Search results for: multivariate statistical analysis

Authors: Yoseph Halala Handiso, Zewdi Gebregziabher

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Background: Malnutrition in hospitalized patients remains a major public health problem in both developed and developing countries. Despite the fact that malnourished patients are more prone to stay longer in hospital, there is limited data regarding the magnitude of malnutrition and its effect on length of stay among surgical patients in Ethiopia, while nutritional assessment is also often a neglected component of the health service practice. Objective: This study aimed to assess the prevalence of malnutrition at admission and its effect on the length of hospital stay among adult surgical patients in Wolaita Sodo University Comprehensive Specialized Hospital, South Ethiopia, 2022. Methods: A facility-based prospective cohort study was conducted among 398 adult surgical patients admitted to the hospital. Participants in the study were chosen using a convenient sampling technique. Subjective global assessment was used to determine the nutritional status of patients with a minimum stay of 24 hours within 48 hours after admission (SGA). Data were collected using the open data kit (ODK) version 2022.3.3 software, while Stata version 14.1 software was employed for statistical analysis. The Cox regression model was used to determine the effect of malnutrition on the length of hospital stay (LOS) after adjusting for several potential confounders taken at admission. Adjusted hazard ratio (HR) with a 95% confidence interval was used to show the effect of malnutrition. Results: The prevalence of hospital malnutrition at admission was 64.32% (95% CI: 59%-69%) according to the SGA classification. Adult surgical patients who were malnourished at admission had higher median LOS (12 days: 95% CI: 11-13) as compared to well-nourished patients (8 days: 95% CI: 8-9), means adult surgical patients who were malnourished at admission were at higher risk of reduced chance of discharge with improvement (prolonged LOS) (AHR: 0.37, 95% CI: 0.29-0.47) as compared to well-nourished patients. Presence of comorbidity (AHR: 0.68, 95% CI: 0.50-90), poly medication (AHR: 0.69, 95% CI: 0.55-0.86), and history of admission (AHR: 0.70, 95% CI: 0.55-0.87) within the previous five years were found to be the significant covariates of the length of hospital stay (LOS). Conclusion: The magnitude of hospital malnutrition at admission was found to be high. Malnourished patients at admission had a higher risk of prolonged length of hospital stay as compared to well-nourished patients. The presence of comorbidity, polymedication, and history of admission were found to be the significant covariates of LOS. All stakeholders should give attention to reducing the magnitude of malnutrition and its covariates to improve the burden of LOS.

Keywords: effect of malnutrition, length of hospital stay, surgical patients, Ethiopia

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Authors: Neeta Kumari, Gopal Pathak

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Artificial neural network has been proved to be an efficient tool for non-parametric modeling of data in various applications where output is non-linearly associated with input. It is a preferred tool for many predictive data mining applications because of its power , flexibility, and ease of use. A standard feed forward networks (FFN) is used to predict the groundwater fluoride content. The ANN model is trained using back propagated algorithm, Tansig and Logsig activation function having varying number of neurons. The models are evaluated on the basis of statistical performance criteria like Root Mean Squarred Error (RMSE) and Regression coefficient (R2), bias (mean error), Coefficient of variation (CV), Nash-Sutcliffe efficiency (NSE), and the index of agreement (IOA). The results of the study indicate that Artificial neural network (ANN) can be used for groundwater fluoride prediction in the limited data situation in the hard rock region like western parts of Jharkhand with sufficiently good accuracy.

Keywords: Artificial neural network (ANN), FFN (Feed-forward network), backpropagation algorithm, Levenberg-Marquardt algorithm, groundwater fluoride contamination

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Authors: Veselin Konstantinov Hristov

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In recent years, the lease contract has become more and more applicable and occupies a key place in commercial relations and business. In Bulgaria, the legal regulation of the leasing contract is relatively new and imperfectly developed. There are many legal loopholes and it is they that determine the need for a comparative legal analysis. The purpose of the study is to analyze the various European legislations regarding the leasing contract and to find effective solutions for the legal system of Bulgaria. First of all, are examined the concept of the leasing contract, which originated in the United States of America around the 1950s and spread in Europe, and the etymology of the term "leasing". After that, the main types of lease contracts – financial and operational – are examined and analyzed in detail. Their features and characteristics were studied, as well as a comparative analysis was made between them. Next, in the research, a comparative-legal analysis of the leasing contract in different European countries was made in terms of its development and distribution, as well as its legal characteristics. The mechanism of action and functioning of the leasing contract in several European countries is analyzed. Conclusions are made regarding the legal framework under which the lease contract is most effective. Types of leasing contracts specific only to certain European countries and their advantages are examined. In conclusion, recommendations are made to improve the legal framework of the leasing contract in Bulgaria.

