Search results for: post processing

Authors: Samantha Rix

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The purpose of this research paper is to investigate the cognitive processing of learners who receive input but produce very little or no output, and who, when they do produce output, exhibit a similar language proficiency as do those learners who produced output more regularly in the language classroom. Previous studies have investigated the benefits of output (with somewhat differing results); therefore, the presentation will begin with an investigation of what may underlie gains in proficiency without output. Consequently, a pilot study was designed and conducted to gain insight into the cognitive processing of low-output language learners looking, for example, at quantity and quality of noticing. This will be carried out within the paradigm of action classroom research, observing and interviewing low-output language learners in an intensive English program at a small Midwest university. The results of the pilot study indicated that autonomy in language learning, specifically utilizing strategies such self-monitoring, self-talk, and thinking 'out-loud', were crucial in the development of language proficiency for academic-level performance. The presentation concludes with an examination of pedagogical implication for classroom use in order to aide students in their language development.

Keywords: cognitive processing, language learners, language proficiency, learning strategies

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Authors: Mohammad Khosravi, Ali Kiani, Behroz Dastar, Parvin Showrang

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Review was carried out on important anti-nutritional compounds of livestock and poultry foods and the effect of radiation usage. Nowadays, with advancement in technology, different methods have been considered for the optimum usage of nutrients in livestock and poultry foods. Steaming, extruding, pelleting, and the use of chemicals are the most common and popular methods in food processing. Use of radiation in food processing researches in the livestock and poultry industry is currently highly regarded. Ionizing (electrons, gamma) and non-ionizing beams (microwave and infrared) are the most useable rays in animal food processing. In recent researches, these beams have been used to remove and reduce the anti-nutritional factors and microbial contamination and improve the digestibility of nutrients in poultry and livestock food. The evidence presented will help researchers to recognize techniques of relevance to them. Simplification of some of these techniques, especially in developing countries, must be addressed so that they can be used more widely.

Keywords: antitrypsin, gamma anti-nutritional components, phytic acid, radiation

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Authors: Natalia Kalinowska

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The adoption of the General Data Protection Regulation, (GDPR) finished the four-year work of the European Commission in this area in the European Union. Considering far-reaching changes, which will be applied by GDPR, the European legislator envisaged two-year transitional period. Member states and companies have to prepare for a new regulation until 25 of May 2018. The idea, which becomes a new look at an attitude to data protection in the European Union is risk-based approach. So far, as a result of implementation of Directive 95/46/WE, in many European countries (including Poland) there have been adopted very particular regulations, specifying technical and organisational security measures e.g. Polish implementing rules indicate even how long password should be. According to the new approach from May 2018, controllers and processors will be obliged to apply security measures adequate to level of risk associated with specific data processing. The risk in GDPR should be interpreted as the likelihood of a breach of the rights and freedoms of the data subject. According to Recital 76, the likelihood and severity of the risk to the rights and freedoms of the data subject should be determined by reference to the nature, scope, context and purposes of the processing. GDPR does not indicate security measures which should be applied – in recitals there are only examples such as anonymization or encryption. It depends on a controller’s decision what type of security measures controller considered as sufficient and he will be responsible if these measures are not sufficient or if his identification of risk level is incorrect. Data protection regulation indicates few levels of risk. Recital 76 indicates risk and high risk, but some lawyers think, that there is one more category – low risk/now risk. Low risk/now risk data processing is a situation when it is unlikely to result in a risk to the rights and freedoms of natural persons. GDPR mentions types of data processing when a controller does not have to evaluate level of risk because it has been classified as „high risk” processing e.g. processing on a large scale of special categories of data, processing with using new technologies. The methodology will include analysis of legal regulations e.g. GDPR, the Polish Act on the Protection of personal data. Moreover: ICO Guidelines and articles concerning risk based approach in GDPR. The main conclusion is that an appropriate risk assessment is a key to keeping data safe and avoiding financial penalties. On the one hand, this approach seems to be more equitable, not only for controllers or processors but also for data subjects, but on the other hand, it increases controllers’ uncertainties in the assessment which could have a direct impact on incorrect data protection and potential responsibility for infringement of regulation.

Keywords: general data protection regulation, personal data protection, privacy protection, risk based approach

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Authors: Theresia El Khoury, Georges Badr, Amir Hajjam El Hassani, Stéphane N’Guyen Van Ky

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The widespread adoption of machine learning and artificial intelligence across different domains can be attributed to the digitization of data over several decades, resulting in vast amounts of data, types, and structures. Thus, data processing and preparation turn out to be a crucial stage. However, applying these techniques to S1000D standard-based data poses a challenge due to its complexity and the need to preserve logical information. This paper describes SALERNO, an S1000d AppLicability dEpended pRocessiNg mOdel. This python-based model analyzes and converts the XML S1000D-based files into an easier data format that can be used in machine learning techniques while preserving the different logic and relationships in files. The model parses the files in the given folder, filters them, and extracts the required information to be saved in appropriate data frames and Excel sheets. Its main idea is to group the extracted information by applicability. In addition, it extracts the full text by replacing internal and external references while maintaining the relationships between files, as well as the necessary requirements. The resulting files can then be saved in databases and used in different models. Documents in both English and French languages were tested, and special characters were decoded. Updates on the technical manuals were taken into consideration as well. The model was tested on different versions of the S1000D, and the results demonstrated its ability to effectively handle the applicability, requirements, references, and relationships across all files and on different levels.

