Search results for: wound rotor induction machine

Authors: Sahriye Sonmez, Salih Ulger, Mustafa Kaplan, Mustafa Karhan

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The objective of this study was to investigate the effects of external ALAR application on nutrients contents in leaf and node in ‘on (bearing)’ and ‘off (non-bearing)’ years in Memecik olive trees. For this purpose; 2000 mg L-1 ALAR was externally applied to Memecik olive trees, and leaf and node samples from olive trees were taken during the induction, initiation and differentiation periods in ‘on’ and ‘off’ years. Nutrients contents (N, P, K, Ca, Mg, Fe, Mn, Zn and Cu) in leaf and node samples were determined. The K, Ca, Mg, Fe, Mn, Zn and Cu contents were determined by atomic absorption spectrophotometry, Nitrogen by Kjeldahl procedure, and P by a spectrophotometric method. The results showed that the N, Ca, Mg, Fe, Mn, Zn and Cu contents in ‘on’ year were higher than ‘off’ year while the K contents in ‘on’ year were lower than ‘off ‘ year, but the P content was not different. The N, Ca, Mg, Fe and Mn contents in leaf samples were higher in the node samples except for K while the P, Zn and Cu contents were not different. The N, K, Ca, Fe, Mn, Zn and Cu contents were lowest during the initiation period while the P content was highest in this period. The Mg content was not different in all period.

Keywords: bearing, differentiation period, induction period, initiation period, non bearing, olive

Procedia PDF Downloads 448

Authors: Hong Li, Tingxian Li, Xudong Wang, Fengliang Zhao

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Unreliable flowering of chilling-required longan (Dimocarpus longan) due to increased air-temperatures have been the common concerns in the tropical areas. Our objectives were to assess the efficiency of chemicals in longan tree flowering and bearing using Growing Degree Days (GDD). The 2-year study was contacted in the tropical Haihan Island during 2012-2013. At pruning (August) the GDD values were started to count. The KClO3 treatments were applied to the root zones under the canopies at GDD 1300ºC while KH2PO4 rates were applied to the leaves at fruit setting at GDD 3000ºC and GDD 4000ºC. The results showed that total cumulative GDD was 6050ºC for longan. The GDD-guided KClO3 applications induced significant tree budding and flowering. The GDD-guided KH2PO4 applications stimulated higher leaf photosynthesis, carbonxylation efficiency, marketable fruit yield and quality (K+ and sugar) (P<0.05). It was concluded that the GDD-based model could efficiently support longan reliable flowering and bearing.

Keywords: canopy nutrition, flowering induction, growing degree days, longan, oxidant KClO3, tree physiology

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Authors: Hatim Laalej, Jon Stammers

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In machining, monitoring of tool wear is essential for achieving the desired dimensional accuracy and surface finish of a machined workpiece. Currently, the task of monitoring the wear on the cutting tool is carried out by the operator who performs manual inspections of the cutting tool, causing undesirable stoppages of machine tools and consequently resulting in costs incurred from loss of productivity. The cutting tool consumable costs may also be higher than necessary when tools are changed before the end of their useful life. Furthermore, damage can be caused to the workpiece when tools are not changed soon enough leading to a significant increase in the costs of manufacturing. The present study is concerned with the development of break sensor printed on the flank surface of poly-crystalline diamond (PCD) cutting to perform on-line condition monitoring of the cutting tool used to machine Titanium Ti-6al-4v bar. The results clearly show that there is a strong correlation between the break sensor measurements and the amount of wear in the cutting tool. These findings are significant in that they help the user/operator of the machine tool to determine the condition of the cutting tool without the need of performing manual inspection, thereby reducing the manufacturing costs such as the machine down time.

Keywords: machining, manufacturing, tool wear, signal processing

Procedia PDF Downloads 237

Authors: M. S. Nikitenko, S. A. Kizilov, D. Y. Khudonogov

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The paper considers an approach to a machine vision operating system combined with using a grid of light markers. This approach is used to solve several scientific and technical problems, such as measuring the capability of an apron feeder delivering coal from a lining return port to a conveyor in the technology of mining high coal releasing to a conveyor and prototyping an autonomous vehicle obstacle detection system. Primary verification of a method of calculating bulk material volume using three-dimensional modeling and validation in laboratory conditions with relative errors calculation were carried out. A method of calculating the capability of an apron feeder based on a machine vision system and a simplifying technology of a three-dimensional modelled examined measuring area with machine vision was offered. The proposed method allows measuring the volume of rock mass moved by an apron feeder using machine vision. This approach solves the volume control issue of coal produced by a feeder while working off high coal by lava complexes with release to a conveyor with accuracy applied for practical application. The developed mathematical apparatus for measuring feeder productivity in kg/s uses only basic mathematical functions such as addition, subtraction, multiplication, and division. Thus, this fact simplifies software development, and this fact expands the variety of microcontrollers and microcomputers suitable for performing tasks of calculating feeder capability. A feature of an obstacle detection issue is to correct distortions of the laser grid, which simplifies their detection. The paper presents algorithms for video camera image processing and autonomous vehicle model control based on obstacle detection machine vision systems. A sample fragment of obstacle detection at the moment of distortion with the laser grid is demonstrated.

