Search results for: natural language grammar models

Authors: Gabriel Dwomoh, Williams Kwasi Boachie, Kofi Kwarteng

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The study looked at the relationship between organizations’ acquired knowledge, skills, abilities, and shareholders wealth with training playing the mediating role. The sample of the study consisted of organizations that spent 10% or more of its annual budget on training and those whose training budget is less than 10% of the organization’s annual budget. A total of 620 questionnaires were distributed to employees working in various organizations out of which 580 representing 93.5% were retrieved. The respondents that constitute the sample were drawn using convenience sampling. The researchers used regression models for their analyses with the help of SPSS 16.0. Analyzing multiple models, it was discovered that organizations training investment plays a considerable indirect and direct effect with partial mediation between organizations acquired skills, knowledge, abilities, and shareholders wealth. Shareholders should allow their agents to invest part of their holdings to develop the human capital of the organization but this should be done with caution since shareholders returns do not depend much on how much organizations spend in developing its human resource capital.

Keywords: skills, knowledge, abilities, shareholders wealth, training investment

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Authors: Gyaltsen Dakpa, K. J. Senthil Kumar, Nai-Wen Tsao, Sheng-Yang Wang

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Context: Coronavirus disease 2019 (COVID-19) is a severe respiratory illness caused by the SARS-CoV-2 virus. One of the hallmarks of COVID-19 is a change in metabolism, which can lead to increased severity and mortality. The mechanism of SARS-CoV-2-mediated perturbations of metabolic pathways has yet to be fully understood. Research Aim: This study aimed to investigate the metabolic alteration caused by SARS-CoV-2 spike protein in Phorbol 12-myristate 13-acetate (PMA)-induced human monocytes (THP-1) and to examine the regulatory effect of natural compounds like Antcins A on SARS-CoV-2 spike protein-induced metabolic alteration. Methodology: The study used a combination of proton nuclear magnetic resonance (1H-NMR) and MetaboAnalyst 5.0 software. THP-1 cells were treated with SARS-CoV-2 spike protein or control, and the metabolomic profiles of the cells were compared. Antcin A was also added to the cells to assess its regulatory effect on SARS-CoV-2 spike protein-induced metabolic alteration. Findings: The study results showed that treatment with SARS-CoV-2 spike protein significantly altered the metabolomic profiles of THP-1 cells. Eight metabolites, including glycerol-phosphocholine, glycine, canadine, sarcosine, phosphoenolpyruvic acid, glutamine, glutamate, and N, N-dimethylglycine, were significantly different between control and spike-protein treatment groups. Antcin A significantly reversed the changes in these metabolites. In addition, treatment with antacid A significantly inhibited SARS-CoV-2 spike protein-mediated up-regulation of TLR-4 and ACE2 receptors. Theoretical Importance The findings of this study suggest that SARS-CoV-2 spike protein can cause significant metabolic alterations in THP-1 cells. Antcin A, a natural compound, has the potential to reverse these metabolic alterations and may be a potential candidate for developing preventive or therapeutic agents for COVID-19. Data Collection: The data for this study was collected from THP-1 cells that were treated with SARS-CoV-2 spike protein or a control. The metabolomic profiles of the cells were then compared using 1H-NMR and MetaboAnalyst 5.0 software. Analysis Procedures: The metabolomic profiles of the THP-1 cells were analyzed using 1H-NMR and MetaboAnalyst 5.0 software. The software was used to identify and quantify the cells' metabolites and compare the control and spike-protein treatment groups. Questions Addressed: The question addressed by this study was whether SARS-CoV-2 spike protein could cause metabolic alterations in THP-1 cells and whether Antcin A can reverse these alterations. Conclusion: The findings of this study suggest that SARS-CoV-2 spike protein can cause significant metabolic alterations in THP-1 cells. Antcin A, a natural compound, has the potential to reverse these metabolic alterations and may be a potential candidate for developing preventive or therapeutic agents for COVID-19.

Keywords: SARS-CoV-2-spike, ¹H-NMR, metabolomics, antcin-A, taiwanofungus camphoratus

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Authors: Ahmet Kurnaz, Eyup Yurt, Ümit Çiftci

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In this study, too, an attempt was made to reveal the place and effects of information technologies on the lives and education of gifted children based on the views of gifted. To this end, the effects of information technologies on gifted are general skills, technology use, academic and social skills, and cooperative and personal skills were investigated. These skills were explored depending on whether or not gifted had their own computers, had internet connection at home, or how often they use the internet, average time period they spent at the computer, how often they played computer games and their use of social media. The study was conducted using the screening model with a quantitative approach. The sample of the study consisted of 129 gifted attending 5-12th classes in 12 provinces in different regions of Turkey. 64 of the participants were female while 65 were male. The research data were collected using the using computer of gifted and information technologies (UCIT) questionnaire which was developed by the researchers and given its final form after receiving expert view. As a result of the study, it was found that UCIT use improved foreign language speaking skills of gifted, enabled them to get to know and understand different cultures, and made use of computer and information technologies while they study. At the end of the study these result were obtained: Gifted have positive idea using computer and communication technology. There are differences whether using the internet about the ideas UCIT. But there are not differences whether having computer, inhabited city, grade level, having internet at home, daily and weekly internet usage durations, playing the computer and internet game, having Facebook and Twitter account about the UCIT. UCIT contribute to the development of gifted vocabulary, allows knowing and understand different cultures, developing foreign language speaking skills, gifted do not give up computer when they do their homework, improve their reading, listening, understanding and writing skills in a foreign language. Gifted children want to have transition to the use of tablets in education. They think UCIT facilitates doing their homework, contributes learning more information in a shorter time. They'd like to use computer-assisted instruction programs at courses. They think they will be more successful in the future if their computer skills are good. But gifted students prefer teacher instead of teaching with computers and they said that learning can be run from home without going to school.

