Search results for: Support vector machine (SVM)

Authors: Seyed Mehdi Ghezi, Hesam Hasanpoor

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This scientific article explores enhancement methods for ensemble learning with the aim of improving the performance of classifiers in the analysis and classification of brain signals. The research approach in this field consists of two main parts, each with its own strengths and weaknesses. The choice of approach depends on the specific research question and available resources. By combining these approaches and leveraging their respective strengths, researchers can enhance the accuracy and reliability of classification results, consequently advancing our understanding of the brain and its functions. The first approach focuses on utilizing machine learning methods to identify the best features among the vast array of features present in brain signals. The selection of features varies depending on the research objective, and different techniques have been employed for this purpose. For instance, the genetic algorithm has been used in some studies to identify the best features, while optimization methods have been utilized in others to identify the most influential features. Additionally, machine learning techniques have been applied to determine the influential electrodes in classification. Ensemble learning plays a crucial role in identifying the best features that contribute to learning, thereby improving the overall results. The second approach concentrates on designing and implementing methods for selecting the best classifier or utilizing meta-classifiers to enhance the final results in ensemble learning. In a different section of the research, a single classifier is used instead of multiple classifiers, employing different sets of features to improve the results. The article provides an in-depth examination of each technique, highlighting their advantages and limitations. By integrating these techniques, researchers can enhance the performance of classifiers in the analysis and classification of brain signals. This advancement in ensemble learning methodologies contributes to a better understanding of the brain and its functions, ultimately leading to improved accuracy and reliability in brain signal analysis and classification.

Keywords: ensemble learning, brain signals, classification, feature selection, machine learning, genetic algorithm, optimization methods, influential features, influential electrodes, meta-classifiers

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Authors: Maxence Queyrel, Edi Prifti, Alexandre Templier, Jean-Daniel Zucker

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Analysis of the human microbiome using metagenomic sequencing data has demonstrated high ability in discriminating various human diseases. Raw metagenomic sequencing data require multiple complex and computationally heavy bioinformatics steps prior to data analysis. Such data contain millions of short sequences read from the fragmented DNA sequences and stored as fastq files. Conventional processing pipelines consist in multiple steps including quality control, filtering, alignment of sequences against genomic catalogs (genes, species, taxonomic levels, functional pathways, etc.). These pipelines are complex to use, time consuming and rely on a large number of parameters that often provide variability and impact the estimation of the microbiome elements. Training Deep Neural Networks directly from raw sequencing data is a promising approach to bypass some of the challenges associated with mainstream bioinformatics pipelines. Most of these methods use the concept of word and sentence embeddings that create a meaningful and numerical representation of DNA sequences, while extracting features and reducing the dimensionality of the data. In this paper we present an end-to-end approach that classifies patients into disease groups directly from raw metagenomic reads: metagenome2vec. This approach is composed of four steps (i) generating a vocabulary of k-mers and learning their numerical embeddings; (ii) learning DNA sequence (read) embeddings; (iii) identifying the genome from which the sequence is most likely to come and (iv) training a multiple instance learning classifier which predicts the phenotype based on the vector representation of the raw data. An attention mechanism is applied in the network so that the model can be interpreted, assigning a weight to the influence of the prediction for each genome. Using two public real-life data-sets as well a simulated one, we demonstrated that this original approach reaches high performance, comparable with the state-of-the-art methods applied directly on processed data though mainstream bioinformatics workflows. These results are encouraging for this proof of concept work. We believe that with further dedication, the DNN models have the potential to surpass mainstream bioinformatics workflows in disease classification tasks.

Keywords: deep learning, disease prediction, end-to-end machine learning, metagenomics, multiple instance learning, precision medicine

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Authors: Hatib Shabbir

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Student support services play an important role in providing technical and motivational support to distance learner. ICT based systems have improved the efficiency and effectiveness of support services. In distance education, students being at distant require quick responses from their institution. In the manual system, it is practically hard to give prompt response to each and every student, so as a result student has to suffer a lot. The best way to minimize inefficiencies is to use automated systems. This project involves the development of centralized automated software that would not only replace the manual degree issuance system of 1.3 million students studying at AIOU but also provide online tracking to all the students applying for Degrees. DTS is also the first step towards the paperless culture which is adopted by the major organizations of the world. DTS would not only save university cost but also save students cost and time too by conveying all the information/objection through email and SMS. Moreover, DTS also monitors the performance of each and every individual working in the exam department AIOU and generates daily, monthly and yearly reports of every individual which helps a lot in continuous performance monitoring of the employees.

Keywords: aiou dts, dts aiou, dts, degree tracking aiou

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Authors: Uwe C. Fischer

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Mental health and well-being for employees working in the human service system are getting more and more important given the increasing rate of absenteeism at work. Besides individual capacities, social and community factors seem to be important in the working setting. Starting from a demand resource framework including the classical demand control aspects, social support systems, specific demands and resources of the client work, and work-family conflict were considered in the present study. We state hypothetically, that these factors have a meaningful association with the mental quality of life of employees working in the field of social, educational and health sectors. 1140 employees, working in human service organizations (education, youth care, nursing etc.) were asked for strains and resources at work (selected scales from Salutogenetic Subjective Work Assessment SALSA and own new scales for client work), work-family conflict, and mental quality of life from the German Short Form Health Survey. Considering the complex influences of the variables, we conducted a multiple hierarchical regression analysis. One third of the whole variance of the mental quality of life can be declared by the different variables of the model. When the variables concerning social influences were included in the hierarchical regression, the influence of work related control resource decreased. Excessive workload, work-family conflict, social support by supervisors, co-workers and other persons outside work, as well as strains and resources associated with client work had significant regression coefficients. Conclusions: Social support systems are crucial in the social, educational and health related service sector, regarding the influence on mental well-being. Especially the work-family conflict focuses on the importance of the work-life balance. Also the specific strains and resources of the client work, measured with new constructed scales, showed great impact on mental health. Therefore occupational health promotion should focus more on the social factors within and outside the working place.