Keywords: aeronautics, big data, data processing, machine learning, S1000D

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Authors: А. V. Panko, Е. V. Ablets, I. G. Kovzun, М. А. Ilyashov

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Based upon generalized analysis of modern know-how in the sphere of processing, concentration and purification of iron-ore raw materials (IORM), in particular, the most widespread ferrioxide-silicate materials (FOSM), containing impurities of phosphorus and other elements compounds, noted special role of nano technological initiatives in improvement of such processes. Considered ideas of role of nano particles in processes of FOSM carbonization with subsequent direct reduction of ferric oxides contained in them to metal phase, as well as in processes of alkali treatment and separation of powered iron from phosphorus compounds. Using the obtained results the wasteless solid-phase processing, concentration and purification of IORM and FOSM from compounds of phosphorus, silicon and other impurities excelling known methods of direct iron reduction from iron ores and metallurgical slimes.

Keywords: iron ores, solid-phase reduction, nanoparticles in reduction and purification of iron from silicon and phosphorus, wasteless method of ores processing

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Authors: Rika Susanti, Eryati Darwin, Dedi Afandi, Yanwirasti, Syahruddin Said, Noverika Windasari, Zelly Dia Rofinda

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Introduction: Blunt head trauma is one of the leading causes of death associated with murders and other deaths involved in criminal acts. Creatine kinase (CKBB) levels have been used as a biomarker for blunt head trauma. Therefore, it is now used as an alternative to an autopsy. The aim of this study is to investigate CKBB levels in cerebrospinal fluid (CSF) and post-mortem serum in order to deduce the cause and time of death. Method: This investigation was conducted through post-test–only group design involving deaths caused by blunt head trauma, which was compared to deaths caused by ketamine poisoning. Results: There were eight treatment groups, each consisting of six adult rats (Rattus norvegicus) Sprague-Dawley strain. Examinations were done at 0 hours, 1 hour, 2 hours, and 3 hours post-mortem, which followed by brain tissue observation. Data were then analyzed statistically with a repeated-measures general linear model. Conclusion: There were increases in the level of CKBB in CSF and postmortem serum in both blunt head trauma and ketamine poisoning treatment groups. However, there were no significant differences between these two groups.

Keywords: blunt head trauma, CKBB, the cause of death, estimated time of death

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Authors: James Jr. Mashiyane, Risuna Nkolele, Stephanie J. Müller, Gciniwe S. Dlamini, Rebone L. Meraba, Darlington S. Mapiye

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When performing language tasks in natural language processing (NLP), the dimensionality of word embeddings is chosen either ad-hoc or is calculated by optimizing the Pairwise Inner Product (PIP) loss. The PIP loss is a metric that measures the dissimilarity between word embeddings, and it is obtained through matrix perturbation theory by utilizing the unitary invariance of word embeddings. Unlike in natural language, in genomics, especially in genome sequence processing, unlike in natural language processing, there is no notion of a “word,” but rather, there are sequence substrings of length k called k-mers. K-mers sizes matter, and they vary depending on the goal of the task at hand. The dimensionality of word embeddings in NLP has been studied using the matrix perturbation theory and the PIP loss. In this paper, the sufficiency and reliability of applying word-embedding algorithms to various genomic sequence datasets are investigated to understand the relationship between the k-mer size and their embedding dimension. This is completed by studying the scaling capability of three embedding algorithms, namely Latent Semantic analysis (LSA), Word2Vec, and Global Vectors (GloVe), with respect to the k-mer size. Utilising the PIP loss as a metric to train embeddings on different datasets, we also show that Word2Vec outperforms LSA and GloVe in accurate computing embeddings as both the k-mer size and vocabulary increase. Finally, the shortcomings of natural language processing embedding algorithms in performing genomic tasks are discussed.

Keywords: word embeddings, k-mer embedding, dimensionality reduction

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Authors: Nawal A. Abu-Shady, Ibrahim M. I. Hamoda, Ahmed R. Z. Baghdadi, Mohammed K. Mohamed

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Background: The aim of this work was to investigate the efficacy of Transcranial Magnetic Therapy (TMT) on balance in hemiparetic stroke patients. It was conducted in outpatient clinic and in BIODEX balance system lab in Faculty of Physical Therapy, Cairo University. Subjects and Methods: Thirty hemiparetic stroke patients from both sexes represent the sample of this study. The patients' ages ranged from 45 to 55 years. They were assigned randomly into two equal groups; the study group (GA) and the control group (GB). control group treated by selected therapeutic physical therapy program. GA treated by the same program of treatment as the GB in addition to TMT. The duration of treatment was six weeks, three times weekly.day after day. The different aspects of dynamic balance (overall stability, anteroposterior stability and mediolateral stability indices) were assessed pre and post treatment objectively by Biodex balance system and clinically by Short Form of Berg Balance Scale (SFBBS) in both groups. Results: Comparison of each variable pre and post treatment in each group revealed a significant improvement in all different parameters in both groups ( p < 0.01), however comparison between post results revealed that the GA showed a high significant improvement higher than the GB in all different variables.

