Search results for: wound rotor induction machine

Authors: Mohammad Hossein Mohammadi Sanjani, Ashknaz Oraee, Oriol Gomis Bellmunt, Vinicius Albernaz Lacerda Freitas

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The use of distributed and renewable sources in power systems has grown significantly, recently. One the most popular sources are wind farms which have grown massively. However, ¬wind farms are connected to the grid, this can cause problems such as reduced voltage stability, frequency fluctuations and reduced dynamic stability. Variable speed generators (asynchronous) are used due to the uncontrollability of wind speed specially Doubley Fed Induction Generators (DFIG). The most important disadvantage of DFIGs is its sensitivity to voltage drop. In the case of faults, a large volume of reactive power is induced therefore, use of FACTS devices such as SVC and STATCOM are suitable for improving system output performance. They increase the capacity of lines and also passes network fault conditions. In this paper, in addition to modeling the reactive power control system in a DFIG with converter, FACTS devices have been used in a DFIG wind turbine to improve the stability of the power system containing two synchronous sources. In the following paper, recent optimal control systems have been designed to minimize fluctuations caused by system disturbances, for FACTS devices employed. For this purpose, a suitable method for the selection of nine parameters for MPSH-phase-post-phase compensators of reactive power compensators is proposed. The design algorithm is formulated ¬¬as an optimization problem searching for optimal parameters in the controller. Simulation results show that the proposed controller Improves the stability of the network and the fluctuations are at desired speed.

Keywords: renewable energy sources, optimization wind power plant, stability, reactive power compensator, double-feed induction generator, optimal control, genetic algorithm

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Authors: Sunil Verma

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This report is concerned with study of autoignition delay characterstics of n-pentane. Experiments are done for different equivalents ratio on Rapid compression machine. Dependence of autoignition delay period is clearly explained from lean to rich mixtures. Equivalence ratio is varied from 0.33 to 0.6.

Keywords: combustion, autoignition, ignition delay, rapid compression machine

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Authors: Bijit Kalita, K. V. N. Surendra

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Rotating disk is one of the most indispensable parts of a rotating machine. Rotating disk has found many applications in the diverging field of science and technology. In this paper, we have taken into consideration the problem of a heavy spinning disk mounted on a rotor system acted upon by boundary traction. Finite element modelling is used at various loading condition to determine the mixed mode stress intensity factors. The effect of combined shear and normal traction on the boundary is incorporated in the analysis under the action of gravity. The variation near the crack tip is characterized in terms of the stress intensity factor (SIF) with an aim to find the SIF for a wide range of parameters. The results of the finite element analyses carried out on the compressed disk of a belt pulley arrangement using fracture mechanics concepts are shown. A total of hundred cases of the problem are solved for each of the variations in loading arc parameter and crack orientation using finite element models of the disc under compression. All models were prepared and analyzed for the uncracked disk, disk with a single crack at different orientation emanating from shaft hole as well as for a disc with pair of cracks emerging from the same center hole. Curves are plotted for various loading conditions. Finally, crack propagation paths are determined using kink angle concepts.

Keywords: crack-tip deformations, static loading, stress concentration, stress intensity factor

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Authors: Nadia Allouache

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The use of solar energy in cooling systems is an interesting alternative to the increasing demand of energy in the world and more specifically in southern countries where the needs of refrigeration and air conditioning are tremendous. This technique is even more attractive with regards to environmental issues. This study focuses on performances analysis and optimization of solar reactor of an adsorption cooling machine working with activated carbon-methanol pair. The modeling of the adsorption cooling machine requires the resolution of the equation describing the energy and mass transfer in the tubular adsorber that is the most important component of the machine. The results show the poor heat conduction inside the porous medium and the resistance between the metallic wall and the bed engender the important temperature gradient and a great difference between the metallic wall and the bed temperature; this is considered as the essential causes decreasing the performances of the machine. For fixed conditions of functioning, the total desorbed mass presents a maximum for an optimal value of the height of the adsorber; this implies the existence of an optimal dimensioning of the adsorber.

Keywords: solar cooling system, performances Analysis, optimization, heat and mass transfer, activated carbon-methanol pair, numerical modeling

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Authors: M. Akhondizadeh, Mohsen Khajoei, Mojtaba Khajoei

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The purpose of the present work was the design of a towing machine which was decided to be manufactured by Arman Gohar-e-Sirjan company in the Gol-e-Gohar iron ore complex in Iran. The load analysis has been conducted to determine the static and dynamic loads at the critical conditions. The inertial forces due to the velocity increment and road bump have been considered in load evaluation. The form of loading of the present machine is hauling and/or conveying the mineral machines on the mini ramp. Several stages of these forms of loading, from the initial touch of the tow and carried machine to the final position, have been assessed to determine the critical state. The stress analysis has been performed by the ANSYS software. Several geometries for the main load-carrying elements have been analyzed to have the optimum design by the minimum weight of the structure. Finally, a structure with a total weight of 38 tons has been designed with a static load-carrying capacity of 80 tons by considering the 40 tons additional capacity for dynamic effects. The stress analysis for 120 tons load gives the minimum safety factor of 1.18.

