Search results for: reduced order models

Authors: Hajer Najjar, Riad Bourguiba, Jaouhar Mouine

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Reduced instruction set computer (RISC) processors are widely used because of their multiple advantages. In fact, they are based on a simple instruction set so that they increase the speed of the processor and reduce its energy consumption. In this paper, we will present a basic RISC architecture processor that will be developed later to converge to a new architecture with runtime reconfiguration.

Keywords: processor, RISC, DLX, pipeline, runtime reconfiguration

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Authors: Chungkuk Jin, Moohyun Kim, Woo Chul Chung

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This paper presents global performance and dynamic behaviors of a discrete-pontoon-type floating bridge with mooring lines in time domain under wind and wave excitations. The structure is designed for long-distance and deep-water crossing and consists of the girder, columns, pontoons, and mooring lines. Their functionality and behaviors are investigated by using elastic-floater/mooring fully-coupled dynamic simulation computer program. Dynamic wind, first- and second-order wave forces, and current loads are considered as environmental loads. Girder’s dynamic responses and mooring tensions are analyzed under different analysis methods and environmental conditions. Girder’s lateral responses are highly influenced by the second-order wave and wind loads while the first-order wave load mainly influences its vertical responses.

Keywords: floating bridge, mooring line, pontoon, wave excitation

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Authors: Truong Nguyen Luan Vu, Le Hieu Giang, Le Linh

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The fractional–order proportional integral (FOPI) controller tuning rules based on the fractional calculus for the cascade control system are systematically proposed in this paper. Accordingly, the ideal controller is obtained by using internal model control (IMC) approach for both the inner and outer loops, which gives the desired closed-loop responses. On the basis of the fractional calculus, the analytical tuning rules of FOPI controller for the inner loop can be established in the frequency domain. Besides, the outer loop is tuned by using any integer PI/PID controller tuning rules in the literature. The simulation study is considered for the stable process model and the results demonstrate the simplicity, flexibility, and effectiveness of the proposed method for the cascade control system in compared with the other methods.

Keywords: Bode’s ideal transfer function, fractional calculus, fractional–order proportional integral (FOPI) controller, cascade control system

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Authors: Chengcao Sun, Cuili Yang, Shujun Li, Ruilin Xue, Yongyong Xi, Liang Wang, Dejia Li

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Backgrounds: Inflammation is widely distributed in patients with Duchenne muscular dystrophy (DMD), and ultimately leads to progressive deterioration of muscle function with the co-effects of chronic muscle damage, oxidative stress, and reduced oxidative capacity. NF-E2-related factor 2 (Nrf2) plays a critical role in defending against inflammation in different tissues via activation of phase II enzymes, heme oxygenase-1 (HO-1). However, whether Nrf2/HO-1 pathway can attenuate muscle inflammation on DMD remains unknown. The purpose of this study was to determine the anti-inflammatory effects of Sulforaphane (SFN) on DMD. Methods: 4-week-old male mdx mice were treated with SFN by gavage (2 mg/kg body weight per day) for 4 weeks. Gastrocnemius, tibial anterior and triceps brachii muscles were collected for related analysis. Immune cell infiltration in skeletal muscles was analyzed by H&E staining and immuno-histochemistry. Moreover, the expressions of inflammatory cytokines,pro-inflammatory cytokines and Nrf2/HO-1 pathway were detected by western blot, qRT-PCR, immunohistochemistry and immunofluorescence assays. Results: Our results demonstrated that SFN treatment increased the expression of muscle phase II enzymes HO-1 in Nrf2 dependent manner. Inflammation in mdx skeletal muscles was reduced by SFN treatment as indicated by decreased immune cell infiltration and lower expressions of the inflammatory cytokines CD45, pro-inflammatory cytokines tumour necrosis factor-α and interleukin-6 in the skeletal muscles of mdx mice. Conclusions: Collectively, these results show that SFN can ameliorate muscle inflammation in mdx mice by Nrf2/HO-1 pathway, which indicates Nrf2/HO-1 pathway may represent a new therapeutic target for DMD.

Keywords: sulforaphane, Nrf2, HO-1, inflammation

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Authors: Congping Lin

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Intracellular transport in fungi has a number of important roles in, e.g., filamentous fungal growth and cellular metabolism. Two basic mechanisms for intracellular transport are motor-driven trafficking along microtubules (MTs) and diffusion. Mathematical modelling has been actively developed to understand such intracellular transport and provide unique insight into cellular complexity. Based on live-cell imaging data in Ustilago hyphal cells, probabilistic models have been developed to study mechanism underlying spatial organization of molecular motors and organelles. In particular, anther mechanism - stochastic motility of dynein motors along MTs has been found to contribute to half of its accumulation at hyphal tip in order to support early endosome (EE) recycling. The EE trafficking not only facilitates the directed motion of peroxisomes but also enhances their diffusive motion. Considering the importance of spatial organization of early endosomes in supporting peroxisome movement, computational and experimental approaches have been combined to a whole-cell level. Results from this interdisciplinary study promise insights into requirements for other membrane trafficking systems (e.g., in neurons), but also may inform future 'synthetic biology' studies.