Keywords: gifted, using computer, communication technology, information technologies

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Authors: Gihan Thilakarathna, Fernando Ishara, Rathnayake Yasith, Bandara A. M. R. Y.

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E-learning is a crucial component of intelligent education. Even in the midst of a pandemic, E-learning is becoming increasingly important in the educational system. Several e-learning programs are accessible for students. Here, we decided to create an e-learning framework for children. We've found a few issues that teachers are having with their online classes. When there are numerous students in an online classroom, how does a teacher recognize a student's focus on academics and below-the-surface behaviors? Some kids are not paying attention in class, and others are napping. The teacher is unable to keep track of each and every student. Key challenge in e-learning is online exams. Because students can cheat easily during online exams. Hence there is need of exam proctoring is occurred. In here we propose an automated online exam cheating detection method using a web camera. The purpose of this project is to present an E-learning platform for math education and include games for kids as an alternative teaching method for math students. The game will be accessible via a web browser. The imagery in the game is drawn in a cartoonish style. This will help students learn math through games. Everything in this day and age is moving towards automation. However, automatic answer evaluation is only available for MCQ-based questions. As a result, the checker has a difficult time evaluating the theory solution. The current system requires more manpower and takes a long time to evaluate responses. It's also possible to mark two identical responses differently and receive two different grades. As a result, this application employs machine learning techniques to provide an automatic evaluation of subjective responses based on the keyword provided to the computer as student input, resulting in a fair distribution of marks. In addition, it will save time and manpower. We used deep learning, machine learning, image processing and natural language technologies to develop these research components.

Keywords: math, education games, e-learning platform, artificial intelligence

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Authors: Ram A. Giri, Amna Bedri, Abdou Niane

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Exclusion in education on the basis of language in multilingual contexts operates at multiple levels. Learners of diverse ethnolinguistic backgrounds are often expected to learn through English and are pushed further down the learning ladder if they also have to access education through Information and Communication Technology (ICT). The paper explores marginalized children’s lived experiences in accessing technology and English in four low-income countries in Africa and Asia. Based on the findings of the first phase of a multinational qualitative research study, we report on the factors or barriers that affect children’s access, opportunities and motivation for learning through technology and English. ICT and English - the language of ICT and education - can enhance learning and can even be essential. However, these two important keys to education can also function as barriers to accessing quality education, and therefore as zones of exclusion. This paper looks into how marginalized children (aged 13-15) engage in learning through ICT and English and to what extent the restrictive access and opportunities contribute to the widening of the already existing gap in education. By applying the conceptual frameworks of “access and accessibility of learning” and “zones of exclusion,” the paper elucidates how the barriers prevent children’s effective engagement with learning and addresses such questions as to how marginalized children access technology and English for learning; whether the children value English, and what their motivation and opportunity to learn it are. In addition, the paper will point out policy and pedagogic implications.

Keywords: exclusion, inclusion, inclusive education, marginalization

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Authors: Maria Angela Bedini, Fabio Bronzini

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The risk of natural disasters affects all the countries of the world, whether it refers to seismic events or tsunamis or hydrogeological disasters. In most cases, the risk can be considered in its three components: hazard, exposure, vulnerability (and urban vulnerability). The aim of this paper is to evaluate how the Italian scientific community has related the contribution of these three components, superimposing the three different maps that summarize the fundamental structure of the risk. Based on the three components considered, the study applies the Regional Planning methodology on the three phases of the risk protection and mitigation process: the prevention phase, the emergency intervention phase, the post-disaster phase. The paper illustrates the Italian experience of the pre-during-post-earthquake intervention. Main results: The study deepens these aspects in the belief that “a historical center” and an “island” can present similar problems at the international level, both in the phase of prevention (earthquake, tsunamis, hydrogeological disasters), in emergency phase (protocols and procedures of intervention) and in the post-disaster phase. The conclusions of the research identify the need to plan in advance how to deal with the post-disaster phase and consider it a priority with respect to the simple reconstruction of destroyed buildings. In fact the main result of the post-disaster intervention must be the return and the social and economic support of the indigenous population, and not only the construction of new housing and equipment. In this sense, the results of the research show that the elderly inhabitants of a historic center can be compared to the indigenous population of an atoll of fishermen, as both constitute the most important resource: the human resource. Their return in conditions of security testifies, with their presence, the culture, customs, and values rooted in the history of a people.

Keywords: post-disaster interventions, risk of natural disasters in Italy and abroad, seismic events in Italy, social and economic protection and support for the native population of historical centers

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Authors: Prashant Verma, Prafulla K. Swain, K. K. Singh, Mukti Khetan

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Objective: In India, around 20,000 women die every year due to abortion-related complications. In the modelling of count variables, there is sometimes a preponderance of zero counts. This article concerns the estimation of various count regression models to predict the average number of spontaneous abortion among women in the Punjab state of India. It also assesses the factors associated with the number of spontaneous abortions. Materials and methods: The study included 27,173 married women of Punjab obtained from the DLHS-4 survey (2012-13). Poisson regression (PR), Negative binomial (NB) regression, zero hurdle negative binomial (ZHNB), and zero-inflated negative binomial (ZINB) models were employed to predict the average number of spontaneous abortions and to identify the determinants affecting the number of spontaneous abortions. Results: Statistical comparisons among four estimation methods revealed that the ZINB model provides the best prediction for the number of spontaneous abortions. Antenatal care (ANC) place, place of residence, total children born to a woman, woman's education and economic status were found to be the most significant factors affecting the occurrence of spontaneous abortion. Conclusions: The study offers a practical demonstration of techniques designed to handle count variables. Statistical comparisons among four estimation models revealed that the ZINB model provided the best prediction for the number of spontaneous abortions and is recommended to be used to predict the number of spontaneous abortions. The study suggests that women receive institutional Antenatal care to attain limited parity. It also advocates promoting higher education among women in Punjab, India.