Keywords: mechanical design, stress analysis, tow structure, dynamic load, static load

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Authors: Jitaree Tantiyasawatdikul, Bantita Jadnok, Sarunya Tijana

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Background: Nutritional status is an important factor before, during, and after an operation. It can help wound healing. If the patients have good nutritional status before and after an operation, wound healing can occur more easily. It can strengthen the immune system leading to decreased infection, reduced length of stay, and reducing the cost to patients and caregivers. Therefore, screening to evaluate the nutritional status of patients in 3B becomes the database for further developing the treatment and also will lead to excellent service from the interdisciplinary team. Objective: To study the nutritional status of patients in surgical ward 3B at Surgical and Orthopedics Nursing Division, Srinagarind Hospital. Method: A descriptive study, to evaluate the nutritional status of 86 patients admitted in 3B between October 2014 and March 2015.The instruments used in this study consisted of two parts: 1) personal data, 2) Screening nutritional status. The data were analyzed by percentage and mean. Results: A sample population of 86 patients aged 22-81 years old, mean age 52.59years, 90.69% are married, female were 55.81%, regular diet 70.93%, patients with no problem oral cavity was 87.21%.The sample population had high incidence of CA 47.67% and secondly cardiovascular disease 36.05 %. Patients with high-risk nutrition was 12.79 % including 45.45% cardiovascular disease and 36.36% CA. Screening of nutritional status of high-risk nutrition was 39.36% severe triceps skinfold (TSF), severe mid-arm muscle circumference(MAMC) 9.09% and severe total lymphocyte 39.36%. Conclusion: The result of nutritional status screening of surgical ward 3B found 12.79% patients with high-risk nutrition including 45.45% with cardiovascular disease .There was no problem with oral cavity and eating.

Keywords: nutritional status, screening, surgical patients, 3B ward, Srinagarind Hospital

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Authors: Byeal-I Han, Michael Lee

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Ageing is associated with an increased risk of diseases such as cancer, and neurodegenerative disorders. Increased autophagy delays ageing and extends longevity. In this study, we investigated the role of autophagy in longevity using human foreskin fibroblast HS68 cells, in which a senescence-like growth arrest can be induced. In particular, cellular senescence is manifested by the irreversible cell cycle arrest, and may contribute to the ageing of organisms. The senescence state was measured with staining for senescence-associated β-galactosidase (SA-β-gal) activity that represents a sensitive and reliable marker to quantify senescent cells. We detected a significantly increased percentage (%) of SA-β-gal positive cells in HS68 cultures at passage 40 (63%) when compared with younger ones at passage 15 (0.5%). As expected, HS68 cells at passage 40 exhibited much lower proliferation rate than cells at passage 15. The basal levels of LC3 were measured by immunoblotting showing a comparison of LC3-I and LC3-II levels at 3 age-points in serially passaged HS68 cells. LC3-II/LC3-I ratio at different passage levels relative to β-actin levels of each band confirmed that cells at passage 34 showed lower conversion of non-autophagic LC3-I to autophagic LC3-II than the cells at passage 16. Furthermore, Cyto-ID autophagy assay also revealed that late passage cells showed lower autophagy than the early passage cells. Together, our findings suggest that senescence induction might be associated with decreased autophagy.

Keywords: ageing, autophagy, senescence, HS68

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Authors: Ashish Dhamaniya, Vineet Jain, Rajesh Chouhan

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Traffic management is one of the gigantic issue in most of the urban roads in al-most all metropolitan cities in India. Speed is one of the critical traffic parameters for effective Intelligent Transportation System (ITS) implementation as it decides the arrival rate of vehicles on an intersection which are majorly the point of con-gestions. The study aimed to leverage Machine Learning (ML) models to produce precise predictions of speed on urban roadway links. The research objective was to assess how categorized traffic volume and road width, serving as variables, in-fluence speed prediction. Four tree-based regression models namely: Decision Tree (DT), Random Forest (RF), Extra Tree (ET), and Extreme Gradient Boost (XGB)are employed for this purpose. The models' performances were validated using test data, and the results demonstrate that Random Forest surpasses other machine learning techniques and a conventional utility theory-based model in speed prediction. The study is useful for managing the urban roadway network performance under mixed traffic conditions and effective implementation of ITS.

