control dataset, the accuracy of the models ranged from 0.27 [0.24; 0.32] for k-nearest neighbors to 0.44 [0.41; 0.45] for the Support Vector Machine with a radial basis function kernel. Conclusion: Therefore, ML models trained on MALDI MS of nasopharyngeal swabs obtained from patients with Covid during the initial phase of the pandemic, as well as symptomatic non-Covid individuals, showed excellent classification performance, which aligns with the results of previous studies. However, when applied to swabs from healthy individuals and a limited sample of patients with Covid in the late phase of the pandemic, ML models exhibited lower classification accuracy.

Keywords: SARS-CoV-2, MALDI-TOF MS, ML models, nasopharyngeal swabs, classification

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Authors: A. Zuchowska, A. Buta, M. Mazurkiewicz-Pawlicka, A. Malolepszy, L. Stobinski, Z. Brzozka

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In recent years, graphene-based materials are finding more and more applications in biological science. As a thin, tough, transparent and chemically resistant materials, they appear to be a very good material for the production of implants and biosensors. Interest in graphene derivatives also resulted at the beginning of research about the possibility of their application in cancer therapy. Currently, the analysis of their potential use in photothermal therapy and as a drug carrier is mostly performed. Moreover, the direct anticancer properties of graphene-based materials are also tested. Nowadays, cytotoxic studies are conducted on in vitro cell culture in standard culture vessels (macroscale). However, in this type of cell culture, the cells grow on the synthetic surface in static conditions. For this reason, cell culture in macroscale does not reflect in vivo environment. The microfluidic systems, called Lab-on-a-chip, are proposed as a solution for improvement of cytotoxicity analysis of new compounds. Here, we present the evaluation of cytotoxic properties of graphene oxide (GO) on breast, liver and colon cancer cell line in a microfluidic system in two spatial models (2D and 3D). Before cell introduction, the microchambers surface was modified by the fibronectin (2D, monolayer) and poly(vinyl alcohol) (3D, spheroids) covering. After spheroid creation (3D) and cell attachment (2D, monolayer) the selected concentration of GO was introduced into microsystems. Then monolayer and spheroids viability/proliferation using alamarBlue® assay and standard microplate reader was checked for three days. Moreover, in every day of the culture, the morphological changes of cells were determined using microscopic analysis. Additionally, on the last day of the culture differential staining using Calcein AM and Propidium iodide were performed. We were able to note that the GO has an influence on all tested cell line viability in both monolayer and spheroid arrangement. We showed that GO caused higher viability/proliferation decrease for spheroids than a monolayer (this was observed for all tested cell lines). Higher cytotoxicity of GO on spheroid culture can be caused by different geometry of the microchambers for 2D and 3D cell cultures. Probably, GO was removed from the flat microchambers for 2D culture. Those results were also confirmed by differential staining. Comparing our results with the studies conducted in the macroscale, we also proved that the cytotoxic properties of GO are changed depending on the cell culture conditions (static/ flow).

Keywords: cytotoxicity, graphene oxide, monolayer, spheroid

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Authors: Mosaad Attia Elkasaby

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The crude oil contains paraffines, aromatics, and asphaltenes in addition to some organic impurities, with increasing demands to reduce the cost of crude oil production, the uses of a pour point depressant is mandatory to maintain good flow rate. The wax materials cause many problems during production, storage, and transport, especially at low temperature, as these waxes tend, at low temperatures, to precipitate on the wall lines, thus leads to the high viscosity of crude oil and impede the flow rate, which represents an additional burden for crude oil pumping system from the place of production to the refinery. There are many ways to solve this problem, including, but not limited to, heat the crude and the use of organic solvents. But one of the most important disadvantages of these methods is the high economic cost. The aim of this innovation is to manufacture some polymeric materials (polymers based on aniline) that are processed locally that can be used as a pour point depressant of crude oil. For the first time, polymer based on aniline is modified and used with a number of organic solvents and tested with solvent (Styrene). It was found that the polymer based on aniline, when modified, had full solubility in styrene, unlike other organic solvent that was used in the past, such as chloroform and toluene. We also used a new solvent (PONA) that is obtained from the process of hydrotreating and separation of straight run naphtha to dissolve polymer based on aniline as a pour point depressant of crude oil. This innovative include studies conducted on highly paraffinic crude oil (C.O.1 and C.O.2). On using concentration (2500 ppm) of polymer based on aniline, the pour point of crude oil has decreased from +33 to - 9°C in case of crude oil (C.O.1) and from + 42 to – 6°C in case crude oil (C.O.2) at the same concentration.