Keywords: count data, spontaneous abortion, Poisson model, negative binomial model, zero hurdle negative binomial, zero-inflated negative binomial, regression

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Authors: Saifalarab A. Mohmmed, Morgana E. Vianna, Jonathan C. Knowles

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The issue of apical periodontitis has received considerable critical attention. Bacteria is integrated into communities, attached to surfaces and consequently form biofilm. The biofilm structure provides bacteria with a series protection skills against, antimicrobial agents and enhances pathogenicity (e.g. apical periodontitis). Sodium hypochlorite (NaOCl) has become the irrigant of choice for elimination of bacteria from the root canal system based on its antimicrobial findings. The aim of the study was to investigate the effect of different agitation techniques on the efficacy of 2.5% NaOCl to eliminate the biofilm from the surface of the lateral canal using the residual biofilm, and removal rate of biofilm as outcome measures. The effect of canal complexity (lateral canal) on the efficacy of the irrigation procedure was also assessed. Forty root canal models (n = 10 per group) were manufactured using 3D printing and resin materials. Each model consisted of two halves of an 18 mm length root canal with apical size 30 and taper 0.06, and a lateral canal of 3 mm length, 0.3 mm diameter located at 3 mm from the apical terminus. E. faecalis biofilms were grown on the apical 3 mm and lateral canal of the models for 10 days in Brain Heart Infusion broth. Biofilms were stained using crystal violet for visualisation. The model halves were reassembled, attached to an apparatus and tested under a fluorescence microscope. Syringe and needle irrigation protocol was performed using 9 mL of 2.5% NaOCl irrigant for 60 seconds. The irrigant was either left stagnant in the canal or activated for 30 seconds using manual (gutta-percha), sonic and ultrasonic methods. Images were then captured every second using an external camera. The percentages of residual biofilm were measured using image analysis software. The data were analysed using generalised linear mixed models. The greatest removal was associated with the ultrasonic group (66.76%) followed by sonic (45.49%), manual (43.97%), and passive irrigation group (control) (38.67%) respectively. No marked reduction in the efficiency of NaOCl to remove biofilm was found between the simple and complex anatomy models (p = 0.098). The removal efficacy of NaOCl on the biofilm was limited to the 1 mm level of the lateral canal. The agitation of NaOCl results in better penetration of the irrigant into the lateral canals. Ultrasonic agitation of NaOCl improved the removal of bacterial biofilm.

Keywords: 3D printing, biofilm, root canal irrigation, sodium hypochlorite

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Authors: Samah Lakehal, A. Meliani, F. Z. Benrebiha, C. Chaouia

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In the last few years, due to the misuse of antibiotics and an increasing incidence of immunodeficiency-related diseases, the development of microbial drug resistance has become more and more of a pressing problem. Recently, natural products from medicinal plants represent a fertile ground for the development of novel antibacterial agents. Plants essential oils have come more into the focus of phytomedicine. The present study describes antimicrobial activity of Rosmarinus officinalis L. essential oil known medicinally for its powerful antibacterial properties. The essential oil of rosemary obtained by hydrodistillation (using Clevenger type apparatus) growing in Algeria (Djelfa city of south Algeria) was investigated by GC-MS. The essential oil yield of the study was 1.4 %. The major components were found to be camphor, camphene, 1,8-cineole. The essential oil has been tested for antimicrobial activity against eight bacteria (Gram-negative and Gram-positive), and three fungi including Candida albicans. Inhibition of growth was tested by the agar diffusion method based on the determination of the diameter of inhibition. The oil was found to have significant antibacterial activity and therefore can be used as a natural antimicrobial agent for the treatment of several infectious diseases caused by those germs, which have developed resistance to antibiotics.

Keywords: antimicrobial activity, Rosmarinus officinalis L., essential oils, GC/MS, camphor

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Authors: Elham Shahrjooi Haghighi

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This research explores how lexical bundles are utilized in writing in the field of linguistics by comparing professional Persian writers with native English writers using corpus-based studies and advanced computational techniques to examine the occurrence and characteristics of lexical bundles in academic writings. The review of literature emphasizes how important lexical bundles are, in organizing discussions and conveying opinions in both spoken and written language contexts across genres and proficiency levels in fields of study. Previous research has indicated that native English writers tend to employ an array and diversity of bundles than non-native writers do; these bundles are essential elements in academic writing. In this study’s methodology section, the research utilizes a corpus-based method to analyze a collection of writings such as research papers and advanced theses at the doctoral and masters’ levels. The examination uncovers variances in the utilization of groupings between writers who are native speakers of Persian and those who are native English speakers with the latter group displaying a greater occurrence and variety, in types of groupings. Furthermore, the research delves into how these groupings contribute to aspects classifying them into categories based on their relevance to research text structure and individuals as outlined in Hyland’s framework. The results show that Persian authors employ phrases and demonstrate distinct structural and functional tendencies in comparison to native English writers. This variation is linked to differing language skills, levels, disciplinary norms and cultural factors. The study also highlights the pedagogical implications of these findings, suggesting that targeted instruction on the use of lexical bundles could enhance the academic writing skills of non-native speakers. In conclusion, this research contributes to the understanding of lexical bundles in academic writing by providing a detailed comparative analysis of their use by Persian and native English writers. The insights from this study have important implications for language education and the development of effective writing strategies for non-native English speakers in academic contexts.

