Search results for: tool validation

Authors: Stephanie Liu Lu

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With the proliferation of artificial intelligence tools in the field of education, it is crucial to explore their impact on language learning outcomes. This paper examines the use of AI tools, such as ChatGPT, in practical writing within business Chinese teaching to investigate how AI can enhance practical writing skills and teaching effectiveness. The study involved third and fourth-year university students majoring in accounting and finance from a university in Hong Kong within the context of a business correspondence writing class. Students were randomly assigned to a control group, who completed business letter writing independently, and an experimental group, who completed the writing with the assistance of AI. In the latter, the AI-assisted business letters were initially drafted by the students issuing commands and interacting with the AI tool, followed by the students' revisions of the draft. The paper assesses the performance of both groups in terms of grammatical expression, communicative effect, and situational awareness. Additionally, the study collected dialogue texts from interactions between students and the AI tool to explore factors that affect text generation and the potential impact of AI on enhancing students' communicative and identity awareness. By collecting and comparing textual performances, it was found that students assisted by AI showed better situational awareness, as well as more skilled organization and grammar. However, the research also revealed that AI-generated articles frequently lacked a proper balance of identity and writing purpose due to limitations in students' communicative awareness and expression during the instruction and interaction process. Furthermore, the revision of drafts also tested the students' linguistic foundation, logical thinking abilities, and practical workplace experience. Therefore, integrating AI tools and related teaching into the curriculum is key to the future of business Chinese teaching.

Keywords: AI-assistance, business Chinese, textual analysis, language education

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Authors: Neha Asthana, Vishal Krishna Prasad

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Collaborative planning and forecasting are the innovative and systematic approaches towards productive integration and assimilation of data synergized into information. The changing and variable market dynamics have persuaded global business chains to incorporate collaborative planning and forecasting as an imperative tool. Thus, it is essential for the supply chains to constantly improvise, update its nature, and mould as per changing global environment.

Keywords: information transfer, forecasting, optimization, supply chain management

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Authors: Edward Schwalb, Matthias Dehmer, Michael Schlenkrich, Farzaneh Taslimi, Ketron Mitchell-Wynne, Horen Kuecuekyan

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We present a generalized feature extraction approach for supporting Machine Learning (ML) algorithms which perform tasks similar to Finite-Element Analysis (FEA). We report results for estimating the Head Injury Categorization (HIC) of vehicle engine compartments across various impact scenarios. Our experiments demonstrate that models learned using features derived with a simple discretization approach provide a reasonable approximation of a full simulation. We observe that Decision Trees could be as effective as Neural Networks for the HIC task. The simplicity and performance of the learned Decision Trees could offer a trade-off of a multiple order of magnitude increase in speed and cost improvement over full simulation for a reasonable approximation. When used as a complement to full simulation, the approach enables rapid approximate feedback to engineering teams before submission for full analysis. The approach produces mesh independent features and is further agnostic of the assembly structure.

Keywords: mechanical design validation, FEA, supervised decision tree, convolutional neural network.

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Authors: Nesrine Gaaliche

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This study provides a finite element dynamic model for analyzing rolling bearing system vibration response. The vibration responses of polypropylene bearings with and without defects are studied using FE analysis and compared to experimental data. The viscoelastic behavior of thermoplastic is investigated in this work to evaluate the influence of material flexibility and damping viscosity. The vibrations are detected using 3D dynamic analysis. Peak vibrations are more noticeable in an inner ring defect than in an outer ring defect, according to test data. The performance of thermoplastic bearings is compared to that of metal parts using vibration signals. Both the test and numerical results show that Polypropylene bearings exhibit less vibration than steel counterparts. Unlike bearings made from metal, polypropylene bearings absorb vibrations and handle shaft misalignments. Following validation of the overall vibration spectrum data, Von Mises stresses inside the rings are assessed under high loads. Stress is significantly high under the balls, according to the simulation findings. For the test cases, the computational findings correspond closely to the experimental results.

Keywords: viscoelastic, FE analysis, polypropylene, bearings

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Authors: Guillaume Mullier, Jean François Chatelain

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Carbon Fiber Reinforced Plastics (CFRPs) are widely used for advanced applications, in particular in aerospace, automotive and wind energy industries. Once cured to near net shape, CFRP parts need several finishing operations such as trimming, milling or drilling in order to accommodate fastening hardware and meeting the final dimensions. The present research aims to study the effect of the cutting temperature in trimming on the mechanical strength of high performance CFRP laminates used for aeronautics applications. The cutting temperature is of great importance when dealing with trimming of CFRP. Temperatures higher than the glass-transition temperature (Tg) of the resin matrix are highly undesirable: they cause degradation of the matrix in the trimmed edges area, which can severely affect the mechanical performance of the entire component. In this study, a 9.50 mm diameter CVD diamond coated carbide tool with six flutes was used to trim 24-plies CFRP laminates. A 300 m/min cutting speed and 1140 mm/min feed rate were used in the experiments. The tool was heated prior to trimming using a blowtorch, for temperatures ranging from 20°C to 300°C. The temperature at the cutting edge was measured using embedded K-Type thermocouples. Samples trimmed for different cutting temperatures, below and above Tg, were mechanically tested using three-points bending short-beam loading configurations. New cutting tools as well as worn cutting tools were utilized for the experiments. The experiments with the new tools could not prove any correlation between the length of cut, the cutting temperature and the mechanical performance. Thus mechanical strength was constant, regardless of the cutting temperature. However, for worn tools, producing a cutting temperature rising up to 450°C, thermal damage of the resin was observed. The mechanical tests showed a reduced mean resistance in short beam configuration, while the resistance in three point bending decreases with increase of the cutting temperature.