Keywords: PPD, aniline, paraffinic crude oils, polymers

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Authors: Aliya K. Salahova

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Scientific thinking, characterized by purposeful knowledge-seeking and the harmonization of theory and facts, holds a crucial role in preparing young minds for an increasingly complex and technologically advanced world. This abstract presents a research study aimed at fostering scientific thinking in early childhood, focusing on children aged 5 to 9 years, through experiential learning in Kids Science Labs (STEM). The study utilized a longitudinal exploration design, spanning 240 weeks from September 2018 to April 2023, to evaluate the effectiveness of the Kids Science Labs program in developing scientific thinking skills. Participants in the research comprised 72 children drawn from local schools and community organizations. Through a formative psychology-pedagogical experiment, the experimental group engaged in weekly STEM activities carefully designed to stimulate scientific thinking, while the control group participated in daily art classes for comparison. To assess the scientific thinking abilities of the participants, a registration table with evaluation criteria was developed. This table included indicators such as depth of questioning, resource utilization in research, logical reasoning in hypotheses, procedural accuracy in experiments, and reflection on research processes. The data analysis revealed dynamic fluctuations in the number of children at different levels of scientific thinking proficiency. While the development was not uniform across all participants, a main leading factor emerged, indicating that the Kids Science Labs program and formative experiment exerted a positive impact on enhancing scientific thinking skills in children within this age range. The study's findings support the hypothesis that systematic implementation of STEM activities effectively promotes and nurtures scientific thinking in children aged 5-9 years. Enriching education with a specially planned STEM program, tailoring scientific activities to children's psychological development, and implementing well-planned diagnostic and corrective measures emerged as essential pedagogical conditions for enhancing scientific thinking abilities in this age group. The results highlight the significant and positive impact of the systematic-activity approach in developing scientific thinking, leading to notable progress and growth in children's scientific thinking abilities over time. These findings have promising implications for educators and researchers, emphasizing the importance of incorporating STEM activities into educational curricula to foster scientific thinking from an early age. This study contributes valuable insights to the field of science education and underscores the potential of STEM-based interventions in shaping the future scientific minds of young children.

Keywords: Scientific thinking, education, STEM, intervention, Psychology, Pedagogy, collaborative learning, longitudinal study

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Authors: Sara Torabi, Sadegh Khazalpour, Mahdi Jamshidi

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Nitro aromatic compounds are valuable materials because of their applications in the preparation of chemical intermediates for the synthesis of dyes, plastics, perfumes, energetic materials, and pharmaceuticals. Chemical and electrochemical procedures are reported for nitration of aromatic compounds. Flavonoid derivatives are present in many vegetables and fruits and are constituent of many common pharmaceuticals and dietary supplements. Electrochemistry provides very versatile means for the electrosynthesis, mechanistic and kinetic studies. To the best of our knowledge, and despite the importance of these compounds in numerous scientific fields, there are no reports on the electrochemical nitration of Quercetin derivatives. Herein, we describe a green electrochemical synthesis of a nitro compound. In this work, electrochemical oxidation of Quercetin has been studied in the presence of nitrite ion as a nucleophile in acetate buffer solution (c = 0.2 M, pH = 6.0), by means of cyclic voltammetry and controlled-potential coulometry. The results indicate the participation of produced o-benzoquinones in Michael reaction with nitrite ion (in the divided cell) to form the corresponding nitro diol (EC mechanism). The purity of product and characterization was done using ¹H NMR, ¹³C NMR, FTIR spectroscopic techniques. The presented strategies use a water/ethanol mixture as solvent. Ethanol as cosolvent was also used in the previous studies because of its low cost, safety, easy availability, recyclability, bioproductability, and biodegradability. These strategies represent a one-pot and facile process for the synthesis of nitro compound in high yield and purity under green conditions.