Keywords: lexical bundles, academic writing, comparative analysis, computational techniques

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Authors: Malik Muhammad Arslan, Muneeb Ullah, Dai Shihan, Daniyal Haider, Xiaodong Yang

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Chest X-rays are instrumental in the detection and monitoring of a wide array of diseases, including viral infections such as COVID-19, tuberculosis, pneumonia, lung cancer, and various cardiac and pulmonary conditions. To enhance the accuracy of diagnosis, artificial intelligence (AI) algorithms, particularly deep learning models like Convolutional Neural Networks (CNNs), are employed. However, these deep learning models demand a substantial and varied dataset to attain optimal precision. Generative Adversarial Networks (GANs) can be employed to create new data, thereby supplementing the existing dataset and enhancing the accuracy of deep learning models. Nevertheless, GANs have their limitations, such as issues related to stability, convergence, and the ability to distinguish between authentic and fabricated data. In order to overcome these challenges and advance the detection and classification of CXR normal and abnormal images, this study introduces a distinctive technique known as DCWGAN (Diverse Conditional Wasserstein GAN) for generating synthetic chest X-ray (CXR) images. The study evaluates the effectiveness of this Idiosyncratic DCWGAN technique using the ResNet50 model and compares its results with those obtained using the traditional GAN approach. The findings reveal that the ResNet50 model trained on the DCWGAN-generated dataset outperformed the model trained on the classic GAN-generated dataset. Specifically, the ResNet50 model utilizing DCWGAN synthetic images achieved impressive performance metrics with an accuracy of 0.961, precision of 0.955, recall of 0.970, and F1-Measure of 0.963. These results indicate the promising potential for the early detection of diseases in CXR images using this Inimitable approach.

Keywords: CNN, classification, deep learning, GAN, Resnet50

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Authors: Warda Ajaz

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This study uses the ‘Community Capitals Framework’ (CCF) to develop a community resilience index that can serve as a useful tool for measuring resilience of communities in diverse contexts and backgrounds. CCF is an important analytical tool to assess holistic community change. This framework identifies seven major types of community capitals: natural, cultural, human, social, political, financial and built, and claims that the communities that have been successful in supporting healthy sustainable community and economic development have paid attention to all these capitals. The framework, therefore, proposes to study the community development through identification of assets in these major capitals (stock), investment in these capitals (flow), and the interaction between these capitals. Capital based approaches have been extensively used to assess community resilience, especially in the context of natural disasters and extreme events. Therefore, this study identifies key indicators for estimating each of the seven capitals through an extensive literature review and then develops an index to calculate a community resilience score. The CCF-based community resilience index presents an innovative way of operationalizing the concept of community resilience and will contribute toward decision-relevant research regarding adaptation and mitigation of community vulnerabilities to climate change-induced, as well as other adverse events.

Keywords: adverse events, community capitals, community resilience, climate change, economic development, sustainability

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Authors: Nadia Akbarpour

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Pancreatic ductal adenocarcinoma is a forceful and obliterating illness, which is portrayed by intrusiveness, fast movement, and significant protection from treatment. Advances in neurotic arrangement and malignant growth hereditary qualities have worked on our illustrative comprehension of this infection; be that as it may, significant parts of pancreatic disease science remain ineffectively comprehended. A superior comprehension of pancreatic disease science should lead the way to more viable medicines. In the course of the most recent couple of years, there have been significant advances in the sub-atomic and organic comprehension of pancreatic malignancy. This included comprehension of the genomic intricacy of the illness, the job of pancreatic malignant growth undifferentiated organisms, the importance of the growth microenvironment, and the one-of-a-kind metabolic transformation of pancreas disease cells to acquire supplements under hypoxic climate. Endeavors have been made towards the advancement of the practical answer for its treatment with compelled achievement due to its complicated science. It is grounded that pancreatic malignancy undifferentiated cells (CSCs), yet present in a little count, contribute extraordinarily to PC inception, movement, and metastasis. Standard chemo and radiotherapeutic choices, notwithstanding, grow general endurance, the connected aftereffects are a huge concern. In the midst of the latest decade, our understanding with regards to atomic and cell pathways engaged with PC and the job of CSCs in its movement has expanded massively. By and by, the center is to target CSCs. The natural items have acquired a lot of thought as of late as they, generally, sharpen CSCs to chemotherapy and target atomic flagging engaged with different cancers, including PC. Some arranged investigations have demonstrated promising outcomes recommending that assessments in this course bring a ton to the table for the treatment of PC. Albeit preclinical investigations uncovered the significance of natural items in lessening pancreatic carcinoma, restricted examinations have been led to assess their part in centers. The current survey gives another knowledge to late advances in pancreatic malignancy science, treatment, and the current status of natural items in its expectation.

Keywords: pancreatic, genomic, organic, cancer

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Authors: Mounir Baccar, Imen Jmal

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Because of the rise in energy costs, thermal storage systems designed for the heating and cooling of buildings are becoming increasingly important. Energy storage can not only reduce the time or rate mismatch between energy supply and demand but also plays an important role in energy conservation. One of the most preferable storage techniques is the Latent Heat Thermal Energy Storage (LHTES) by Phase Change Materials (PCM) due to its important energy storage density and isothermal storage process. This paper presents a numerical study of the solidification of a PCM (paraffin RT27) in a rectangular thermal storage exchanger for air conditioning systems taking into account the presence of natural convection. Resolution of continuity, momentum and thermal energy equations are treated by the finite volume method. The main objective of this numerical approach is to study the effect of natural convection on the PCM solidification time and the impact of fins number on heat transfer enhancement. It also aims at investigating the temporal evolution of PCM solidification, as well as the longitudinal profiles of the HTF circling in the duct. The present research undertakes the study of two cases: the first one treats the solidification of PCM in a PCM-air heat exchanger without fins, while the second focuses on the solidification of PCM in a heat exchanger of the same type with the addition of fins (3 fins, 5 fins, and 9 fins). Without fins, the stratification of the PCM from colder to hotter during the heat transfer process has been noted. This behavior prevents the formation of thermo-convective cells in PCM area and then makes transferring almost conductive. In the presence of fins, energy extraction from PCM to airflow occurs at a faster rate, which contributes to the reduction of the discharging time and the increase of the outlet air temperature (HTF). However, for a great number of fins (9 fins), the enhancement of the solidification process is not significant because of the effect of confinement of PCM liquid spaces for the development of thermo-convective flow. Hence, it can be concluded that the effect of natural convection is not very significant for a high number of fins. In the optimum case, using 3 fins, the increasing temperature of the HTF exceeds approximately 10°C during the first 30 minutes. When solidification progresses from the surfaces of the PCM-container and propagates to the central liquid phase, an insulating layer will be created in the vicinity of the container surfaces and the fins, causing a low heat exchange rate between PCM and air. As the solid PCM layer gets thicker, a progressive regression of the field of movements is induced in the liquid phase, thus leading to the inhibition of heat extraction process. After about 2 hours, 68% of the PCM became solid, and heat transfer was almost dominated by conduction mechanism.

