Search results for: machine repair
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3309

Search results for: machine repair

1659 Using the Smith-Waterman Algorithm to Extract Features in the Classification of Obesity Status

Authors: Rosa Figueroa, Christopher Flores

Abstract:

Text categorization is the problem of assigning a new document to a set of predetermined categories, on the basis of a training set of free-text data that contains documents whose category membership is known. To train a classification model, it is necessary to extract characteristics in the form of tokens that facilitate the learning and classification process. In text categorization, the feature extraction process involves the use of word sequences also known as N-grams. In general, it is expected that documents belonging to the same category share similar features. The Smith-Waterman (SW) algorithm is a dynamic programming algorithm that performs a local sequence alignment in order to determine similar regions between two strings or protein sequences. This work explores the use of SW algorithm as an alternative to feature extraction in text categorization. The dataset used for this purpose, contains 2,610 annotated documents with the classes Obese/Non-Obese. This dataset was represented in a matrix form using the Bag of Word approach. The score selected to represent the occurrence of the tokens in each document was the term frequency-inverse document frequency (TF-IDF). In order to extract features for classification, four experiments were conducted: the first experiment used SW to extract features, the second one used unigrams (single word), the third one used bigrams (two word sequence) and the last experiment used a combination of unigrams and bigrams to extract features for classification. To test the effectiveness of the extracted feature set for the four experiments, a Support Vector Machine (SVM) classifier was tuned using 20% of the dataset. The remaining 80% of the dataset together with 5-Fold Cross Validation were used to evaluate and compare the performance of the four experiments of feature extraction. Results from the tuning process suggest that SW performs better than the N-gram based feature extraction. These results were confirmed by using the remaining 80% of the dataset, where SW performed the best (accuracy = 97.10%, weighted average F-measure = 97.07%). The second best was obtained by the combination of unigrams-bigrams (accuracy = 96.04, weighted average F-measure = 95.97) closely followed by the bigrams (accuracy = 94.56%, weighted average F-measure = 94.46%) and finally unigrams (accuracy = 92.96%, weighted average F-measure = 92.90%).

Keywords: comorbidities, machine learning, obesity, Smith-Waterman algorithm

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1658 Crack Growth Life Prediction of a Fighter Aircraft Wing Splice Joint Under Spectrum Loading Using Random Forest Regression and Artificial Neural Networks with Hyperparameter Optimization

Authors: Zafer Yüce, Paşa Yayla, Alev Taşkın

Abstract:

There are heaps of analytical methods to estimate the crack growth life of a component. Soft computing methods have an increasing trend in predicting fatigue life. Their ability to build complex relationships and capability to handle huge amounts of data are motivating researchers and industry professionals to employ them for challenging problems. This study focuses on soft computing methods, especially random forest regressors and artificial neural networks with hyperparameter optimization algorithms such as grid search and random grid search, to estimate the crack growth life of an aircraft wing splice joint under variable amplitude loading. TensorFlow and Scikit-learn libraries of Python are used to build the machine learning models for this study. The material considered in this work is 7050-T7451 aluminum, which is commonly preferred as a structural element in the aerospace industry, and regarding the crack type; corner crack is used. A finite element model is built for the joint to calculate fastener loads and stresses on the structure. Since finite element model results are validated with analytical calculations, findings of the finite element model are fed to AFGROW software to calculate analytical crack growth lives. Based on Fighter Aircraft Loading Standard for Fatigue (FALSTAFF), 90 unique fatigue loading spectra are developed for various load levels, and then, these spectrums are utilized as inputs to the artificial neural network and random forest regression models for predicting crack growth life. Finally, the crack growth life predictions of the machine learning models are compared with analytical calculations. According to the findings, a good correlation is observed between analytical and predicted crack growth lives.

Keywords: aircraft, fatigue, joint, life, optimization, prediction.

Procedia PDF Downloads 165
1657 Use of Short Piles for Stabilizing the Side Slope of the Road Embankment along the Canal

Authors: Monapat Sasingha, Suttisak Soralump

Abstract:

This research presents the behavior of slope of the road along the canal stabilized by short piles. In this investigation, the centrifuge machine was used, modelling the condition of the water levels in the canal. The centrifuge tests were performed at 35 g. To observe the movement of the soil, visual analysis was performed to evaluate the failure behavior. Conclusively, the use of short piles to stabilize the canal slope proved to be an effective solution. However, the certain amount of settlement was found behind the short pile rows.