Keywords: composites, trimming, thermal damage, surface quality

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Authors: Tan Lay Cheng (Cheryl), Low Huiqi

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Background: All children learn at different pace. Individualized learning is an approach that tailors to the individual learning needs of each child. When implementing this approach, educators have to base their lessons on the understanding that all students learn differently and that what works for one student may not work for another. In the current early childhood environment, individualized learning is for children with diverse needs. However, a typical developing child is also able to benefit from individualized learning. This research abstract explores the concept of utilizing DNA-MILE, a patented (in Singapore) DNA-based assessment tool that can be used to measure a variety of factors that can impact learning. The assessment report includes the dominant intelligence of the user or, in this case, the child. From the result, a personalized learning plan that is tailored to each individual student's needs. Methods: A study will be conducted to investigate the effectiveness of DNA-MILE in supporting individualized learning. The study will involve a group of 20 preschoolers who were randomly assigned to either a DNA-MILE-assessed group (experimental group) or a control group. 10 children in each group. The experimental group will receive DNA Mile assessments and personalized learning plans, while the control group will not. The children in the experimental group will be taught using the dominant intelligence (as shown in the DNA-MILE report) to enhance their learning in other domains. The children in the control group will be taught using the curriculum and lesson plan set by their teacher for the whole class. Parents’ and teachers’ interviews will be conducted to provide information about the children before the study and after the study. Results: The results of the study will show the difference in the outcome of the learning, which received DNA Mile assessments and personalized learning plans, significantly outperformed the control group on a variety of measures, including standardized tests, grades, and motivation. Conclusion: The results of this study suggest that DNA Mile can be an effective tool for supporting individualized learning. By providing personalized learning plans, DNA Mile can help to improve learning outcomes for all students.

Keywords: individualized, DNA-MILE, learning, preschool, DNA, multiple intelligence

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Authors: Ogar Ofut Tumenayu, Olga Shabalina

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This paper describes the application of two types of pedagogical agents’ technology with different functions in an adaptive educational game with the sole aim of improving learning and enhancing interactivities in Digital Educational Games (DEG). This idea could promote the elimination of some problems of DEG, like isolation in game-based learning, by introducing a tutor and tutee pedagogical agents. We present an analysis of a learning companion interacting in a peer tutoring environment as a step toward improving social interactions in the educational game environment. We show that tutor and tutee agents use different interventions and interactive approaches: the tutor agent is engaged in tracking the learner’s activities and inferring the learning state, while the tutee agent initiates interactions with the learner at the appropriate times and in appropriate manners. In order to provide motivation to prevent mistakes and clarity a game task, the tutor agent uses the help dialog tool to provide assistance, while the tutee agent provides collaboration assistance by using the hind tool. We presented our idea on a prototype game called “Pyramid Programming Game,” a 2D game that was developed using Libgdx. The game's Pyramid component symbolizes a programming task that is presented to the player in the form of a puzzle. During gameplay, the Agents can instruct, direct, inspire, and communicate emotions. They can also rapidly alter the instructional pattern in response to the learner's performance and knowledge. The pyramid must be effectively destroyed in order to win the game. The game also teaches and illustrates the advantages of utilizing educational agents such as TrA and TeA to assist and motivate students. Our findings support the idea that the functionality of a pedagogical agent should be dualized into an instructional and learner’s companion agent in order to enhance interactivity in a game-based environment.

Keywords: tutor agent, tutee agent, learner’s companion interaction, agent collaboration

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Authors: Carine Platat, Fatima Qshadi, Ghofran Kayed, Nour Hussein, Amjad Jarrar, Habiba Ali

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Nowadays, smartphones are very popular. They are offering a variety of easy-to-use and free applications among which step counters and fitness tests. The number of users is huge making of such applications a potentially efficient new strategy to encourage people to become more active. Nonetheless, data on their reliability and validity are very scarce and when available, they are often negative and contradictory. Besides, weight status, which is likely to introduce a bias in the physical activity assessment, was not often considered. Hence, the use of these applications as motivational tool, assessment tool and in research is questionable. PACER is one of the free step counters application. Even though it is one of the best rated free application by users, it has never been tested for reliability and validity. Prior any use of PACER, this remains to be investigated. The objective of this work is to investigate the reliability and validity of the smartphone application PACER in measuring the number of steps and in assessing the cardiorespiratory fitness by the 6 minutes walking test. 20 overweight or obese students (10 male and 10 female) were recruited at the United Arab Emirate University, aged between 18 and 25 years old. Reliability and validity were tested in real life conditions and in controlled conditions by using a treadmill. Test-retest experiments were done with PACER on 2 days separated by a week in real life conditions (24 hours each time) and in controlled conditions (30 minutes on treadmill, 3km/h). Validity was tested against the pedometer OMRON in the same conditions. During treadmill test, video was recorded and steps numbers were compared between PACER, pedometer and video. The validity of PACER in estimating the cardiorespiratory fitness (VO2max) as part of the 6 minutes walking test (6MWT) was studied against the 20m shuttle running test. Reliability was studied by calculating intraclass correlation coefficients (ICC), 95% confidence interval (95%CI) and by Bland-Altman plots. Validity was studied by calculating Spearman correlation coefficient (rho) and Bland-Altman plots. PACER reliability was good in both male and female in real life conditions (p≤10-3) but only in female in controlled conditions (p=0.01). PACER was valid against OMRON pedometer in male and female in real life conditions (rho=0.94, p≤10-3 ; rho=0.64, p=0.01, in male and female respectively). In controlled conditions, PACER was not valid against pedometer. But, PACER was valid against video in female (rho=0.72, p≤10-3). PACER was valid against the shuttle run test in male and female (rho-=0.66, p=0.01 ; rho=0.51, p=0.04) to estimate VO2max. This study provides data on the reliability and viability of PACER in overweight or obese male and female young adults. Globally, PACER was shown as reliable and valid in real life conditions in overweight or obese male and female to count steps and assess fitness. This supports the use of PACER to assess and promote physical activity in clinical follow-up and community interventions.