Keywords: heat transfer enhancement, front solidification, PCM, natural convection

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Authors: Rabia Korkmaz Tan, Şebnem Bora

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The major problem encountered when modeling complex systems with agent-based modeling and simulation techniques is the existence of large parameter spaces. A complex system model cannot be expected to reflect the whole of the real system, but by specifying the most appropriate parameters, the actual system can be represented by the model under certain conditions. When the studies conducted in recent years were reviewed, it has been observed that there are few studies for parameter tuning problem in agent based simulations, and these studies have focused on tuning parameters of a single model. In this study, an approach of parameter tuning is proposed by using metaheuristic algorithms such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Artificial Bee Colonies (ABC), Firefly (FA) algorithms. With this hybrid structured study, the parameter tuning problems of the models in the different fields were solved. The new approach offered was tested in two different models, and its achievements in different problems were compared. The simulations and the results reveal that this proposed study is better than the existing parameter tuning studies.

Keywords: parameter tuning, agent based modeling and simulation, metaheuristic algorithms, complex systems

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Authors: Iveta Nováková, Martin-Andrè S. Husby, Boy-Arne Buyle

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The building industry has one of the most significant contributions to global warming due to the production of building materials, transportation, building activities, and demolition of structures when they reach the end of their life. Implementation of circular material flow and circular economy can significantly reduce greenhouse gasses and simultaneously reduce the need for natural resources. The use of recycled concrete aggregates (RCA) is one of the possibilities for reducing the depletion of raw materials for concrete production. Concrete is the most used building material worldwide, and aggregates constitute 70% of its volume. RCA can replace a certain amount of natural aggregates (NA), and concrete will still perform as required. The aim of this scientific paper is to evaluate RCA properties with and without mechanical treatment. Analysis of RCA itself will be followed by compressive strength of concrete containing various amounts of treated and non-treated RCA. Results showed improvement in compressive strength of the mix with mechanically treated RCA compared to standard RCA, and even the strength of concrete with mechanically treated RCA in dose 50% of coarse aggregates was higher than the reference mix by 4%. Based on obtained results, it can be concluded that integration of RCA in industrial concrete production is feasible, at a replacement ratio of 50% for mechanically treated RCA and 30% if untreated RCA is used, without affecting the compressive strength negatively.

Keywords: recycled concrete aggregates, mechanical treatment, aggregate properties, compression strength

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Authors: K. Bencherif, M. Bellifa

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The expected climatic changes in North Africa are the increase of both intensity and frequencies of the summer droughts and a reduction in water availability during growing season. The exiting coppices and forest formations in the national park of Tlemcen are dominated by holm oak, zen oak and cork oak. These opened-fragmented structures don’t seem enough strong so to hope durable protection against climate change. According to the observed climatic tendency, the objective is to analyze the climatic context and its evolution taking into account the eventual behaving of the oak species during the next 20-30 years on one side and the landscaped context in relation with the most adequate sylvicultural models to choose and especially in relation with human activities on another side. The study methodology is based on Climatic synthesis and Floristic and spatial analysis. Meteorological data of the decade 1989-2009 are used to characterize the current climate. An another approach, based on dendrochronological analysis of a 120 years sample Aleppo pine stem growing in the park, is used so to analyze the climate evolution during one century. Results on the climate evolution during the 50 years obtained through climatic predictive models are exploited so to predict the climate tendency in the park. Spatially, in each forest unit of the Park, stratified sampling is achieved so to reduce the degree of heterogeneity and to easily delineate different stands using the GPS. Results from precedent study are used to analyze the anthropogenic factor considering the forecasts for the period 2025-2100, the number of warm days with a temperature over 25°C would increase from 30 to 70. The monthly mean temperatures of the maxima’s (M) and the minima’s (m) would pass respectively from 30.5°C to 33°C and from 2.3°C to 4.8°C. With an average drop of 25%, precipitations will be reduced to 411.37 mm. These new data highlight the importance of the risk fire and the water stress witch would affect the vegetation and the regeneration process. Spatial analysis highlights the forest and the agricultural dimensions of the park compared to the urban habitat and bare soils. Maps show both fragmentation state and forest surface regression (50% of total surface). At the level of the park, fires affected already all types of covers creating low structures with various densities. On the silvi cultural plan, Zen oak form in some places pure stands and this invasion must be considered as a natural tendency where Zen oak becomes the structuring specie. Climate-related changes have nothing to do with the real impact that South-Mediterranean forests are undergoing because human constraints they support. Nevertheless, hardwoods stand of oak in the national park of Tlemcen will face up to unexpected climate changes such as changing rainfall regime associated with a lengthening of the period of water stress, to heavy rainfall and/or to sudden cold snaps. Faced with these new conditions, management based on mixed uneven aged high forest method promoting the more dynamic specie could be an appropriate measure.