Keywords: intracellular transport, stochastic process, molecular motors, spatial organization

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Authors: Mostafa Jafarian Abyaneh, Khashayar Jafari, Vahab Toufigh

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The cost of experiments on different types of concrete has raised the demand for prediction of their behavior with numerical analysis. In this research, an advanced numerical model has been presented to predict the complete elastic-plastic behavior of polymer concrete (PC), high-strength concrete (HSC), high performance concrete (HPC) along with different steel fiber contents under uniaxial compression. The accuracy of the numerical response was satisfactory as compared to other conventional simple models such as Mohr-Coulomb and Drucker-Prager. In order to predict the complete elastic-plastic behavior of specimens including softening behavior, disturbed state concept (DSC) was implemented by nonlinear finite element analysis (NFEA) and hierarchical single surface (HISS) failure criterion, which is a failure surface without any singularity.

Keywords: disturbed state concept (DSC), hierarchical single surface (HISS) failure criterion, high performance concrete (HPC), high-strength concrete (HSC), nonlinear finite element analysis (NFEA), polymer concrete (PC), steel fibers, uniaxial compression test

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Authors: Sanja Pfeifer, Nataša Šarlija, Marina Jeger, Ana Bilandžić

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The purpose of this study is to explore the different facets of growth among micro, small and medium-sized firms in Croatia and to analyze the differences between models designed for all micro, small and medium-sized firms and those in creative industries. Three growth prediction models were designed and tested using the growth of sales, employment and assets of the company as dependent variables. The key drivers of sales growth are: prudent use of cash, industry affiliation and higher share of intangible assets. Growth of assets depends on retained profits, internal and external sources of financing, as well as industry affiliation. Growth in employment is closely related to sources of financing, in particular, debt and it occurs less frequently than growth in sales and assets. The findings confirm the assumption that growth strategies of small and medium-sized enterprises (SMEs) in creative industries have specific differences in comparison to SMEs in general. Interestingly, only 2.2% of growing enterprises achieve growth in employment, assets and sales simultaneously.

Keywords: creative industries, growth prediction model, growth determinants, growth measures

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Authors: Chang Soo Chon, Cheol Woong Ko, Han Sung Kim

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The aim of this study is to develop an anterior lumbar interbody fusion (ALIF) PEEK cage suitable for Korean people. In this study, CT images were obtained from Korean male (173cm, 71kg) and 3D Korean lumbar models were reconstructed based on the CT images to investigate anatomical characteristics. Major design parameters of anterior lumbar interbody fusion (ALIF) PEEK Cage were selected using the morphological measurement information of the Korean Lumbar models. Through finite element analysis and mechanical tests, the developed ALIF PEEK Cage prototype was compared with the Fidji Cage (Zimmer.Inc, USA) and it was found that the ALIF prototype showed similar and/or superior mechanical performance compared to the FidJi Cage. Also, clinical validation for the ALIF PEEK Cage prototype was carried out to check predictable troubles in surgical operations. Finally, it is considered that the convenience and stability of the prototype was clinically verified.

Keywords: inter-body anterior fusion, ALIF cage, PEEK, Korean lumbar, CT image, animal test

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Authors: Mustapha Kamel Mihoubi, Essadik Kerkar, Abdelhamid Hebbouche

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According to the randomness of most of the factors affecting the stability of a gravity dam, probability theory is generally used to TESTING the risk of failure and there is a confusing logical transition from the state of stability failed state, so the stability failure process is considered as a probable event. The control of risk of product failures is of capital importance for the control from a cross analysis of the gravity of the consequences and effects of the probability of occurrence of identified major accidents and can incur a significant risk to the concrete dam structures. Probabilistic risk analysis models are used to provide a better understanding the reliability and structural failure of the works, including when calculating stability of large structures to a major risk in the event of an accident or breakdown. This work is interested in the study of the probability of failure of concrete dams through the application of the reliability analysis methods including the methods used in engineering. It is in our case of the use of level II methods via the study limit state. Hence, the probability of product failures is estimated by analytical methods of the type FORM (First Order Reliability Method), SORM (Second Order Reliability Method). By way of comparison, a second level III method was used which generates a full analysis of the problem and involving an integration of the probability density function of, random variables are extended to the field of security by using of the method of Mont-Carlo simulations. Taking into account the change in stress following load combinations: normal, exceptional and extreme the acting on the dam, calculation results obtained have provided acceptable failure probability values which largely corroborate the theory, in fact, the probability of failure tends to increase with increasing load intensities thus causing a significant decrease in strength, especially in the presence of combinations of unique and extreme loads. Shear forces then induce a shift threatens the reliability of the structure by intolerable values of the probability of product failures. Especially, in case THE increase of uplift in a hypothetical default of the drainage system.