Keywords: machine vision, machine vision operating system, light markers, measuring capability, obstacle detection system, autonomous transport

Procedia PDF Downloads 107

Authors: Sangeeta Palekar, Neeraj Rangwani, Akash Poddar, Jayu Kalambe

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The bio-medical analysis is an indispensable procedure for identifying health-related diseases like diabetes. Monitoring the glucose level in our body regularly helps us identify hyperglycemia and hypoglycemia, which can cause severe medical problems like nerve damage or kidney diseases. This paper presents a method for predicting the glucose concentration in blood samples using image processing and machine learning algorithms. The glucose solution is prepared by the glucose oxidase (GOD) and peroxidase (POD) method. An experimental database is generated based on the colorimetric technique. The image of the glucose solution is captured by the raspberry pi camera and analyzed using image processing by extracting the RGB, HSV, LUX color space values. Regression algorithms like multiple linear regression, decision tree, RandomForest, and XGBoost were used to predict the unknown glucose concentration. The multiple linear regression algorithm predicts the results with 97% accuracy. The image processing and machine learning-based approach reduce the hardware complexities of existing platforms.

Keywords: artificial intelligence glucose detection, glucose oxidase, peroxidase, image processing, machine learning

Procedia PDF Downloads 198

Authors: Asifa Amara, Prachi Singh, Kanishka, Debargho Pathak, Akshat Kumar, Jayakumar Eravelly

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Today's generation is totally dependent on technology that uses data as its fuel. The present study is all about innovations and developments in data science and gives an idea about how efficiently to use the data provided. This study will help to understand the core concepts of data science. The concept of artificial intelligence was introduced by Alan Turing in which the main principle was to create an artificial system that can run independently of human-given programs and can function with the help of analyzing data to understand the requirements of the users. Data science comprises business understanding, analyzing data, ethical concerns, understanding programming languages, various fields and sources of data, skills, etc. The usage of data science has evolved over the years. In this review article, we have covered a part of data science, i.e., machine learning. Machine learning uses data science for its work. Machines learn through their experience, which helps them to do any work more efficiently. This article includes a comparative study image between human understanding and machine understanding, advantages, applications, and real-time examples of machine learning. Data science is an important game changer in the life of human beings. Since the advent of data science, we have found its benefits and how it leads to a better understanding of people, and how it cherishes individual needs. It has improved business strategies, services provided by them, forecasting, the ability to attend sustainable developments, etc. This study also focuses on a better understanding of data science which will help us to create a better world.

Keywords: data science, machine learning, data analytics, artificial intelligence

Procedia PDF Downloads 78

Authors: Raghuram Kandimalla, Sanjeeb Kalita, Bhaswati Choudhury, Jibon Kotoky

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The quest for developing an ideal suture material prompted our interest to develop a novel suture with advantageous characteristics to market available ones. We developed novel suture biomaterial from muga silk (Antheraea assama) and ramie (Boehmeria nivea) plant fiber. Field emission scanning electron microscopy (FE-SEM), energy-dispersive X-ray spectroscopy (EDX), attenuated total reflection fourier transform infrared spectroscopy (ATR-FTIR) and thermo gravimetric analysis (TGA) results revealed the physicochemical properties of the fibers which supports the suitability of fibers for suture fabrication. Tensile properties of the prepared sutures were comparable with market available sutures and it found to be biocompatible towards human erythrocytes and nontoxic to mammalian cells. The prepared sutures completely healed the superficial deep wound incisions within seven days in adult male wister rats leaving no rash and scar. Histopathology studies supports the wound healing ability of sutures, as rapid synthesis of collagen, connective tissue and other skin adnexal structures were observed within seven days of surgery. Further muga suture surface modified by exposing the suture to oxygen plasma which resulted in formation of nanotopography on suture surface. Broad spectrum antibiotic amoxicillin was functionalized on the suture surface to prepare an advanced antimicrobial muga suture. Surface hydrophilicity induced by oxygen plasma results in an increase in drug-impregnation efficiency of modified muga suture by 16.7%. In vitro drug release profiles showed continuous and prolonged release of amoxicillin from suture up to 336 hours. The advanced muga suture proves to be effective against growth inhibition of Staphylococcus aureus and Escherichia coli, whereas normal muga suture offers no antibacterial activity against both types of bacteria. In vivo histopathology studies and colony-forming unit count data revealed accelerated wound healing activity of advanced suture over normal one through rapid synthesis and proliferation of collagen, hair follicle and connective tissues.

Keywords: sutures, biomaterials, silk, Ramie

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Authors: Rim Messaoudi, Nogaye-Gueye Gning, François Azelart

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Automatic text classification applies mostly natural language processing (NLP) and other AI-guided techniques to automatically classify text in a faster and more accurate manner. This paper discusses the subject of using predictive maintenance to manage incident tickets inside the sociality. It focuses on proposing a tool that treats and analyses comments and notes written by administrators after resolving an incident ticket. The goal here is to increase the quality of these comments. Additionally, this tool is based on NLP and machine learning techniques to realize the textual analytics of the extracted data. This approach was tested using real data taken from the French National Railways (SNCF) company and was given a high-quality result.