Keywords: global warming, mediterranean forest, oak shrub-lands, Tlemcen

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Authors: Teresa Mili

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The significance of political and economic factors have barely been neglected while assessing bilateral relations, but the significance of culture as a soft power in Japan-Vietnam relations has largely been understated. While the close ties had their birth ever since the 14th century, this paper sets out with an inductive lens to analyze the role of culture as a variable in bilateral relations. Vietnam, which then had a history of war devastation had taken refuge in Japan and later sought inspiration from Japan’s economy with the simultaneous influence of culture since Japan was a developed nation, and Vietnam a third world country. Evidencing facts with illustrations, the paper shows how the twenty-first century has brought a growing bond as well as the onset of stronger ties between the two states based, primarily, on an emerging convergence of interests and culture. The cultural influence of Japan may be seen much in the Vietnamese cities, through evidences like the growing numbers of Japanese items on sale. The variety in cultural influence may be seen through the acceptance of Japanese fashion trends, mange comic, pop music, cuisine, tourism, Japanese studies and language, the translations of Japanese literature which are very much popular at Vietnam. Using secondary sources as well as assessing travel accounts and official websites, this research work will try to find out how much Japanese culture has influenced Vietnam and whether such influences will be strong enough to qualify culture as an intervening variable in the bilateral relations.

Keywords: influence, culture, language, cold war

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Authors: Nikolaos Papadimas, Joanna Bennett, Amir Sakhaei, Timothy Dodwell

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Composite modeling of consolidation processes is playing an important role in the process and part design by indicating the formation of possible unwanted prior to expensive experimental iterative trial and development programs. Composite materials in their uncured state display complex constitutive behavior, which has received much academic interest, and this with different models proposed. Errors from modeling and statistical which arise from this fitting will propagate through any simulation in which the material model is used. A general hyperelastic polynomial representation was proposed, which can be readily implemented in various nonlinear finite element packages. In our case, FEniCS was chosen. The coefficients are assumed uncertain, and therefore the distribution of parameters learned using Markov Chain Monte Carlo (MCMC) methods. In engineering, the approach often followed is to select a single set of model parameters, which on average, best fits a set of experiments. There are good statistical reasons why this is not a rigorous approach to take. To overcome these challenges, A hierarchical Bayesian framework was proposed in which population distribution of model parameters is inferred from an ensemble of experiments tests. The resulting sampled distribution of hyperparameters is approximated using Maximum Entropy methods so that the distribution of samples can be readily sampled when embedded within a stochastic finite element simulation. The methodology is validated and demonstrated on a set of consolidation experiments of AS4/8852 with various stacking sequences. The resulting distributions are then applied to stochastic finite element simulations of the consolidation of curved parts, leading to a distribution of possible model outputs. With this, the paper, as far as the authors are aware, represents the first stochastic finite element implementation in composite process modelling.

Keywords: data-driven , material consolidation, stochastic finite elements, surrogate models

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Authors: Müzeyyen Balçikanli, Erdoğan Özbay, Hakan Tacettin Türker, Okan Karahan, Cengiz Duran Atiş

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In this research, effect of curing time (TC), curing temperature (CT), sodium concentration (SC) and silicate modules (SM) on the compressive strength, chloride ion permeability, and water absorption capacity of alkali activated slag (AAS) concretes were investigated. For maximization of compressive strength while for minimization of chloride ion permeability and water absorption capacity of AAS concretes, best possible combination of CT, CTime, SC and SM were determined. An experimental program was conducted by using the central composite design method. Alkali solution-slag ratio was kept constant at 0.53 in all mixture. The effects of the independent parameters were characterized and analyzed by using statistically significant quadratic regression models on the measured properties (dependent parameters). The proposed regression models are valid for AAS concretes with the SC from 0.1% to 7.5%, SM from 0.4 to 3.2, CT from 20 °C to 94 °C and TC from 1.2 hours to 25 hours. The results of test and analysis indicate that the most effective parameter for the compressive strength, chloride ion permeability and water absorption capacity is the sodium concentration.

Keywords: alkali activation, slag, rapid chloride permeability, water absorption capacity

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Authors: Muhammad Azam, Micheal Olaolu Arowolo, Fei He, Mihail Popescu, Dong Xu

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The number of biological papers is growing quickly, which means that the number of biological pathway figures in those papers is also increasing quickly. Each pathway figure shows extensive biological information, like the names of genes and how the genes are related. However, manually annotating pathway figures takes a lot of time and work. Even though using advanced image understanding models could speed up the process of curation, these models still need to be made more accurate. To improve gene name recognition from pathway figures, we applied a Siamese network to map image segments to a library of pictures containing known genes in a similar way to person recognition from photos in many photo applications. We used a triple loss function and a triplet spatial pyramid pooling network by combining the triplet convolution neural network and the spatial pyramid pooling (TSPP-Net). We compared VGG19 and VGG16 as the Siamese network model. VGG16 achieved better performance with an accuracy of 93%, which is much higher than OCR results.

Keywords: biological pathway, image understanding, gene name recognition, object detection, Siamese network, VGG

Procedia PDF Downloads 282

Authors: M. Al-Saedi, A. Chegenizadeh, H. Nikraz

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Experimental investigations are conducted to assess a layered structure of glass (G) - rock (R) blends under the impact of repeated loading. Laboratory tests included sieve analyses, modified compaction test and repeated load triaxial test (RLTT) is conducted on different structures of stratified GR samples to reach the objectives of this study. Waste materials are such essential components in the climate system, and also commonly used in minimising the need for natural materials in many countries. Glass is one of the most widely used groups of waste materials which have been extensively using in road applications. Full range particle size and colours of glass are collected and mixed at different ratios with natural rock material trying to use the blends in pavement layers. Whole subsurface specimen sequentially consists of a single layer of R and a layer of G-R blend. 12G/88R and 45G/55R mix ratios are employed in this research, the thickness of G-R layer was changed, and the results were compared between the pure rock and the layered specimens. The relations between resilient module (Mr) and permanent deformation with sequence number are presented. During the earlier stages of RLTT, the results indicated that the 45G/55R specimen shows higher moduli than R specimen.