Keywords: dam, failure, limit state, monte-carlo, reliability, probability, sliding, Taylor

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Authors: Mina Jafari, Kobra Hamraee, Saied Hossein Hosseini

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The prediction of breast cancer disease is one of the challenges in medicine. In this paper we collected 528 records of women’s information who live in Kabul including demographic, life style, diet and pregnancy data. There are many classification algorithm in breast cancer prediction and tried to find the best model with most accurate result and lowest error rate. We evaluated some other common supervised algorithms in data mining to find the best model in prediction of breast cancer disease among afghan women living in Kabul regarding to momography result as target variable. For evaluating these algorithms we used Cross Validation which is an assured method for measuring the performance of models. After comparing error rate and accuracy of three models: Decision Tree, Naive Bays and Rule Induction, Decision Tree with accuracy of 94.06% and error rate of %15 is found the best model to predicting breast cancer disease based on the health care records.

Keywords: decision tree, breast cancer, probability, data mining

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Authors: Mergim Gasia, Bojan Milovanovica, Sanjin Gumbarevic

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Better energy performance of the building envelope is one of the most important aspects of energy savings if the goals set by the European Union are to be achieved in the future. Dynamic heat transfer simulations are being used for the calculation of building energy consumption because they give more realistic energy demands compared to the stationary calculations that do not take the building’s thermal mass into account. Software used for these dynamic simulation use methods that are based on the analytical models since numerical models are insufficient for longer periods. The analytical models used in this research fall in the category of the conduction transfer functions (CTFs). Two methods for calculating the CTFs covered by this research are the Laplace method and the State-Space method. The literature review showed that the main disadvantage of these methods is that they are inadequate for heavyweight façade elements and shorter time periods used for the calculation. The algorithms for both the Laplace and State-Space methods are implemented in Mathematica, and the results are compared to the results from EnergyPlus and TRNSYS since these software use similar algorithms for the calculation of the building’s energy demand. This research aims to check the efficiency of the Laplace and the State-Space method for calculating the building’s energy demand for heavyweight building elements and shorter sampling time, and it also gives the means for the improvement of the algorithms used by these methods. As the reference point for the boundary heat flux density, the finite difference method (FDM) is used. Even though the dynamic heat transfer simulations are superior to the calculation based on the stationary boundary conditions, they have their limitations and will give unsatisfactory results if not properly used.

Keywords: Laplace method, state-space method, conduction transfer functions, finite difference method

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Authors: Yakui Bai, Chen Sun, Ke Wang

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An experimental investigation of environmental effect on fatigue behavior in SA508 Gr.3 Cl.2 Steam Generator Forging CAP1400 nuclear power plant has been carried out. In order to simulate actual loading condition, a range of strain amplitude was applied in different low cycle fatigue (LCF) tests. The current American Society of Mechanical Engineers (ASME) design fatigue code does not take full account of the interactions of environmental, loading, and material's factors. A range of strain amplitude was applied in different low cycle fatigue (LCF) tests at a strain rate of 0.01%s⁻¹. A design fatigue model was constructed by taking environmentally assisted fatigue effects into account, and the corresponding design curves were given for the convenience of engineering applications. The corrosion fatigue experiment was performed in a strain control mode in 320℃ borated and lithiated water environment to evaluate the effects of a mixed environment on fatigue life. Stress corrosion cracking (SCC) in steam generator large forging in primary water of pressurized water reactor was also observed. In addition, it is found that the CF life of SA508 Gr.3 Cl.2 decreases with increasing temperature in the water environment. The relationship between the reciprocal of temperature and the logarithm of fatigue life was found to be linear. Through experiments and subsequent analysis, the mechanisms of reduced low cycle fatigue life have been investigated for steam generator forging.

Keywords: failure behavior, low alloy steel, steam generator forging, stress corrosion cracking

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Authors: Muneera Mohammed Al-Dossary, Fatimah Mohammed Al-Dossary, Mashael Al-Shahrani, Amal Al-Tammemi

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Johns Hopkins Aramco Healthcare (JAHA), a joint venture between Saudi Aramco and Johns Hopkins Medicine, delivers comprehensive healthcare services to a diverse patient population. Despite achieving high patient satisfaction rates and surpassing several operational targets, JAHA faces challenges such as appointment delays and resource inefficiencies. These issues highlight the need for an advanced, integrated approach to operational management. This paper proposes a Business Intelligence (BI) framework to address these challenges, leveraging tools such as Epic electronic health records and Tableau dashboards. The framework focuses on data integration, real-time monitoring, and predictive analytics to streamline operations and enhance decision-making. Key outcomes include reduced wait times (e.g., a 23% reduction in specialty clinic wait times) and improved operating room efficiency (from 95.83% to 98% completion rates). These advancements align with JAHA’s strategic objectives of optimizing resource utilization and delivering superior patient care. The findings underscore the transformative potential of BI in healthcare, enabling a shift from reactive to proactive operations management. The success of this implementation lays the foundation for future innovations, including machine learning models for more precise demand forecasting and resource allocation.