Keywords: smartphone application, pacer, reliability, validity, steps, fitness, physical activity

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Authors: Omid Khodabakhshi, Amir Rozdel

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The subject of cloud computing security research has allocated a number of challenges and competitions because the data center is comprised of complex private information and are always faced various risks of information disclosure by hacker attacks or internal enemies. Accordingly, the security of virtual machines in the cloud computing infrastructure layer is very important. So far, there are many software solutions to develop security in virtual machines. But using software alone is not enough to solve security problems. The purpose of this article is to examine the challenges and security requirements for accessing and storing data in an insecure cloud environment. In other words, in this article, a structure is proposed for the implementation of highly isolated security-sensitive codes using secure computing hardware in virtual environments. It also allows remote code validation with inputs and outputs. We provide these security features even in situations where the BIOS, the operating system, and even the super-supervisor are infected. To achieve these goals, we will use the hardware support provided by the new Intel and AMD processors, as well as the TPM security chip. In conclusion, the use of these technologies ultimately creates a root of dynamic trust and reduces TCB to security-sensitive codes.

Keywords: code, cloud computing, security, virtual machines

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Authors: Sally Ibrahim, Mohamed Hedia, Mohamed Taqi, Mohamed Derbala, Karima Mahmoud, Youssef Ahmed, Sayed Ismail, Mohamed El-Belely

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The identification and quantification of serum microRNA (miRNA) from mares with endometritis might serve as useful and implementable clinical biomarkers for the early diagnosis of endometiritis. Aims of the current study were (I) to study the expression pattern of eca-miR-155, eca-miR-223, eca-miR-17, eca-miR-200a, and eca-miR-205, and (II) to determine the levels of interleukin 6 (IL-6), prostaglandins (PGF₂α and PGE₂), in the serum of Arabian mares with healthy and abnormal uterine status (endometritis). This study was conducted on 80 Arabian mares (4-14 years old). Mares were divided into 48 sub-fertile mares suspected of endometritis and 32 fertile at stud farms. The criteria for mares to be enrolled in the endometritis group were that they had been bred three or more times unsuccessfully in the breeding season or had a history of more than one year of reproductive failure. In addition, two or more of the following criteria on a checklist were present: abnormal clinical findings, transrectal ultrasonographic uterine examination showed abnormal fluid in the uterus (echogenic or ≥2 cm in diameter), positive endometrial cytology; and bacterial and/or fungal growth. Serum samples were collected for measuring IL-6, PGF₂α, and PGE₂ concentrations, as well as serum miRNA isolation and quantitative real-time PCR. Serum concentrations of IL-6, PGE₂, and PGF₂α were higher (P ≤ 0.001) in mares with endometritis compared to the control healthy ones. The expression profile of eca-miR-155, eca-miR-223, eca-miR-17, eca-miR-200a, and eca-miR-205 increased (P≤0.001) in mares with endometritis compared to the control ones. To the best of our knowledge, this is the first study that revealed that serum miRNA and serum inflammatory mediators (IL-6, PGE₂, and PGF₂α) could be used as non-invasive gold standard biomarkers, and therefore might be served as an important additional diagnostic tool for endometritis in Arabian mares. Moreover, estimation of the serum concentrations of serum miRNA, IL-6, PGE₂, and PGF₂α is a promising recommended tool during the breeding soundness examination in mares.

Keywords: Arabian Mares, endometritis, inflammatory mediators, serum miRNA

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Authors: R. Christopher, C. Brandt, N. Damons

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Background: The sequence of prevention model states that by constant assessment of injury, injury mechanisms and risk factors are identified, highlighting that collecting and recording of data is a core approach for preventing injuries. Several screening tools are available for use in the clinical setting. These screening techniques only recently received research attention, hence there is a dearth of inconsistent and controversial data regarding their applicability, validity, and reliability. Several systematic reviews related to common soccer injuries have been conducted; however, none of them addressed the screening tools for common soccer injuries. Objectives: The purpose of this study was to conduct a review of screening tools and their accuracy for common injuries in soccer. Methods: A systematic scoping review was performed based on the Joanna Briggs Institute procedure for conducting systematic reviews. Databases such as SPORT Discus, Cinahl, Medline, Science Direct, PubMed, and grey literature were used to access suitable studies. Some of the key search terms included: injury screening, screening, screening tool accuracy, injury prevalence, injury prediction, accuracy, validity, specificity, reliability, sensitivity. All types of English studies dating back to the year 2000 were included. Two blind independent reviewers selected and appraised articles on a 9-point scale for inclusion as well as for the risk of bias with the ACROBAT-NRSI tool. Data were extracted and summarized in tables. Plot data analysis was done, and sensitivity and specificity were analyzed with their respective 95% confidence intervals. I² statistic was used to determine the proportion of variation across studies. Results: The initial search yielded 95 studies, of which 21 were duplicates, and 54 excluded. A total of 10 observational studies were included for the analysis: 3 studies were analysed quantitatively while the remaining 7 were analysed qualitatively. Seven studies were graded low and three studies high risk of bias. Only high methodological studies (score > 9) were included for analysis. The pooled studies investigated tools such as the Functional Movement Screening (FMS™), the Landing Error Scoring System (LESS), the Tuck Jump Assessment, the Soccer Injury Movement Screening (SIMS), and the conventional hamstrings to quadriceps ratio. The accuracy of screening tools was of high reliability, sensitivity and specificity (calculated as ICC 0.68, 95% CI: 52-0.84; and 0.64, 95% CI: 0.61-0.66 respectively; I² = 13.2%, P=0.316). Conclusion: Based on the pooled results from the included studies, the FMS™ has a good inter-rater and intra-rater reliability. FMS™ is a screening tool capable of screening for common soccer injuries, and individual FMS™ scores are a better determinant of performance in comparison with the overall FMS™ score. Although meta-analysis could not be done for all the included screening tools, qualitative analysis also indicated good sensitivity and specificity of the individual tools. Higher levels of evidence are, however, needed for implication in evidence-based practice.