Keywords: stroke, TMT, SFBBS, biodex balance system

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Authors: Ramanen Sugunesegran, Michael L. Williams

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Over the past two decades surgical approaches for mitral valve (MV) disease have evolved with the advent of minimally invasive techniques. Robotic mitral valve repair (RMVr) safety and efficacy has been well documented, however, mid- to long-term data are limited. The aim of this review was to provide a comprehensive analysis of the available mid- to long-term term data for RMVr. Electronic searches of five databases were performed to identify all relevant studies reporting minimum 5-year data on RMVr. Pre-defined primary outcomes of interest were overall survival, freedom from MV reoperation and freedom from moderate or worse mitral regurgitation (MR) at 5-years or more post-RMVr. A meta-analysis of proportions or means was performed, utilizing a random effects model, to present the data. Kaplan-Meier curves were aggregated using reconstructed individual patient data. Nine studies totaling 3,300 patients undergoing RMVr were identified. Rates of overall survival at 1-, 5- and 10-years were 99.2%, 97.4% and 92.3%, respectively. Freedom from MV reoperation at 8-years post RMVr was 95.0%. Freedom from moderate or worse MR at 7-years was 86.0%. Rates of early post-operative complications were low with only 0.2% all-cause mortality and 1.0% cerebrovascular accident. Reoperation for bleeding was low at 2.2% and successful RMVr was 99.8%. Mean intensive care unit and hospital stay were 22.4 hours and 5.2 days, respectively. RMVr is a safe procedure with low rates of early mortality and other complications. It can be performed with low complication rates in high volume, experienced centers. Evaluation of available mid-term data post-RMVr suggests favorable rates of overall survival, freedom from MV reoperation and freedom from moderate or worse MR recurrence.

Keywords: mitral valve disease, mitral valve repair, robotic cardiac surgery, robotic mitral valve repair

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Authors: Amit Kumar, Himanshu Singal, Arnav Bhavsar

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In this modern era of automation, most of the academic exams and competitive exams are Multiple Choice Questions (MCQ). The responses of these MCQ based exams are recorded in the Optical Mark Reader (OMR) sheet. Evaluation of the OMR sheet requires separate specialized machines for scanning and marking. The sheets used by these machines are special and costs more than a normal sheet. Available process is non-economical and dependent on paper thickness, scanning quality, paper orientation, special hardware and customized software. This study tries to tackle the problem of evaluating the OMR sheet without any special hardware and making the whole process economical. We propose an image processing based algorithm which can be used to read and evaluate the scanned OMR sheets with no special hardware required. It will eliminate the use of special OMR sheet. Responses recorded in normal sheet is enough for evaluation. The proposed system takes care of color, brightness, rotation, little imperfections in the OMR sheet images.

Keywords: OMR, image processing, hough circle trans-form, interpolation, detection, binary thresholding

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Authors: Suvidha Gupta, R. A. Pandey, Sanjay Pawar

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The effluents from various food processing industries are found with high BOD, COD, suspended solids, nitrate, and phosphate. Mixotrophic growth of microalgae using food processing industrial wastewater as an organic carbon source has emerged as more effective and energy intensive means for the nutrient removal and COD reduction. The present study details the treatment of non-sterilized unfiltered food processing industrial wastewater by microalgae for nutrient removal as well as to determine the tolerance to COD by taking different dilutions of wastewater. In addition, the effect of different inoculum percentages of microalgae on removal efficiency of the nutrients for given dilution has been studied. To see the effect of dilution and COD tolerance, the wastewater having initial COD 5000 mg/L (±5), nitrate 28 mg/L (±10), and phosphate 24 mg/L (±10) was diluted to get COD of 3000 mg/L and 1000 mg/L. The experiments were carried out in 1L conical flask by intermittent aeration with different inoculum percentage i.e. 10%, 20%, and 30% of Chlorella sp. isolated from nearby area of NEERI, Nagpur. The experiments were conducted for 6 days by providing 12:12 light- dark period and determined various parameters such as COD, TOC, NO3-- N, PO4-- P, and total solids on daily basis. Results revealed that, for 10% and 20% inoculum, over 90% COD and TOC reduction was obtained with wastewater containing COD of 3000 mg/L whereas over 80% COD and TOC reduction was obtained with wastewater containing COD of 1000 mg/L. Moreover, microalgae was found to tolerate wastewater containing COD 5000 mg/L and obtained over 60% and 80% reduction in COD and TOC respectively. The obtained results were found similar with 10% and 20% inoculum in all COD dilutions whereas for 30% inoculum over 60% COD and 70% TOC reduction was obtained. In case of nutrient removal, over 70% nitrate removal and 45% phosphate removal was obtained with 20% inoculum in all dilutions. The obtained results indicated that Microalgae assisted nutrient removal gives maximum COD and TOC reduction with 3000 mg/L COD and 20% inoculum. Hence, microalgae assisted wastewater treatment is not only effective for removal of nutrients but also can tolerate high COD up to 5000 mg/L and solid content.