Keywords: business intelligence, operational efficiency, healthcare management, predictive analytics, patient care improvement, data integration, real-time monitoring, resource optimization, Johns Hopkins Aramco Healthcare, electronic health records, Tableau dashboards, predictive modeling, efficiency metrics, resource utilization, patient satisfaction

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Authors: Ergin Toros, Manar Aslan

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This study was planned as a descriptive study in order to learn the opinions of the students who are studying in nursing undergraduate program about their theoretical/practical lessons and departments. The education in the undergraduate nursing programs has great importance because it contains the knowledge and skills to prepare student nurses to the clinic in the future. In order to provide quality-nursing services in the future, the quality of nursing education should be measured, and opinions of student nurses about education should be taken. The research population was composed of students educated in a university with 1-4 years of theoretical and clinical education (N=550), and the sample was composed of 460 students that accepted to take part in the study. It was reached to 83.6% of target population. Data collected through a survey developed by the researchers. Survey consists of 48 questions about sociodemographic characteristics (9 questions), theoretical courses (9 questions), laboratory applications (7 questions), clinical education (14 questions) and services provided by the faculty (9 questions). It was determined that 83.3% of the nursing students found the nursing profession to be suitable for them, 53% of them selected nursing because of easy job opportunity, and 48.9% of them stayed in state dormitory. Regarding the theoretical courses, 84.6% of the students were determined to agree that the question ‘Course schedule is prepared before the course and published on the university web page.’ 28.7% of them were determined to do not agree that the question ‘Feedback is given to students about the assignments they prepare.’. It has been determined that 41,5% of the students agreed that ‘The time allocated to laboratory applications is sufficient.’ Students said that physical conditions in laboratory (41,5%), and the materials used are insufficient (44.6%), and ‘The number of students in the group is not appropriate for laboratory applications.’ (45.2%). 71.3% of the students think that the nurses view in the clinics the students as a tool to remove the workload, 40.7% of them reported that nurses in the clinic area did not help through the purposes of the course, 39.6% of them said that nurses' communication with students is not good. 37.8% of students stated that nurses did not provide orientation to students, 37.2% of them think that nurses are not role models for students. 53.7% of the students stated that the incentive and support for the student exchange program were insufficient., %48 of the students think that career planning services, %47.2 security services,%45.4 the advisor spent time with students are not enough. It has been determined that nursing students are most disturbed by the approach of the nurses in the clinical area within the undergraduate education program. The clinical area education which is considered as an integral part of nursing education is important and affect to student satisfaction.

Keywords: nursing education, student, clinical area, opinion

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Authors: Gyoomi Kim, Jiyoung Bae

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The purpose of this study was to propose a framework that verifies the structural relationships among students’ use of digital English learning strategy (DELS), affective domains, and their individual variables. The study developed a hypothetical model based on previous studies on language learning strategy use as well as digital language learning. The participants were 720 Korean high school students and 430 university students. The instrument was a self-response questionnaire that contained 70 question items based on Oxford’s SILL (Strategy Inventory for Language Learning) as well as the previous studies on language learning strategies in digital learning environment in order to measure DELS and affective domains. The collected data were analyzed through structural equation modeling (SEM). This study used quantitative data analysis procedures: Explanatory factor analysis (EFA) and confirmatory factor analysis (CFA). Firstly, the EFA was conducted in order to verify the hypothetical model; the factor analysis was conducted preferentially to identify the underlying relationships between measured variables of DELS and the affective domain in the EFA process. The hypothetical model was established with six indicators of learning strategies (memory, cognitive, compensation, metacognitive, affective, and social strategies) under the latent variable of the use of DELS. In addition, the model included four indicators (self-confidence, interests, self-regulation, and attitude toward digital learning) under the latent variable of learners’ affective domain. Secondly, the CFA was used to determine the suitability of data and research models, so all data from the present study was used to assess model fits. Lastly, the model also included individual learner factors as covariates and five constructs selected were learners’ gender, the level of English proficiency, the duration of English learning, the period of using digital devices, and previous experience of digital English learning. The results verified from SEM analysis proposed a theoretical model that showed the structural relationships between Korean students’ use of DELS and their affective domains. Therefore, the results of this study help ESL/EFL teachers understand how learners use and develop appropriate learning strategies in digital learning contexts. The pedagogical implication and suggestions for the further study will be also presented.