Keywords: client interaction, human service system, mental health, social support, work-family conflict

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Authors: Yuhang Wang, Jorg Schluter, Sergiy Shelyag

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The high cost associated with high-resolution computational fluid dynamics (CFD) is one of the main challenges that inhibit the design, development, and optimisation of new combustion systems adapted for renewable fuels. In this study, we propose a physics-guided CNN-based model to predict turbulence evolution and mixing without requiring a traditional CFD solver. The model architecture is built upon U-Net and the inception module, while a physics-guided loss function is designed by introducing two additional physical constraints to allow for the conservation of both mass and pressure over the entire predicted flow fields. Then, the model is trained on the Large Eddy Simulation (LES) results of a natural turbulent mixing layer with two different Reynolds number cases (Re = 3000 and 30000). As a result, the model prediction shows an excellent agreement with the corresponding CFD solutions in terms of both spatial distributions and temporal evolution of turbulent mixing. Such promising model prediction performance opens up the possibilities of doing accurate high-resolution manifold-based combustion simulations at a low computational cost for accelerating the iterative design process of new combustion systems.

Keywords: computational fluid dynamics, turbulence, machine learning, combustion modelling

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Authors: Yang Yang, Dan Liu

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Anomaly detection models for network flow based on machine learning have poor detection performance under extremely unbalanced training data conditions and also have slow detection speed and large resource consumption when deploying on network edge devices. Embedding multi-teacher knowledge distillation (mKD) in anomaly detection can transfer knowledge from multiple teacher models to a single model. Inspired by this, we proposed a state-of-the-art model, mKDNAD, to improve detection performance. mKDNAD mine and integrate the knowledge of one-dimensional sequence and two-dimensional image implicit in network flow to improve the detection accuracy of small sample classes. The multi-teacher knowledge distillation method guides the train of the student model, thus speeding up the model's detection speed and reducing the number of model parameters. Experiments in the CICIDS2017 dataset verify the improvements of our method in the detection speed and the detection accuracy in dealing with the small sample classes.

Keywords: network flow anomaly detection (NAD), multi-teacher knowledge distillation, machine learning, deep learning

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Authors: Ramadhan Febriansyah, Sarah Novianti, Santi Agustini

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Indonesia is a big country with Moslem population. The government must fulfill all needs of the people. However, we do not have a good policy yet especially on healthy, safety and halal food. We try to offer a new solution to overcome this with ASUH (Aman, Sehat, Utuh, Halal) or in English is SHIH (Safe, Healthy, Intact, Halal) as alternative Indonesian policy on food security. This policy is Indonesian Government’s commitment to support Sustainability Development Goals program for the zero hunger (end hunger, to achieve food security and improved nutrition for Indonesian people, of course, to promote sustainable agriculture). Hopefully, it not only can increasing quality on food especially on livestock goods (meat, egg, milk) but also to guarantee the halal food. However, this policy can be an example to others country especially Moslem countries to support SDG’s programs. This research conducted means of the descriptive method; the authors find compare the secondary data obtained from journals, textbook and scientific articles in order to determine the factors that influence food safety and food security. Relevant data used and contain a description of SDG’s as well as about the system food safety and food security that SHIH (Safe, Healthy, Intact and Halal) so these ideas can be implemented.

Keywords: food safety, food security, food sovereignty, halal SDG's

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Authors: Abdullah E. Al-Mazrooei

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In this paper, we present a new kind of the bilinear systems in the form of state space model. The evolution of this system depends on the product of state vector by its self. The well known Lotak Volterra and Lorenz models are special cases of this new model. We also present here a generalization of Kalman filter which is suitable to work with the new bilinear model. An application to real measurements is introduced to illustrate the efficiency of the proposed algorithm.

Keywords: bilinear systems, state space model, Kalman filter, application, models

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Authors: Renzo Munoz-Najar, Cristina Wong, Daniel De La Torre Ugarte

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The literature on price transmission usually deals with asymmetries related to different commodities and/or the short and long term. The role of domestic regional differences and the relationship with asymmetries within a country are usually left out. This paper looks at the asymmetry in the transmission of rice prices from the international price to the farm gate prices in four northern regions of Peru for the last period 2001-2016. These regions are San Martín, Piura, Lambayeque and La Libertad. The relevance of the study lies in its ability to assess the need for policies aimed at improving the competitiveness of the market and ensuring the benefit of producers. There are differences in planting and harvesting dates, as well as in geographic location that justify the hypothesis of the existence of differences in the price transition asymmetries between these regions. Those differences are due to at least three factors geography, infrastructure development, and distribution systems. For this, the Threshold Vector Error Correction Model and the Autoregressive Vector Model with Threshold are used. Both models, collect asymmetric effects in the price adjustments. In this way, it is sought to verify that farm prices react more to falls than increases in international prices due to the high bargaining power of intermediaries. The results of the investigation suggest that the transmission of prices is significant only for Lambayeque and La Libertad. Likewise, the asymmetry in the transmission of prices for these regions is checked. However, these results are not met for San Martin and Piura, the main rice producers nationwide. A significant price transmission is verified only in the Lambayeque and La Libertad regions. San Martin and Piura, in spite of being the main rice producing regions of Peru, do not present a significant transmission of international prices; a high degree of self-sufficient supply might be at the center of the logic for this result. An additional finding is the short-term adjustment with respect to international prices, it is higher in La Libertad compared to Lambayeque, which could be explained by the greater bargaining power of intermediaries in the last-mentioned region due to the greater technological development in the mills.