Keywords: alternative financing, leasing contract, financing instruments, innovation

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Authors: Shingo Murakami, Shinichi Enoki

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In structures, stress concentration is a factor of fatigue fracture. Basically, the stress concentration is a phenomenon that should be avoided. However, it is difficult to avoid the stress concentration. Therefore, relaxation of the stress concentration is important. The stress concentration arises from notches and circular holes. There is a relaxation method that a composite patch covers a notch and a circular hole. This relaxation method is used to repair aerial wings, but it is not systematized. Composites are more expensive than single materials. Accordingly, we propose the relaxation method that a single material patch covers a notch and a circular hole, and aim to systematize this relaxation method. We performed FEA (Finite Element Analysis) about an object by using a three-dimensional FEA model. The object was that a patch adheres to a plate with a circular hole. And, a uniaxial tensile load acts on the patched plate with a circular hole. In the three-dimensional FEA model, it is not easy to model the adhesion layer. Basically, the yield stress of the adhesive is smaller than that of adherents. Accordingly, the adhesion layer gets to plastic deformation earlier than the adherents under the yield load of adherents. Therefore, we propose the three-dimensional FEA model which is applied a nonlinear elastic region to the adhesion layer. The nonlinear elastic region was calculated by a bilinear approximation. We compared the analysis results with the tensile test results to confirm whether the analysis model has usefulness. As a result, the analysis results agreed with the tensile test results. And, we confirmed that the analysis model has usefulness. As a result that the three-dimensional FEA model was used to the analysis, it was confirmed that an out-of-plane deformation occurred to the patched plate with a circular hole. The out-of-plane deformation causes stress increase of the patched plate with a circular hole. Therefore, we investigated that the out-of-plane deformation affects relaxation of the stress concentration in the plate with a circular hole on this relaxation method. As a result, it was confirmed that the out-of-plane deformation inhibits relaxation of the stress concentration on the plate with a circular hole.

Keywords: stress concentration, patch, out-of-plane deformation, Finite Element Analysis

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Authors: Seyed Reza Agha Seyed Hosseini, Nicolas Hamelin

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Many marketing executives are looking for a comprehensive plan for delivering quality services and products that will create a distinct and unforgettable long-term experience for customers in dealing with their brand. Various brand management experts believe that a company looking to enhance its brand experience in the minds of customers should have a plan to increase customer satisfaction as well as customer loyalty. The purpose of this research was to investigate the role of brand experience in customer satisfaction and customer loyalty in Ayandeh Bank branches in Tehran. The study employed a quantitative methodology. For data gathering, a questionnaire was utilised to measure all the variables of the research. The statistical population of the study consisted of all the customers of Ayandeh Bank branches in Tehran, and the study data was gathered from 400 respondents. The findings indicate that brand experience has a direct and meaningful impact on customer satisfaction and customer loyalty, and, furthermore, that customer satisfaction has a direct and significant effect on customer loyalty in the branches of Ayandeh Bank in Tehran.

Keywords: brand experience, customer satisfaction, customer loyalty, bank

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Authors: Saleh Alotaibi, Mohammed Quddus, Craig Morton, Jobair Bin Alam

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This paper explores the role of large-scale investment in transport sectors and the impact of increased railway accessibility on the efficiency of the regional economic productivity in the Kingdom of Saudi Arabia (KSA). There are considerable differences among the KSA regions in terms of their levels of investment and productivity due to their geographical scale and location, which in turn greatly affect their relative efficiency. The study used a non-parametric linear programming technique - Data Envelopment Analysis (DEA) - to measure the regional efficiency change over time and determine the drivers of inefficiency and their scope of improvement. In addition, Window DEA analysis is carried out to compare the efficiency performance change for various time periods. Malmquist index (MI) is also analyzed to identify the sources of productivity change between two subsequent years. The analysis involves spatial and temporal panel data collected from 1999 to 2018 for the 13 regions of the country. Outcomes reveal that transport investment and improved railway accessibility, in general, have significantly contributed to regional economic development. Moreover, the endowment of the new railway stations has spill-over effects. The DEA Window analysis confirmed the dynamic improvement in the average regional efficiency over the study periods. MI showed that the technical efficiency change was the main source of regional productivity improvement. However, there is evidence of investment allocation discrepancy among regions which could limit the achievement of development goals in the long term. These relevant findings will assist the Saudi government in developing better strategic decisions for future transport investments and their allocation at the regional level.

Keywords: data envelopment analysis, transport investment, railway accessibility, efficiency

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Authors: Ankur Sachan

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The ability to make quick yet intelligent and value-added decisions to develop new fields has always been of great significance. In situations where the capital expenses and subsurface risk are high, carefully analyzing the inherent uncertainties in the reservoir and how they impact the predicted hydrocarbon accumulation and production becomes a daunting task. The problem is compounded in offshore environments, especially in the presence of heavy oils and disconnected sands where the margin for error is small. Uncertainty refers to the degree to which the data set may be in error or stray from the predicted values. To understand and quantify the uncertainties in reservoir model is important when estimating the reserves. Uncertainty parameters can be geophysical, geological, petrophysical etc. Identification of these parameters is necessary to carry out the uncertainty analysis. With so many uncertainties working at different scales, it becomes essential to have a consistent and efficient way of incorporating them into our analysis. Ranking the uncertainties based on their impact on reserves helps to prioritize/ guide future data gathering and uncertainty reduction efforts. Assigning probabilistic ranges to key uncertainties also enables the computation of probabilistic reserves. With this in mind, this paper, with the help the uncertainty and optimization process in petrel RE shows how the most influential uncertainties can be determined efficiently and how much impact so they have on the reservoir model thus helping in determining a cost effective and accurate model of the reservoir.