Keywords: stream speed, urban roads, machine learning, traffic flow

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Authors: Madhu Patial, Dharam Pal, Jagdish Kumar, H. K. Chaudhary

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Doubled haploid breeding serves as a useful technique in wheat improvement by providing instant and complete homozygosity. Of the various techniques employed for haploid production chromosome elimination has a large scale practical application in wheat improvement. Barclay (1975) initiated the technique in wheat by crossing wheat variety Chinese spring with Hordeum bulbosum, but due to presence of the dominant crossability inhibitor genes Kr7 and Kr2 in many wheat varieties, the technique was however genotypic specific. The discovery of wheat X maize system of haploid production being genotype non-specific is quite successful but still maize needs to be grown in greenhouse to coincide flowering with wheat crop. Recently, wheat X Imperate cylindrica has been identified as a new chromosome mediated DH approach for efficient haploid induction. An experiment to use this technique in wheat was set up by crossing six F1s and two three way F1s with Imperata cylindrica. The data was recorded for the three component traits of haploid induction viz., seed formation, embryo formation and regeneration frequency. Variation among wheat F1s was observed and higher frequency for all the traits were recorded in cross HD 2997/2*FL-8/DONSK-POLL and KLE/BER/2*FL-8/DONSK-POLL.

Keywords: wheat, haploid, imperata cylindrica, chromosome elimination technique

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Authors: Prasanna Ramachandran, Kareem Graham, Helena Kiefel, Sunit Jain, Todd DeSantis

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Microbes that reside inside the mammalian GI tract, commonly referred to as the gut microbiome, have been shown to have therapeutic effects in animal models of disease. We hypothesize that specific proteins produced by these microbes are responsible for this activity and may be used directly as therapeutics. To speed up the discovery of these key proteins from the big-data metagenomics, we have applied machine learning techniques. Using amino acid sequences of known epitopes and their corresponding binding partners, protein interaction descriptors (PID) were calculated, making a positive interaction set. A negative interaction dataset was calculated using sequences of proteins known not to interact with these same binding partners. Using Random Forest and positive and negative PID, a machine learning model was trained and used to predict interacting versus non-interacting proteins. Furthermore, the continuous variable, cosine similarity in the interaction descriptors was used to rank bacterial therapeutic candidates. Laboratory binding assays were conducted to test the candidates for their potential as therapeutics. Results from binding assays reveal the accuracy of the machine learning prediction and are subsequently used to further improve the model.

Keywords: protein-interactions, machine-learning, metagenomics, microbiome

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Authors: Victoria Bila, Iryna Ventskivska, Oleksandra Zahorodnia

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The goal of the study: To study the distribution of patients of the Kiyv Perinatal Center according to the Robson system and compare it with world data. Materials and methods: a comparison of the distribution of patients of Kiyv Perinatal center according to the Robson system for 2 periods - the first quarter of 2019 and 2020. For each group, 3 indicators were analyzed - the share of this group in the overall structure of patients of the Perinatal Center for the reporting period, the frequency of abdominal delivery in this group, as well as the contribution of this group to the total number of abdominal delivery. Obtained data were compared with those of the WHO in the guidelines for the implementation of the Robson system in 2017. Results and its discussion: The distribution of patients of the Perinatal Center into groups in the Robson classification is not much different from that recommended by the author. So, among all women, patients of group 1 dominate; this indicator does not change in dynamics. A slight increase in the share of group 2 (6.7% in 2019 and 9.3% - 2020) was due to an increase in the number of labor induction. At the same time, the number of patients of groups 1 and 2 in the Perinatal Center is greater than in the world population, which is determined by the hospitalization of primiparous women with reproductive losses in the past. The Perinatal Center is distinguished from the world population and the proportion of women of group 5 - it was 5.4%, in the world - 7.6%. The frequency of caesarean section in the Perinatal Center is within limits typical for most countries (20.5-20.8%). Moreover, the dominant groups in the structure of caesarean sections are group 5 (21-23.3%) and group 2 (21.9-22.9%), which are the reserve for reducing the number of abdominal delivery. In group 2, certain results have already been achieved in this matter - the frequency of cesarean section in 2019 here amounted to 67.8%, in the first quarter of 2020 - 51.6%. This happened due to a change in the leading method of induction of labor. Thus, the Robson system is a convenient and affordable tool for assessing the structure of caesarean sections. The analysis showed that, in general, the structure of caesarean sections in the Perinatal Center is close to world data, and the identified deviations have explanations related to the specialization of the Center.

Keywords: cesarian section, Robson system, Kyiv Perinatal Center, labor induction

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Authors: Youn-Sung Kim, Jin-Ho Jo, Mi-Sung Kim, Jae-Kun Lee

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Accelerated life cycle test is applied to various products or components in order to reduce the time of life cycle test in industry. It must be considered for many test conditions according to the product characteristics for the test and the selection of acceleration parameter is especially very important. We have carried out the general life cycle test and the accelerated life cycle test by applying the acceleration factor (AF) considering the characteristics of brushless DC (BLDC) motor for washing machine. The final purpose of this study is to verify the validity by analyzing the results of the general life cycle test and the accelerated life cycle test. It will make it possible to reduce the life test time through the reasonable accelerated life cycle test.