Keywords: asymmetric price transmission, rice prices, price transmission, regional economics

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Authors: Ilyas Khan. Liliane Pintelon, Harry Martin, Michael Shömig

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The increasing costs of healthcare on one hand, and the rise in aging population and associated chronic disease, on the other hand, are putting increasing burden on the current health care system in many Western countries. For instance, chronic kidney disease (CKD) is a common disease and in Europe, the cost of renal replacement therapy (RRT) is very significant to the total health care cost. However, the recent advancement in healthcare technology, provide the opportunity to treat patients at home in their own comfort. It is evident that home healthcare offers numerous advantages apparently, low costs and high patients’ quality of life. Despite these advantages, the intake of home hemodialysis (HHD) therapy is still low in particular in Germany. Many factors are accounted for the low number of HHD intake. However, this paper is focusing on patients’ safety-related factors of current HHD practices in Germany. The aim of this paper is to analyze the current HHD practices in Germany and to identify risks related factors if any exist. A case study has been conducted in a dialysis center which consists of four dialysis centers in the south of Germany. In total, these dialysis centers have 350 chronic dialysis patients, of which, four patients are on HHD. The centers have 126 staff which includes six nephrologists and 120 other staff i.e. nurses and administration. The results of the study revealed several risk-related factors. Most importantly, these centers do not offer allied health services at the pre-dialysis stage, the HHD training did not have an established curriculum; however, they have just recently developed the first version. Only a soft copy of the machine manual is offered to patients. Surprisingly, the management was not aware of any standard available for home assessment and installation. The home assessment is done by a third party (i.e. the machines and equipment provider) and they may not consider the hygienic quality of the patient’s home. The type of machine provided to patients at home is similar to the one in the center. The model may not be suitable at home because of its size and complexity. Even though portable hemodialysis machines, which are specially designed for home use, are available in the market such as the NxStage series. Besides the type of machine, no assistance is offered for space management at home in particular for placing the machine. Moreover, the centers do not offer remote assistance to patients and their carer at home. However, telephonic assistance is available. Furthermore, no alternative is offered if a carer is not available. In addition, the centers are lacking medical staff including nephrologists and renal nurses.

Keywords: home hemodialysis, home hemodialysis practices, patients’ related risks in the current home hemodialysis practices, patient safety in home hemodialysis

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Authors: Leszek Szpakowski, Daniel Celiński, Sławomir Pilip, Grzegorz Michalak

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The aim of the study was to analyse the usefulness of the 'E-rescuer' pilot project planned to be implemented in a chosen area of Eastern Poland in the cases of suspected sudden cardiac arrests in the extra-urban areas. Inventing an application allowing to dispatch simultaneously both Medical Emergency Teams and the E-rescuer to the place of the accident is the crucial assumption of the mentioned pilot project. The E-rescuer is defined to be the trained person able to take effective basic life support and to use automated external defibrillator. Having logged in using a smartphone, the E-rescuer's readiness is reported online to provide cardiopulmonary resuscitation exactly at the given location. Due to the accurately defined location of the E-rescuer, his arrival time is possible to be precisely fixed, and the substantive support through the displayed algorithms is capable of being provided as well. Having analysed the medical records in the years 2015-2016, cardiopulmonary resuscitation was considered to be effective when an early indication of circulation was provided, and the patient was taken to hospital. In the mentioned term, there were 2.291 cases of a sudden cardiac arrest. Cardiopulmonary resuscitation was taken in 621 patients in total including 205 people in the urban area and 416 in the extra-urban areas. The effectiveness of cardiopulmonary resuscitation in the extra-urban areas was much lower (33,8%) than in the urban (50,7%). The average ambulance arrival time was respectively longer in the extra-urban areas, and it was 12,3 minutes while in the urban area 3,3 minutes. There was no significant difference in the average age of studied patients - 62,5 and 64,8 years old. However, the average ambulance arrival time was 7,6 minutes for effective resuscitations and 10,5 minutes for ineffective ones. Hence, the ambulance arrival time is a crucial factor influencing on the effectiveness of cardiopulmonary resuscitation, especially in the extra-urban areas where it is much longer than in the urban. The key role of trained E-rescuers being nearby taking basic life support before the ambulance arrival can effectively support Emergency Medical Services System in Poland.