Keywords: accuracy, screening tools, sensitivity, soccer injuries, specificity

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Authors: Abdorrasoul Malekpour, Mohammad Ghorbani Mojtaba Mortazavi, Mohammadreza Fattahi, Mohammad Hassan Meshkibaf, Ali Fakhrzad, Saeid Salehi, Saeideh Zahedi, Amir Ahmadimoghaddam, Parviz Farzadnia Dr., Mohammadreza Hajyani Asl Bs

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Hepatitis B as an infectious disease has eight main genotypes (A–H). The aim of this study is to Bioinformatically identify Rare Codon Clusters (RCC) in proteins structure of HBV. For detection of protein family accession numbers (Pfam) of HBV proteins; used of uni-prot database and Pfam search tool were used. Obtained Pfam IDs were analyzed in Sherlocc program and RCCs in HBV proteins were detected. In further, the structures of TrEMBL entries proteins studied in PDB database and 3D structures of the HBV proteins and locations of RCCs were visualized and studied using Swiss PDB Viewer software. Pfam search tool have found nine significant hits and 0 insignificant hits in 3 frames. Results of Pfams studied in the Sherlocc program show this program not identified RCCs in the external core antigen (PF08290) and truncated HBeAg protein (PF08290). By contrast the RCCs become identified in Hepatitis core antigen (PF00906) Large envelope protein S (PF00695), X protein (PF00739), DNA polymerase (viral) N-terminal domain (PF00242) and Protein P (Pf00336). In HBV genome, seven RCC identified that found in hepatitis core antigen, large envelope protein S and DNA polymerase proteins and proteins structures of TrEMBL entries sequences that reported in Sherlocc program outputs are not complete. Based on situation of RCC in structure of HBV proteins, it suggested those RCCs are important in HBV life cycle. We hoped that this study provide a new and deep perspective in protein research and drug design for treatment of HBV.

Keywords: rare codon clusters, hepatitis B virus, bioinformatic study, infectious disease

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Authors: Charles Iledun Oyewole

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The daunting challenge that the ‘man with the hoe’ is going to face in the coming decades will be complex and interwoven. With global population already above 7 billion people, it has been estimated that food (crop) production must more than double by 2050 to meet up with the world’s food requirements. Nigeria population is also expected to reach over 240 million people by 2050, at the current annual population growth of 2.61 per cent. The country’s farming population is estimated at over 65 per cent, but the country still depends on food importation to complement production. The small scale farmer, who depends on simple hand tools: hoes and cutlasses, remains the centre of agricultural production, accounting for 90 per cent of the total agricultural output and 80 per cent of the market flow. While the hoe may have been a tool for sustainable development at a time in human history, this role has been smothered by population growth, which has brought too many mouths to be fed (over 170 million), as well as many industries to fuel with raw materials. It may then be argued that the hoe is unfortunately not a tool for the coming challenges and that agricultural mechanization should be the focus. However, agriculture as an enterprise is a ‘complete wheel’ which does not work when broken, particularly, in respect to mechanization. Generally, mechanization will prompt increase production, where land is readily available; increase production, will require post-harvest handling mechanisms, crop processing and subsequent storage. An important aspect of this is readily available and favourable markets for such produce; fuel by good agricultural policies. A break in this wheel will lead to the process of mechanization crashing back to subsistence production, and probably reversal to the hoe. The focus of any agricultural policy should be to chart a course for sustainable mechanization that is environmentally friendly, that may ameliorate Nigeria’s food and raw material gaps. This is the focal point of this article.

Keywords: Crop production, Farmer, Hoes, Mechanization, Policy framework, Population, Growth, Rural areas

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Authors: Subhadip Biswas, Shivendra Maurya, Satish Chandra, Indrajit Ghosh

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Developing speed model is a challenging task particularly under mixed traffic condition where the traffic composition plays a significant role in determining vehicular speed. The present research has been conducted to model individual vehicular speed in the context of mixed traffic on an urban arterial. Traffic speed and volume data have been collected from three midblock arterial road sections in New Delhi. Using the field data, a volume based speed prediction model has been developed adopting the methodology of Artificial Neural Network (ANN). The model developed in this work is capable of estimating speed for individual vehicle category. Validation results show a great deal of agreement between the observed speeds and the predicted values by the model developed. Also, it has been observed that the ANN based model performs better compared to other existing models in terms of accuracy. Finally, the sensitivity analysis has been performed utilizing the model in order to examine the effects of traffic volume and its composition on individual speeds.