Keywords: Rock base course, Layered Structure, Glass, Resilient Modulus

Procedia PDF Downloads 121

Authors: Tomas Premoli, Sareh Rowlands

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In this study, we investigate the impact of various convolutional neural network (CNN) architectures on the accuracy of diagnosing Alzheimer’s disease (AD) using patient MRI scans. Alzheimer’s disease is a debilitating neurodegenerative disorder that affects millions worldwide. Early, accurate, and non-invasive diagnostic methods are required for providing optimal care and symptom management. Deep learning techniques, particularly CNNs, have shown great promise in enhancing this diagnostic process. We aim to contribute to the ongoing research in this field by comparing the effectiveness of different CNN architectures and providing insights for future studies. Our methodology involved preprocessing MRI data, implementing multiple CNN architectures, and evaluating the performance of each model. We employed intensity normalization, linear registration, and skull stripping for our preprocessing. The selected architectures included VGG, ResNet, and DenseNet models, all implemented using the Keras library. We employed transfer learning and trained models from scratch to compare their effectiveness. Our findings demonstrated significant differences in performance among the tested architectures, with DenseNet201 achieving the highest accuracy of 86.4%. Transfer learning proved to be helpful in improving model performance. We also identified potential areas for future research, such as experimenting with other architectures, optimizing hyperparameters, and employing fine-tuning strategies. By providing a comprehensive analysis of the selected CNN architectures, we offer a solid foundation for future research in Alzheimer’s disease diagnosis using deep learning techniques. Our study highlights the potential of CNNs as a valuable diagnostic tool and emphasizes the importance of ongoing research to develop more accurate and effective models.

Keywords: Alzheimer’s disease, convolutional neural networks, deep learning, medical imaging, MRI

Procedia PDF Downloads 67

Authors: S. H. Iranmanesh, L. Aliabadi, A. Mollajan

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Integrated resilience engineering (IRE) is capable of returning banking systems to the normal state in extensive economic circumstances. In this study, information system of a large bank (with several branches) is assessed and optimized under severe economic conditions. Data envelopment analysis (DEA) models are employed to achieve the objective of this study. Nine IRE factors are considered to be the outputs, and a dummy variable is defined as the input of the DEA models. A standard questionnaire is designed and distributed among executive managers to be considered as the decision-making units (DMUs). Reliability and validity of the questionnaire is examined based on Cronbach's alpha and t-test. The most appropriate DEA model is determined based on average efficiency and normality test. It is shown that the proposed integrated design provides higher efficiency than the conventional RE design. Results of sensitivity and perturbation analysis indicate that self-organization, fault tolerance, and reporting culture respectively compose about 50 percent of total weight.

Keywords: banking system, Data Envelopment Analysis (DEA), Integrated Resilience Engineering (IRE), performance evaluation, perturbation analysis

Procedia PDF Downloads 180

Authors: Atheer Al-Nuaimi, Harry Evdorides

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Every day many people die or get disabled or injured on roads around the world, which necessitates more specific treatments for transportation safety issues. International road assessment program (iRAP) model is one of the comprehensive road safety models which accounting for many factors that affect road safety in a cost-effective way in low and middle income countries. In iRAP model road safety has been divided into five star ratings from 1 star (the lowest level) to 5 star (the highest level). These star ratings are based on star rating score which is calculated by iRAP methodology depending on road attributes, traffic volumes and operating speeds. The outcome of iRAP methodology are the treatments that can be used to improve road safety and reduce fatalities and serious injuries (FSI) numbers. These countermeasures can be used separately as a single countermeasure or mix as multiple countermeasures for a location. There is general agreement that the adequacy of a countermeasure is liable to consistent losses when it is utilized as a part of mix with different countermeasures. That is, accident diminishment appraisals of individual countermeasures cannot be easily added together. The iRAP model philosophy makes utilization of a multiple countermeasure adjustment factors to predict diminishments in the effectiveness of road safety countermeasures when more than one countermeasure is chosen. A multiple countermeasure correction factors are figured for every 100-meter segment and for every accident type. However, restrictions of this methodology incorporate a presumable over-estimation in the predicted crash reduction. This study aims to adjust this correction factor by developing new models to calculate the effect of using multiple countermeasures on the number of fatalities for a location or an entire road. Regression models have been used to establish relationships between crash frequencies and the factors that affect their rates. Multiple linear regression, negative binomial regression, and Poisson regression techniques were used to develop models that can address the effectiveness of using multiple countermeasures. Analyses are conducted using The R Project for Statistical Computing showed that a model developed by negative binomial regression technique could give more reliable results of the predicted number of fatalities after the implementation of road safety multiple countermeasures than the results from iRAP model. The results also showed that the negative binomial regression approach gives more precise results in comparison with multiple linear and Poisson regression techniques because of the overdispersion and standard error issues.

Keywords: international road assessment program, negative binomial, road multiple countermeasures, road safety

Procedia PDF Downloads 235

Authors: Neslihan Şahin Çelik, Ali Eraslan

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In recent years, mathematics educators have frequently stressed the necessity of instructing students about models and modeling approaches that encompass cognitive and metacognitive thought processes, starting from the first years of school and continuing on through the years of higher education. The purpose of this study is to examine the thought processes of 4th-grade primary school students in their modeling activities and to explore the difficulties encountered in these processes, if any. The study, of qualitative design, was conducted in the 2015-2016 academic year at a public state-school located in a central city in the Black Sea Region of Turkey. A preliminary study was first implemented with designated 4th grade students, after which the criterion sampling method was used to select three students that would be recruited into the focus group. The focus group that was thus formed was asked to work on the model eliciting activity of the Paper Airplane Problem and the entire process was recorded on video. The Paper Airplane Problem required the students to determine the winner with respect to: (a) the plane that stays in the air for the longest time; (b) the plane that travels the greatest distance in a straight-line path; and (c) the overall winner for the contest. A written transcript was made of the video recording, after which the recording and the students' worksheets were analyzed using the Blum and Ferri modeling cycle. The results of the study revealed that the students tested the hypotheses related to daily life that they had set up, generated ideas of their own, verified their models by making connections with real life, and tried to make their models generalizable. On the other hand, the students had some difficulties in terms of their interpretation of the table of data and their ways of operating on the data during the modeling processes.