Keywords: basic life support, bystander, effectiveness, resuscitation

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Authors: Shu-Ling Wang

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Background: Multiple studies showed early skin-to-skin contact (SSC) with mothers was beneficial to newborns such as breastfeeding and maternal childcare. In cases of newborns unable to have early SSC with mothers, fathers’ involvement could let early SSC continue without interruption. However, few studies had explored the effects of early SSC by fathers in comparison to early SSC with mothers. Paternal involvement of early SSC should be equally important in term of childcare and breastfeeding. The purpose of this study was to evaluate the efficacy of early SSC by fathers in particular in their support of breastfeeding. Methods: A quasi-experimental design was employed by the study. One hundred and forty-four father-infant pairs had participated the study, in which infants were assigned either to SSC with their fathers (n = 72) or to routine care (n = 72) as the control group. The study was conducted at a regional hospital in northern Taiwan. Participants included parents of both vaginal delivery (VD) and caesarean section birth (CS) infants. To be eligible for inclusion, infants must be over 37-week gestational ages. Data were collected twice: as pretest upon admission and as posttest with online questionnaire during first, second, and third postpartum months. The questionnaire included items for Breastfeeding Social Support, methods of feeding, and the mother-infant 24-hour rooming-in rate. The efficacy of early SSC with fathers was evaluated using the generalized estimating equation (GEE) modeling. Research Result: The primary finding was that SSC with fathers had positive impact on fathers’ support of breastfeeding. Analysis of the online questionnaire indicated that early SSC with fathers improved the support of breastfeeding than the control group (VD: t = -4.98, p < .001; CS: t = -2.37, p = .02). Analysis of mother-infant 24-hour rooming-in rate showed that SSC with fathers after CS had a positive impact on the rooming-in rate (χ² = 5.79, p = .02); however, with VD the difference between early SSC with fathers and the control group was insignificant (χ² = .23, p = .63). Analysis of the rate of exclusive breastfeeding indicated that early SSC with fathers had a higher rate than the control group during first three postpartum months for both delivery methods (VD: χ² = 12.51, p < .001 on 1st postpartum month, χ² = 8.13, p < .05 on 2nd postpartum month, χ² = 4.43, p < .05 on 3rd postpartum month; CS: χ² = 6.92, p < .05 on 1st postpartum month, χ² = 7.41, p < .05 on 2nd postpartum month, χ² = 6.24, p < .05 on 3rd postpartum month). No significant difference was found on the rate of exclusive breastfeeding with both methods of delivery between two groups during hospitalization. (VD: χ² =2 .00, p = .16; CS: χ² = .73, p = .39). Conclusion: Implementing early SSC with fathers has many benefits to both parents. The result of this study showed increasing fathers’ support of breastfeeding. This encourages our nursing personnel to focus the needs of father during breastfeeding, therefore further enhancing the quality of parental care, the rate and duration of breastfeeding.

Keywords: breastfeeding, skin-to-skin contact, support of breastfeeding, rooming-in

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Authors: R. Pérez Castells, J. M. Carbajo

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Sepiolite is used as a processing aid in the manufacture of fibre cement from the start of the replacement of asbestos in the 80s. Sepiolite increases the inter-laminar bond between cement layers and improves homogeneity of the slurries. A new type of sepiolite processed product, Wollatrop TF/C, has been checked as a retention agent for fine particles in the production of fibre cement in a Hatschek machine. The effect of Wollatrop T/FC on filtering and fine particle losses was studied as well as the interaction with anionic polyacrylamide and microsilica. The design of the experiments were factorial and the VDT equipment used for measuring retention and drainage was modified Rapid Köethen laboratory sheet former. Wollatrop TF/C increased the fine particle retention improving the economy of the process and reducing the accumulation of solids in recycled process water. At the same time, drainage time increased sharply at high concentration, however drainage time can be improved by adjusting APAM concentration. Wollatrop TF/C and microsilica are having very small interactions among them. Microsilica does not control fine particle losses while Wollatrop TF/C does efficiently. Further research on APAM type (molecular weight and anionic character) is advisable to improve drainage.

Keywords: drainage, fibre-reinforced cement, fine particle losses, flocculation, microsilica, sepiolite

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Authors: Retno Supriyanti, Teguh Budiono, Yogi Ramadhani, Haris B. Widodo, Arwita Mulyawati

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Cervical cancer is the leading cause of mortality in cancer-related diseases. In this diagnosis doctors usually perform several tests to determine the presence of cervical cancer in a patient. However, these checks require support equipment to get the results in more detail. One is by using ultrasonography. However, for the developing countries most of the existing ultrasonography has a low resolution. The goal of this research is to obtain abnormalities on low-resolution ultrasound images especially for cervical cancer case. In this paper, we emphasize our work to use Image Enhancement for pre-processing image quality improvement. The result shows that pre-processing stage is promising to support further analysis.

Keywords: cervical cancer, mortality, low-resolution, image enhancement.

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Authors: Akinwale S. O., Koya O. A.

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The need to provide ecologically-friendly and effective lawn mowing solution is crucial for the well-being of humans. This study involved the modification of a human-powered lawn mower designed to cut tall grasses in residential areas. This study designed and fabricated a reel-type mower blade system and a pedal-powered test rig for the blade system. It also evaluated the performance of the machine. The machine was tested on some overgrown grass plots at College of Education Staff School Ilesa. Parameters such as theoretical field capacity, field efficiency and effective field capacity were determined from the data gathered. The quality of cut achieved by the unit was also documented. Test results showed that the fabricated cutting system produced a theoretical field capacity of 0.11 ha/h and an effective field capacity of 0.08ha/h. Moreover, the unit’s cutting system showed a substantial improvement over existing reel mower designs in its ability to cut on both the forward and reverse phases of its motion. This study established that the blade system described herein has the capacity to cut tall grasses. Hence, this device can therefore eliminate the need for powered mowers entirely on small residential lawns.

Keywords: effective field capacity, field efficiency, theoretical field capacity, quality of cut

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Authors: Anandita Mitro, Archana Srivastava, Bidisha Banerjee

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The present paper attempts to analyze the hierarchy and interconnection of factors responsible for the uptake of BCG vaccination in India. The study uses National Family Health Survey (NFHS-5) data which was conducted during 2019-21. The univariate logistic regression method is used to understand the univariate effects while the interconnection effects have been studied using the Categorical Inference Tree (CIT) which is a non-parametric Machine Learning (ML) model. The hierarchy of the factors is further established using Conditional Inference Forest which is an extension of the CIT approach. The results suggest that BCG vaccination coverage was influenced more by system-level factors and awareness than education or socio-economic status. Factors such as place of delivery, antenatal care, and postnatal care were crucial, with variations based on delivery location. Region-specific differences were also observed which could be explained by the factors. Awareness of the disease was less impactful along with the factor of wealth and urban or rural residence, although awareness did appear to substitute for inadequate ANC. Thus, from the policy point of view, it is revealed that certain subpopulations have less prevalence of vaccination which implies that there is a need for population-specific policy action to achieve a hundred percent coverage.