Keywords: accelerated life cycle test, reliability test, motor for washing machine, brushless dc motor test

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Authors: David F. Nettleton, Christian Wasiak, Jonas Dorissen, David Gillen, Alexandr Tretyak, Elodie Bugnicourt, Alejandro Rosales

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In this work, preliminary results are given for the modeling and calibration of two inline processes, pultrusion, and laser ablation, using machine learning techniques. The end product of the processes is the core of a medical guidewire, manufactured to comply with a user specification of diameter and flexibility. An ensemble approach is followed which requires training several models. Two state of the art machine learning algorithms are benchmarked: Kernel Recursive Least Squares (KRLS) and Support Vector Regression (SVR). The final objective is to build a precise digital model of the pultrusion and laser ablation process in order to calibrate the resulting diameter and flexibility of a medical guidewire, which is the end product while taking into account the friction on the forming die. The result is an ensemble of models, whose output is within a strict required tolerance and which covers the required range of diameter and flexibility of the guidewire end product. The modeling and automatic calibration of complex in-line industrial processes is a key aspect of the Industry 4.0 movement for cyber-physical systems.

Keywords: calibration, data modeling, industrial processes, machine learning

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Authors: Noha Seddik, Sherine Youssef, Mohamed Kholeif

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The automated epileptic seizure detection research field has emerged in the recent years; this involves analyzing the Electroencephalogram (EEG) signals instead of the traditional visual inspection performed by expert neurologists. In this study, a Support Vector Machine (SVM) that uses Weighted Permutation Entropy (WPE) as the input feature is proposed for classifying normal and seizure EEG records. WPE is a modified statistical parameter of the permutation entropy (PE) that measures the complexity and irregularity of a time series. It incorporates both the mapped ordinal pattern of the time series and the information contained in the amplitude of its sample points. The proposed system utilizes the fact that entropy based measures for the EEG segments during epileptic seizure are lower than in normal EEG.

Keywords: electroencephalogram (EEG), epileptic seizure detection, weighted permutation entropy (WPE), support vector machine (SVM)

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Authors: Huseyin A. Yavasoglu, Yusuf Ziya Tengiz, Ali Göksenli

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In this study, an automatic feeding machine for different type and class of bovine animals is designed. Daily nutrition of a bovine consists of grass, corn, straw, silage, oat, wheat and different vitamins and minerals. The amount and mixture amount of each of the nutrition depends on different parameters of the bovine. These parameters are; age, sex, weight and maternity of the bovine, also outside temperature. The problem in a farm is to constitute the correct mixture and amount of nutrition for each animal. Faulty nutrition will cause an insufficient feeding of the animal concluding in an unhealthy bovine. To solve this problem, a new automatic feeding machine is designed. Travelling of the machine is performed by four tires, which is pulled by a tractor. The carrier consists of eight bins, which each of them carries a nutrition type. Capacity of each unit is 250 kg. At the bottom of each chamber is a sensor measuring the weight of the food inside. A funnel is at the bottom of each chamber by which open/close function is controlled by a valve. Each animal will carry a RFID tag including ID on its ear. A receiver on the feeding machine will read this ID and by given previous information by the operator (veterinarian), the system will detect the amount of each nutrition unit which will be given to the selected animal for feeding. In the system, each bin will open its exit gate by the help of the valve under the control of PLC (Programmable Logic Controller). The amount of each nutrition type will be controlled by measuring the open/close time. The exit canals of the bins are collected in a reservoir. To achieve a homogenous nitration, the collected feed will be mixed by a worm gear. Further the mixture will be transported by a help of a funnel to the feeding unit of the animal. The feeding process can be performed in 100 seconds. After feeding of the animal, the tractor pulls the travelling machine to the next animal. By the help of this system animals can be feeded by right amount and mixture of nutrition

Keywords: bovine, feeding, nutrition, transportation, automatic

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Authors: Prashant Verma

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Commercial banks are facing immense pressure, including financial disintermediation, interest rate volatility and digital ways of finance. Retaining an existing customer is 5 to 25 less expensive than acquiring a new one. This paper explores customer churn prediction, based on various statistical & machine learning models and uses under-sampling, to improve the predictive power of these models. The results show that out of the various machine learning models, Random Forest which predicts the churn with 78% accuracy, has been found to be the most powerful model for the scenario. Customer vintage, customer’s age, average balance, occupation code, population code, average withdrawal amount, and an average number of transactions were found to be the variables with high predictive power for the churn prediction model. The model can be deployed by the commercial banks in order to avoid the customer churn so that they may retain the funds, which are kept by savings bank (SB) customers. The article suggests a customized campaign to be initiated by commercial banks to avoid SB customer churn. Hence, by giving better customer satisfaction and experience, the commercial banks can limit the customer churn and maintain their deposits.