Keywords: electrochemical synthesis, green chemistry, cyclic voltammetry, molecular docking

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Authors: Canan Duzan

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For most language learners, mastery of the speaking skill is the proof of the mastery of the foreign language. On the other hand, the speaking skill is considered as the most difficult aspect of language learning to develop for both learners and teachers. Especially in countries like Turkey where exposure to the target language is minimum and resources and opportunities provided for language practice are scarce, teaching and learning to speak the language become a real struggle for teachers and learners alike. Data collected from students, instructors, faculty members and the business sector in needs analysis studies conducted previously at Middle East Technical University (METU) consistently revealed the need for addressing the problem of lack of confidence in speaking English. Action was taken during the design of the only EAP speaking course offered in Modern Languages Department since lack of confidence is considered to be a serious barrier for effective communication and causes learners to suffer from insecurity, uncertainty and fear. “Confidence building” served as the guiding principle in the syllabus design, nature of the tasks created for the course and the assessment procedures to help learners become more confident speakers of English. In order to see the effectiveness of the decisions made during the design phase of the course and whether students become more confident speakers upon completion of the course, a case study was carried out with 100 students at METU. A questionnaire including both Likert-Scale and open-ended items were administered to students to collect data and this data were analyzed using the SPSS program. Group interviews were also carried out to gain more insight into the effectiveness of the course in terms of building speaking confidence. This presentation will explore the specific actions taken to develop students’ confidence based on the findings of program evaluation studies and to what extent the students believe these actions to be effective in improving their confidence. The unique design of this course and strategies adopted for confidence building are highly applicable in other EAP contexts and may yield similar positive results.

Keywords: confidence, EAP, speaking, strategy

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Authors: Ian O'Loughlin

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Memory networks aim to integrate some of the recent successes in machine learning with a dynamic memory base that can be updated and deployed in artificial reasoning tasks. These models involve training networks to identify, update, and operate over stored elements in a large memory array in order, for example, to ably perform question and answer tasks parsing real-world and simulated discourses. This family of approaches still faces numerous challenges: the performance of these network models in simulated domains remains considerably better than in open, real-world domains, wide-context cues remain elusive in parsing words and sentences, and even moderately complex sentence structures remain problematic. This innovation, employing an array of stored and updatable ‘memory’ elements over which the system operates as it parses text input and develops responses to questions, is a compelling one for at least two reasons: first, it addresses one of the difficulties that standard machine learning techniques face, by providing a way to store a large bank of facts, offering a way forward for the kinds of long-term reasoning that, for example, recurrent neural networks trained on a corpus have difficulty performing. Second, the addition of a stored long-term memory component in artificial reasoning seems psychologically plausible; human reasoning appears replete with invocations of long-term memory, and the stored but dynamic elements in the arrays of memory networks are deeply reminiscent of the way that human memory is readily and often characterized. However, this apparent psychological plausibility is belied by a recent turn in the study of human memory in cognitive science. In recent years, the very notion that there is a stored element which enables remembering, however dynamic or reconstructive it may be, has come under deep suspicion. In the wake of constructive memory studies, amnesia and impairment studies, and studies of implicit memory—as well as following considerations from the cognitive neuroscience of memory and conceptual analyses from the philosophy of mind and cognitive science—researchers are now rejecting storage and retrieval, even in principle, and instead seeking and developing models of human memory wherein plasticity and dynamics are the rule rather than the exception. In these models, storage is entirely avoided by modeling memory using a recurrent neural network designed to fit a preconceived energy function that attains zero values only for desired memory patterns, so that these patterns are the sole stable equilibrium points in the attractor network. So although the array of long-term memory elements in memory networks seem psychologically appropriate for reasoning systems, they may actually be incurring difficulties that are theoretically analogous to those that older, storage-based models of human memory have demonstrated. The kind of emergent stability found in the attractor network models more closely fits our best understanding of human long-term memory than do the memory network arrays, despite appearances to the contrary.