Keywords: vaccination, NFHS, machine learning, public health

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Authors: Ruth Nalugya, Claire Nimusiima, Elizabeth Kawesa, Harriet Nambejja, Geert van Hove, Janet Seeley, Femke Bannink Mbazzi

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Background: ‘Obuntu bulamu’, an intervention for children, parents, and teachers to improve the participation and inclusion of children with disabilities (CwD) through peer-to-peer support, was developed and tested in central Uganda between 2017 and 2019. The intervention consisted of children, parents, and teachers' training sessions and peer to peer support activities directed at disability inclusion using an African disability framework. In this paper, we discuss parent participation in and parent evaluation of the ‘Obuntu bulamu’ intervention. Methods: This qualitative Afrocentric intervention study was implemented in 10 communities in the Wakiso district in Central Uganda. We purposely selected children aged 8 to 14 years with different impairments, their peers, and parents, with different levels of household income and familial support, who were enrolled in primary schools in the ten communities with on average three children with disabilities per community. Sixty four parents (33 parents of CwDs and 31 peers) participating in the ‘Obuntu bulamu’ study were interviewed at baseline and endline. Two focus group discussions were held with parents at the midline. Parents also participated in a consultative meeting about the intervention design at baseline, and two evaluation workshops held at midline and endline. Thematic data analysis of the interview and focus group data was conducted. Results: Findings showed parents found the group-based activities inspiring and said they built hope and confidence. Parents felt the intervention was acceptable, culturally appropriate, and supportive as it built on values and practices from their own traditions. Parents reported the intervention enhanced a sense of togetherness and belonging through the group meetings and follow-up activities. Parents also mentioned that the training helped them develop more positive attitudes towards CwD and disability inclusion. Parents felt that the invention increased a child’s participation and inclusion at home, school, and in communities. Conclusion: The Obuntu bulamu peer to peer support intervention is an acceptable, culturally appropriate intervention that has the potential to improve the inclusion of CwD. A larger randomized control trial is needed to evaluate the impact of the intervention model.

Keywords: inclusion, participation, inclusive education, peer support, belonging, Ubuntu, ‘Obuntu bulamu’

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Authors: Gulnaz Erkomaishvili

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Introduction: The pandemic and the current economic crisis have created problems for entrepreneurship and, therefore for start-up entrepreneurs. The paper presents the challenges of start-up entrepreneurs in Georgia in the time of pandemic and the analysis of the state economic policy measures. Despite many problems, the study found that in 54.2% of start-ups surveyed under the pandemic, innovation opportunities were growing. It can be stated that the pandemic was a good opportunity to increase the innovative capacity of the enterprise. 52% of the surveyed start-up entrepreneurs managed to adapt to the current situation and increase the sale of their products/services through remote channels. As for the assessment of state support measures by start-up entrepreneurs, a large number of Georgian start-ups do not assess the measures implemented by the state positively. Methodology: The research process uses methods of analysis and synthesis, quantitative and qualitative, interview/survey, grouping, relative and average values, graphing, comparison, data analysis, and others. Main Findings: Studies have shown that for the start-up entrepreneurs, the main problem remains: inaccessible funding, workers' qualifications gap, inflation, taxes, regulation, political instability, inadequate provision of infrastructure, amount of taxes, and other factors. Conclusions: The state should take the following measures to support business start-ups: create an attractive environment for investment, availability of soft loans, creation of an insurance system, infrastructure development, increase the effectiveness of tax policy (simplicity of the tax system, clarity, optimal tax level ); promote export growth (develop strategy for opening up international markets, build up a broad marketing network, etc.).

Keywords: start-up entrepreneurs, startups, start-up entrepreneurs support programs, start-up entrepreneurs support economic policy

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Authors: Ismail Sualman, Mohd Khairuddin Othman

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General Election has been the backbone of democracy that permits people to choose their representatives as they deem fit. The support preferences of the voter differ from one to another, particularly in a plural society like Malaysia. The turning up of high numbers of young voters during the Malaysia 14th General Election has been said to have been caused by social media including Facebook, Twitter, WhatsApp, Instagram, YouTube and Telegram, WeChat and SMS/MMs. It has been observed that, besides using social media as an interaction tool among social friends, it is also an important source of information to know about issues, politics and politicians. This paper exhibits the role of social media in providing political information to young voters, before an election and during the election campaign. This study examines how this information is being translated into election support. A total of 799 Malay young respondents in Selangor have been surveyed and interviewed. This study revealed that social media has become the source of political information among Malay young voters. This research suggested that social media had a significant effect on the support during the election. Social media plays an important role in carrying information such as current issues, voting trends, candidate imagery and matters that may influence the view of young voters. The information obtained from social media has been translated into a voting decision.

Keywords: social media, political behaviour, voters’ choice, election.

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Authors: Rupinder Kaler, Faith Ndebele, Nadia Saleem, Hafsa Sheikh

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Background: Workplace related violence and aggression seems to be considered an acceptable occupational hazard for staff in mental health services. There is literature evidence that healthcare workers in mental health settings are at higher risk from aggression from patients. Aggressive behaviours pose a physical and psychological threat to the psychiatric staff and can result in stress, burnout, sickness, and exhaustion. Further evidence informs that health professionals are the most exposed to psychological disorders such as anxiety, depression and post-traumatic stress disorder. Fear that results from working in a dangerous environment and exhaustion can have a damaging impact on patient care and healthcare relationship. Aim: The aim of this study is to investigate the prevalence and impact of aggressive behaviour on staff working at Coventry and Warwickshire Partnership Trust. Methodology: The study methodology included carrying out a manual, anonymised, multi-disciplinary cross-sectional survey questionnaire across all clinical and non-clinical staff at CWPT from both inpatient and community settings. Findings: The unsurprising finding was that of higher prevalence of aggressive behaviours in in-patients in comparison to community staff. Conclusion: There is a high rate of verbal and physical aggression at work and this has a negative impact on the staff emotional and physical well- being. There is also a higher reliance on colleagues for support on an informal basis than formal organisational support systems. Recommendations: A workforce that is well and functioning is the biggest resource for an organisation. Staff safety during working hours is everyone's responsibility and sits with both individual staff members and the organisation. Post-incident organisational support needs to be consolidated, and hands-on, timely support offered to help maintain emotionally well staff on CWPT. The authors recommend development of preventative and practical protocols for aggression with patient and carer involvement. Post-incident organisational support needs to be consolidated, and hands-on, timely support offered to help maintain emotionally well staff on CWPT.