Keywords: savings bank, customer churn, customer retention, random forests, machine learning, under-sampling

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Authors: Vignesh Ratnaraj, Jaewon Chang

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Background: Frailty is associated with poorer outcomes in cardiac surgery, but the heterogeneity in frailty assessment tools makes it difficult to ascertain its true impact in cardiac surgery. Slow gait speed is a simple, validated, and reliable marker of frailty. We performed a systematic review and meta-analysis to examine the effect of slow gait speed on postoperative cardiac surgical patients. Methods: PubMED, MEDLINE, and EMBASE databases were searched from January 2000 to August 2021 for studies comparing slow gait speed and “normal” gait speed. The primary outcome was in-hospital mortality. Secondary outcomes were composite mortality and major morbidity, AKI, stroke, deep sternal wound infection, prolonged ventilation, discharge to a healthcare facility, and ICU length of stay. Results: There were seven eligible studies with 36,697 patients. Slow gait speed was associated with an increased likelihood of in-hospital mortality (risk ratio [RR]: 2.32; 95% confidence interval [CI]: 1.87–2.87). Additionally, they were more likely to suffer from composite mortality and major morbidity (RR: 1.52; 95% CI: 1.38–1.66), AKI (RR: 2.81; 95% CI: 1.44–5.49), deep sternal wound infection (RR: 1.77; 95% CI: 1.59–1.98), prolonged ventilation >24 h (RR: 1.97; 95% CI: 1.48–2.63), reoperation (RR: 1.38; 95% CI: 1.05–1.82), institutional discharge (RR: 2.08; 95% CI: 1.61–2.69), and longer ICU length of stay (MD: 21.69; 95% CI: 17.32–26.05). Conclusion: Slow gait speed is associated with poorer outcomes in cardiac surgery. Frail patients are twofold more likely to die during hospital admission than non-frail counterparts and are at an increased risk of developing various perioperative complications.

Keywords: cardiac surgery, gait speed, recovery, frailty

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Authors: Saurabh Kumar

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In the fiercely competitive landscape of e-commerce, understanding and mitigating customer churn has become paramount for sustainable business growth. This paper presents a thorough investigation into the application of machine learning techniques for churn prediction in e-commerce, aiming to provide actionable insights for businesses seeking to enhance customer retention strategies. We conduct a comparative study of various machine learning algorithms, including traditional statistical methods and ensemble techniques, leveraging a rich dataset sourced from Kaggle. Through rigorous evaluation, we assess the predictive performance, interpretability, and scalability of each method, elucidating their respective strengths and limitations in capturing the intricate dynamics of customer churn. We identified the XGBoost classifier to be the best performing. Our findings not only offer practical guidelines for selecting suitable modeling approaches but also contribute to the broader understanding of customer behavior in the e-commerce domain. Ultimately, this research equips businesses with the knowledge and tools necessary to proactively identify and address churn, thereby fostering long-term customer relationships and sustaining competitive advantage.

Keywords: customer churn, e-commerce, machine learning techniques, predictive performance, sustainable business growth

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Authors: Oscar Kallay

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Objective: This study compares the sustainability, financial implications, and surgical efficiency of two phacoemulsification cassette systems for cataract surgery: a machine with single-use cassettes and another with daily, reusable ones. Methods: The observational study involves retrospective cataract surgery data collection at the Centre Médical de l'Alliance, Braine-L’alleud, Belgium, a tertiary eye care center. Information on cassette weight, quantities, and transport volume was obtained from routine procedures and purchasing records. The costs for each machine were calculated by reviewing the invoices received from the accounting department. Results: We found significant differences across comparisons. The reusable cassette machine, when compared to the single-use machine, used 306.7 kg less plastic (75.3% reduction), required 2,494 cubic meters less storage per 1000 surgeries (67.7% decrease), and cost €54.16 less per 10 procedures (16.9% reduction). The machine with daily reusable cassettes also exhibited a 7-minute priming time advantage for 10 procedures, reducing downtime between cases. Conclusions: Our findings underscore the benefits of adopting reusable cassette systems: reduced plastic consumption, storage volume, and priming time, as well as enhanced efficiency and cost savings. Healthcare professionals and institutions are encouraged to embrace environmentally conscious initiatives. The use of reusable cassette systems for cataract surgeries offers a pathway to sustainable practices.