Keywords: artificial reasoning, human memory, machine learning, neural networks

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Authors: Malephole Philomena Sefotho

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Nowadays, it is a fact that the majority of people, worldwide, are bilingual rather than monolingual due to the surge of globalisation and mobility. Consequently, bilingual education is a topical issue of discussion among researchers. Several studies that have focussed on it have highlighted the importance and need for incorporating learners’ linguistic repertoires in multilingual classrooms and move away from the colonial approach which is a monolingual bias – one language at a time. Researchers pointed out that a systematic approach that involves the concurrent use of languages and not a separation of languages must be implemented in bilingual classroom settings. Translanguaging emerged as a systematic approach that assists learners to make meaning of their world and it involves allowing learners to utilize all their linguistic resources in their classrooms. The South African language policy also room for diverse languages use in bi/multilingual classrooms. This study, therefore, sought to explore how teachers apply translanguaging in bilingual classrooms in incorporating learners’ linguistic repertoires. It further establishes teachers’ perspectives in the use of more than one language in teaching and learning. The participants for this study were language teachers who teach at bilingual primary schools in Johannesburg in South Africa. Semi-structured interviews were conducted to establish their perceptions on the concurrent use of languages. Qualitative research design was followed in analysing data. The findings showed that teachers were reluctant to allow translanguaging to take place in their classrooms even though they realise the importance thereof. Not allowing bilingual learners to use their linguistic repertoires has resulted in learners’ negative attitude towards their languages and contributed in learners’ loss of their identity. This article, thus recommends a drastic change to decolonised approaches in teaching and learning in multilingual settings and translanguaging as a decolonial move where learners are allowed to translanguage freely in their classroom settings for better comprehension and making meaning of concepts and/or related ideas. It further proposes continuous conversations be encouraged to bring eminent cultural and linguistic genocide to a halt.

Keywords: bilingualism, decolonisation, linguistic repertoires, translanguaging

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Authors: Godaye Gobena Gomiole

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The purpose of this study was to investigate school context-related factors that affect principals' instructional leadership competence in primary schools in Tarcha Town, Ethiopia. A qualitative case study research design was used. The data were collected through semi-structured interviews and document analysis. Twelve senior principals were included in the study through purposive sampling. Interviews were used to collect in-depth data. The data was analyzed thematically. The findings of the study indicated that primary school principals face both internal and external challenges. Internally, they face limited knowledge and skills, a lack of courage and commitment, and administrative work overload. Their external challenges included negative attitudes from parents and teachers, a lack of instructional materials, and little support from local education authorities. Consequently, they can't serve effectively as instructional leaders or resource people. Based on the findings, it is recommended that the Ministry of Education, South West Regional Education Bureau, Dawuro Zone Education Department, and Tarcha Town Administration Education Officers and Cluster Supervisors regularly monitor and support school leaders and prepare and provide pertinent teaching materials and training so that the principals can lead in the capacity that is appropriate for the position.

Keywords: instructional leadership, primary school, principals, school context related factors

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Authors: Mikael Soini, Kari Björn

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Metropolia University of Applied Sciences (MUAS) Information and Communication Technology (ICT) Degree Programme provides full-time Bachelor-level undergraduate studies. ICT Degree Programme has seven different major options; this paper focuses on Health Technology. In Health Technology, a significant curriculum change in 2014 enabled transition from fragmented curriculum including dozens of courses to a new integrated curriculum built around three 30 ECTS themes. This paper focuses especially on the second theme called Customer Oriented Software Applications. From students’ point of view, the goal of this theme is to get familiar with existing health related ICT solutions and systems, understand business around health technology, recognize social and healthcare operating principles and services, and identify customers and users and their special needs and perspectives. This also acts as a background for health related web application development. Built web application is tested, developed and evaluated with real users utilizing versatile user centred development methods. This paper presents experiences obtained from the first implementation of Customer Oriented Software Applications theme. Student feedback was gathered with two questionnaires, one in the middle of the theme and other at the end of the theme. Questionnaires had qualitative and quantitative parts. Similar questionnaire was implemented in the first theme; this paper evaluates how the theme-based integrated curriculum has progressed in Health Technology major by comparing results between theme 1 and 2. In general, students were satisfied for the implementation, timing and synchronization of the courses, and the amount of work. However there is still room for development. Student feedback and teachers’ observations have been and will be used to develop the content and operating principles of the themes and whole curriculum.