Keywords: safer staff, survey of staff experiences, violence and aggression, mental health

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Authors: Natacha Fery, Guilherme L. Dalledonne, Xiangyang Zheng, Cheng Tang, Roberto Mayerle

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A Decision Support System (DSS) for supporting decision makers in the management of the Shandong Peninsula has been developed. Emphasis has been given to coastal protection, coastal cage aquaculture and harbors. The investigations were done in the framework of a joint research project funded by the German Ministry of Education and Research (BMBF) and the Chinese Academy of Sciences (CAS). In this paper, a description of the DSS, the development of its components, and results of its application are presented. The system integrates in-situ measurements, process-based models, and a database management system. Numerical models for the simulation of flow, waves, sediment transport and morphodynamics covering the entire Bohai Sea are set up based on the Delft3D modelling suite (Deltares). Calibration and validation of the models were realized based on the measurements of moored Acoustic Doppler Current Profilers (ADCP) and High Frequency (HF) radars. In order to enable cost-effective and scalable applications, a database management system was developed. It enhances information processing, data evaluation, and supports the generation of data products. Results of the application of the DSS to the management of coastal protection, coastal cage aquaculture and harbors are presented here. Model simulations covering the most severe storms observed during the last decades were carried out leading to an improved understanding of hydrodynamics and morphodynamics. Results helped in the identification of coastal stretches subjected to higher levels of energy and improved support for coastal protection measures.

Keywords: coastal protection, decision support system, in-situ measurements, numerical modelling

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Authors: Maria Ezziani, Rabie Zine, Amine Amar, Ilhame Kissani

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This paper introduces a predictive model for urban transportation engineering, which is vital for efficient traffic management. Utilizing comprehensive datasets and advanced statistical techniques, the model accurately forecasts travel times by considering temporal variations and traffic dynamics. Machine learning algorithms, including regression trees and neural networks, are employed to capture sequential dependencies. Results indicate significant improvements in predictive accuracy, particularly during peak hours and holidays, with the incorporation of traffic flow and speed variables. Future enhancements may integrate weather conditions and traffic incidents. The model's applications range from adaptive traffic management systems to route optimization algorithms, facilitating congestion reduction and enhancing journey reliability. Overall, this research extends beyond travel time estimation, offering insights into broader transportation planning and policy-making realms, empowering stakeholders to optimize infrastructure utilization and improve network efficiency.

Keywords: predictive analytics, traffic flow, travel time estimation, urban transportation, machine learning, traffic management

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Authors: Liying Li, Han Guo

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Considering the environmental issues generated by the building sector for its energy consumption, solid waste generation, water use, land use, and global greenhouse gas (GHG) emissions, this review pointed out to LCA as a decision-support tool to substantially improve the sustainability in the building and construction industry. The comprehensiveness and simplicity of LCA make it one of the most promising decision support tools for the sustainable design and construction of future buildings. This paper contains a comprehensive review of existing studies related to LCAs with a focus on their advantages and limitations when applied in the building sector. The aim of this paper is to enhance the understanding of a building life-cycle analysis, thus promoting its application for effective, sustainable building design and construction in the future. Comparisons and discussions are carried out between four categories of LCA methods: building material and component combinations (BMCC) vs. the whole process of construction (WPC) LCA，attributional vs. consequential LCA, process-based LCA vs. input-output (I-O) LCA, traditional vs. hybrid LCA. Classical case studies are presented, which illustrate the effectiveness of LCA as a tool to support the decisions of practitioners in the design and construction of sustainable buildings. (i) BMCC and WPC categories of LCA researches tend to overlap with each other, as majority WPC LCAs are actually developed based on a bottom-up approach BMCC LCAs use. (ii) When considering the influence of social and economic factors outside the proposed system by research, a consequential LCA could provide a more reliable result than an attributional LCA. (iii) I-O LCA is complementary to process-based LCA in order to address the social and economic problems generated by building projects. (iv) Hybrid LCA provides a more superior dynamic perspective than a traditional LCA that is criticized for its static view of the changing processes within the building’s life cycle. LCAs are still being developed to overcome their limitations and data shortage (especially data on the developing world), and the unification of LCA methods and data can make the results of building LCA more comparable and consistent across different studies or even countries.

Keywords: decision support tool, life-cycle analysis, LCA tools and data, sustainable building design

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Authors: Igor A. Krichtafovitch