Keywords: cataract, epidemiolog, surgery treatment, lens and zonules, public health

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Authors: Balakrishna Valluru, Ruth Suckling

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A 16 year old male was found collapsed on the road following stab injuries to the chest and abdomen and was transported to the emergency department by ambulance. On arrival in the emergency department the patient was breathless and appeared pale. He was maintaining his airway with spontaneous breathing and had a heart rate of 122 beats per minute with a blood pressure of 83/63 mmHg. He was resuscitated initially with three units of packed red cells. Clinical examination identified three incisional wounds each measuring 2 cm. These were in the left para-sternal region, right infra-scapular region and left upper quadrant of the abdomen. The chest wound over the left parasternal area at the level of 4tth intercostal space was bleeding intermittently on leaning forwards and was relieving his breathlessness intermittently. CT imaging was performed to characterize his injuries and determine his management. CT scan of chest and abdomen showed moderate size haemopericardium with left sided haemopneumothorax. The patient underwent urgent surgical repair of the left ventricle and left anterior descending artery. He recovered without complications and was discharged from the hospital. This case highlights the fact that the potential to develop a life threatening cardiac tamponade was mitigated by the left parasternal stab wound. This injury fortuitously provided a pericardial window through which the bleeding from the injured left ventricle and left anterior descending artery could drain into the left hemithorax providing an opportunity for timely surgical intervention to repair the cardiac injuries.

Keywords: stab, incisional, haemo-pericardium, haemo-pneumothorax

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Authors: Tai Yuan Yu, Pei-Jen Wang

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Oil-free turbomachinery is considered one of the critical technologies for future green power generation systems as rotor machinery systems. Oil-free technology allows clean, compact, and maintenance-free working, and gas foil bearings, abbreviated as GFBs, are important for the technology. Since the first applications in the auxiliary power units and air cycle machines in the 1970s, obvious improvement has been created to the computational models for dynamic rotor behavior. However, many technical issues are still poorly understood or remain unsolved, and some of those are thermal management and the pattern of how pressure will be distributed in bearing clearance. This paper presents a three-dimensional, abbreviated as 3D, fluid-structure interaction model of single pad foil bearings and three pad foil bearings to predict bearing working behavior that researchers could compare characteristics of those. The coupling analysis model involves dynamic working characteristics applied to all the gas film and mechanical structures. Therefore, the elastic deformation of foil structure and the hydrodynamic pressure of gas film can both be calculated by a finite element method program. As a result, the temperature distribution pattern could also be iteratively solved by coupling analysis. In conclusion, the working fluid state in a gas film of various pad forms of bearings working characteristic at constant rotational speed for both can be solved for comparisons with the experimental results.

Keywords: fluid-structure interaction, multi-physics simulations, gas foil bearing, oil-free, transient thermo-hydrodynamic

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Authors: Suleyman Kizil, Tahsin Sogut, Khalid M. Khawar

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Genus Allium includes 600 to 750 species and most of these including Allium tuncelianum (Kollman) N. Ozhatay, B. Mathew & Siraneci; Syn; A. macrochaetum Boiss. and Hausskn. subsp. tuncelianum Kollman] or Tunceli garlic is endemic to Eastern Turkish Province of Tunceli and Munzur mountains. They are edible, bear attractive white-to-purple flowers and fertile black seeds with deep seed dormancy. This study aimed to break seed dormancy of Tunceli garlic and determine the conditions for induction of bulblets on these seeds and increase their diameter by culturing them on MS medium supplemented different strengths of KNO3. Tunceli garlic seeds were collected from field grown plants. They were germinated on MS medium with or without 20 g/l sucrose followed by their culture on 1 × 1900 mg/l, 2 × 1900 mg/l, 4 ×1900 mg/l and 6 × 1900 mg/l mg/l KNO3 supplemented with 20 g/l sucrose to increase bulb diameter. Improved seeds germination was noted on MS medium with and without sucrose but with variation compared to previous reports. The bulb development percentage on each of the sprouted seeds was not parallel to the percentage of seed germination. The results showed 34% and 28.5% bulb induction was noted on germinated seeds after 150 and 158 days on MS medium containing 20 g l-1 sucrose and no sucrose respectively showing a delay of 8 days on the latter compared to the former. The results emphatically noted role of cold stratification on agar solidified MS medium supplemented with sucrose to improve seed germination. The best increase in bulb diameter was noted on MS medium containing 1 × 1900 mg/l KNO3 after 178 days with bulblet diameter and bulblet weight of 0.54 cm and 0.048 g, respectively. Consequently, the bulbs induced on sucrose containing MS medium could be transferred to pots earlier. Increased (>1 × 1900 mg/l KNO3) strengths of KNO3 induced negative effect on growth and development of Tunceli garlic bulbs. The strategy of seed germination and bulblet induction reported in this study could be positively used for conservation of this endemic plant species.