Keywords: Chlorella sp., chemical oxygen demand, food processing industrial wastewater, mixotrophic growth

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Authors: Leon Pan

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The first programming course within post-secondary education has long been recognized as a challenging endeavor for both educators and students alike. Historically, these courses have exhibited high failure rates and a notable number of dropouts. Instructors often lament students' lack of effort in their coursework, and students often express frustration that the teaching methods employed are not effective. Drawing inspiration from the successful principles of Extreme Programming, this study introduces an approach—the Extremes-based teaching model — aimed at enhancing the teaching of introductory programming courses. To empirically determine the effectiveness of the model, a comparison was made between a section taught using the extreme-based model and another utilizing traditional teaching methods. Notably, the extreme-based teaching class required students to work collaboratively on projects while also demanding continuous assessment and performance enhancement within groups. This paper details the application of the extreme-based model within the post-secondary online classroom context and presents the compelling results that emphasize its effectiveness in advancing the teaching and learning experiences. The extreme-based model led to a significant increase of 13.46 points in the weighted total average and a commendable 10% reduction in the failure rate.

Keywords: extreme-based teaching model, innovative pedagogical methods, project-based learning, team-based learning

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Authors: R. Dimitri Halley

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The research within Jungian Psychology presented here is on the wave state of Self. What has been discovered via shared dreaming, independently correlating dreams across dreamers, is beyond the Self stage into the deepest layer or the wave state Self: the very quantum ocean, the Self archetype is embedded in. A quantum wave or rhyming of meaning constituting synergy across several dreamers was discovered in dreams and in extensively shared dream work with small groups at a post therapy stage. Within the format of shared dreaming, we find synergy patterns beyond what Jung called the Self archetype. Jung led us up to the phase of Individuation and delivered the baton to Von Franz to work out the next synchronistic stage, here proposed as the finding of the quantum patterns making up the wave state of Self. These enfolded synchronistic patterns have been found in group format of shared dreaming of individuals approximating individuation, and the unfolding of it is carried by belief and faith. The reason for this format and operating system is because beyond therapy and of living reality, we find no science – no thinking or even awareness in the therapeutic sense – but rather a state of mental processing resembling more like that of spiritual attitude. Thinking as such is linear and cannot contain the deepest layer of Self, the quantum core of the human being. It is self reflection which is the container for the process at the wave state of Self. Observation locks us in an outside-in reactive flow from a first-person perspective and hence toward the surface we see to believe, whereas here, the direction of focus shifts to inside out/intrinsic. The operating system or language at the wave level of Self is thus belief and synchronicity. Belief has up to now been almost the sole province of organized religions but was viewed by Jung as an inherent property in the process of Individuation. The shared dreaming stage of the synchronistic patterns forms a larger story constituting a deep connectivity unfolding around individual Selves. Dreams of independent dreamers form larger patterns that come together as puzzles forming a larger story, and in this sense, this group work level builds on Jung as a post individuation collective stage. Shared dream correlations will be presented, illustrating a larger story in terms of trails of shared synchronicity.

Keywords: belief, shared dreaming, synchronistic patterns, wave state of self

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Authors: Javier A. Dominguez Caballero, Graeme A. Manson, Matthew B. Marshall

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Cutting tools with ceramic inserts are often used in the process of machining many types of superalloy, mainly due to their high strength and thermal resistance. Nevertheless, during the cutting process, the plastic flow wear generated in these inserts enhances and propagates cracks due to high temperature and high mechanical stress. This leads to a very variable failure of the cutting tool. This article explores the relationship between the continuous wear that ceramic SiAlON (solid solutions based on the Si3N4 structure) inserts experience during a high-speed machining process and the evolution of sparks created during the same process. These sparks were analysed through pictures of the cutting process recorded using an SLR camera. Features relating to the intensity and area of the cutting sparks were extracted from the individual pictures using image processing techniques. These features were then related to the ceramic insert’s crater wear area.

Keywords: ceramic cutting tools, high speed machining, image processing, tool condition monitoring, tool wear

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Authors: Marji Umil, Miane Karyle Urolaza, Ian Winston Dale Uy, John Charle Magne Valdez, Karen Elizabeth Valdez, Ervin Charles Valencia, Cheryleen Tan-Chua

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Objective: Distraction techniques can be successful in reducing the anxiety of children during medical procedures. Dental procedures, in particular, are associated with dental anxiety which has been identified as a significant and common problem in children, however, only limited studies were conducted to address such problem. Thus, this study determined the effectiveness of computer video games on the levels of anxiety of children between 5-12 years old scheduled for tooth extraction. Methods: A pre-test post-test quasi-experimental study was conducted involving 30 randomly-assigned subjects, 15 in the experimental and 15 in the control. Subjects in the experimental group played computer video games for a maximum of 15 minutes, however, no intervention was done on the control. The modified Yale Pre-operative Anxiety Scale (m-YPAS) with a Cronbach’s alpha of 0.9 was used to assess anxiety at two different points: upon arrival in the clinic (pre-test anxiety) and 15 minutes after the first measurement (post-test anxiety). Paired t-test and ANCOVA were used to analyze the gathered data. Results: Results showed that there is a significant difference between the pre-test and post-test anxiety scores of the control group (p=0.0002) which indicates an increased anxiety. A significant difference was also noted between the pre-test and post-test anxiety scores of the experimental group (p=0.0002) which indicates decreased anxiety. Comparatively, the experimental group showed lower anxiety score (p=<0.0001) than the control. Conclusion: The use of computer video games is effective in reducing the pre-operative anxiety among children and can be an alternative non-pharmacological management in giving pre-operative care.