Keywords: Digital English Learning Strategy, DELS, individual variables, learners' affective domains, Structural Equation Modeling, SEM

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Authors: Betty Johanna Garzon Rozo, Jonathan Crook, Fernando Moreira

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Operational risk losses are heavy tailed and are likely to be asymmetric and extremely dependent among business lines/event types. We propose a new methodology to assess, in a multivariate way, the asymmetry and extreme dependence between severity distributions, and to calculate the capital for Operational Risk. This methodology simultaneously uses (i) several parametric distributions and an alternative mix distribution (the Lognormal for the body of losses and the Generalized Pareto Distribution for the tail) via extreme value theory using SAS®, (ii) the multivariate skew t-copula applied for the first time for operational losses and (iii) Bayesian theory to estimate new n-dimensional skew t-copula models via Markov chain Monte Carlo (MCMC) simulation. This paper analyses a newly operational loss data set, SAS Global Operational Risk Data [SAS OpRisk], to model operational risk at international financial institutions. All the severity models are constructed in SAS® 9.2. We implement the procedure PROC SEVERITY and PROC NLMIXED. This paper focuses in describing this implementation.

Keywords: operational risk, loss distribution approach, extreme value theory, copulas

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Authors: Mehrdad Shahrbanozadeh, Gholam Abbas Barani, Saeed Shojaee

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In this study, a finite element (Seep3D model) and an artificial neural network (ANN) model were developed to simulate flow through dam foundation. Seep3D model is capable of simulating three-dimensional flow through a heterogeneous and anisotropic, saturated and unsaturated porous media. Flow through the Shahid Abbaspour dam foundation has been used as a case study. The FEM with 24960 triangular elements and 28707 nodes applied to model flow through foundation of this dam. The FEM being made denser in the neighborhood of the curtain screen. The ANN model developed for Shahid Abbaspour dam is a feedforward four layer network employing the sigmoid function as an activator and the back-propagation algorithm for the network learning. The water level elevations of the upstream and downstream of the dam have been used as input variables and the piezometric heads as the target outputs in the ANN model. The two models are calibrated and verified using the Shahid Abbaspour’s dam piezometric data. Results of the models were compared with those measured by the piezometers which are in good agreement. The model results also revealed that the ANN model performed as good as and in some cases better than the FEM.

Keywords: seepage, dam foundation, finite element method, neural network, seep 3D model

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Authors: Tiago do Carmo Nogueira, Cássio Dener Noronha Vinhal, Gélson da Cruz Júnior, Matheus Rudolfo Diedrich Ullmann

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Generating automatic image descriptions through natural language is a challenging task. Image captioning is a task that consistently describes an image by combining computer vision and natural language processing techniques. To accomplish this task, cutting-edge models use encoder-decoder structures. Thus, Convolutional Neural Networks (CNN) are used to extract the characteristics of the images, and Recurrent Neural Networks (RNN) generate the descriptive sentences of the images. However, cutting-edge approaches still suffer from problems of generating incorrect captions and accumulating errors in the decoders. To solve this problem, we propose a model based on the encoder-decoder structure, introducing a module that generates the weights according to the importance of the word to form the sentence, using the part-of-speech (PoS). Thus, the results demonstrate that our model surpasses state-of-the-art models.

Keywords: gated recurrent units, caption generation, convolutional neural network, part-of-speech

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Authors: Azizah Che Omar

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The study provides a systematic literature review which analyzed the literature for the purpose of looking for concepts, theories, approaches and guidelines in order to propose a conceptual design model of interactive television advertising toward impulse purchase (iTVAdIP). An extensive review of literature was purposely carried out to understand the concepts of interactive television (iTV). Therefore, some elements; iTV guidelines, advertising theories, persuasive approaches, and the impulse purchase elements were analyzed to reach the scope of this work. The extensive review was also a necessity to achieve the objective of this study, which was to determine the concept of iTVAdIP design model. Through systematic review analysis, this study discovered that all the previous models did not emphasize the conceptual design model of interactive television advertising. As a result, the finding showed that the concept of the proposed model should contain the iTV guidelines, advertising theory, persuasive approach and impulse purchase elements. In addition, a summary diagram for the development of the proposed model is depicted to provide clearer understanding towards the concepts of conceptual design model of iTVAdIP.

Keywords: impulse purchase, interactive television advertising, human computer interaction, advertising theories

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Authors: Tella Toluwani, Adegbegi Ademuyiwa, Musei Chiedu, Adekunle Odola, Ayangbenro Ayansina, Adaramoye Oluwatosin