Keywords: machine learning, text classification, NLP techniques, semantic representation

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Authors: Yi-Min Lan, Hung-Wen Cheng, Hsuan-Ling Chang, Jou-Ping Yu

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The study applies machine learning models to construct momentum strategies and utilizes the information coefficient as an indicator for selecting stocks with strong and weak momentum characteristics. Through this approach, the study has built investment portfolios capable of generating superior returns and conducted a thorough analysis. Compared to existing research on momentum strategies, machine learning is incorporated to capture non-linear interactions. This approach enhances the conventional stock selection process, which is often impeded by difficulties associated with timeliness, accuracy, and efficiency due to market risk factors. The study finds that implementing bidirectional momentum strategies outperforms unidirectional ones, and momentum factors with longer observation periods exhibit stronger correlations with returns. Optimizing the number of stocks in the portfolio while staying within a certain threshold leads to the highest level of excess returns. The study presents a novel framework for momentum strategies that enhances and improves the operational aspects of asset management. By introducing innovative financial technology applications to traditional investment strategies, this paper can demonstrate significant effectiveness.

Keywords: information coefficient, machine learning, momentum, portfolio, return prediction

Procedia PDF Downloads 51

Authors: Kairat Uteulin, Azhar Iskakova, Serik Mukhambetzhanov, Bayan Yesbolayeva, Gabit Bari, Aslan Zheksenbai, Kabyl Zhambakin, Chingis Dzhabykbayev, Vladimir Piven, Izbasar Rakhimbaiev

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To explore the potential for in vitro rapid regeneration of Russian dandelion (Taraxacum kok-saghyz Rodin), different concentrations of 6-Benzylaminopurine (BAP), 2,4-Dichlorophenoxyacetic acid (2.4-D) and BAP combined with Indole-3-acetic acid (IAA) were evaluated for their effects on the induction of somatic embryos from leaf, seed stem and root explants. Different explants were cultured on MS medium supplemented with various concentrations (0, 0.5, 1, 1.5, 2, 2.5 and 3 mg/l) of each kind of hormone. Callus induction percentage, fresh weight, color and texture of the callus were assessed after 14 and 28 days of culture. The optimum medium for the proliferation of embryogenic calli from leaf and root explants was MS supplemented with 2.5 mg/L BAP and 0.5 mg/L 2.4-D. Concentrations of 2.5 mg/L BAP and 1.5 mg/L IAA also had a remarkable effect on root and stem explants. The best concentration to produce callus from stem explants was 0.5 mg/L BAP and 1 mg/L IAA. Results of mean comparison showed that BAP and 2.4-D were more effective on different explants than BAP and IAA. Results of the double staining method proved that somatic embryogenesis occurred in the most concentrations of BAP and 2.4-D. Under microscopic observations, the different developmental stages of the embryos (globular, heart, torpedo and cotyledonary) were revealed together in callus cells, indicating that the most tested hormone combinations were effective for somatic embryogenesis formation in this species. Seed explants formed torpedo and cotyledonary stages faster than leaf and root explants in the most combinations. Most calli from seed explants were cream colored and friable, while calli were compact and light green from leaf and root explants. Some combinations gave direct regeneration and (3 mg/L BAP and 2 mg/L IAA) in seed explants and (0.5 mg/L BAP and 2.5 mg/L IAA) in leaf explants had the highest number of shoots with average of 21 and 27 shoots per callus. The developed protocol established the production of different callus types from seed, leaf, and root explants and plant regeneration through somatic embryogenesis.

Keywords: taraxacum kok-saghyz Rodin, callus, somatic embryogenesis

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Authors: Nishanth Venugopal Menon, Chuah Yon Jin, Samantha Phey, Wu Yingnan, Zhang Ying, Vincent Chan, Kang Yuejun

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Cell Migration is a vital phenomenon that the cells undergo in various physiological processes like wound healing, disease progression, embryogenesis, etc. Cell migration depends primarily on the chemical and physical cues available in the cellular environment. The chemical cue involves the chemokines secreted and gradients generated in the environment while physical cues indicate the impact of matrix properties like nanotopography and stiffness on the cells. Mesenchymal Stem Cells (MSCs) have been shown to have a role wound healing in vivo and its migration to the site of the wound has been shown to have a therapeutic effect. In the field of stem cell based tissue regeneration of bones and cartilage, one approach has been to introduce scaffold laden with MSCs into the site of injury to enable tissue regeneration. In this work, we have studied the combinatorial impact of the substrate physical properties on MSC migration. A microfluidic in vitro model was created to perform the migration studies. The microfluidic model used is a three compartment device consisting of two cell seeding compartments and one migration compartment. Four different PDMS substrates with varying substrate roughness, stiffness and hydrophobicity were created. Its surface roughness and stiffness was measured using Atomic Force Microscopy (AFM) while its hydrphobicity was measured from the water contact angle using an optical tensiometer. These PDMS substrates are sealed to the microfluidic chip following which the MSCs are seeded and the cell migration is studied over the period of a week. Cell migration was quantified using fluorescence imaging of the cytoskeleton (F-actin) to find out the area covered by the cells inside the migration compartment. The impact of adhesion proteins on cell migration was also quantified using a real-time polymerase chain reaction (qRT PCR). These results suggested that the optimal substrate for cell migration would be one with an intermediate level of roughness, stiffness and hydrophobicity. A higher or lower value of these properties affected cell migration negatively. These observations have helped us in understanding that different substrate properties need to be considered in tandem, especially while designing scaffolds for tissue regeneration as cell migration is normally impacted by the combinatorial impact of the matrix. These observations may lead us to scaffold optimization in future tissue regeneration applications.