Keywords: play therapy, preoperative anxiety, tooth extraction, video games

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Authors: Supreet Singh, Manpreet Kaur, Manoj Kumar

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High temperature corrosion is an imperative material degradation method experienced in thermal power plants and other energy generation sectors. Metallic materials such as ferritic steels have special properties such as easy fabrication and machinibilty, low cost, but a serious drawback of these materials is the worsening in properties initiating from the interaction with the environments. The metallic materials do not endure higher temperatures for extensive period of time because of their poor corrosion resistance. Friction Stir Processing (FSP), has emerged as the potent surface modification means and control of microstructure in thermo mechanically heat affecting zones of various metal alloys. In the current research work, FSP was done on the boiler tube of SA 210 Grade A1 material which is regularly used by thermal power plants. The strengthening of SA210 Grade A1 boiler steel through microstructural refinement by Friction Stir Processing (FSP) and analyze the effect of the same on high temperature corrosion behavior. The high temperature corrosion performance of the unprocessed and the FSPed specimens were evaluated in the laboratory using molten salt environment of Na₂SO₄-82%Fe₂(SO₄). The unprocessed and FSPed low carbon steel Gr A1 evaluation was done in terms of microstructure, corrosion resistance, mechanical properties like hardness- tensile. The in-depth characterization was done by EBSD, SEM/EDS and X-ray mapping analyses with an aim to propose the mechanism behind high temperature corrosion behavior of the FSPed steel.

Keywords: boiler steel, characterization, corrosion, EBSD/SEM/EDS/XRD, friction stir processing

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Authors: Christoph Lohr, Hanna Wund, Peter Elsner, Kay André Weidenmann

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Injection molding is one of the most commonly used techniques in the industrial polymer processing. In the conventional process of injection molding, the liquid polymer is injected into the cavity of the mold, where the polymer directly starts hardening at the cooled walls. To compensate the shrinkage, which is caused predominantly by the immediate cooling, holding pressure is applied. Through that whole process, residual stresses are produced by the temperature difference of the polymer melt and the injection mold and the relocation of the polymer chains, which were oriented by the high process pressures and injection speeds. These residual stresses often weaken or change the structural behavior of the parts or lead to deformation of components. One solution to reduce the residual stresses is the use of variothermal processing. Hereby the mold is heated – i.e. near/over the glass transition temperature of the polymer – the polymer is injected and before opening the mold and ejecting the part the mold is cooled. For the next cycle, the mold gets heated again and the procedure repeats. The rapid heating and cooling of the mold are realized indirectly by convection of heated and cooled liquid (here: water) which is pumped through fluid channels underneath the mold surface. In this paper, the influences of variothermal processing on the residual stresses are analyzed with samples in a larger scale (500 mm x 250 mm x 4 mm). In addition, the influence on functional elements, such as abrupt changes in wall thickness, bosses, and ribs, on the residual stress is examined. Therefore the polycarbonate samples are produced by variothermal and isothermal processing. The melt is injected into a heated mold, which has in our case a temperature varying between 70 °C and 160 °C. After the filling of the cavity, the closed mold is cooled down varying from 70 °C to 100 °C. The pressure and temperature inside the mold are monitored and evaluated with cavity sensors. The residual stresses of the produced samples are illustrated by birefringence where the effect on the refractive index on the polymer under stress is used. The colorful spectrum can be uncovered by placing the sample between a polarized light source and a second polarization filter. To show the achievement and processing effects on the reduction of residual stress the birefringence images of the isothermal and variothermal produced samples are compared and evaluated. In this comparison to the variothermal produced samples have a lower amount of maxima of each color spectrum than the isothermal produced samples, which concludes that the residual stress of the variothermal produced samples is lower.