Keywords: engineering education, integrated curriculum, learning and teaching methods, learning experience

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Authors: Yi-Hsiang Pan, Chen-Hui Huang, Wei-Ting Hsu

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The purposes of the study were to understand these topics as follows: 1. To explore the effect of merging teaching personal and social responsibility (TPSR) with sports education model on students' game performance and responsibility. 2. To explore the effect of sports education model on students' game performance and responsibility. 3. To compare the difference between "merging TPSR with sports education model" and "sports education model" on students' game performance and responsibility. The participants include three high school physical education teachers and six physical education classes. Every teacher teaches an experimental group and a control group. The participants had 121 students, including 65 students in the experimental group and 56 students in the control group. The research methods had game performance assessment, questionnaire investigation, interview, focus group meeting. The research instruments include personal and social responsibility questionnaire and game performance assessment instrument. Paired t-test test and MANCOVA were used to test the difference between "merging TPSR with sports education model" and "sports education model" on students' learning performance. 1) "Merging TPSR with sports education model" showed significant improvements in students' game performance, and responsibilities with self-direction, helping others, cooperation. 2) "Sports education model" also had significant improvements in students' game performance, and responsibilities with effort, self-direction, helping others. 3.) There was no significant difference in game performance and responsibilities between "merging TPSR with sports education model" and "sports education model". 4)."Merging TPSR with sports education model" significantly improve learning atmosphere and peer relationships, it may be developed in the physical education curriculum. The conclusions were as follows: Both "Merging TPSR with sports education model" and "sports education model" can help improve students' responsibility and game performance. However, "Merging TPSR with sports education model" can reduce the competitive atmosphere in highly intensive games between students. The curricular projects of hybrid TPSR-Sport Education model is a good approach for moral character education.

Keywords: curriculum and teaching model, sports self-efficacy, sport enthusiastic, character education

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Authors: Amirreza Fazely Hamedani, Muzzamil Aziz, Philipp Wieder, Ramin Yahyapour

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Software-defined networking in recent years came into the sight of so many network designers as a successor to the traditional networking. Unlike traditional networks where control and data planes engage together within a single device in the network infrastructure such as switches and routers, the two planes are kept separated in software-defined networks (SDNs). All critical decisions about packet routing are made on the network controller, and the data level devices forward the packets based on these decisions. This type of network is vulnerable to DDoS attacks, degrading the overall functioning and performance of the network by continuously injecting the fake flows into it. This increases substantial burden on the controller side, and the result ultimately leads to the inaccessibility of the controller and the lack of network service to the legitimate users. Thus, the protection of this novel network architecture against denial of service attacks is essential. In the world of cybersecurity, attacks and new threats emerge every day. It is essential to have tools capable of managing and analyzing all this new information to detect possible attacks in real-time. These tools should provide a comprehensive solution to automatically detect, predict and prevent abnormalities in the network. Big data encompasses a wide range of studies, but it mainly refers to the massive amounts of structured and unstructured data that organizations deal with on a regular basis. On the other hand, it regards not only the volume of the data; but also that how data-driven information can be used to enhance decision-making processes, security, and the overall efficiency of a business. This paper presents an intelligent big data framework as a solution to handle illegitimate traffic burden on the SDN network created by the numerous DDoS attacks. The framework entails an efficient defence and monitoring mechanism against DDoS attacks by employing the state of the art machine learning techniques.