Keywords: cell migration, microfluidics, in vitro model, stem cell migration, scaffold, substrate properties

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Authors: Y. Kim, H. Lee, M. Park, B. Lee

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Planning is understood as the determination of what has to be performed, how, in which sequence, when, what resources are needed, and their cost within the organization before execution. In most construction project, it is evident that the inherent nature of planning is dynamic, and initial planning is subject to be changed due to various uncertain conditions of construction project. Planners take a continuous revision process during the course of a project and until the very end of project. However, current practice lacks reliable, systematic tool for setting variance thresholds to determine when and what corrective actions to be taken. Rather it is heavily dependent on the level of experience and knowledge of the planner. Thus, this paper introduces a machine learning approach to evaluate project control threshold reliability incorporating project-specific data and presents a method to automate the process. The results have shown that the model improves the efficiency and accuracy of the monitoring process as an early warning.

Keywords: machine learning, project control, project progress monitoring, schedule

Procedia PDF Downloads 239

Authors: Tuji Mohammed Sani

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Back ground: An open tibial fracture is an injury where the fractured bone directly communicates with the outside environment. Due to the specific anatomical features of the tibia (limited soft tissue coverage), more than quarter of its fractures are classified as open, representing the most common open long-bone injuries. Open tibial fractures frequently cause significant bone comminution, periosteal stripping, soft tissue loss, contamination and are prone to bacterial entry with biofilm formation, which increases the risk of deep bone infection. Objective: The main objective of the study was to determine Prevalence of infection and its associated factors in surgically treated open tibial fracture in Addis Ababa Burn Emergency and Trauma (AaBET) center. Method: A facility based retrospective cross-sectional study was conducted among patient treated for open tibial fracture at AaBET center from September 2018 to September 2021. The data was collected from patient’s chart using structured data collection form, and Data was entered and analyzed using SPSS version 26. Bivariable and multiple binary logistic regression were fitted. Multicollinearity was checked among candidate variables using variance inflation factor and tolerance, which were less than 5 and greater than 0.2, respectively. Model adequacy were tested using Hosmer-Lemeshow goodness of fitness test (P=0.711). AOR at 95% CI was reported, and P-value < 0.05 was considered statistically significant. Result: This study found that 33.9% of the study participants had an infection. Initial IV antibiotic time (AOR=2.924, 95% CI:1.160- 7.370) and time of wound closure from injury (AOR=3.524, 95% CI: 1.798-6.908), injury to admission time (AOR=2.895, 95% CI: 1.402 – 5.977). and definitive fixation method (AOR=0.244, 95% CI: 0.113 – 0.4508) were the factors found to have a statistically significant association with the occurrence of infection. Conclusion: The rate of infection in open tibial fractures indicates that there is a need to improve the management of open tibial fracture treated at AaBET center. Time from injury to admission, time from injury to first debridement, wound closure time, and initial Intra Venous antibiotic time from the injury are an important factor that can be readily amended to improve the infection rate. Whether wound closed before seven days or not were more important factor associated with occurrences of infection.

Keywords: infection, open tibia, fracture, magnitude

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Authors: Hakan Duger, Alparslan Ersoy, Canan Ersoy

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The improvement of surgical techniques in recent years has reduced the frequency of postoperative complications in kidney transplant recipients. Novel immunosuppressive agents have reduced rates of graft loss due to acute rejection to less than 1%. However, surgical complications may still lead graft loss and morbidity in recipients. Because of potent immunosuppression, impaired wound healing and complications are frequent after transplantation. We compared the frequency of post-operative surgical complications in diabetic and non-diabetic patients after kidney transplantation. Materials and Methods: This retrospective study conducted in consecutive patients (213 females, 285 males, median age 39 years) who underwent kidney transplant surgery at our center between December 2005 and October 2015. The patients were divided into two groups: diabetics (46 ± 10 year, 26 males, 16 females) and non-diabetics (39 ± 12 year, 259 males, 197 females). Characteristics of both groups were obtained from medical records. Results: We performed 225 living and 273 deceased donor transplantations. Renal replacement type was hemodialysis in 60.8%, peritoneal dialysis in 17.3% and preemptive in 12%. The mean body mass indexes of the recipients were 24 ± 4.6 kg/m², donor age was 48.6 ± 14.3 years, cold ischemic time was 11.3 ± 6.1 hours, surgery time was 4.9 ± 1.2 hours, and recovery time was 54±31 min. The mean hospitalization duration was 19.1 ± 13.5 days. The frequency of postoperative surgical complications was 43.8%. There was no significant difference between the ratios of post-operative surgical complications in non-diabetic (43.5%) and diabetic (47.4%) groups (p=0.648). Post-operative surgical complications were lymphocele (24.6% vs. 23.7%), delayed wound healing (13.2% vs. 7.6%), hematoma (7.8% vs.15.8 %), urinary leak (4.6% vs. 5.3%), hemorrhage (5.1% vs. 0%), hydronephrosis (2.2% vs. 0%), renal artery thrombosis (1.5% vs. 0%), renal vein thrombosis (1% vs. 2.6%), urinoma (0.7% vs. 0%), urinary obstruction (0.5% vs. 0%), ureteral stenosis (0.5% vs. 0%) and ureteral reflux (0.2% vs. 0%) in non-diabetic and diabetic groups, respectively (p > 0.05). Mean serum creatinine levels in non-diabetics and diabetics were 1.43 ± 0.81 and 1.61 ± 0.96 mg/dL at 1st month (p=0.198). At the 6th month, the mean graft and patient survival times in patients with post-operative surgical complications were significantly lower than in those who did not (162.9 ± 3.4 vs. 175.6 ± 1.5 days, p=0.008, and 171 ± 2.9 vs. 176.1 ± 1.6 days, p=0.047, respectively). However, patient survival durations of non-diabetic (173 ± 27) and diabetic (177 ± 13 day) groups were comparable (p=0.396). Conclusion: As a result, we concluded that surgical complications such as lymphocele and delayed wound healing were common and that frequency of these complications in diabetic recipients did not differ from non-diabetic one. All persons involved in the postoperative care of kidney transplant recipients be aware of the potential surgical complications for rapid diagnosis and treatment.