Keywords: birefringence, injection molding, polycarbonate, residual stress, variothermal processing

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Authors: Cinthya Olivares Garita

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Untangling language processing in second language development has been either a taken-for-granted and overlooked task for some English language teaching (ELT) instructors or a considerable feat for others. From the most traditional language instruction to the most communicative methodologies, how to assist L2 learners in processing language in the classroom has become a challenging matter in second language teaching. Amidst an ample array of methods, strategies, and techniques to teach a target language, finding a suitable model to lead learners to process, interpret, and negotiate meaning to communicate in a second language has imposed a great responsibility on language teachers; committed teachers are those who are aware of their role in equipping learners with the appropriate tools to communicate in the target language in a 21stcentury society. Unfortunately, one might find some English language teachers convinced that their job is only to lecture students; others are advocates of textbook-based instruction that might hinder second language processing, and just a few might courageously struggle to facilitate second language learning effectively. Grounded on the most representative empirical studies on comprehensible input, processing instruction, and focus on form, this analysis aims to facilitate the understanding of how second language learners process and automatize input and propose a pedagogical framework for the successful development of a second language. In light of this, this paper is structured to tackle noticing and attention and structured input as the heart of processing instruction, comprehensible input as the missing link in second language learning, and form-meaning connections as opposed to traditional grammar approaches to language teaching. The author finishes by suggesting a pedagogical framework involving noticing-attention-comprehensible-input-form (NACIF based on their acronym) to support ELT instructors, teachers, and scholars on the challenging task of facilitating the understanding of effective second language development.

Keywords: second language development, pedagogical framework, noticing, attention, comprehensible input, form

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Authors: Ebtehag Tolba, Ahmed Mousa, Mohamed Abd El-Salam

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The study presents a proposed program for nursery school children in Egypt. The program consists of a collection of artistic activities and aims to develop the language, mathematical, and artistic skills of preschool children. Furthermore, the researcher has presented a questionnaire to experts about the link between the target group and the content. Finally, the proposed program was applied to group of 30 children. In addition, the researcher has prepared another questionnaire for measuring the effect of the program. This questionnaire was used as a pre-test and post-test, and at the end of the study, a significant difference was determined in favour of the post-test results.

Keywords: developing, concepts, nursery, children, artistic activities

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Authors: Maria Tsompanoglou, Dimitris Armenis

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Vessel behavior in different operational and weather conditions constitutes the main area of interest for the ship operator. Ship speed and fuel consumption are the most decisive parameters in this respect, as their correlation provides information about the economic and environmental efficiency of the vessel, becoming the basis of decision making in terms of maintenance and trading. In the analysis of vessel operational profile for the evaluation of fuel consumption and the equivalent CO2 emissions footprint, the indications of Speed Through Water are widely used. The seasonal and regional variations in seawater characteristics, which are available nowadays, can provide the basis for accurate estimation of the errors in Speed Through Water indications at any time. Accuracy in the speed value on a route basis can enable operator identify the ship fuel and propulsion efficiency and proceed with improvements. This paper discusses case studies, where the actual vessel speed was corrected by a post-processing algorithm. The effects of the vessel correction to standard Key Performance Indicators, as well as operational findings not identified earlier, are also discussed.

Keywords: data analytics, MATLAB, vessel performance monitoring, speed through water

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Authors: Eteri Kharaishvili

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Introduction. The paper analyzes the main indicators of export and import of Georgian agri-food products; identifies positive and negative trends under the pandemic; based on the revealed problemssubstantiates the need formodernization ofin agri-food sector. It is argued that low production and productivity rates of food products negatively impact achieving the optimal export-to-import ratio; therefore, it leads toincreaseddependence on other countries andreduces the level of food security. Research objectives. The objective of the research is to identify the key challenges based on the analysis of export-import indicators of Georgian food products during the pandemic period and develop recommendations on the possibilities of post-pandemic perspectives. Research methods. Various theoretical and methodological research tools are used in the paper; in particular, a desk research is carried out on the research topic; endogenous and exogenous variables affecting export and import are determined through factor analysis; SWOT and PESTEL analysis are used to identify development opportunities; selection and groupingof data, identification of similarities and differences is carried outby using analysis, synthesis, sampling, induction and other methods; a qualitative study is conducted based on a survey of agri-food experts and exporters for clarifying the factors that impede export-import flows. Contributions. The factors that impede the export of Georgian agri-food products in the short run under COVID-19 pandemic are identified. These are: reduced income of farmers, delays in the supply of raw materials and supplies to the agri-food sectorfrom the neighboring industries, as well as in harvesting, processing, marketing, transportation, and other sectors; increased indirect costs, etc. The factors that impede the export in the long run areas follows loss of public confidence in the industry, risk of losing positions in traditional markets, etc. Conclusions are made on the problems in the field of export and import of Georgian agri-food products in terms of the pandemic; development opportunities are evaluated based on the analysis of the agri-food sector potential. Recommendations on the development opportunities for export and import of Georgian agri-food products in the post-pandemic period are proposed.

Keywords: agri-food products, export, and import, pandemic period, hindering factor, development potential

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Authors: Siti Fatimah Kader Maideen, Abdul Rashid, Nur Indah Ahmad

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Introduction: Indigenous people have an increased risk of contracting zoonotic infections due to their practices. Similarly, the aborigines in Peninsular Malaysia, the Orang Asli, have a higher risk too. This study aimed to empower the Jahai children on the prevention of zoonotic infections by implementing a health promotion intervention program. Methods: A non-experimental pre and post-test interventional study was conducted among the indigenous primary school children aged between nine and 12 years in Perak, Malaysia. A structured questionnaire was used to assess the pre-and post-knowledge and attitudes towards zoonotic infections and hand hygiene practice. This is followed by three sessions of the health promotion program. Ethical approval was obtained prior to the data collection. Data were analysed using SPSS software. Results: The knowledge on whether diseases can spread from animals to humans, transmission via saliva and faeces, types of organisms that can infect, and signs and symptoms increased significantly between pre and post. Significant improvements were observed in the attitude and practices too. Conclusion: The intervention program demonstrated improvement in the knowledge, attitude, and practice among the children. The continuous program needs to be conducted for a sustainable outcome.