Keywords: primary school students, model eliciting activity, mathematical modeling, modeling process, paper airplane problem

Procedia PDF Downloads 354

Authors: Abdulkabir Abdullahi

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Nigeria has not yet welcomed phonics into its primary schools. In government-owned primary schools teachers are functionally ignorant of the stories of the reading wars amongst international scholars. There are few or no Nigerian-authored phonics textbooks, and there has been no government-owned phonics curriculum either. There are few or no academic journal articles on phonics in the country and there is, in fact, a certain danger of confusion between phonics and phonetics among Nigerian publishers, authors, writers and academics as if Nigerian teachers of English and the educational policy makers of the country were unaware of reading failures/problems amongst Nigerian children, or had never heard of phonics or read of the stories of the reading wars or the annual phonics test in the United Kingdom, the United States of America and other parts of the world. It is on this note that this article reviews and examines, in the style of a qualitative inquiry, the body of arguments on phonics, and explores the effectiveness of phonics teaching, particularly, in a second-language learning contexts. While the merit of the paper is, perhaps, situated in its supreme effort to draw global attention to reading failures/problems in Nigeria and the ways the situation may affect English language learning, international academic relations and the educational future of the country, it leaves any quantitative verification of its claims to interested quantitative researchers in the world.

Keywords: graphemes, phonics, reading, reading wars, reading theories, phonemic awareness

Procedia PDF Downloads 229

Authors: Kayla Marie Sarte

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This study sought to describe mother tongue-based classes in the light of classroom interactional discourse using the Sinclair and Coulthard model. It specifically identified the exchanges, grouped into Teaching and Boundary types; moves, coded as Opening, Answering and Feedback; and the occurrence of the 13 acts (Bid, Cue, Nominate, Reply, React, Acknowledge, Clue, Accept, Evaluate, Loop, Comment, Starter, Conclusion, Aside and Silent Stress) in the classroom, and determined what these reveal about the teaching and learning processes in the MTB classroom. Being a qualitative study, using the Single Collective Case Within-Site (embedded) design, varied data collection procedures such as non-participant observations, audio-recordings and transcription of MTB classes, and semi-structured interviews were utilized. The results revealed the presence of all the codes in the model (except for the silent stress) which also implied that the Hiligaynon mother tongue-based class was eclectic, cultural and communicative, and had a healthy, analytical and focused environment which aligned with the aims of MTB-MLE, and affirmed the purported benefits of mother tongue teaching. Through the study, gaps in the mother tongue teaching and learning were also identified which involved the difficulty of children in memorizing Hiligaynon terms expressed in English in their homes and in the communities.

Keywords: discourse analysis, language teaching and learning, mother tongue-based education, multilingualism

Procedia PDF Downloads 256

Authors: Rajendra Chetty

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The paper aims to address two aspects of postgraduate studies: interdisciplinary research and creative models of supervision. Interdisciplinary research can be viewed as a key imperative to solve complex problems. While excellent research requires a context of disciplinary strength, the cutting edge is often found at the intersection between disciplines. Interdisciplinary research foregrounds a team approach and information, methodologies, designs, and theories from different disciplines are integrated to advance fundamental understanding or to solve problems whose solutions are beyond the scope of a single discipline. Our aim should also be to generate research that transcends the original disciplines i.e. transdisciplinary research. Complexity is characteristic of the knowledge economy, hence, postgraduate research and engaged scholarship should be viewed by universities as primary vehicles through which knowledge can be generated to have a meaningful impact on society. There are far too many ‘ordinary’ studies that fall into the realm of credentialism and certification as opposed to significant studies that generate new knowledge and provide a trajectory for further academic discourse. Secondly, the paper will look at models of supervision that are different to the dominant ‘apprentice’ or individual approach. A reflective practitioner approach would be used to discuss a range of supervision models that resonate well with the principles of interdisciplinarity, growth in the postgraduate sector and a commitment to engaged scholarship. The global demand for postgraduate education has resulted in increased intake and new demands to limited supervision capacity at institutions. Team supervision lodged within large-scale research projects, working with a cohort of students within a research theme, the journal article route of doctoral studies and the professional PhD are some of the models that provide an alternative to the traditional approach. International cooperation should be encouraged in the production of high-impact research and institutions should be committed to stimulating international linkages which would result in co-supervision and mobility of postgraduate students and global significance of postgraduate research. International linkages are also valuable in increasing the capacity for supervision at new and developing universities. Innovative co-supervision and joint-degree options with global partners should be explored within strategic planning for innovative postgraduate programmes. Co-supervision of PhD students is probably the strongest driver (besides funding) for collaborative research as it provides the glue of shared interest, advantage and commitment between supervisors. The students’ field serves and informs the co-supervisors own research agendas and helps to shape over-arching research themes through shared research findings.

Keywords: interdisciplinarity, internationalisation, postgraduate, supervision

Procedia PDF Downloads 233

Authors: Arūnas Burinskas

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Although Europe is on the threshold of a new industrial revolution called Industry 4.0, many believe that this will increase the flexibility of production, the mass adaptation of products to consumers and the speed of their service; it will also improve product quality and dramatically increase productivity. However, as expected, all the benefits of Industry 4.0 face many of the inevitable changes and challenges they pose. One of them is the inevitable transformation of current competition and business models. This article examines the possible results of competitive conversion from the classic Bertrand and Cournot models to qualitatively new competition based on innovation. Ability to deliver a new product quickly and the possibility to produce the individual design (through flexible and quickly configurable factories) by reducing equipment failures and increasing process automation and control is highly important. This study shows that the ongoing transformation of the competition model is changing the game. This, together with the creation of complex value networks, means huge investments that make it particularly difficult for small and medium-sized enterprises. In addition, the ongoing digitalization of data raises new concerns regarding legal obligations, intellectual property, and security.

Keywords: Bertrand and Cournot Competition, competition model, industry 4.0, industrial organisation, monopolistic competition

Procedia PDF Downloads 135