Keywords: kidney transplantation, diabetes mellitus, surgery, complication

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Authors: Dahna Alkahtani, Faryal Suraya, Fadah Alanazi

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Background: Buccal mucosal graft for urethral augmentation has surpassed other grafting options, and is now considered the standard of choice for substitution Urethroplasty. The graft has gained its popularity due to its excellent short and long-term results, easy harvesting as well as its ability in withstanding wet environments. However, although Buccal mucosal grafts are an excellent option, it is not free of complications, potential intraoral complications are bleeding, pain, swelling, injury to the nerve resulting in numbness, lip deviation or retraction. Objectives: The current study aims to evaluate the intraoral complications of buccal mucosa grafts harvested from one cheek, and used in Augmentation Urethroplasty. Methodology: The study was conducted retrospectively using the medical records of patients who underwent open augmentation urethroplasty with a buccal mucosa graft at King Khalid University Hospital, Saudi Arabia. Data collection of demographics included the type of graft used, presence or absence of strictures and its etiological factors. Pre-operative and post-operative evaluations were carried out on the subjects including the medical history, physical examination, uroflowmetry, retrograde urethrography, voiding cystourethrography and urine cultures were also noted. Further, the quality of life and complications of the procedure including the presence or occurrence of bleeding within 3-days post-procedure, the severity of pain, oral swelling after grafting, length of return to normal daily diet, painful surgical site, intake of painkillers, presence or absence of speech disturbance, numbness in the cheeks and lips were documented. Results: Thirty-two male subjects with ages ranging from 15 years to 72 years were included in the current study. Following the procedure, a hundred percent of the subjects returned to their normal daily diet by the sixth postoperative day. Further, the majority of the patients reported experiencing mild pain accounting for 61.3%, and 90.3% of the subjects reported using painkillers to control the pain. Surgical wound Pain was reportedly more common at the perineal site as 48.4% of the subjects experienced it; on the other hand, 41.9% of the patients experienced pain in the oral mucosa. The presence of speech disorders, as assessed through medical history, was found to be present in 3.2% of patients. The presence of numbness in the cheeks and lips was found in 3.2% of patients. Other complications such as parotid duct injury, delayed wound healing, non-healing wound and suture granuloma were rare as 90.3% of the subjects denied experiencing any of them, there were nonetheless reports of parotid duct injury by 6.5% of the patients, and non-healing wound by the 3.2% of patients. Conclusion: Buccal Mucosa Graft in Augmentation Urethroplasty is an ideal source of allograft, although not entirely painless; it is considerably safe with minimal intra-oral complication and undetectable strain on the patients’ quality of life.

Keywords: augmentation, buccal, graft, oral

Procedia PDF Downloads 172

Authors: Shuai Zhao, Shalendra D. Sharma, Jin Xu

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This research uses advanced machine learning models to learn a number of hypotheses regarding political executives. Specifically, it analyses the impact these powerful leaders have on economic growth by using leaders’ data from the Archigos database from 1835 to the end of 2015. The data is processed by the AutoGluon, which was developed by Amazon. Automated Machine Learning (AutoML) and AutoGluon can automatically extract features from the data and then use multiple classifiers to train the data. Use a linear regression model and classification model to establish the relationship between leaders and economic growth (GDP per capita growth), and to clarify the relationship between their characteristics and economic growth from a machine learning perspective. Our work may show as a model or signal for collaboration between the fields of statistics and artificial intelligence (AI) that can light up the way for political researchers and economists.

Keywords: comparative politics, political executives, leaders’ characteristics, artificial intelligence

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Authors: Anna Costanza Russo, Daniele Landi, Michele Germani