Keywords: health promotion, zoonotic infections, aborigines, knowledge, practice

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Authors: Subir Gupta, Subhas Ganguly

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In this paper, we demonstrate the new area of application of image processing in metallurgical images to develop the more opportunity for structure-property correlation based approaches of alloy design. The present exercise focuses on the development of image processing tools suitable for phrase segmentation, grain boundary detection and recognition of micro-constituents in SEM micrographs of ferrite and pearlite steels. A comprehensive data of micrographs have been experimentally developed encompassing the variation of ferrite and pearlite volume fractions and taking images at different magnification (500X, 1000X, 15000X, 2000X, 3000X and 5000X) under scanning electron microscope. The variation in the volume fraction has been achieved using four different plain carbon steel containing 0.1, 0.22, 0.35 and 0.48 wt% C heat treated under annealing and normalizing treatments. The obtained data pool of micrographs arbitrarily divided into two parts to developing training and testing sets of micrographs. The statistical recognition features for ferrite and pearlite constituents have been developed by learning from training set of micrographs. The obtained features for microstructure pattern recognition are applied to test set of micrographs. The analysis of the result shows that the developed strategy can successfully detect the micro constitutes across the wide range of magnification and variation of volume fractions of the constituents in the structure with an accuracy of about +/- 5%.

Keywords: SEM micrograph, metallurgical image processing, ferrite pearlite steel, microstructure

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Authors: Sajjad Ahmed, Knut Hinkelmann, Flavio Corradini

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Fake news detection research is still in the early stage as this is a relatively new phenomenon in the interest raised by society. Machine learning helps to solve complex problems and to build AI systems nowadays and especially in those cases where we have tacit knowledge or the knowledge that is not known. We used machine learning algorithms and for identification of fake news; we applied three classifiers; Passive Aggressive, Naïve Bayes, and Support Vector Machine. Simple classification is not completely correct in fake news detection because classification methods are not specialized for fake news. With the integration of machine learning and text-based processing, we can detect fake news and build classifiers that can classify the news data. Text classification mainly focuses on extracting various features of text and after that incorporating those features into classification. The big challenge in this area is the lack of an efficient way to differentiate between fake and non-fake due to the unavailability of corpora. We applied three different machine learning classifiers on two publicly available datasets. Experimental analysis based on the existing dataset indicates a very encouraging and improved performance.

Keywords: fake news detection, natural language processing, machine learning, classification techniques.

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Authors: S. Öcal, A. Erakgün, E. Yüksel, M. N. Deniz, E. Erhan, A. Çertuğ

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Background: Emergence agitation (EA) is defined as a dissociated state of consciousness during the early post-anesthesia period in which the child is inconsolable, irritable, uncompromising or uncooperative, typically thrashing, crying, moaning, or incoherent, and not recognizing or identifying familiar and known objects or people. Some studies found preoperative parental anxiety to be a predictor of EA. Methods: Seventy-four children, between the ages of 3-12 undergoing adenoidectomy/tonsillectomy at Ege University Hospital, were studied. Anesthesia was induced and maintained using 2% sevoflurane in 50% oxygen and 50% air following a premedicative dose of 0.5mg/kg oral midazolam. After the children were taken into the operating theater, the mothers were given the State-Trait Anxiety Inventory (STAI) questionnaire. To evaluate EA, Post Anesthetic Emergence Delirium (PAED) score of the children were noted every 10min during the first 30min of the postoperative period. EA was defined with a highest PAED score of ≥ 10, and non-EA with a highest PAED score of ≤ 9. Results: In this study, the incidence of postoperative EA was 31% (34% under the age of 6 and 19% over). Mothers of children with EA were found not to be significantly more anxious on STAI compared to mothers of non-EA children. Conclusions: Contrary to some earlier studies, we were unable to find an association between preoperative parental anxiety and postoperative EA.

Keywords: parental anxiety, emergence agittion, Post Anesthetic Emergence Delirium, anesthesia

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Authors: Abdelghani Chahmi

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This article examines the detection and localization of faults in electrical systems, particularly those using asynchronous machines. First, the process of failure will be characterized, relevant symptoms will be defined and based on those processes and symptoms, a model of those malfunctions will be obtained. Second, the development of the diagnosis of the machine will be shown. As studies of malfunctions in electrical systems could only rely on a small amount of experimental data, it has been essential to provide ourselves with simulation tools which allowed us to characterize the faulty behavior. Fault detection uses signal processing techniques in known operating phases.