Keywords: speed model, artificial neural network, arterial, mixed traffic

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Authors: Teklu Urgessa, Wookjae Maeng, Joong Seek Lee

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Application of five implementations of three data mining classification techniques was experimented for extracting important insights from tourism data. The aim was to find out the best performing algorithm among the compared ones for tourism knowledge discovery. Knowledge discovery process from data was used as a process model. 10-fold cross validation method is used for testing purpose. Various data preprocessing activities were performed to get the final dataset for model building. Classification models of the selected algorithms were built with different scenarios on the preprocessed dataset. The outperformed algorithm tourism dataset was Random Forest (76%) before applying information gain based attribute selection and J48 (C4.5) (75%) after selection of top relevant attributes to the class (target) attribute. In terms of time for model building, attribute selection improves the efficiency of all algorithms. Artificial Neural Network (multilayer perceptron) showed the highest improvement (90%). The rules extracted from the decision tree model are presented, which showed intricate, non-trivial knowledge/insight that would otherwise not be discovered by simple statistical analysis with mediocre accuracy of the machine using classification algorithms.

Keywords: classification algorithms, data mining, knowledge discovery, tourism

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Authors: Aldin Justin Sundararaj, Austin Lord Tennyson, Divya Jose, A. N. Subash

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Blast waves are generated due to the explosions of high energy materials. An explosion yielding a blast wave has the potential to cause severe damage to buildings and its personnel. In order to understand the physics of effects of blast pressure on buildings, studies in the shock tube on generic configurations are carried out at various pressures on discrete models. The strength of shock wave is systematically varied by using different driver gases and diaphragm thickness. The basic material of the diaphragm is Aluminum. To simulate the effect of shock waves on discrete models a shock tube was used. Generic models selected for this study are suitably scaled cylinder, cone and cubical blocks. The experiments were carried out with 2mm diaphragm with burst pressure ranging from 28 to 31 bar. Numerical analysis was carried out over these discrete models. A 3D model of shock-tube with different discrete models inside the tube was used for CFD computation. It was found that cone has dissipated most of the shock pressure compared to cylinder and cubical block. The robustness and the accuracy of the numerical model were validation with the analytical and experimental data.

Keywords: shock wave, blast wave, discrete models, shock tube

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Authors: Jaishree Ranganathan, MuthuPriya Shanmugakani Velsamy, Shamika Kulkarni, Angelina Tzacheva

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Emotions play an important role in everyday life. An-alyzing these emotions or feelings from social media platforms like Twitter, Facebook, blogs, and forums based on user comments and reviews plays an important role in various factors. Some of them include brand monitoring, marketing strategies, reputation, and competitor analysis. The opinions or sentiments mined from such data helps understand the current state of the user. It does not directly provide intuitive insights on what actions to be taken to benefit the end user or business. Actionable Pattern Mining method provides suggestions or actionable recommendations on what changes or actions need to be taken in order to benefit the end user. In this paper, we propose automatic classification of emotions in Twitter data using Recurrent Neural Network - Gated Recurrent Unit. We achieve training accuracy of 87.58% and validation accuracy of 86.16%. Also, we extract action rules with respect to the user emotion that helps to provide actionable suggestion.

Keywords: emotion mining, twitter, recurrent neural network, gated recurrent unit, actionable pattern mining

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Authors: Dheyaa Hussein, Peter Armstrong

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The phenomenon of visual disorder is prominent in contemporary townscapes. This paper provides a theoretical framework for the assessment of visual consistency in townscape in order to achieve more favourable outcomes for users. In this paper, visual consistency refers to the amount of similarity between adjacent components of townscape. The paper investigates parameters which relate to visual consistency in townscape, explores the relationships between them and highlights their significance. The paper uses arithmetic methods from outside the domain of urban design to enable the establishment of an objective approach of assessment which considers subjective indicators including users’ preferences. These methods involve the standard of deviation, colour distance and the distance between points. The paper identifies urban space as a key representative of the visual parameters of townscape. It focuses on its two components, geometry and colour in the evaluation of the visual consistency of townscape. Accordingly, this article proposes four measurements. The first quantifies the number of vertices, which are points in the three-dimensional space that are connected, by lines, to represent the appearance of elements. The second evaluates the visual surroundings of urban space through assessing the location of their vertices. The last two measurements calculate the visual similarity in both vertices and colour in townscape by the calculation of their variation using methods including standard of deviation and colour difference. The proposed quantitative assessment is based on users’ preferences towards these measurements. The paper offers a theoretical basis for a practical tool which can alter the current understanding of architectural form and its application in urban space. This tool is currently under development. The proposed method underpins expert subjective assessment and permits the establishment of a unified framework which adds to creativity by the achievement of a higher level of consistency and satisfaction among the citizens of evolving townscapes.