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The evolutionary processes are not linear. Long periods of quiet and slow development turn to rather rapid emergences of new species and even phyla. During Cambrian explosion, 22 new phyla were added to the previously existed 3 phyla. Contrary to the common credence the natural selection or a survival of the fittest cannot be accounted for the dominant evolution vector which is steady and accelerated advent of more complex and more intelligent living organisms. Neither Darwinism nor alternative concepts including panspermia and intelligent design propose a satisfactory solution for these phenomena. The proposed hypothesis offers a logical and plausible explanation of the evolutionary processes in general. It is based on two postulates: a) the Biosphere is a single living organism, all parts of which are interconnected, and b) the Biosphere acts as a giant biological supercomputer, storing and processing the information in digital and analog forms. Such supercomputer surpasses all human-made computers by many orders of magnitude. Living organisms are the product of intelligent creative action of the biosphere supercomputer. The biological evolution is driven by growing amount of information stored in the living organisms and increasing complexity of the biosphere as a single organism. Main evolutionary vector is not a survival of the fittest but an accelerated growth of the computational complexity of the living organisms. The following postulates may summarize the proposed hypothesis: biological evolution as a natural life origin and development is a reality. Evolution is a coordinated and controlled process. One of evolution’s main development vectors is a growing computational complexity of the living organisms and the biosphere’s intelligence. The intelligent matter which conducts and controls global evolution is a gigantic bio-computer combining all living organisms on Earth. The information is acting like a software stored in and controlled by the biosphere. Random mutations trigger this software, as is stipulated by Darwinian Evolution Theories, and it is further stimulated by the growing demand for the Biosphere’s global memory storage and computational complexity. Greater memory volume requires a greater number and more intellectually advanced organisms for storing and handling it. More intricate organisms require the greater computational complexity of biosphere in order to keep control over the living world. This is an endless recursive endeavor with accelerated evolutionary dynamic. New species emerge when two conditions are met: a) crucial environmental changes occur and/or global memory storage volume comes to its limit and b) biosphere computational complexity reaches critical mass capable of producing more advanced creatures. The hypothesis presented here is a naturalistic concept of life creation and evolution. The hypothesis logically resolves many puzzling problems with the current state evolution theory such as speciation, as a result of GM purposeful design, evolution development vector, as a need for growing global intelligence, punctuated equilibrium, happening when two above conditions a) and b) are met, the Cambrian explosion, mass extinctions, happening when more intelligent species should replace outdated creatures.

Keywords: supercomputer, biological evolution, Darwinism, speciation

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Authors: J. Ramos, V. Gil, A. F. Torres

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The nodular iron is a material that has shown great advantages respect to other materials (steel and gray iron) in the production of machine elements. The engineering industry, especially automobile, are potential users of this material. As it is known, the alloying elements modify the properties of steels and castings. Copper has been investigated as a structural modifier of nodular iron, but studies of its mechanical and tribological implications still need to be addressed for industrial use. With the aim of improving the mechanical properties of nodular iron, alloying elements (Mn, Si, and Cu) are added in order to increase their pearlite (or ferrite) structure according to the percentage of the alloying element. In this research (using induction furnace process) nodular iron with three different percentages of copper (residual, 0,5% and 1,2%) was obtained. Chemical analysis was performed by optical emission spectrometry and microstructures were characterized by Optical Microscopy (ASTM E3) and Scanning Electron Microscopy (SEM). The study of mechanical behavior was carried out in a mechanical test machine (ASTM E8) and a Pin on disk tribometer (ASTM G99) was used to assess wear resistance. It is observed that copper increases the pearlite structure improving the wear behavior; tension behavior. This improvement is observed in higher proportion with 0,5% due to the fact that too much increase of pearlite leads to ductility loss.

Keywords: copper, mechanical properties, nodular iron, pearlite structure, wear

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Authors: K. Sushma Varma, Rajesh Singh

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Non-engineered landfills cause serious environmental damage due to toxic emissions and mobilization of persistent pollutants, organic and inorganic contaminants, as well as soluble metal ions. The available treatment technologies for landfill leachate and solid waste are not effective from an economic, environmental, and social standpoint. The present study assesses the potential of the bioelectrochemical system (BES) integrated with sulfate-reducing bacteria (SRB) in the sustainable treatment and decontamination of landfill wastes. For this purpose, solid waste and landfill leachate collected from different landfill sites were evaluated for long-term treatment using the integrated SRB-BES anaerobic designed bioreactors after pre-treatment. Based on periodic gas composition analysis, physicochemical characterization of the leachate and solid waste, and metal concentration determination, the present system demonstrated significant improvement in volumetric hydrogen production by suppressing methanogenesis. High reduction percentages of Be, Cr, Pb, Cd, Sb, Ni, Cr, COD, and sTOC removal were observed. This mineralization can be attributed to the synergistic effect of ammonia-assisted pre-treatment complexation and microbial sulphide formation. Despite being amended with 0.1N ammonia, the treated leachate level of NO³⁻ was found to be reduced along with SO₄²⁻. This integrated SRB-BES system can be recommended as an eco-friendly solution for landfill reclamation. The BES-treated solid waste was evidently more stabilized, as shown by a five-fold increase in surface area, and potentially useful for leachate immobilization and bio-fortification of agricultural fields. The vector arrangement and magnitude showed similar treatment with differences in magnitudes for both leachate and solid waste. These findings support the efficacy of SRB-BES in the treatment of landfill leachate and solid waste sustainably, inching a step closer to our sustainable development goals. It utilizes low-cost treatment, and anaerobic SRB adapted to landfill sites. This technology may prove to be a sustainable treatment strategy upon scaling up as its outcomes are two-pronged: landfill waste treatment and energy recovery.

Keywords: bio-electrochemical system, leachate /solid waste treatment, landfill leachate, sulfate-reducing bacteria

Procedia PDF Downloads 102

Authors: N. Khodarahmi, L. Ford

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Decades of research on the impact of trauma in early childhood suggest severe risks to the mental health, emotional, social and physical development of a young child. Trauma-exposed students can pose a variety of different levels of challenges to schools and educators of young children and to date, few studies have addressed ECE teachers’ role in providing trauma support. The present study aims to contribute to this literature by exploring the beliefs of British Columbia’s (BC) early childhood education (ECE) teachers in their level of readiness and capability to work within a trauma-informed practice (TIP) framework to support their trauma-exposed students. Through a sequential, mix-methods approach, a self-report questionnaire and semi-structured interviews will be used to gauge BC ECE teachers’ knowledge of TIP, their preparedness, and their ability in using this framework to support their most vulnerable students. Teacher participants will be recruited through the ECEBC organization and various school districts in the Greater Vancouver Area. Questionnaire data will be primarily collected through an online survey tool whereas interviews will be taking place in-person and audio-recorded. Data analysis of survey responses will be largely descriptive, whereas interviews, once transcribed, will be employing thematic content analysis to generate themes from teacher responses. Ultimately, this study hopes to highlight the necessity of utilizing the TIP framework in BC ECE classrooms in order to support both trauma-exposed students and provide essential resources to compassionate educators of young children.