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Dithiocarbamates are very useful biological agents with antioxidant properties. Diclofenac (DIC) is a non-steroidal analgesic, anti-inflammatory, and antipyretic agent. The use of diclofenac has been linked with reproductive toxicity/damage. The purpose of this study is (i) To investigate the therapeutic potential of diisopropyldithiocarbamate sodium salt (Na(i-Pr₂dtc)) and vitamin E (VIT E) against diclofenac induced toxicity in the testes of male Wistar rats. (ii) To investigate the effect of (Na(i-Pr₂dtc)) and vitamin E on ameliorating damage done to the testes through histological analysis of the testes. Thirty-six (36) male Wistar rats were used for the experiment, they were divided into six (6) groups, the animals in group 1 served as control, animals in groups 2, 3, 4, 5 and 6 received DIC only, DIC and (Na(i-Pr₂dtc)), DIC and VIT E, (Na(i-Pr₂dtc) only and VIT E only respectively. A single dose of 100 mg/kg body weight of DIC was administered to male Wistar rats, while 30 mg/kg body weight of (Na(i-Pr₂dtc)) was used to treat both normal and DIC treated animals, control animals were treated with the vehicle, after 24 hrs of treatment the animals were euthanized and the testes were removed for analysis. The treatment of rats with Na(i-Pr₂dtc) significantly restored catalase (CAT) activity depressed by diclofenac. (Na(i-Pr₂dtc)) also restored glutathione levels reduced by DIC treatment and this was also accompanied by reduced lipid peroxidation (LPO) level. VIT E significantly restored superoxide dismutase (SOD) activity when compared with DIC only treated animals. Photomicrographs of testes from (Na(i-Pr₂dtc)) treated rats showed seminiferous epithelium with no lesions. We conclude that (Na(i-Pr₂dtc)) has an antioxidant effect, which might be related to the dose and duration of administration.

Keywords: diisopropyldithiocarbamate sodium salt, diclofenac, vitamin E, testes

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Authors: Thota Sai Prakash, B. Yaswanth, Jhade Bhuvaneswar, Marreddy Divakar Reddy, Shyam Ji Gupta

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Across the globe, there are a lot of chronic diseases, and heart disease stands out as one of the most perilous. Sadly, many lives are lost to this condition, even though early intervention could prevent such tragedies. However, identifying heart disease in its initial stages is not easy. To address this challenge, we propose an automated system aimed at predicting the presence of heart disease using advanced techniques. By doing so, we hope to empower individuals with the knowledge needed to take proactive measures against this potentially fatal illness. Our approach towards this problem involves meticulous data preprocessing and the development of predictive models utilizing classification algorithms such as Support Vector Machines (SVM), Decision Tree, and Random Forest. We assess the efficiency of every model based on metrics like accuracy, ensuring that we select the most reliable option. Additionally, we conduct thorough data analysis to reveal the importance of different attributes. Among the models considered, Random Forest emerges as the standout performer with an accuracy rate of 96.04% in our study.

Keywords: support vector machines, decision tree, random forest

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Authors: Deepika Christopher, Garima Anand

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To determine the best model for churn prediction in the telecom industry, this paper compares 11 machine learning algorithms, namely Logistic Regression, Support Vector Machine, Random Forest, Decision Tree, XGBoost, LightGBM, Cat Boost, AdaBoost, Extra Trees, Deep Neural Network, and Hybrid Model (MLPClassifier). It also aims to pinpoint the top three factors that lead to customer churn and conducts customer segmentation to identify vulnerable groups. According to the data, the Logistic Regression model performs the best, with an F1 score of 0.6215, 81.76% accuracy, 68.95% precision, and 56.57% recall. The top three attributes that cause churn are found to be tenure, Internet Service Fiber optic, and Internet Service DSL; conversely, the top three models in this article that perform the best are Logistic Regression, Deep Neural Network, and AdaBoost. The K means algorithm is applied to establish and analyze four different customer clusters. This study has effectively identified customers that are at risk of churn and may be utilized to develop and execute strategies that lower customer attrition.

Keywords: attrition, retention, predictive modeling, customer segmentation, telecommunications

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Authors: A. Bayle, F. Plouraboué

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Water Distribution Network (WDN) still suffers from a lack of knowledge about fast pressure transient events prediction, although the latter may considerably impact their durability. Accidental or planned operating activities indeed give rise to complex pressure interactions and may drastically modified the local pressure value generating leaks and, in rare cases, pipe’s break. In this context, a numerical predictive analysis is conducted to prevent such event and optimize network management. A couple of Python/FORTRAN 90, home-made software, has been developed using Method Of Characteristic (MOC) solving for water-hammer equations. The solver is validated by direct comparison with theoretical and experimental measurement in simple configurations whilst afterward extended to network analysis. The algorithm's most costly steps are designed for parallel computation. A various set of boundary conditions and energetic losses models are considered for the network simulations. The results are analyzed in both real and frequencies domain and provide crucial information on the pressure distribution behavior within the network.

Keywords: energetic losses models, method of characteristic, numerical predictive analysis, water distribution network, water hammer

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Authors: Thanh Van Hoang, Tien Yin Chou, Yao Min Fang, Yi Min Huang, Xuan Linh Nguyen

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Reliable information on the spatial distribution of annual rainfall and temperature is essential in research projects relating to urban and regional planning. This research presents results of a classification of temperature and rainfall in the Red River Delta of northern Vietnam based on measurements from seven meteorological stations (Ha Nam, Hung Yen, Lang, Nam Dinh, Ninh Binh, Phu Lien, Thai Binh) in the river basin over a thirty-years period from 1982-2011. The average accumulated rainfall trends in the delta are analysed and form the basis of research essential to weather and climate forecasting. This study employs interpolation based on the Kriging Method for daily rainfall (min and max) and daily temperature (min and max) in order to improve the understanding of sources of variation and uncertainly in these important meteorological parameters. To the Kriging method, the results will show the different models and the different parameters based on the various precipitation series. The results provide a useful reference to assist decision makers in developing smart agriculture strategies for the Red River Delta in Vietnam.