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Nowadays, the European Ecodesign Directive has emerged as a new approach to integrate environmental concerns into the product design and related processes. Ecodesign aims to minimize environmental impacts throughout the product life cycle, without compromising performances and costs. In addition, the recent Ecodesign Directives require products which are increasingly eco-friendly and eco-efficient, preserving high-performances. It is very important for producers measuring performances, for electric cooking ranges, hobs, ovens, and grills for household use, and a low power consumption of appliances represents a powerful selling point, also in terms of ecodesign requirements. The Ecodesign Directive provides a clear framework about the sustainable design of products and it has been extended in 2009 to all energy-related products, or products with an impact on energy consumption during the use. The European Regulation establishes measures of ecodesign of ovens, hobs, and kitchen hoods, and domestic use and energy efficiency of a product has a significant environmental aspect in the use phase which is the most impactful in the life cycle. It is important that the product parameters and performances are not affected by ecodesign requirements from a user’s point of view, and the benefits of reducing energy consumption in the use phase should offset the possible environmental impact in the production stage. Accurate measurements of cooking appliance performance are essential to help the industry to produce more energy efficient appliances. The development of ecodriven products requires ecoinnovation and ecodesign tools to support the sustainability improvement. The ecodesign tools should be practical and focused on specific ecoobjectives in order to be largely diffused. The main scope of this paper is the development, implementation, and testing of an innovative tool, which could be an improvement for the sustainable design of induction hobs. In particular, a prototypical software tool is developed in order to simulate the energy performances of the induction hobs. The tool is focused on a multiphysics model which is able to simulate the energy performances and the efficiency of induction hobs starting from the design data. The multiphysics model is composed by an electromagnetic simulation and a thermal simulation. The electromagnetic simulation is able to calculate the eddy current induced in the pot, which leads to the Joule heating of material. The thermal simulation is able to measure the energy consumption during the operational phase. The Joule heating caused from the eddy currents is the output of electromagnetic simulation and the input of thermal ones. The aims of the paper are the development of integrated tools and methodologies of virtual prototyping in the context of the ecodesign. This tool could be a revolutionary instrument in the field of industrial engineering and it gives consideration to the environmental aspects of product design and focus on the ecodesign of energy-related products, in order to achieve a reduced environmental impact.

Keywords: ecodesign, energy efficiency, induction hobs, virtual prototyping

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Authors: Rosna Mat Taha, Sakinah Abdullah, Sadegh Mohajer, Asmah Awal

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Lycium barbarum L. (Goji) belongs to Solanaceae family and native to some areas of China. Ethnobotanical studies have shown that this plant has been consumed by the Chinese since ancient times. It has been used as medicine in providing excellent effects on cardiovascular system and cholesterol level, besides contains high antioxidant and antidiabetic properties. In the present study, some tissue culture work has been carried out to induce callus, in vitro regeneration from various explants of Goji and also some acclimatization protocols were followed to transfer the regenerated plants to soil. The main aims being to establish high efficient regeneration system for mass production and commercialization for future uses, since the growth of this species is very limited in Malaysia. The optimum hormonal regime and the most suitable and responsive explants were identified. It was found that leaves and stems gave good responses. Murashige and Skoog’s (MS) medium supplemented with 2.0 mg/L NAA and 0.5 mg/L BAP was the best for callus induction and MS media fortified with 1.0 mg/L NAA and 1.0 mg/L BAP was optimum for in vitro regeneration. The survival rates of plantlets after acclimatization was 63±1.5 % on black soil and 50±1.3 % on mixed soil (combination of black and red soil at a ratio of 2 to 1), respectively.

Keywords: callus, acclimatization, in vitro culture, regeneration

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Authors: Sadixa Sanjel, Ahmed Sadek, Naseef Mansoor, Zelalem Denekew

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Collegiate ice hockey (NCAA) sports analytics is different from the national level hockey (NHL). We apply and compare multiple machine learning models such as Linear Regression, Random Forest, and Neural Networks to predict the win ratio for a team based on their statistics. Data exploration helps determine which statistics are most useful in increasing the win ratio, which would be beneficial to coaches and team managers. We ran experiments to select the best model and chose Random Forest as the best performing. We conclude with how to bridge the gap between the college and national levels of sports analytics and the use of machine learning to enhance team performance despite not having a lot of metrics or budget for automatic tracking.

Keywords: NCAA, NHL, sports analytics, random forest, regression, neural networks, game predictions

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Authors: Jing Zhang, Jie Chen

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In this paper, we deal with the optimal I/O point location in an automated parking system. In this system, the S/R machine (storage and retrieve machine) travels independently in vertical and horizontal directions. Based on the characteristics of the parking system and the basic principle of AS/RS system (Automated Storage and Retrieval System), we obtain the continuous model in units of time. For the single command cycle using the randomized storage policy, we calculate the probability density function for the system travel time and thus we develop the travel time model. And we confirm that the travel time model shows a good performance by comparing with discrete case. Finally in this part, we establish the optimal model by minimizing the expected travel time model and it is shown that the optimal location of the I/O point is located at the middle of the left-hand above corner.

Keywords: parking system, optimal location, response time, S/R machine

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Authors: Dalu Zhang, Xiang Jin, Dejiang Zhou, Jianpeng Wang, Haiying Jiang

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Traditional TCP/IP network is showing lots of shortages and research for future networks is becoming a hotspot. FIA (Future Internet Architecture) and FIA-NP (Next Phase) are supported by US NSF for future Internet designing. Moreover, virtual machine migration is a significant technique in cloud computing. As a network application, it should also be supported in XIA (expressive Internet Architecture), which is in both FIA and FIA-NP projects. This paper is an experimental study aims at verifying the feasibility of VM migration over XIA. We present three ways to maintain VM connectivity and communication states concerning DAG design and routing table modification. VM migration experiments are conducted intra-AD and inter-AD with KVM instances. The procedure is achieved by a migration control protocol which is suitable for the characters of XIA. Evaluation results show that our solutions can well supports full live VM migration over XIA network respectively, keeping services seamless.