Keywords: apache spark, apache kafka, big data, DDoS attack, machine learning, SDN network

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Authors: Elham Dehghan, A. Shirzadi Javid, Mohsen Tadayon

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Labor productivity is very important and gained special concerns among professionals in the construction industry, worldwide. Productivity improvements on labors achieve higher cost savings with minimal investment. Due to the fact that profit margins are small on construction projects, cost savings associated with productivity are crucial to become a successful contractor. This research program studies and highlights the factors affecting labor productivity in Iranian construction industry. A questionnaire was used to gather the relevant data from respondents who involve in managing various types of projects in wide areas in Iran. It involved ranking 57 predefined factors divided into 5 categories: Human/Labor; Financial; Management; Equipments/Materials and Environmental. Total 62 feedbacks were analyzed through the Relative Importance Index (RII) technique. The top ten factors affecting construction labor productivity in Iran are: 1) Professional capability of contractor project manager, 2) skills of contractor’s project management team, 3) professional capability of owner project manager, 4) professional capability of Consulting Project manager, 5) discipline working, 6) delay payments by the owner, 7) material shortages, 8) delays in delivery of materials, 9) turnover power of the owner, 10) poor site management. Recommendations have been made in the study to address these factors. The research has direct benefits to key stakeholders in Iranian construction industry.

Keywords: Iranian construction projects, labor, productivity, relative importance index

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Authors: Tomasz Zarebski

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A very important element of the education system is its evaluation procedure. Each education system should be systematically evaluated and improved. Among the criteria subject to evaluation, attention should be paid to the following: structure of the study programme, implementation of the study programme, admission to studies, verification of learning outcomes achievement by students, giving credit for individual semesters and years, and awarding diplomas, competence, experience, qualifications and the number of staff providing education, staff development, and in-service training, education infrastructure, cooperation with social and economic stakeholders on the development, conditions for and methods of improving the internationalisation of education provided as part of the degree programme, supporting learning, social, academic or professional development of students and their entry on the labour market, public access to information about the study programme and quality assurance policy. Concerning the assessment process and the individual assessment indicators, the participation of students in these processes is essential. The purpose of this paper is to analyse the rules of student participation in accreditation processes on the example of individual countries in Europe. The rules of students' participation in the work of accreditation committees and their influence on the final grade of the committee were analysed. Most of the higher education institutions follow similar rules for accreditation. The general model gives the individual institution freedom to organize its own quality assurance, as long as the system lives up to the criteria for quality and relevance laid down in the particular provisions. This point also applies to students. The regulations of the following countries were examined in the legal-comparative aspect: Poland (Polish Accreditation Committee), Denmark (The Danish Accreditation Institution), France (High Council for the Evaluation of Research and Higher Education), Germany (Agency for Quality Assurance through Accreditation of Study Programmes) and Italy (National Agency for the Evaluation of Universities and Research Institutes).

Keywords: accreditation, student, study programme, quality assurance in higher education

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Authors: Yohann R. J. Thomas, Sébastien Solan