Keywords: townscape, urban design, visual assessment, visual consistency

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Authors: Mukhtar Maigari

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The landscape of Higher Education (HE) institutions, especially following the CVID-19 pandemic, necessitates advanced approaches to manage Indoor Environmental Quality (IEQ) which is crucial for the comfort, health, and productivity of students and staff. This study investigates the application of Building Information Modelling (BIM) as a multifaceted tool for monitoring, assessing, and controlling IEQ in HE buildings aiming to bridge the gap between traditional management practices and the innovative capabilities of BIM. Central to the study is a comprehensive literature review, which lays the foundation by examining current knowledge and technological advancements in both IEQ and BIM. This review sets the stage for a deeper investigation into the practical application of BIM in IEQ management. The methodology consists of Post-Occupancy Evaluation (POE) which encompasses physical monitoring, questionnaire surveys, and interviews under the umbrella of case studies. The physical data collection focuses on vital IEQ parameters such as temperature, humidity, CO2 levels etc, conducted by using different equipment including dataloggers to ensure accurate data. Complementing this, questionnaire surveys gather perceptions and satisfaction levels from students, providing valuable insights into the subjective aspects of IEQ. The interview component, targeting facilities management teams, offers an in-depth perspective on IEQ management challenges and strategies. The research delves deeper into the development of a conceptual BIM-based framework, informed by the insight findings from case studies and empirical data. This framework is designed to demonstrate the critical functions necessary for effective IEQ monitoring, assessment, control and automation with real time data handling capabilities. This BIM-based framework leads to the developing and testing a BIM-based prototype tool. This prototype leverages on software such as Autodesk Revit with its visual programming tool i.e., Dynamo and an Arduino-based sensor network thereby allowing for real-time flow of IEQ data for monitoring, control and even automation. By harnessing the capabilities of BIM technology, the study presents a forward-thinking approach that aligns with current sustainability and wellness goals, particularly vital in the post-COVID-19 era. The integration of BIM in IEQ management promises not only to enhance the health, comfort, and energy efficiency of educational environments but also to transform them into more conducive spaces for teaching and learning. Furthermore, this research could influence the future of HE buildings by prompting universities and government bodies to revaluate and improve teaching and learning environments. It demonstrates how the synergy between IEQ and BIM can empower stakeholders to monitor IEQ conditions more effectively and make informed decisions in real-time. Moreover, the developed framework has broader applications as well; it can serve as a tool for other sustainability assessments, like energy analysis in HE buildings, leveraging measured data synchronized with the BIM model. In conclusion, this study bridges the gap between theoretical research and real-world application by practicalizing how advanced technologies like BIM can be effectively integrated to enhance environmental quality in educational institutions. It portrays the potential of integrating advanced technologies like BIM in the pursuit of improved environmental conditions in educational institutions.

Keywords: BIM, POE, IEQ, HE-buildings

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Authors: Hadjoui Abdelhamid, Saimi Ahmed

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The hybrid h-p finite element method for the dynamic behavior of nonlinear rotors is described in this paper. The standard h-version method of discretizing the problem is retained, but modified to allow the use of polynomially-enriched beam elements. A hierarchically enriching element will thus not affect the nodal displacement and rotation, but will influence the values of the nodal bending moment and shear force is used. The deterministic movements of rotation and translation of the support which are coupled to the excitations due to unbalance are also taken into account. We study also the geometric dissymmetry of the shaft and the disc, thus the equations of motion of the rotor contain variable parametric coefficients over time that can lead to a lateral dynamic instability. The effects of movements combined support for bearings are analyzed and discussed through Campbell diagrams and spectral analyses. A program is made in Matlab. After validation of the program, several examples are studied. The influence of physical and geometric parameters on the natural frequencies of the shaft is determined through the study of these examples. Among these parameters, we include the variation in the diameter and the thickness of the rotor, the position of the disc.

Keywords: Campbell diagram, critical speeds, nonlinear rotor, version h-p of FEM

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Authors: Amani Kappi, Ana Maria Linares, Gia Mudd-Martin

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Children with Attention Deficit Hyperactivity Disorder (ADHD) are more likely to develop social skills deficits that can lead to academic underachievement, peer rejection, and maladjustment. Surveying teachers about children's social skills with ADHD will become a significant factor in identifying whether the children will be diagnosed with social skills deficits. The teacher-specific version of the Social Skills Rating System scale (SSRS-T) has been used as a screening tool for children's social behaviors. The psychometric properties of the SSRS-T have been evaluated in various populations and settings, such as when used by teachers to assess social skills for children with learning disabilities. However, few studies have been conducted to examine the psychometric properties of the SSRS-T when used to assess children with ADHD. The purpose of this study was to examine the psychometric properties of the SSRS-T and two SSRS-T subscales, Social Skills and Problem Behaviors. This was a secondary analysis of longitudinal data from the Fragile Families and Child Well-Being Study. This study included a sample of 194 teachers who used the SSRS-T to assess the social skills of children aged 8 to 10 years with ADHD. Exploratory principal components factor analysis was used to assess the construct validity of the SSRS-T scale. Cronbach’s alpha value was used to assess the internal consistency reliability of the total SSRS-T scale and the subscales. Item analyses included item-item intercorrelations, item-to-subscale correlations, and Cronbach’s alpha value changes with item deletion. The results of internal consistency reliability for both the total scale and subscales were acceptable. The results of the exploratory factor analysis supported the five factors of SSRS-T (Cooperation, Self-control, Assertion, Internalize behaviors, and Externalize behaviors) reported in the original version. Findings indicated that SSRS-T is a reliable and valid tool for assessing the social behaviors of children with ADHD.

Keywords: ADHD, children, social skills, SSRS-T, psychometric properties

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Authors: Songul Cinaroglu

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Machine learning regression methods are recommended as an alternative to classical regression methods in the existence of variables which are difficult to model. Data for health expenditure is typically non-normal and have a heavily skewed distribution. This study aims to compare machine learning regression methods by hyperparameter tuning to predict health expenditure per capita. A multiple regression model was conducted and performance results of Lasso Regression, Random Forest Regression and Support Vector Machine Regression recorded when different hyperparameters are assigned. Lambda (λ) value for Lasso Regression, number of trees for Random Forest Regression, epsilon (ε) value for Support Vector Regression was determined as hyperparameters. Study results performed by using 'k' fold cross validation changed from 5 to 50, indicate the difference between machine learning regression results in terms of R², RMSE and MAE values that are statistically significant (p < 0.001). Study results reveal that Random Forest Regression (R² ˃ 0.7500, RMSE ≤ 0.6000 ve MAE ≤ 0.4000) outperforms other machine learning regression methods. It is highly advisable to use machine learning regression methods for modelling health expenditures.