Keywords: DAG, downtime, virtual machine migration, XIA

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Authors: Seyedali Seyedkavoosi, Mohammad Obadat, Seantorrion Boyle

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The purpose of this study is to assess the effectiveness of a nontraditional experiential learning strategy in improving the success and interest of mechanical engineering students, using the Kinematics/Dynamics of Machine course as a case study. This upper-division technical course covers a wide range of topics, including mechanism and machine system analysis and synthesis, yet the complexities of ideas like acceleration, motion, and machine component relationships are hard to explain using standard teaching techniques. To solve this problem, a thorough design project was created that gave students hands-on experience developing, manufacturing, and testing their inventions. The main goals of the project were to improve students' grasp of machine design and kinematics, to develop problem-solving and presenting abilities, and to familiarize them with professional software. A questionnaire survey was done to evaluate the effect of this technique on students' performance and interest in mechanical engineering. The outcomes of the study shed light on the usefulness of nontraditional experiential learning approaches in engineering education.

Keywords: experiential learning, nontraditional teaching, hands-on design project, engineering education

Procedia PDF Downloads 91

Authors: Jiangyong Liu, Xiangxiang Xu, Bote Luo, Xiaoxue Luo, Jiang Zhu, Lingzhi Yi

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To address the problems of non-linearity and high randomness of the original power load sequence causing the degradation of power load forecasting accuracy, a short-term load forecasting method is proposed. The method is based on the Least Square Support Vector Machine optimized by an Improved Sparrow Search Algorithm combined with the Variational Mode Decomposition proposed in this paper. The application of the variational mode decomposition technique decomposes the raw power load data into a series of Intrinsic Mode Functions components, which can reduce the complexity and instability of the raw data while overcoming modal confounding; the proposed improved sparrow search algorithm can solve the problem of difficult selection of learning parameters in the least Square Support Vector Machine. Finally, through comparison experiments, the results show that the method can effectively improve prediction accuracy.

Keywords: load forecasting, variational mode decomposition, improved sparrow search algorithm, least square support vector machine

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Authors: Asmaa El Harat, Toumi Hicham, Youssef Baddi

Abstract:

This survey delves into the complex realm of Internet of Things (IoT) security, highlighting the urgent need for effective cybersecurity measures as IoT devices become increasingly common. It explores a wide array of cyber threats targeting IoT devices and focuses on mitigating these attacks through the combined use of deep learning and machine learning algorithms, as well as edge and cloud computing paradigms. The survey starts with an overview of the IoT landscape and the various types of attacks that IoT devices face. It then reviews key machine learning and deep learning algorithms employed in IoT cybersecurity, providing a detailed comparison to assist in selecting the most suitable algorithms. Finally, the survey provides valuable insights for cybersecurity professionals and researchers aiming to enhance security in the intricate world of IoT.

Keywords: internet of things (IoT), cybersecurity, machine learning, deep learning

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Authors: Natheer Alatawneh

Abstract:

The finite element analysis of magnetic fields in electromagnetic devices shows that the machine cores experience different flux patterns including alternating and rotating fields. The rotating fields are generated in different configurations range between circular and elliptical with different ratios between the major and minor axis of the flux locus. Experimental measurements on electrical steel exposed to different flux patterns disclose different magnetic losses in the samples under test. Consequently, electric machines require special attention during the cores loss calculation process to consider the flux patterns. In this study, a circular rotational single sheet tester is employed to measure the core losses in electric steel sample of M36G29. The sample was exposed to alternating field, circular field, and elliptical fields with axis ratios of 0.2, 0.4, 0.6 and 0.8. The measured data was implemented on 6-4 switched reluctance motor at three different frequencies of interest to the industry as 60 Hz, 400 Hz, and 1 kHz. The results disclose a high margin of error that may occur during the loss calculations if the flux patterns issue is neglected. The error in different parts of the machine associated with considering the flux patterns can be around 50%, 10%, and 2% at 60Hz, 400Hz, and 1 kHz, respectively. The future work will focus on the optimization of machine geometrical shape which has a primary effect on the flux pattern in order to minimize the magnetic losses in machine cores.

Keywords: alternating core losses, electric machines, finite element analysis, rotational core losses

Procedia PDF Downloads 246

Authors: Jose Melena, Rosa Santander, Tanya Gonzalez, Richard Duque, Juan Illanes

Abstract:

Ecuador is one of the countries with the greatest aquatic biodiversity worldwide. In particular, there are at least a dozen native marine species with great aquaculture potential locally. This research concerns one of those species. It has proposed to implement experimental protocols in order to induce spawning and to generate the early larval development of the penshell Atrina maura under controlled conditions. Bioassays were carried out with one adult batch (n= 26) with an average valvar length of 307,6 ± 9,4 mm, which were collected in the Puerto El Morro Mangrove (2° 42' 33'' S, 80° 14' 28'' W), Guayas Province. During a short acclimation stage, five adults of penshell A. maura were sacrificed in order to determine their sexual maturity degree and to estimate their sex ratio. Dissection showed that three were ripe females (60%) and two were ripe males (40%). Later, three groups (n= 7 by each) were tested with two treatments in order to induce the broodstock spawning: thermal stress, osmotic shock, and one control. Spawning induction was achieved by the immersion in water to 0 g L⁻¹ per 1 h and immersion in sea water to 34 g L⁻¹ per 1 h. After the delivery of gametes, it was achieved 1,35 × 10⁶ viable zygotes. As results, fertilized eggs had 60 µm diameter; while first and second cell divisions were observed to 1 h post-fertilization, with individual average length of 65 ± 4 µm and polar body. Latter cell divisions, including gastrula stage, appeared at 9 h post-fertilization, with individual average length of 71 ± 4 µm; and trochophore stage at 16 h post-fertilization with individual average length of 75 ± 5 µm. In addition, veliger stage was registered at 20 h post-fertilization with individual average length of 81 ± 5 µm. Umboned larvae appeared at day 8 post-fertilization, with individual average length of 145 ± 6 µm. These pioneering results in Ecuador can strengthen the local conservation process of the overexploited A. maura and to encourage its production for commercial purposes.