Keywords: early childhood education, early learning classrooms, refugee students, trauma-exposed students, trauma-informed practice

Procedia PDF Downloads 141

Authors: May George

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Inference plays an important role in the learning process and it can lead to a rapid acquisition of a second language. When learning a non-native language, i.e., a critical language like Arabic, the students depend on the teacher’s support most of the time to learn new concepts. The students focus on memorizing the new vocabulary and stress on learning all the grammatical rules. Hence, the students became mechanical and cannot produce the language easily. As a result, they are unable to predict the meaning of words in the context by relying heavily on the teacher, in that they cannot link their prior knowledge or even identify the meaning of the words without the support of the teacher. This study explores how the teacher guides students learning during the inference process and what are the processes of learning that can direct student’s inference.

Keywords: inference, reading, Arabic, language acquisition

Procedia PDF Downloads 531

Authors: Chia-Chen Wei, Pack Hsieh, Jeffrey Chen

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Surface Mount Technology (SMT) is widely used in the area of the electronic assembly in which the electronic components are mounted to the surface of the printed circuit board (PCB). Most of the defects in the SMT process are mainly related to the quality of solder paste printing. These defects lead to considerable manufacturing costs in the electronics assembly industry. Therefore, the solder paste inspection (SPI) machine for controlling and monitoring the amount of solder paste printing has become an important part of the production process. So far, the setting of the SPI threshold is based on statistical analysis and experts’ experiences to determine the appropriate threshold settings. Because the production data are not normal distribution and there are various variations in the production processes, defects related to solder paste printing still occur. In order to solve this problem, this paper proposes an online machine learning algorithm, called the automatic threshold adjustment (ATA) algorithm, and closed-loop architecture in the SMT process to determine the best threshold settings. Simulation experiments prove that our proposed threshold settings improve the accuracy from 99.85% to 100%.

Keywords: big data analytics, Industry 4.0, SPI threshold setting, surface mount technology

Procedia PDF Downloads 116

Authors: Kunal Garg, Louise Theusen Hermansan, Kanoktip Puttaraska, Oliver Hendricks, Heidi Pirttinen, Leona Gilbert

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The Germ Theory (one infectious determinant is equal to one disease) has unarguably evolved our capability to diagnose and treat infectious diseases over the years. Nevertheless, the advent of technology, climate change, and volatile human behavior has brought about drastic changes in our environment, leading us to question the relevance of the Germ Theory in our day, i.e. will vector-borne disease (VBD) sufferers produce multiple immune responses when tested for multiple microbes? Vector diseased patients producing multiple immune responses to different microbes would evidently suggest human polymicrobial infections (HPI). Ongoing diagnostic tools are exceedingly unequipped with the current research findings that would aid in diagnosing patients for polymicrobial infections. This shortcoming has caused misdiagnosis at very high rates, consequently diminishing the patient’s quality of life due to inadequate treatment. Equipped with the state-of-art scientific knowledge, PolyScan intends to address the pitfalls in current VBD diagnostics. PolyScan is a multiplex and multifunctional enzyme linked Immunosorbent assay (ELISA) platform that can test for numerous VBD microbes and allow simultaneous screening for multiple types of antibodies. To validate PolyScan, Lyme Borreliosis (LB) and spondyloarthritis (SpA) patient groups (n = 54 each) were tested for Borrelia burgdorferi, Borrelia burgdorferi Round Body (RB), Borrelia afzelii, Borrelia garinii, and Ehrlichia chaffeensis against IgM and IgG antibodies. LB serum samples were obtained from Germany and SpA serum samples were obtained from Denmark under relevant ethical approvals. The SpA group represented chronic LB stage because reactive arthritis (SpA subtype) in the form of Lyme arthritis links to LB. It was hypothesized that patients from both the groups will produce multiple immune responses that as a consequence would evidently suggest HPI. It was also hypothesized that the multiple immune response proportion in SpA patient group would be significantly larger when compared to the LB patient group across both antibodies. It was observed that 26% LB patients and 57% SpA patients produced multiple immune responses in contrast to 33% LB patients and 30% SpA patients that produced solitary immune responses when tested against IgM. Similarly, 52% LB patients and an astounding 73% SpA patients produced multiple immune responses in contrast to 30% LB patients and 8% SpA patients that produced solitary immune responses when tested against IgG. Interestingly, IgM immune dysfunction in both the patient groups was also recorded. Atypically, 6% of the unresponsive 18% LB with IgG antibody was recorded producing multiple immune responses with the IgM antibody. Similarly, 12% of the unresponsive 19% SpA with IgG antibody was recorded producing multiple immune responses with the IgM antibody. Thus, results not only supported hypothesis but also suggested that IgM may atypically prevail longer than IgG. The PolyScan concept will aid clinicians to detect patients for early, persistent, late, polymicrobial, & immune dysfunction conditions linked to different VBD. PolyScan provides a paradigm shift for the VBD diagnostic industry to follow that will drastically shorten patient’s time to receive adequate treatment.

Keywords: diagnostics, immune dysfunction, polymicrobial, TICK-TAG

Procedia PDF Downloads 327