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Conventional battery technology includes the assembly of electrode/separator/electrode by standard techniques such as stacking or winding, depending on the format size. In that type of batteries, coating or pasting techniques are only used for the electrode process. The processes are suited for large scale production of batteries and perfectly adapted to plenty of application requirements. Nevertheless, as the demand for both easier and cost-efficient production modes, flexible, custom-shaped and efficient small sized batteries is rising. Thin-film, printable batteries are one of the key areas for printed electronics. In the frame of European BASMATI project, we are investigating the feasibility of a new design of lithium-ion battery: interdigitated planar core design. Polymer substrate is used to produce bendable and flexible rechargeable accumulators. Direct fully printed batteries lead to interconnect the accumulator with other electronic functions for example organic solar cells (harvesting function), printed sensors (autonomous sensors) or RFID (communication function) on a common substrate to produce fully integrated, thin and flexible new devices. To fulfill those specifications, a high resolution printing process have been selected: Aerosol jet printing. In order to fit with this process parameters, we worked on nanomaterials formulation for current collectors and electrodes. In addition, an advanced printed polymer-electrolyte is developed to be implemented directly in the printing process in order to avoid the liquid electrolyte filling step and to improve safety and flexibility. Results: Three different current collectors has been studied and printed successfully. An ink of commercial copper nanoparticles has been formulated and printed, then a flash sintering was applied to the interdigitated design. A gold ink was also printed, the resulting material was partially self-sintered and did not require any high temperature post treatment. Finally, carbon nanotubes were also printed with a high resolution and well defined patterns. Different electrode materials were formulated and printed according to the interdigitated design. For cathodes, NMC and LFP were efficaciously printed. For anodes, LTO and graphite have shown to be good candidates for the fully printed battery. The electrochemical performances of those materials have been evaluated in a standard coin cell with lithium-metal counter electrode and the results are similar with those of a traditional ink formulation and process. A jellified plastic crystal solid state electrolyte has been developed and showed comparable performances to classical liquid carbonate electrolytes with two different materials. In our future developments, focus will be put on several tasks. In a first place, we will synthesize and formulate new specific nano-materials based on metal-oxyde. Then a fully printed device will be produced and its electrochemical performance will be evaluated.

Keywords: high resolution digital printing, lithium-ion battery, nanomaterials, solid-state electrolytes

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Authors: Yaolin Tian, Shanxiong Chen, Fujia Zhao, Xiaoyu Lin, Hailing Xiong

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Ancient books are significant culture inheritors and their background textures convey the potential history information. However, multi-style texture recovery of ancient books has received little attention. Restricted by insufficient ancient textures and complex handling process, the generation of ancient textures confronts with new challenges. For instance, training without sufficient data usually brings about overfitting or mode collapse, so some of the outputs are prone to be fake. Recently, image generation and style transfer based on deep learning are widely applied in computer vision. Breakthroughs within the field make it possible to conduct research upon multi-style texture recovery of ancient books. Under the circumstances, we proposed a network of layout analysis and image fusion system. Firstly, we trained models by using Deep Convolution Generative against Networks (DCGAN) to synthesize multi-style ancient textures; then, we analyzed layouts based on the Position Rearrangement (PR) algorithm that we proposed to adjust the layout structure of foreground content; at last, we realized our goal by fusing rearranged foreground texts and generated background. In experiments, diversified samples such as ancient Yi, Jurchen, Seal were selected as our training sets. Then, the performances of different fine-turning models were gradually improved by adjusting DCGAN model in parameters as well as structures. In order to evaluate the results scientifically, cross entropy loss function and Fréchet Inception Distance (FID) are selected to be our assessment criteria. Eventually, we got model M8 with lowest FID score. Compared with DCGAN model proposed by Radford at el., the FID score of M8 improved by 19.26%, enhancing the quality of the synthetic images profoundly.

Keywords: deep learning, image fusion, image generation, layout analysis

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Authors: P. B. Sob, A. A. Alugongo, T. B. Tengen

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The activation volume of 6082T6 aluminum is investigated at different temperatures on grain size variants. The deformation activation volume was computed on the basis of the relationship between the Boltzmann’s constant k, the testing temperatures, the material strain rate sensitivity and the material yield stress of grain size variants. The material strain rate sensitivity is computed as a function of yield stress and strain rate of grain size variants. The effect of the material strain rate sensitivity and the deformation activation volume of 6082T6 aluminum at different temperatures of 3-D grain are discussed. It is shown that the strain rate sensitivities and activation volume are negative for the grain size variants during the deformation of nanostructured materials. It is also observed that the activation volume vary in different ways with the equivalent radius, semi minor axis radius, semi major axis radius and major axis radius. From the obtained results it is shown that the variation of activation volume increased and decreased with the testing temperature. It was revealed that, increased in strain rate sensitivity led to decrease in activation volume whereas increased in activation volume led to decrease in strain rate sensitivity.

Keywords: nanostructured materials, grain size variants, temperature, yield stress, strain rate sensitivity, activation volume

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