Keywords: centrifuge test, slope failure, embankment, stability of slope

Procedia PDF Downloads 261
1656 Culture of Primary Cortical Neurons on Hydrophobic Nanofibers Induces the Formation of Organoid-Like Structures

Authors: Nick Weir, Robert Stevens, Alan Hargreaves, Martin McGinnity, Chris Tinsley

Abstract:

Hydrophobic materials have previously demonstrated the ability to elevate cell-cell interactions and promote the formation of neural networks whilst aligned nanofibers demonstrate the ability to induce extensive neurite outgrowth in an aligned manner. Hydrophobic materials typically elicit an immune response upon implantation and thus materials used for implantation are typically hydrophilic. Poly-L-lactic acid (PLLA) is a hydrophobic, non-immunogenic, FDA approved material that can be electrospun to form aligned nanofibers. Primary rat cortical neurons cultured for 10 days on aligned PLLA nanofibers formed 3D cell clusters, approximately 800 microns in diameter. Neurites that extended from these clusters were highly aligned due to the alignment of the nanofibers they were cultured upon and fasciculation was also evident. Plasma treatment of the PLLA nanofibers prior to seeding of cells significantly reduced the hydrophobicity and abolished the cluster formation and neurite fasciculation, whilst reducing the extent and directionality of neurite outgrowth; it is proposed that hydrophobicity induces the changes to cellular behaviors. Aligned PLLA nanofibers induced the formation of a structure that mimics the grey-white matter compartmentalization that is observed in vivo and thus represents a step forward in generating organoids or biomaterial-based implants. Upon implantation into the brain, the biomaterial architectures described here may provide a useful platform for both brain repair and brain remodeling initiatives.

Keywords: hydrophobicity, nanofibers, neurite fasciculation, neurite outgrowth, PLLA

Procedia PDF Downloads 149
1655 Interfacing and Replication of Electronic Machinery Using MATLAB/SIMULINK

Authors: Abdulatif Abdulsalam, Mohamed Shaban

Abstract:

This paper introduces interfacing and replication of electronic tools based on the MATLAB/ SIMULINK mock-up package. Mock-up components contain dc-dc converters, power issue rectifiers, motivation machines, dc gear, synchronous gear, and more entire systems. Power issue rectifier model includes solid state device models. The tools are the clear-cut structure and mock-up of complex energetic systems connecting with power electronic machines.

Keywords: power electronics, machine, MATLAB, simulink

Procedia PDF Downloads 343
1654 Design Data Sorter Circuit Using Insertion Sorting Algorithm

Authors: Hoda Abugharsa

Abstract:

In this paper we propose to design a sorter circuit using insertion sorting algorithm. The circuit will be designed using Algorithmic State Machines (ASM) method. That means converting the insertion sorting flowchart into an ASM chart. Then the ASM chart will be used to design the sorter circuit and the control unit.

Keywords: insert sorting algorithm, ASM chart, sorter circuit, state machine, control unit

Procedia PDF Downloads 440
1653 Biodegradable and Bioactive Scaffold for Bone Tissue Engineering

Authors: A. M. Malagon Escandon, J. A. Arenas Alatorre, C. P. Chaires Rosas, N. A. Vazquez Torres, B. Hernandez Tellez, G. Pinon Zarate, M. Herrera Enriquez, A. E. Castell Rodriguez

Abstract:

The current approach to the treatment of bone defects involves the use of scaffolds that provide a biological and mechanically stable niche to favor tissue repair. Despite the significant progress in the field of bone tissue engineering, several main problems associated are attributed to giving a low biodegradation degree, does not promote osseointegration and regeneration, if the bone is not healing as well as expected or fails to heal, will not be given a proper ossification or new bone formation. The actual approaches of bone tissue regeneration are directed to the use of decellularized native extracellular matrices, which are able of retain their own architecture, mechanic properties, biodegradability and promote new bone formation because they are capable of conserving proteins and other factors that are founded in physiological concentrations. Therefore, we propose an extracellular matrix-based bioscaffolds derived from bovine cancellous bone, which is processed by decellularization, demineralization, and hydrolysis of the collagen protein, these protocols have been successfully carried out in other organs and tissues; the effectiveness of its biosafety has also been previously evaluated in vivo and Food and Drug Administration (FDA) approved. In the specific case of bone, a more complex treatment is needed in comparison with other organs and tissues because is necessary demineralization and collagen denaturalization. The present work was made in order to obtain a temporal scaffold that succeed in degradation in an inversely proportional way to the synthesis of extracellular matrix and the maturation of the bone by the cells of the host.