Keywords: uncertainty, reservoir model, parameters, optimization analysis

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Authors: Pavel Shcherban, Vlad Golovanov

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Nowadays, the depletion of hydrocarbon deposits on the land of the Kaliningrad region leads to active geological exploration and development of oil and natural gas reserves in the southeastern part of the Baltic Sea. LLC 'Lukoil-Kaliningradmorneft' implements a comprehensive program for the development of the region's shelf in 2014-2023. Due to heterogeneity of reservoir rocks in various open fields, as well as with ambiguous conclusions on the contours of deposits, additional geological prospecting and refinement of the recoverable oil reserves are carried out. The key element is use of an effective technique of computer stock modeling at the first stage of processing of the received data. The following step uses information for the cluster analysis, which makes it possible to optimize the field development approaches. The article analyzes the effectiveness of various methods for reserves' calculation and computer modelling methods of the offshore hydrocarbon fields. Cluster analysis allows to measure influence of the obtained data on the development of a technical and economic model for mining deposits. The relationship between the accuracy of the calculation of recoverable reserves and the need of modernization of existing mining infrastructure, as well as the optimization of the scheme of opening and development of oil deposits, is observed.

Keywords: cluster analysis, computer modelling of deposits, correction of the feasibility study, offshore hydrocarbon fields

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Authors: Samia Ait Ali Yahia

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Several steles with Libyan inscriptions were discovered in Grande Kabylia (Algeria), but very few researchers were interested in these inscriptions. Our work is to list, if possible all these steles in order to do a descriptive study of the corpus. The steles analysis will be focused on the iconographic and epigraphic level and on the different forms of Libyan characters in order to highlight the alphabet used by the Grande Kabylia.

Keywords: epigraphy, stele, Libyan inscription, Grande Kabylia

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Authors: Paua Ketan, Bhagate Rajkumar, Adiga Ganesh, M. Kiran

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Low gear noise is an important sound quality feature in modern passenger cars. Annoying gear noise from the gearbox is influenced by the gear design, gearbox shaft layout, manufacturing deviations in the components, assembly errors and the mounting arrangement of the complete gearbox. Geometrical deviations in the form of profile and lead errors are often present on the flanks of the inspected gears. Ghost frequencies of a gear are very challenging to identify in standard gear measurement and analysis process due to small wavelengths involved. In this paper, gear whine noise occurring at non-integral multiples of gear mesh frequency of passenger car gearbox is investigated and the root cause is identified using the displacement deviation analysis (DDA) method. DDA method is applied to identify ghost frequency excitations on the flanks of gears arising out of generation grinding. Frequency identified through DDA correlated with the frequency of vibration and noise on the end-of-line machine as well as vehicle level measurements. With the application of DDA method along with standard lead profile measurement, gears with ghost frequency geometry deviations were identified on the production line to eliminate defective parts and thereby eliminate ghost frequency noise from a vehicle. Further, displacement deviation analysis can be used in conjunction with the manufacturing process simulation to arrive at suitable countermeasures for arresting the ghost frequency.

Keywords: displacement deviation analysis, gear whine, ghost frequency, sound quality

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Authors: S. Mat Radzi, N. J. Abd Rahman, H. Mohd Noor, N. Ariffin

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Ferulic acid has widespread industrial potential by virtue of its antioxidant properties. However, it is partially soluble in aqueous media, limiting their usefulness in oil-based processes in food, cosmetic, pharmaceutical, and material industry. Therefore, modification of ferulic acid should be made by producing of more lipophilic derivatives. In this study, a preliminary investigation of lipase-catalyzed trans-esterification reaction of ethyl ferulate and olive oil was investigated. The reaction was catalyzed by immobilized lipase from Candida antarctica (Novozym 435), to produce ferulate ester, a sunscreen agent. A statistical approach of Response surface methodology (RSM) was used to evaluate the interactive effects of reaction temperature (40-80°C), reaction time (4-12 hours), and amount of enzyme (0.1-0.5 g). The optimum conditions derived via RSM were reaction temperature 60°C, reaction time 2.34 hours, and amount of enzyme 0.3 g. The actual experimental yield was 59.6% ferulate ester under optimum condition, which compared well to the maximum predicted value of 58.0%.