Keywords: machine learning, lasso regression, random forest regression, support vector regression, hyperparameter tuning, health expenditure

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Authors: Reena Murali, David Peter S.

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The small interfering RNA (siRNA) alters the regulatory role of mRNA during gene expression by translational inhibition. Recent studies shows that up regulation of mRNA cause serious diseases like Cancer. So designing effective siRNA with good knockdown effects play an important role in gene silencing. Various siRNA design tools had been developed earlier. In this work, we are trying to analyze the existing good scoring second generation siRNA predicting tools and to optimize the efficiency of siRNA prediction by designing a computational model using Artificial Neural Network and whole stacking energy (ΔG), which may help in gene silencing and drug design in cancer therapy. Our model is trained and tested against a large data set of siRNA sequences. Validation of our results is done by finding correlation coefficient of experimental versus observed inhibition efficacy of siRNA. We achieved a correlation coefficient of 0.727 in our previous computational model and we could improve the correlation coefficient up to 0.753 when the threshold of whole tacking energy is greater than or equal to -32.5 kcal/mol.

Keywords: artificial neural network, double stranded RNA, RNA interference, short interfering RNA

Procedia PDF Downloads 526

Authors: Sabiu Bala Muhammad, Rosli Saad

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Multiple linear regression (MLR) models for fast estimation of true subsurface resistivity from apparent resistivity field measurements are developed and assessed in this study. The parameters investigated were apparent resistivity (ρₐ), horizontal location (X) and depth (Z) of measurement as the independent variables; and true resistivity (ρₜ) as the dependent variable. To achieve linearity in both resistivity variables, datasets were first transformed into logarithmic domain following diagnostic checks of normality of the dependent variable and heteroscedasticity to ensure accurate models. Four MLR models were developed based on hierarchical combination of the independent variables. The generated MLR coefficients were applied to another data set to estimate ρₜ values for validation. Contours of the estimated ρₜ values were plotted and compared to the observed data plots at the colour scale and blanking for visual assessment. The accuracy of the models was assessed using coefficient of determination (R²), standard error (SE) and weighted mean absolute percentage error (wMAPE). It is concluded that the MLR models can estimate ρₜ for with high level of accuracy.

Keywords: apparent resistivity, depth, horizontal location, multiple linear regression, true resistivity

Procedia PDF Downloads 276

Authors: Khaled Ayfi

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In industrial oxygen systems at high temperature and high pressure, contamination by solid particles is one of the principal causes of ignition hazards. Indeed, gas can sweep away particles, generated by corrosion inside the pipes or during maintenance operations (welding residues, careless disassembly, etc.) and produce accumulations at places where the gas velocity decrease. Moreover, in such an environment rich in oxygen (oxidant), particles are highly reactive and can ignite system walls more actively and at higher temperatures. Oxidation based thermal effects are responsible for mechanical properties lost, leading to the destruction of the pressure equipment wall. To deal with this problem, a numerical analysis is done regarding a sample representative of a wall subjected to pressure and temperature. The validation and analysis are done comparing the numerical simulations results to experimental measurements. More precisely, in this work, we propose a numerical model that describes the thermomechanical behavior of thin metal disks under pressure and subjected to laser heating. This model takes into account the geometric and material nonlinearity and has been validated by the comparison of simulation results with experimental measurements.

Keywords: ignition, oxygen, numerical simulation, thermomechanical behavior

Procedia PDF Downloads 105

Authors: Aika Umemuro, Mitsuru Sato, Mizuki Narita, Saya Hori, Saya Sakurai, Tomomi Nakayama, Ayano Nakazawa, Toshihiro Ogura

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Mammography requires the detection of very small calcifications, and physicians search for microcalcifications by magnifying the images as they read them. The mouse is necessary to zoom in on the images, but this can be tiring and distracting when many images are read in a single day. Therefore, an image magnification system combining an eye-detector and a simple electroencephalograph (EEG) scanner was devised, and its operability was evaluated. Two experiments were conducted in this study: the measurement of eye-detection error using an eye-detector and the measurement of the time required for image magnification using a simple EEG scanner. Eye-detector validation showed that the mean distance of eye-detection error ranged from 0.64 cm to 2.17 cm, with an overall mean of 1.24 ± 0.81 cm for the observers. The results showed that the eye detection error was small enough for the magnified area of the mammographic image. The average time required for point magnification in the verification of the simple EEG scanner ranged from 5.85 to 16.73 seconds, and individual differences were observed. The reason for this may be that the size of the simple EEG scanner used was not adjustable, so it did not fit well for some subjects. The use of a simple EEG scanner with size adjustment would solve this problem. Therefore, the image magnification system using the eye-detector and the simple EEG scanner is useful.