Keywords: spatial interpolation method, ArcGIS, temperature variability, rainfall variability, Red River Delta, Vietnam

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Authors: Shulamit Sternin

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Athletes experience injuries that can have both a physical and psychological impact on the individual. In such instances, athletes are able to rely on the established field of sports psychology to facilitate holistic rehabilitation. Musicians, like athletes rely on their bodies to perform in much the same way athletes do and are also susceptible to injury. Due to the similar performative nature of succeeding as an athletes or a musician, these careers share many of the same primary psychological concerns and therefore it is reasonable that athletes and musicians may require similar rehabilitation post-injury. However, musicians face their own unique psychological challenges and understanding the needs of an injured athlete can serve as a foundation for understanding the injured musician but is not enough to fully rehabilitate an injured musician. The current research surrounding musicians and their injuries is primarily focused on physiological aspects of injury and rehabilitation; the psychological aspects have not yet received adequate attention resulting in poor musician rehabilitation post- injury. This review paper uses current models of psychological response to injury in athletes to draw parallels with the psychological response to injury in musicians. Search engines such as Medline and PsycInfo were systematically searched using specific key words, such as psychological response, injury, athlete, and musician. Studies that focused on post-injury psychology of either the musician or the athlete were included. Within the literature there is evidence to support psychological responses, unique to the musician, that are not accounted for by current models of response in athletes. The models of psychological response to injury in athletes are inadequate tools for application to the musician. Future directions for performance arts research that can fill the gaps in our understanding and modeling of musicians’ response to injury are discussed. A better understanding of the psychological impact of injuries on musicians holds significant implications for health care practitioners working with injured musicians. Understanding the unique barriers musicians face post-injury, and how support for this population must be tailored to properly suit musicians’ needs will aid in more holistic rehabilitation and a higher likelihood of musician’s returning to pre-injury performance levels.

Keywords: athlete, injury, musician, psychological response

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Authors: Jatindra Lahkar

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The effect of chemical reaction on laminar mixed convection flow and heat and mass transfer along a vertical unsteady stretching sheet is investigated, in the presence of heat generation/absorption with variable viscosity and viscous dissipation. The governing non-linear partial differential equations are reduced to ordinary differential equations using similarity transformation and solved numerically using the fourth order Runge-Kutta method along with shooting technique. The effects of various flow parameters on the velocity, temperature and concentration distributions are analyzed and presented graphically. Skin-friction coefficient, Nusselt number and Sherwood number are derived at the sheet. It is observed that the influence of chemical reaction, the fluid flow along the sheet accelerate with the increase of chemical reaction parameter, on the other hand, temperature of the fluid increases with increase of chemical reaction parameter but concentration of the fluid reduces with it. The boundary layer decreases on the surface of the sheet for all values of unsteadiness parameter, increasing values of the chemical reaction parameter. The increases in the values of Sc cause the species concentration and its boundary layer thickness to decrease resulting in less induced flow and higher fluid temperatures. This is depicted in the decreases in the velocity and species concentration and increases in the fluid temperature as Sc increases.

Keywords: chemical reaction, heat generation/absorption, magnetic number, unsteadiness, variable viscosity

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Authors: Selma Bouasria, Mahi Abdelkader, Abbès Azzi, Herouz Keltoum

Abstract:

Ventilation in buildings is a key element to provide high indoor air quality. Its efficiency appears as one of the most important factors in maintaining thermal comfort for occupants of buildings. Personal displacement ventilation is a new ventilation concept that combines the positive features of displacement ventilation with those of task conditioning or personalized ventilation. This work aims to study numerically the supply air flow in a room to optimize a comfortable microclimate for an occupant. The room is heated, and a dummy is designed to simulate the occupant. Two types of configurations were studied. The first consist of a room without windows; and the second one is a local equipped with a window. The influence of the blowing speed and the solar radiation coming from the window on the thermal comfort of the occupant is studied. To conduct this study we used the turbulence models, namely the high Reynolds k-e, the RNG and the SST models. The numerical tool used is based on the finite volume method. The numerical simulation of the supply air flow in a room can predict and provide a significant information about indoor comfort.