Keywords: Atrina maura, Ecuador, larval development, spawning induction

Procedia PDF Downloads 157

Authors: Mohammad Java Esmaeily

Abstract:

Background: We evaluate the effects of tissue and organ perfusion during and after coronary artery bypass graft surgery with either colloid (Voluven) or crystalloid (Lactated ringers) as a prime solution. Materials and Methods: In this prospective randomized-controlled trial study, 70 patients undergoing on-pump coronary artery bypass graft surgery were randomly assigned to receive either colloid (Voluven) or crystalloid (Lactated ringer's) as a prime solution for initiation of cardiopulmonary bypass machine procedure. Tissue and organ perfusion markers, including lactate, troponin I, liver and renal function tests and electrolytes, were measured sequentially before induction (T1) to the second days after surgery (T5). Results: With the exception of chloride and potassium levels, no significant differences were detected in other measurements, and laboratory results were identical entirely in the two groups. Conclusion: Voluven® (hydroxyethyl starch, HES 130/0.4) has a not significant difference in comparison with crystalloid (Lactated ringer's) as priming solution on the basis of organ and tissue perfusion tests assessment.

Keywords: prime, colloid, crystalloid, lactate, troponin, hydroxyethyl starch

Procedia PDF Downloads 82

Authors: Rachel Y. Zhang, Christopher K. Anderson

Abstract:

A critical aspect of revenue management is a firm’s ability to predict demand as a function of price. Historically hotels have used simple time series models (regression and/or pick-up based models) owing to the complexities of trying to build casual models of demands. Machine learning approaches are slowly attracting attention owing to their flexibility in modeling relationships. This study provides an overview of approaches to forecasting hospitality demand – focusing on the opportunities created by machine learning approaches, including K-Nearest-Neighbors, Support vector machine, Regression Tree, and Artificial Neural Network algorithms. The out-of-sample performances of above approaches to forecasting hotel demand are illustrated by using a proprietary sample of the market level (24 properties) transactional data for Las Vegas NV. Causal predictive models can be built and evaluated owing to the availability of market level (versus firm level) data. This research also compares and contrast model accuracy of firm-level models (i.e. predictive models for hotel A only using hotel A’s data) to models using market level data (prices, review scores, location, chain scale, etc… for all hotels within the market). The prospected models will be valuable for hotel revenue prediction given the basic characters of a hotel property or can be applied in performance evaluation for an existed hotel. The findings will unveil the features that play key roles in a hotel’s revenue performance, which would have considerable potential usefulness in both revenue prediction and evaluation.

Keywords: hotel revenue, k-nearest-neighbors, machine learning, neural network, prediction model, regression tree, support vector machine

Procedia PDF Downloads 127

Authors: Baghdasaryan Marinka

Abstract:

The operation modes of the synchronous motors used in the production processes are greatly conditioned by the accidentally changing technological and power indices.  As a result, the electrical drive synchronous motor may appear in irregular operation regimes. Although there are numerous works devoted to the development of the regulator for the synchronous motor operation modes, their application for the motors working in the irregular modes is not expedient. In this work, to estimate the issues concerning the stability of the synchronous electrical drive system, the transfer functions of the electrical drive synchronous motors operating in the synchronous and induction modes have been obtained.  For that purpose, a model for investigating the frequency characteristics has been developed in the LabView environment. Frequency characteristics for assessing the transient process of the electrical drive system, operating in the synchronous and induction modes have been obtained, and based on their assessment, a regulator for improving the operation modes of the motor has been proposed. The proposed regulator can be successfully used to prevent the irregular modes of the electrical drive synchronous motor, as well as to estimate the operation state of the drive motor of the mechanism with a changing load.

Keywords: electrical drive system, synchronous motor, regulator, stability, transition process

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Authors: Benyamin Ahmadnia, Javier Serrano

Abstract:

In this paper we compare two different approaches for translating from Persian to Spanish, as a language pair with scarce parallel corpus. The first approach involves direct transfer using an statistical machine translation system, which is available for this language pair. The second approach involves translation through English, as a pivot language, which has more translation resources and more advanced translation systems available. The results show that, it is possible to achieve better translation quality using English as a pivot language in either approach outperforms direct translation from Persian to Spanish. Our best result is the pivot system which scores higher than direct translation by (1.12) BLEU points.

Keywords: statistical machine translation, direct translation approach, pivot language translation approach, parallel corpus

Procedia PDF Downloads 482