Keywords: Tunceli garlic, seed, dormancy, bulblets, bulb growth

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Authors: Karina Zaccari, Ernesto Cordeiro Marujo

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This paper presents a Machine Learning (ML) approach to support Meningitis diagnosis in patients at a children’s hospital in Sao Paulo, Brazil. The aim is to use ML techniques to reduce the use of invasive procedures, such as cerebrospinal fluid (CSF) collection, as much as possible. In this study, we focus on predicting the probability of Meningitis given the results of a blood and urine laboratory tests, together with the analysis of pain or other complaints from the patient. We tested a number of different ML algorithms, including: Adaptative Boosting (AdaBoost), Decision Tree, Gradient Boosting, K-Nearest Neighbors (KNN), Logistic Regression, Random Forest and Support Vector Machines (SVM). Decision Tree algorithm performed best, with 94.56% and 96.18% accuracy for training and testing data, respectively. These results represent a significant aid to doctors in diagnosing Meningitis as early as possible and in preventing expensive and painful procedures on some children.

Keywords: machine learning, medical diagnosis, meningitis detection, pediatric research

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Authors: Andrey Yatsun, Andrei Malchikov

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Exoskeletons are used to support and compensate for the load on the human musculoskeletal system. Elastomers are an important component of exoskeletons, providing additional support and compensating for the load. The algorithm of the active elastomer tension system provides the required auxiliary force depending on the angle of rotation and the tilt speed of the operator's torso. Feedback for the drive is provided by a force sensor integrated into the attachment of the exoskeleton vest. The use of direct force measurement ensures the required accuracy in all settings of the man-machine system. Non-adjustable elastic elements make it difficult to move without load, tilt forward and walk. A strategy for the organization of the auxiliary forces management system is proposed based on the allocation of 4 operating modes of the human-machine system.

Keywords: soft exoskeleton, mathematical modeling, pre-tension elastomer, human-machine interaction

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Authors: Oscar E. Cariceo, Claudia V. Casal

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Machine learning offers a set of techniques to promote social work interventions and can lead to support decisions of practitioners in order to predict new behaviors based on data produced by the organizations, services agencies, users, clients or individuals. Machine learning techniques include a set of generalizable algorithms that are data-driven, which means that rules and solutions are derived by examining data, based on the patterns that are present within any data set. In other words, the goal of machine learning is teaching computers through 'examples', by training data to test specifics hypothesis and predict what would be a certain outcome, based on a current scenario and improve that experience. Machine learning can be classified into two general categories depending on the nature of the problem that this technique needs to tackle. First, supervised learning involves a dataset that is already known in terms of their output. Supervising learning problems are categorized, into regression problems, which involve a prediction from quantitative variables, using a continuous function; and classification problems, which seek predict results from discrete qualitative variables. For social work research, machine learning generates predictions as a key element to improving social interventions on complex social issues by providing better inference from data and establishing more precise estimated effects, for example in services that seek to improve their outcomes. This paper exposes the results of a classification algorithm to predict cyberbullying among adolescents. Data were retrieved from the National Polyvictimization Survey conducted by the government of Chile in 2017. A logistic regression model was created to predict if an adolescent would experience cyberbullying based on the interaction and behavior of gender, age, grade, type of school, and self-esteem sentiments. The model can predict with an accuracy of 59.8% if an adolescent will suffer cyberbullying. These results can help to promote programs to avoid cyberbullying at schools and improve evidence based practice.

Keywords: cyberbullying, evidence based practice, machine learning, social work research

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Authors: Marcel Verwey, Anna M. Joubert, Elsie M. Nolte, Wolfgang Dohle, Barry V. L. Potter, Anne E. Theron