Keywords: local, comfort, thermique, ventilation, internal environment

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Authors: Weiliang Wen, Xinyu Guo, Ying Zhang, Jianjun Du, Boxiang Xiao

Abstract:

Reconstructing and analyzing three-dimensional (3D) models from situ measured data is important for a number of researches and applications in plant science, including plant phenotyping, functional-structural plant modeling (FSPM), plant germplasm resources protection, agricultural technology popularization. It has many scales like cell, tissue, organ, plant and canopy from micro to macroscopic. The techniques currently used for data capture, feature analysis, and 3D reconstruction are quite different of different scales. In this context, morphological data acquisition, 3D analysis and modeling of plants on different scales are introduced systematically. The commonly used data capture equipment for these multiscale is introduced. Then hot issues and difficulties of different scales are described respectively. Some examples are also given, such as Micron-scale phenotyping quantification and 3D microstructure reconstruction of vascular bundles within maize stalks based on micro-CT scanning, 3D reconstruction of leaf surfaces and feature extraction from point cloud acquired by using 3D handheld scanner, plant modeling by combining parameter driven 3D organ templates. Several application examples by using the 3D models and analysis results of plants are also introduced. A 3D maize canopy was constructed, and light distribution was simulated within the canopy, which was used for the designation of ideal plant type. A grape tree model was constructed from 3D digital and point cloud data, which was used for the production of science content of 11th international conference on grapevine breeding and genetics. By using the tissue models of plants, a Google glass was used to look around visually inside the plant to understand the internal structure of plants. With the development of information technology, 3D data acquisition, and data processing techniques will play a greater role in plant science.

Keywords: plant, three dimensional modeling, multi-scale, plant phenotyping, three dimensional data acquisition

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Authors: Selena Gutiérrez, Araceli Martínez

Abstract:

One of the most important challenges worldwide, scientific and technological, is to have a sustainable energy source; friendly to the environment and widely available. Currently, the 85% of the energy used comes from the fossil sources. Another important environmental problem is that several rubber products (tires, gloves, hoses, among others) are discarded practically without any treatment. In nature, the degradation of such products will take at least 500 years. In 2009, the worldwide rubber production was about 23.6 million tons. In order to solve this problems, our research focus in an alternative synthesis of biofuels in a two-step approach: The metathesis degradation of industrial rubber (models of rubber waste), and the oligomers transesterification. Thus, cis-1,4-polybutadiene (Mn= 9.1x105, Mw/Mn= 2.2) and styrene-butadiene block copolymers with 30% (Mn= 1.61x105; Mw/Mn= 1.3) and 21% wt styrene (Mn= 1.92x105; Mw/Mn= 1.4) were degraded via metathesis with soybean oil as chain transfer agent (CTA) and green solvent; using [(PCy3)2Cl2Ru=CHPh] and [(1,3-diphenyl-4,5-dihydroimidazol-2-ylidene)(PCy3)Ru=CHPh] catalysts. Afterwards, the products were transesterified by basic homogeneous catalysis. Before transesterification, the polystyrene microblocks (Mn= 16,761; Mw/Mn= 1.2) were isolated. Finally, the biofuels obtained (BO) were purified, characterized and showed similar properties to standards biodiesel (SB) (Norms: EN 14214-03 and ASTM D6751-02), i.e. (SB / BO): molecular weight [Daltons] (570 / 543-596), density [g/cm3] (0.86-0.90 / 0.88), kinematic viscosity [mm2/s] (1.90-6.0 / 3.5-4.5), iodine (97 / 97-98) and cetane number (Min.47 / 56-58).

Keywords: biofuels, industrial rubber, metathesis, vegetable oils

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Authors: A. Katsman, L. Bloch, Y. Etinger, Y. Kauffmann, B. Pokroy

Abstract:

Various nanosized amorphous alumina thin films in the range of (2.4 - 63.1) nm were deposited onto amorphous carbon and amorphous Si3N4 membrane grids. Transmission electron microscopy (TEM), electron energy loss spectroscopy (EELS), X-ray photoelectron spectroscopy (XPS) and differential scanning calorimetry (DSC) techniques were used to probe the size effect on the short range order and the amorphous to crystalline phase transition temperature. It was found that the short-range order changes as a function of size: the fraction of tetrahedral Al sites is greater in thinner amorphous films. This result correlates with the change of amorphous alumina density with the film thickness demonstrated by the reflectivity experiments: the thinner amorphous films have the less density. These effects are discussed in terms of surface reconstruction of the amorphous alumina films. The average atomic binding energy in the thin film layer decreases with decease of the thickness, while the average O-Al interatomic distance increases. The reconstruction of amorphous alumina is induced by the surface reconstruction, and the short range order changes being dependent on the density. Decrease of the surface energy during reconstruction is the driving force of the alumina reconstruction (density change) followed by relaxation process (short range order change). The amorphous to crystalline phase transition temperature measured by DSC rises with the decrease in thickness from 997.6°C for 13.9 nm to 1020.4 °C for 2.7 nm thick. This effect was attributed to the different film densities: formation of nanovoids preceding and accompanying crystallization process influences the crystallization rate, and by these means, the temperature of crystallization peak.

Keywords: amorphous alumina, density, short range order, size effect

Procedia PDF Downloads 468