Keywords: ferulic acid, enzymatic synthesis, esters, RSM

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Authors: Sara Asham Mahrous Kamel

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A descriptive statistical analysis of the data showed that the most important factor evoking negative attitudes among teachers is student behavior. have been presented as useful models for understanding the risk factors and protective factors associated with the emergence of autistic traits. Although these "syndrome" forms of autism reach clinical thresholds, they appear to be distinctly different from the idiopathic or "non-syndrome" autism phenotype. Most teachers reported that kindergartens did not prepare them for the educational needs of children with autism, particularly in relation to non-verbal skills. The study is important and points the way for improving teacher inclusion education in Thailand. Inclusive education for students with autism is still in its infancy in Thailand. Although the number of autistic children in schools has increased significantly since the Thai government introduced the Education Regulations for Persons with Disabilities Act in 2008, there is a general lack of services for autistic students and their families. This quantitative study used the Teaching Skills and Readiness Scale for Students with Autism (APTSAS) to test the attitudes and readiness of 110 elementary school teachers when teaching students with autism in general education classrooms. To uncover the true nature of these co morbidities, it is necessary to expand the definition of autism to include the cognitive features of the disorder, and then apply this expanded conceptualization to examine patterns of autistic syndromes. This study used various established eye-tracking paradigms to assess the visual and attention performance of children with DS and FXS who meet the autism thresholds defined in the Social Communication Questionnaire. To study whether the autistic profiles of these children are associated with visual orientation difficulties ("sticky attention"), decreased social attention, and increased visual search performance, all of which are hallmarks of the idiopathic autistic child phenotype. Data will be collected from children with DS and FXS, aged 6 to 10 years, and two control groups matched for age and intellectual ability (i.e., children with idiopathic autism).In order to enable a comparison of visual attention profiles, cross-sectional analyzes of developmental trajectories are carried out. Significant differences in the visual-attentive processes underlying the presentation of autism in children with FXS and DS have been suggested, supporting the concept of syndrome specificity. The study provides insights into the complex heterogeneity associated with autism syndrome symptoms and autism itself, with clinical implications for the utility of autism intervention programs in DS and FXS populations.

Keywords: attitude, autism, teachers, sports activities, movement skills, motor skills

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Authors: Cara Williams

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In 2006, the UK Labour government published a Green Paper introducing Employment and Support Allowance (ESA) as a replacement for Incapacity Benefit (IB), as well as a new Work Capability Assessment (WCA); signalling a controversial political and economic shift in disability welfare policy. In 2016, the Conservative government published Improving Lives: The Work, Health, and Disability Green Paper, as part of their social reform agenda, evidently to address the ‘injustice’ of the ‘disability employment gap’. This paper contextualises ESA in the wider ideology and rhetoric of ‘welfare to work’, ‘dependency’ and ‘responsibility’. Using the British ‘social model of disability’ as a theoretical framework, the study engages in a critical discourse analysis of these two Green Papers. By uncovering the medicalised conceptions embedded in the texts, the analysis has revealed ESA is linked with late capitalisms concern with the ‘disability category’.

Keywords: disability, employment, social security, welfare

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Authors: Masaya Yoshikawa, Toshiya Asai, Ryoma Matsuhisa, Yusuke Nozaki, Kensaku Asahi

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Recently, side-channel attacks, which estimate secret keys using side-channel information such as power consumption and compromising emanations of cryptography circuits embedded in hardware, have become a serious problem. In particular, electromagnetic analysis attacks against cryptographic circuits between information processing and electromagnetic fields, which are related to secret keys in cryptography circuits, are the most threatening side-channel attacks. Therefore, it is important to evaluate tamper resistance against electromagnetic analysis attacks for cryptography circuits. The present study performs basic examination of the tamper resistance of cryptography circuits using electromagnetic analysis attacks with noise resources.

Keywords: tamper resistance, cryptographic circuit, hardware security evaluation, noise resources

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Authors: Ghafor Ahmadi, Nader Bohloli Zynab

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Rapid scientific changes are the driving force of upheaval. As new technologies arrive, human’s life changes and information becomes one of the productive sources besides other factors. Optimum application of each technology depends on precise recognition of that technology. Options of mobile phones are constantly developing and evolving. Meanwhile, one of the influential variables for improving the performance and eternity of organizations is creativity. One of the new technologies tied with development and innovation is mobile phone. In this research, the contribution of different dimensions of mobile technologies such as perceived use, perceived enjoyment, continuance intention, confirmation and satisfaction to creativity of employees were investigated. Statistical population included 510 employees of Kermanshah Petrochemical Company. Sample size was defined 217 based on Morgan and Krejcie table. This study is descriptive and data gathering instrument was a questionnaire. Applying SPSS software, linear regression was analyzed. It was found out that all dimensions of mobile technologies except satisfaction affect on creativity of employees.

Keywords: mobile technologies, continuance intention, perceived enjoyment, perceived use, confirmation, satisfaction, creativity

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Authors: Piyush Swami, Bijaya Ketan Panigrahi, Sneh Anand, Manvir Bhatia, Tapan Gandhi

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Visual inspection of electroencephalogram (EEG) signals to detect epileptic signals is very challenging and time-consuming task even for any expert neurophysiologist. This problem is most challenging in under-developed and developing countries due to shortage of skilled neurophysiologists. In the past, notable research efforts have gone in trying to automate the seizure detection process. However, due to high false alarm detections and complexity of the models developed so far, have vastly delimited their practical implementation. In this paper, we present a novel scheme for epileptic seizure detection using empirical mode decomposition technique. The intrinsic mode functions obtained were then used to calculate the standard deviations. This was followed by probability density based classifier to discriminate between non-ictal and ictal patterns in EEG signals. The model presented here demonstrated very high classification rates ( > 97%) without compromising the statistical performance. The computation timings for each testing phase were also very low ( < 0.029 s) which makes this model ideal for practical applications.