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A tetrahydroisoquinolinone (THIQ) core can be used to mimic the A,B-ring of colchicine site-binding microtubule disruptors such as 2-methoxyestradiol in the design of anti-cancer agents. Steroidomimeric microtubule disruptors were synthesized by introducing C'2 and C'3 of the steroidal A-ring to C'6 and C'7 of the THIQ core and by introducing a decorated hydrogen bond acceptor motif projecting from the steroidal D-ring to N'2. For this in vitro study, four non-steroidal THIQ-based analogues were investigated and comparative studies were done between the non-sulphamoylated compound STX 3450 and the sulphamoylated compounds STX 2895, STX 3329 and STX 3451. The objective of this study was to investigate the modes of cell death induced by these four THIQ-based analogues in A549 lung carcinoma epithelial cells and metastatic breast adenocarcinoma MDA-MB-231 cells. Cytotoxicity studies to determine the half maximal growth inhibitory concentrations were done using spectrophotometric quantification via crystal violet staining and lactate dehydrogenase (LDH) assays. Microtubule integrity and morphologic changes of exposed cells were investigated using polarization-optical transmitted light differential interference contrast microscopy, transmission electron microscopy and confocal microscopy. Flow cytometric quantification was used to determine apoptosis induction and the effect that THIQ-based analogues have on cell cycle progression. Signal transduction pathways were elucidated by quantification of the mitochondrial membrane integrity, cytochrome c release and caspase 3, -6 and -8 activation. Induction of autophagic cell death by the THIQ-based analogues was investigated by morphological assessment of fluorescent monodansylcadaverine (MDC) staining of acidic vacuoles and by quantifying aggresome formation via flow cytometry. Results revealed that these non-steroidal microtubule disrupting analogues inhibited 50% of cell growth at nanomolar concentrations. Immunofluorescence microscopy indicated microtubule depolarization and the resultant mitotic arrest was further confirmed through cell cycle analysis. Apoptosis induction via the intrinsic pathway was observed due to depolarization of the mitochondrial membrane, induction of cytochrome c release as well as, caspase 3 activation. Potential involvement of programmed cell death type II was observed due to the presence of acidic vacuoles and aggresome formation. Necrotic cell death did not contribute significantly, indicated by stable LDH levels. This in vitro study revealed the induction of the intrinsic apoptotic pathway as well as possible involvement of autophagy after exposure to these THIQ-based analogues in both MDA-MB-231- and A549 cells. Further investigation of this series of anticancer drugs still needs to be conducted to elucidate the temporal, mechanistic and functional crosstalk mechanisms between the two observed programmed cell deaths pathways.

Keywords: apoptosis, autophagy, cancer, microtubule disruptor

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Authors: Kang Zijian, Zhang Tingyu, Burra Venkata Durga Kumar

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This article investigates the challenges in memory migration during the live migration of virtual machines. We found three challenges probably existing in pre-copy technology. One of the main challenges is the challenge of downtime migration. Decrease the downtime could promise the normal work for a virtual machine. Although pre-copy technology is greatly decreasing the downtime, we still need to shut down the machine in order to finish the last round of data transfer. This paper provides an optimization scheme for the problems existing in pro-copy technology, mainly the optimization of the dirty page migration mechanism. The typical pre-copy technology copy n-1th’s dirty pages in nth turn. However, our idea is to create a double iteration method to solve this problem.

Keywords: virtual machine, pre-copy technology, memory migration process, downtime, dirty pages migration method

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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: P. Halder, A. Zaman

Abstract:

It is estimated that heart disease accounts for one in ten deaths worldwide. United States deaths due to heart disease are among the leading causes of death according to the World Health Organization. Cardiovascular diseases (CVDs) account for one in four U.S. deaths, according to the Centers for Disease Control and Prevention (CDC). According to statistics, women are more likely than men to die from heart disease as a result of strokes. A 50% increase in men's mortality was reported by the World Health Organization in 2009. The consequences of cardiovascular disease are severe. The causes of heart disease include diabetes, high blood pressure, high cholesterol, abnormal pulse rates, etc. Machine learning (ML) can be used to make predictions and decisions in the healthcare industry. Thus, scientists have turned to modern technologies like Machine Learning and Data Mining to predict diseases. The disease prediction is based on four algorithms. Compared to other boosts, the Ada boost is much more accurate.

Keywords: heart disease, cardiovascular disease, coronary artery disease, feature selection, random forest, AdaBoost, SVM, decision tree

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Authors: Rabeb Triki, Hassene Djemel, Mounir Baccar

Abstract:

Surface scraping is a passive heat transfer enhancement technique that is directly used in scraped surface heat exchanger (SSHE). The scraping action prevents the accumulation of the product on the inner wall, which intensifies the heat transfer and avoids the formation of dead zones. SSHEs are widely used in industry for several applications such as crystallization, sterilization, freezing, gelatinization, and many other continuous processes. They are designed to deal with products that are viscous, sticky or that contain particulate matter. This research work presents a three-dimensional numerical simulation of the coupled thermal and hydrodynamic behavior within a SSHE which includes Archimedes’ screw instead of scraper blades. The finite volume Fluent 15.0 was used to solve continuity, momentum and energy equations using multiple reference frame formulation. The process fluid investigated under this study is the pure glycerin. Different geometrical parameters were studied in the case of steady, non-isothermal, laminar flow. In particular, attention is focused on the effect of the conicity of the rotor and the pitch of Archimedes’ screw on temperature and velocity distribution and heat transfer rate. Numerical investigations show that the increase of the number of turns in the screw from five to seven turns leads to amelioration of heat transfer coefficient, and the increase of the conicity of the rotor from 0.1 to 0.15 leads to an increase in the rate of heat transfer. Further studies should investigate the effect of different operating parameters (axial and rotational Reynolds number) on the hydrodynamic and thermal behavior of the SSHE.

Keywords: ANSYS-Fluent, hydrodynamic behavior, scraped surface heat exchange, thermal behavior

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