Keywords: EEG scanner, eye-detector, mammography, observers

Procedia PDF Downloads 215

Authors: Shanti Faridah Salleh, Azzahrah Anuar, Hamimah Ujir, Rohana Sapawi, Wan Hashim Wan Ibrahim, Noraziah Abdul Wahab, Majina Sulaiman, Raudhah Ahmadi, Al-Khalid Othman, Johari Abdullah

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Integrated Cumulative Grade Point Average or iCGPA is an evaluation and reporting system that represents a comprehensive development of students’ achievement in their academic programs. Universiti Malaysia Sarawak, UNIMAS has started its implementation of iCGPA in 2016. iCGPA is driven by the Outcome-Based Education (OBE) system that has been long integrated into the higher education in Malaysia. iCGPA is not only a tool to enhance the OBE concept through constructive alignment but it is also an integrated mechanism to assist various stakeholders in making decisions or planning for program improvement. The outcome of this integrated system is the reporting of students’ academic performance in terms of cognitive (knowledge), psychomotor (skills), and affective (attitude) of which the students acquire throughout the duration of their study. The iCGPA reporting illustrates the attainment of student’s attribute in the eight domains of learning outcomes listed in the Malaysian Qualifications Framework (MQF). This paper discusses on the implementation of iCGPA in UNIMAS on the policy and strategy to direct the whole university to implement the iCGPA. The steps and challenges in integrating the exsting Outcome-Based Education and utilising iCGPA as a tool to quantify the students’ achievement are also highlighted in this paper. Finally, the ACADEMIA system, which is a dedicated centralised program ensure the implementation of iCGPA is a success has been developed. This paper discusses the structure and the analysis of ACADEMIA program and concludes the analysis made on the improvement made on the implementation of constructive alignment in all 40 programs involves in iCGPA implementation.

Keywords: constructive alignment, holistic graduates, mapping of assessment, programme outcome

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Authors: Amjed Sid Ahmed, Rosilah Hassan, Nor Effendy Othman

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Limited functioning of the Internet Protocol version 4 (IPv4) has necessitated the development of the Internetworking Protocol next generation (IPng) to curb the challenges. Indeed, the IPng is also referred to as the Internet Protocol version 6 (IPv6) and includes the Neighbor Discovery Protocol (NDP). The latter performs the role of Address Auto-configuration, Router Discovery (RD), and Neighbor Discovery (ND). Furthermore, the role of the NDP entails redirecting the service, detecting the duplicate address, and detecting the unreachable services. Despite the fact that there is an NDP’s assumption regarding the existence of trust the links’ nodes, several crucial attacks may affect the Protocol. Internet Engineering Task Force (IETF) therefore has recommended implementation of Secure Neighbor Discovery Protocol (SEND) to tackle safety issues in NDP. The SEND protocol is mainly used for validation of address rights, malicious response inhibiting techniques and finally router certification procedures. For routine running of these tasks, SEND utilizes on the following options, Cryptographically Generated Address (CGA), RSA Signature, Nonce and Timestamp option. CGA is produced at extra high costs making it the most notable disadvantage of SEND. In this paper a clear description of the constituents of CGA, its operation and also recommendations for improvements in its generation are given.

Keywords: CGA, IPv6, NDP, SEND

Procedia PDF Downloads 385

Authors: R. Ziaie Moayed, M. Hossein Zade

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Out of all methods for ground improvement, stone column became more popular these days due to its simple construction and economic consideration. Installation of stone column especially in loose fine graded soil causes increasing in load bearing capacity and settlement reduction. Encased granular stone columns (EGCs) are commonly subjected to vertical load. However, they may also be subjected to significant amount of shear loading. In this study, three-dimensional finite element (FE) analyses were conducted to estimate the shear load capacity of EGCs in sandy soil. Two types of different cases, stone column and geosynthetic encased stone column were studied at different normal pressures varying from 15 kPa to 75 kPa. Also, the effect of diameter in two cases was considered. A close agreement between the experimental and numerical curves of shear stress - horizontal displacement trend line is observed. The obtained result showed that, by increasing the normal pressure and diameter of stone column, higher shear strength is mobilized by soil; however, in the case of encased stone column, increasing the diameter had more dominated effect in mobilized shear strength.

Keywords: encased stone column, laterally load, ordinary stone column, validation

Procedia PDF Downloads 369

Authors: Yaxin Bi, Peter Nicholl

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The rapid advancement of Information and communication technologies (ICT) is extremely influencing every aspect of Higher Education. It has transformed traditional teaching, learning, assessment and feedback into a new era of Digital Education. This also introduces many challenges in capturing and understanding student engagement with their studies in Higher Education. The School of Computing at Ulster University has developed a Feedback And Notification (FAN) Online tool that has been used to send students links to personalized feedback on their submitted assessments and record students’ frequency of review of the shared feedback as well as the speed of collection. The feedback that the students initially receive is via a personal email directing them through to the feedback via a URL link that maps to the feedback created by the academic marker. This feedback is typically a Word or PDF report including comments and the final mark for the work submitted approximately three weeks before. When the student clicks on the link, the student’s personal feedback is viewable in the browser and they can view the contents. The FAN tool provides the academic marker with a report that includes when and how often a student viewed the feedback via the link. This paper presents an investigation into student engagement through analyzing the interaction timestamps and frequency of review by the student. We have proposed an approach to modeling interaction timestamps and use sentiment classification techniques to analyze the data collected over the last five years for a set of modules. The data studied is across a number of final years and second-year modules in the School of Computing. The paper presents the details of quantitative analysis methods and describes further their interactions with the feedback overtime on each module studied. We have projected the students into different groups of engagement based on sentiment analysis results and then provide a suggestion of early targeted intervention for the set of students seen to be under-performing via our proposed model.

Keywords: feedback, engagement, interaction modelling, sentiment analysis

Procedia PDF Downloads 103