Keywords: induction motor, modeling, bearing damage, airgap eccentricity, torque variation

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Authors: Abderrahim Elmoataz

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More and more contemporary applications involve data in the form of functions defined on irregular and topologically complicated domains (images, meshs, points clouds, networks, etc). Such data are not organized as familiar digital signals and images sampled on regular lattices. However, they can be conveniently represented as graphs where each vertex represents measured data and each edge represents a relationship (connectivity or certain affinities or interaction) between two vertices. Processing and analyzing these types of data is a major challenge for both image and machine learning communities. Hence, it is very important to transfer to graphs and networks many of the mathematical tools which were initially developed on usual Euclidean spaces and proven to be efficient for many inverse problems and applications dealing with usual image and signal domains. Historically, the main tools for the study of graphs or networks come from combinatorial and graph theory. In recent years there has been an increasing interest in the investigation of one of the major mathematical tools for signal and image analysis, which are Partial Differential Equations (PDEs) variational methods on graphs. The normalized p-laplacian operator has been recently introduced to model a stochastic game called tug-of-war-game with noise. Part interest of this class of operators arises from the fact that it includes, as particular case, the infinity Laplacian, the mean curvature operator and the traditionnal Laplacian operators which was extensiveley used to models and to solve problems in image processing. The purpose of this paper is to introduce and to study a new class of normalized p-Laplacian on graphs. The introduction is based on the extension of p-harmonious function introduced in as discrete approximation for both infinity Laplacian and p-Laplacian equations. Finally, we propose to use these operators as a framework for solving many inverse problems in image processing.

Keywords: normalized p-laplacian, image processing, stochastic game, inverse problems

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Authors: Behailu Shigute Habtemariam

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The aim of the study was to examine the effects of training load on some selected fitness performance variables of volleyball players in the case of U-17 female volleyball project players in the central Ethiopia region. Methods: In this study, quasi-experimental design was used. For the purpose of this study, twenty-three volleyball players were used as a subject from the two projects. The data collected through fitness performance assessment were analyzed and interpreted into a meaningful idea using manually as well as with computer in order to compare physical fitness variables and changes observed among participants. Those are taking part in the effects of training load on some selected physical fitness variables. The collected data were analyzed by means of the Statistical Package for Social Science version (SPSS V 20). The independent t-test was used to show the mean differences between the groups, and the paired T-test was used to compare the mean differences of the pre and post-training within each group. The level of significance will be set at Alfa 0.05. Results: The results are displayed using tables and figures. A significant difference was found in the mean differences of pre-test values (19.7 cm) and post-test values (37.5 cm) of the Durame city project on the flexibility test (MD =17.8 cm, P = 0.00). On the other hand, there was a significant difference in the mean difference of pre-test values of (18 cm) and post-test values (26.3 cm) of the Hosana city project on the flexibility test ( MD = 8.3 cm, P = 0.00). Conclusion: According to the results of the present studies, there were significant improvements from pre to post-test at Durame City and Hosana City projects on agility, flexibility, power, and speed fitness tests. On the other hand, a significant difference was not found before beginning the exercise between the two projects; however, a significant difference was found after 12 weeks of training.

Keywords: overload, performance, training, volleyball

Procedia PDF Downloads 90

Authors: Mallikarjuna Rao Gundavarapu, Ch. Mallikarjuna Rao, K. Anuradha Bai

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Real Time Video Tracking is a challenging task for computing professionals. The performance of video tracking techniques is greatly affected by background detection and elimination process. Local regions of the image frame contain vital information of background and foreground. However, pixel-level processing of local regions consumes a good amount of computational time and memory space by traditional approaches. In our approach we have explored the concurrent computational ability of General Purpose Graphic Processing Units (GPGPU) to address this problem. The Gaussian Mixture Model (GMM) with adaptive weighted kernels is used for detecting the background. The weights of the kernel are influenced by local regions and are updated by inter-frame variations of these corresponding regions. The proposed system has been tested with GPU devices such as GeForce GTX 280, GeForce GTX 280 and Quadro K2000. The results are encouraging with maximum speed up 10X compared to sequential approach.

Keywords: connected components, embrace threads, local weighted kernel, structuring elements

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Authors: Aarushi Agarwal, Tara Singh, I.L Singh, Anju Lata Singh, Trayambak Tiwari

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Simple discrimination in near absence of attention has been widely observed. Dual-task studies with natural scenes studies have been claimed as being preattentive in nature that facilitated categorization simultaneously with the attentional demanding task. So in this study, multiple images at the periphery are presented, initiating parallel processing in near absence of attention. For the central demanding task rotated letters were presented in both conditions, while in periphery natural and animal images were presented. To understand the breakpoint of ability to perform in near absence of attention one, two and three peripheral images were presented simultaneously with central task and subjects had to respond when all belong to the same category. Individual participant performance did not show a significant difference in both conditions central and peripheral task when the single peripheral image was shown. In case of two images high-level parallel processing could take place with little attentional resources. The eye tracking results supports the evidence as no major saccade was made in a large number of trials. Three image presentations proved to be a breaking point of the capacities to perform outside attentional assistance as participants showed a confused eye gaze pattern which failed to make the natural and animal image discriminations. Thus, we can conclude attention and awareness being independent mechanisms having limited capacities.

Keywords: attention, dual task pardigm, parallel processing, break point, saccade

Procedia PDF Downloads 214