Keywords: electroencephalogram (EEG), epilepsy, ictal patterns, empirical mode decomposition

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Authors: Ammarah Irum, Muhammad Ali Tahir

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Document-level sentiment analysis in Urdu is a challenging Natural Language Processing (NLP) task due to the difficulty of working with lengthy texts in a language with constrained resources. Deep learning models, which are complex neural network architectures, are well-suited to text-based applications in addition to data formats like audio, image, and video. To investigate the potential of deep learning for Urdu sentiment analysis, we implemented five different deep learning models, including Bidirectional Long Short Term Memory (BiLSTM), Convolutional Neural Network (CNN), Convolutional Neural Network with Bidirectional Long Short Term Memory (CNN-BiLSTM), and Bidirectional Encoder Representation from Transformer (BERT). In this study, we developed a hybrid deep learning model called BiLSTM-Single Layer Multi Filter Convolutional Neural Network (BiLSTM-SLMFCNN) by fusing BiLSTM and CNN architecture. The proposed and baseline techniques are applied on Urdu Customer Support data set and IMDB Urdu movie review data set by using pre-trained Urdu word embedding that are suitable for sentiment analysis at the document level. Results of these techniques are evaluated and our proposed model outperforms all other deep learning techniques for Urdu sentiment analysis. BiLSTM-SLMFCNN outperformed the baseline deep learning models and achieved 83%, 79%, 83% and 94% accuracy on small, medium and large sized IMDB Urdu movie review data set and Urdu Customer Support data set respectively.

Keywords: urdu sentiment analysis, deep learning, natural language processing, opinion mining, low-resource language

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Authors: S. O. Ologe, U. P. Anaidhuno, Duru C. A.

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This research investigated the design and analysis of a rear bumper of an automobile with a hybrid polymer composite of OPEBF/Banana fibre. OPEBF/Banana fibre hybrid polymers composite is of low cost, lightweight, as well as possesses satisfactory mechanical properties. In this research work, hybrid composites have been developed using the hand layup technique based on the percentage combination of OPEBF/Banana fibre at 10:90, 20:80, 30:70, 40:60, 50:50. 60:40, 70:30. 20:80, 90:10, 95:5. The mechanical properties in the context of compressive strength of 65MPa, a flexural strength of 20MPa, and impact strength of 3.25Joule were observed, and the simulation analysis on the induction of 500N load at the factor of safety of 3 was observed to have displayed a good strength suitable for automobile bumper with the advantages of weight reduction.

Keywords: OPEBF, Banana, fibre, hybrid

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Authors: Bimrisha Mali

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The present study investigates the type of errors English as a second language (ESL) learners produce using the definite article ‘the’. The participants were provided a questionnaire on the learner's ability test. The questionnaire consists of three cloze tests and two free composition tests. Each participant's response was received in the form of written data. A total of 78 participants from three government schools participated in the study. The participants are high-school students from Rural Assam. Assam is a north-eastern state of India. Their age ranged between 14-15. The medium of instruction and the communication among the students take place in the local language, i.e., Assamese. Pit Corder’s steps for conducting error analysis have been followed for the analysis procedure. Four types of errors were found (1) deletion of the definite article, (2) use of the definite article as modifiers as adjectives, (3) incorrect use of the definite article with singular proper nouns, (4) substitution of the definite article by the indefinite article ‘a’. Classifiers in Assamese that express definiteness is used with nouns, adjectives, and numerals. It is found that native language (L1) transfer plays a pivotal role in the learners’ errors. The analysis reveals the learners' inability to acquire the semantic connotation of definiteness in English due to native language (L1) interference.

Keywords: definite article error, l1 transfer, error analysis, ESL

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Authors: Clare Flood, Shareen Forbes

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Background: Type 1 diabetes mellitus (T1DM) is an autoimmune disorder affecting >400,000 people in the UK alone, with the global prevalence expected to double in the next decade. Islet transplant offers a minimally-invasive procedure with very low morbidity and almost no mortality, and is now as effective as whole pancreas transplant. The procedure was introduced to the UK in 2011 for patients with the most severe type 1 diabetes mellitus (T1DM) – those with unstable blood glucose, frequently occurring episodes of severe hypoglycemia and impaired awareness of hypoglycemia (IAH). Objectives: To evaluate the effectiveness of islet transplantation in improving glycemic control, reducing the burden of hypoglycemia and improving awareness of hypoglycemia through a single-centre cohort study at the Royal Infirmary of Edinburgh. Glycemic control and degree of hypoglycemic awareness will be determined and monitored pre- and post-transplantation to determine effectiveness of the procedure. Methods: A retrospective analysis of data collected over three years from the 16 patients who have undergone islet transplantation in Scotland. Glycated haemoglobin (HbA1c) was measured and continuous glucose monitoring systems (CGMS) were utilised to assess glycemic control, while Gold and Clarke score questionnaires tested IAH. Results: All patients had improved glycemic control following transplant, with optimal control seen visually at 3 months post-transplant. Glycemic control significantly improved, as illustrated by percentage time in hypoglycemia in the months following transplant (p=0.0211) and HbA1c (p=0.0426). Improved Clarke (p=0.0034) and Gold (p=0.0001) scores indicate improved glycemic awareness following transplant. Conclusion: While the small sample of islet transplant recipients at the Royal Infirmary of Edinburgh prevents definitive conclusions being drawn, it is indicated that through our retrospective, single-centre cohort study of 16 patients, islet transplant is capable of improving glycemic control, reducing the burden of hypoglycemia and IAH post-transplant. Data can be combined with similar trials at other centres to increase statistical power but from research in Edinburgh, it can be suggested that the minimally invasive procedure of islet transplantation offers selected patients with extremely unstable T1DM the incredible opportunity to regain control of their condition and improve their quality of life.

Keywords: diabetes, islet, transplant, CGMS

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Authors: Hyunchul Ahn, William X. S. Wong

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Corporate credit rating prediction is one of the most important topics, which has been studied by researchers in the last decade. Over the last decade, researchers are pushing the limit to enhance the exactness of the corporate credit rating prediction model by applying several data-driven tools including statistical and artificial intelligence methods. Among them, multiclass support vector machine (MSVM) has been widely applied due to its good predictability. However, heuristics, for example, parameters of a kernel function, appropriate feature and instance subset, has become the main reason for the critics on MSVM, as they have dictate the MSVM architectural variables. This study presents a hybrid MSVM model that is intended to optimize all the parameter such as feature selection, instance selection, and kernel parameter. Our model adopts genetic algorithm (GA) to simultaneously optimize multiple heterogeneous design factors of MSVM.

Keywords: corporate credit rating prediction, Feature selection, genetic algorithms, instance selection, multiclass support vector machines

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Authors: Ş. Karabulut, A. Güllü, A. Güldaş, R. Gürbüz

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This study investigates the effects of the lead angle and chip thickness variation on surface roughness during the machining of compacted graphite iron using ceramic cutting tools under dry cutting conditions. Analytical models were developed for predicting the surface roughness values of the specimens after the face milling process. Experimental data was collected and imported to the artificial neural network model. A multilayer perceptron model was used with the back propagation algorithm employing the input parameters of lead angle, cutting speed and feed rate in connection with chip thickness. Furthermore, analysis of variance was employed to determine the effects of the cutting parameters on surface roughness. Artificial neural network and regression analysis were used to predict surface roughness. The values thus predicted were compared with the collected experimental data, and the corresponding percentage error was computed. Analysis results revealed that the lead angle is the dominant factor affecting surface roughness. Experimental results indicated an improvement in the surface roughness value with decreasing lead angle value from 88° to 45°.

Keywords: CGI, milling, surface roughness, ANN, regression, modeling, analysis

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Authors: Michael K.O. Ayomoh, Khaled A. Abou-El-Hossein., Sameh F.M. Ghobashy

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This paper proposes a numerical modelling scheme for surface roughness prediction. The approach is premised on the use of 3D difference analysis method enhanced with the use of feedback control loop where a set of adaptive weights are generated. The surface roughness values utilized in this paper were adapted from [1]. Their experiments were carried out using S55C high carbon steel. A comparison was further carried out between the proposed technique and those utilized in [1]. The experimental design has three cutting parameters namely: depth of cut, feed rate and cutting speed with twenty-seven experimental sample-space. The simulation trials conducted using Matlab software is of two sub-classes namely: prediction of the surface roughness readings for the non-boundary cutting combinations (NBCC) with the aid of the known surface roughness readings of the boundary cutting combinations (BCC). The following simulation involved the use of the predicted outputs from the NBCC to recover the surface roughness readings for the boundary cutting combinations (BCC). The simulation trial for the NBCC attained a state of total stability in the 7th iteration i.e. a point where the actual and desired roughness readings are equal such that error is minimized to zero by using a set of dynamic weights generated in every following simulation trial. A comparative study among the three methods showed that the proposed difference analysis technique with adaptive weight from feedback control, produced a much accurate output as against the abductive and regression analysis techniques presented in this.

Keywords: Difference Analysis, Surface Roughness; Mesh- Analysis, Feedback control, Adaptive weight, Boundary Element

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Authors: Abdulhameed Babatunde Owolabi, Benyoh Emmanuel Kigha Nsafon, Jeung-Soo Huh

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Energy efficiency measures for residential buildings in South Korea is a national issue because most of the apartments built in the last decades were constructed without proper energy efficiency measures making the energy performance of old buildings to be very poor when compared with new buildings. However, the adoption of advanced building technologies and regulatory building codes are effective energy efficiency strategies for new construction. There is a need to retrofits the existing building using energy conservation measures (ECMs) equipment’s in order to conserve energy and reduce GHGs emissions. To achieve this, the Institute for Global Climate Change and Energy (IGCCE), Kyungpook National University (KNU), Daegu, South Korea employed RETScreen Expert software to carry out measurement and verification (M&V) analysis on an existing building in Korea by using six years gas consumption data collected from Daesung Energy Co., Ltd in order to determine the building energy performance after the introduction of ECM. Through the M&V, energy efficiency is attained, and the resident doubt was reduced. From the analysis, a total of 657 Giga Joules (GJ) of liquefied natural gas (LNG) was consumed at the rate of 0.34 GJ/day having a peak in the year 2015, which cost the occupant the sum of $10,821.

Keywords: energy efficiency, measurement and verification, performance analysis, RETScreen experts

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Authors: Margarida Plana

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End-users behavior has become one of the main aspects to be solved on energy efficiency projects. Especially on the residential sector, the end-users have a direct impact that affects the achievement of energy saving’s targets. This paper is focused on presenting and quantify the impact of end-users behavior on basis of the analysis of real projects’ data. The analysis study which is the role of buiding’s occupants and how their behavior can change the success of energy efficiency projects how to limit their impact. The results obtained show two main conclusions. The first one is easiest to solve: we need to control and limit the end-users interaction with the equipment operation to be able to reach the targets fixed. The second one: as the plugged equipment are increasing exponentially on the residential sector, big efforts of disseminations are needed in order to explain to citizens the impact of their day by day actions through dissemination campaigns.

Keywords: end-users impacts, energy efficiency, energy savings, impact limitations

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Authors: Mahmoud Nadir, Adel Ghenaiet

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The main purpose of this study is the thermodynamic modeling, the parametric analysis, and the optimization of three pressure level reheat HRSG (Heat Recovery Steam Generator) using PSO method (Particle Swarm Optimization). In this paper, a parametric analysis followed by a thermodynamic optimization is presented. The chosen objective function is the specific work of the steam cycle that may be, in the case of combined cycle (CC), a good criterion of thermodynamic performance analysis, contrary to the conventional steam turbines in which the thermal efficiency could be also an important criterion. The technologic constraints such as maximal steam cycle temperature, minimal steam fraction at steam turbine outlet, maximal steam pressure, minimal stack temperature, minimal pinch point, and maximal superheater effectiveness are also considered. The parametric analyses permitted to understand the effect of design parameters and the constraints on steam cycle specific work variation. PSO algorithm was used successfully in HRSG optimization, knowing that the achieved results are in accordance with those of the previous studies in which genetic algorithms were used. Moreover, this method is easy to implement comparing with the other methods.

Keywords: combined cycle, HRSG thermodynamic modeling, optimization, PSO, steam cycle specific work

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Authors: Seyed-Ali Sadegh-Zadeh, Kaveh Kavianpour, Hamed Atashbar, Elham Heidari, Saeed Shiry Ghidary, Amir M. Hajiyavand

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Evaluation metrics play a critical role in assessing the performance of machine learning models. In this review paper, we provide a comprehensive overview of performance measurement approaches for machine learning models. For each category, we discuss the most widely used metrics, including their mathematical formulations and interpretation. Additionally, we provide a comparative analysis of performance measurement approaches for metric combinations. Our review paper aims to provide researchers and practitioners with a better understanding of performance measurement approaches and to aid in the selection of appropriate evaluation metrics for their specific applications.

Keywords: evaluation metrics, performance measurement, supervised learning, unsupervised learning, reinforcement learning, model robustness and stability, comparative analysis

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Authors: Arifur Rahman, Ardeshir Amirkhani, Honghua Hu, Mark Molloy, Karen Vickery

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Introduction and Objectives: Staphylococcus aureus and coagulase-negative staphylococci comprises approximately 65% of infections associated with medical devices and are well known for their biofilm formatting ability. Biofilm-related infections are extremely difficult to eradicate owing to their high tolerance to antibiotics and host immune defences. Currently, there is no efficient method for early biofilm detection. A better understanding to enable detection of biofilm specific proteins in vitro and in vivo can be achieved by studying planktonic and different growth phases of biofilms using a proteome analysis approach. Our goal was to construct a reference map of planktonic and biofilm associated proteins of S. aureus. Methods: S. aureus reference strain (ATCC 25923) was used to grow 24 hours planktonic, 3-day wet biofilm (3DWB), and 12-day wet biofilm (12DWB). Bacteria were grown in tryptic soy broth (TSB) liquid medium. Planktonic growth was used late logarithmic bacteria, and the Centres for Disease Control (CDC) biofilm reactor was used to grow 3 days, and 12-day hydrated biofilms, respectively. Samples were subjected to reduction, alkylation and digestion steps prior to Multiplex labelling using Tandem Mass Tag (TMT) 10-plex reagent (Thermo Fisher Scientific). The labelled samples were pooled and fractionated by high pH RP-HPLC which followed by loading of the fractions on a nanoflow UPLC system (Eksigent UPLC system, AB SCIEX). Mass spectrometry (MS) data were collected on an Orbitrap Elite (Thermo Fisher Scientific) Mass Spectrometer. Protein identification and relative quantitation of protein levels were performed using Proteome Discoverer (version 1.3, Thermo Fisher Scientific). After the extraction of protein ratios with Proteome Discoverer, additional processing, and statistical analysis was done using the TMTPrePro R package. Results and Discussion: The present study showed that a considerable proteomic difference exists among planktonic and biofilms from S. aureus. We identified 1636 total extracellular secreted proteins, of which 350 and 137 proteins of 3DWB and 12DWB showed significant abundance variation from planktonic preparation, respectively. Of these, simultaneous up-regulation in between 3DWB and 12DWB proteins such as extracellular matrix-binding protein ebh, enolase, transketolase, triosephosphate isomerase, chaperonin, peptidase, pyruvate kinase, hydrolase, aminotransferase, ribosomal protein, acetyl-CoA acetyltransferase, DNA gyrase subunit A, glycine glycyltransferase and others we found in this biofilm producer. On the contrary, simultaneous down-regulation in between 3DWB and 12DWB proteins such as alpha and delta-hemolysin, lipoteichoic acid synthase, enterotoxin I, serine protease, lipase, clumping factor B, regulatory protein Spx, phosphoglucomutase, and others also we found in this biofilm producer. In addition, we also identified a big percentage of hypothetical proteins including unique proteins. Therefore, a comprehensive knowledge of planktonic and biofilm associated proteins identified by S. aureus will provide a basis for future studies on the development of vaccines and diagnostic biomarkers. Conclusions: In this study, we constructed an initial reference map of planktonic and various growth phase of biofilm associated proteins which might be helpful to diagnose biofilm associated infections.

Keywords: bacterial biofilms, CDC bioreactor, S. aureus, mass spectrometry, TMT

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Authors: A. H. Taghdisi, M. Mirmohammadi, S. Kamali

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Evening primrose (Oenothera biennis L.) is a biennial and herbaceous and one of the most important species of medicinal plants in the world. due to the production of unsaturated fatty acids such as linoleic acid, alpha-linolenic acid, etc. in its seeds and roots, and compounds such as kaempferol in its leaves, Evening primrose has important medicinal efficiency such as reducing premenstrual problems, acceleration of wound healing, inhibiting platelet aggregation, sedation of cardiovascular diseases, and treatment of viral infections. The sap of the plant is used to treat warts, and the plant itself is used as a charm against mental and spiritual diseases and poisonous animals. Its leaves have significant antibacterial activity against yellow staphylococci. It is also used in the treatment of poisoning, especially the toxication caused by the consumption of alcoholic beverages, in the treatment of arteriosclerosis and diseases caused by liver cell insufficiency. Low germination and production speed are the problems of evening primrose growth and propagation. In the present study, extracts were obtained from four components (flowers, stems, seeds, leaves) of the evening primrose plant using the Soxhlet apparatus. To measure the antibacterial properties against MDR bacteria, microbial methods, including dilution, cultivation on a plate containing nutrient agar culture medium, and disc diffusion in agar, were performed using Staphylococcus aureus and Escherichia coli bacteria on all four extracts. The maximum antibacterial activity related to the dilution method was obtained in all extracts. In the plate culture method, antibacterial activity was obtained for all extracts in the nutrient agar medium. The maximum diameter of the non-growth halo was obtained in the disc diffusion method in agar in the leaf extract. The statistical analysis of the microbial part was done by one-way ANOVA test (SPSS). By comparing the amount of omega-3 in extracts of Iranian and foreign oils available in the market and the extracts extracted from evening primrose plant samples with gas chromatography, it is shown that the stem extract had the most omega-3 (oleic acid) and compared to the extract of the mentioned oils, it had the highest amount of omega-3 overall. Also, the amount of omega-3 in the extract of Iranian oils was much higher than in the extract of foreign oils. It should be noted that the extract of foreign oils had a more complete composition of omega-3 than the extract of Iranian oils.

Keywords: antibacterial activity, MDR bacteria, evening primrose, omega-3

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Authors: Femi Elegbeleye, Omobayo Esan, Muienge Mbodila, Patrick Bowe

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This paper focused on cost effective storage architecture using fog and cloud data storage gateway and presented the design of the framework for the data privacy model and data analytics framework on a real-time analysis when using machine learning method. The paper began with the system analysis, system architecture and its component design, as well as the overall system operations. The several results obtained from this study on data privacy model shows that when two or more data privacy model is combined we tend to have a more stronger privacy to our data, and when fog storage gateway have several advantages over using the traditional cloud storage, from our result shows fog has reduced latency/delay, low bandwidth consumption, and energy usage when been compare with cloud storage, therefore, fog storage will help to lessen excessive cost. This paper dwelt more on the system descriptions, the researchers focused on the research design and framework design for the data privacy model, data storage, and real-time analytics. This paper also shows the major system components and their framework specification. And lastly, the overall research system architecture was shown, its structure, and its interrelationships.

Keywords: IoT, fog, cloud, data analysis, data privacy

Procedia PDF Downloads 92