Keywords: bioactive, biodegradable, bone, extracellular matrix-based bioscaffolds, stem cells, tissue engineering

Procedia PDF Downloads 150
1652 Comparison between XGBoost, LightGBM and CatBoost Using a Home Credit Dataset

Authors: Essam Al Daoud

Abstract:

Gradient boosting methods have been proven to be a very important strategy. Many successful machine learning solutions were developed using the XGBoost and its derivatives. The aim of this study is to investigate and compare the efficiency of three gradient methods. Home credit dataset is used in this work which contains 219 features and 356251 records. However, new features are generated and several techniques are used to rank and select the best features. The implementation indicates that the LightGBM is faster and more accurate than CatBoost and XGBoost using variant number of features and records.

Keywords: gradient boosting, XGBoost, LightGBM, CatBoost, home credit

Procedia PDF Downloads 164
1651 An Unusual Cause of Electrocardiographic Artefact: Patient's Warming Blanket

Authors: Sanjay Dhiraaj, Puneet Goyal, Aditya Kapoor, Gaurav Misra

Abstract:

In electrocardiography, an ECG artefact is used to indicate something that is not heart-made. Although technological advancements have produced monitors with the potential of providing accurate information and reliable heart rate alarms, despite this, interference of the displayed electrocardiogram still occurs. These interferences can be from the various electrical gadgets present in the operating room or electrical signals from other parts of the body. Artefacts may also occur due to poor electrode contact with the body or due to machine malfunction. Knowing these artefacts is of utmost importance so as to avoid unnecessary and unwarranted diagnostic as well as interventional procedures. We report a case of ECG artefacts occurring due to patient warming blanket and its consequences. A 20-year-old male with a preoperative diagnosis of exstrophy epispadias complex was posted for surgery under epidural and general anaesthesia. Just after endotracheal intubation, we observed nonspecific ECG changes on the monitor. At a first glance, the monitor strip revealed broad QRs complexes suggesting a ventricular bigeminal rhythm. Closer analysis revealed these to be artefacts because although the complexes were looking broad on the first glance there was clear presence of normal sinus complexes which were immediately followed by 'broad complexes' or artefacts produced by some device or connection. These broad complexes were labeled as artefacts as they were originating in the absolute refractory period of the previous normal sinus beat. It would be physiologically impossible for the myocardium to depolarize so rapidly as to produce a second QRS complex. A search for the possible reason for the artefacts was made and after deepening the plane of anaesthesia, ruling out any possible electrolyte abnormalities, checking of ECG leads and its connections, changing monitors, checking all other monitoring connections, checking for proper grounding of anaesthesia machine and OT table, we found that after switching off the patient’s warming apparatus the rhythm returned to a normal sinus one and the 'broad complexes' or artefacts disappeared. As misdiagnosis of ECG artefacts may subject patients to unnecessary diagnostic and therapeutic interventions so a thorough knowledge of the patient and monitors allow for a quick interpretation and resolution of the problem.

Keywords: ECG artefacts, patient warming blanket, peri-operative arrhythmias, mobile messaging services

Procedia PDF Downloads 265
1650 Non-Linear Control in Positioning of PMLSM by Estimates of the Load Force by MRAS Method

Authors: Maamar Yahiaoui, Abdelrrahmene Kechich, Ismail Elkhallile Bousserhene

Abstract:

This article presents a study in simulation by means of MATLAB/Simulink software of the nonlinear control in positioning of a linear synchronous machine with the esteemed force of load, to have effective control in the estimator in all tests the wished trajectory follows and the disturbance of load start. The results of simulation prove clearly that the control proposed can detect the reference of positioning the value estimates of load force equal to the actual value.

Keywords: mathematical model, Matlab, PMLSM, control, linearization, estimator, force, load, current

Procedia PDF Downloads 598
1649 Snapchat’s Scanning Feature

Authors: Reham Banwair, Lana Alshehri, Sara Hadrawi

Abstract:

The purpose of this project is to identify user satisfaction with the AI functions on Snapchat, in order to generate improvement proposals that allow its development within the app. To achieve this, a qualitative analysis was carried out through interviews to people who usually use the application, revealing their satisfaction or dissatisfaction with the usefulness of the AI. In addition, the background of the company and its introduction in these algorithms were analyzed. Furthermore, the characteristics of the three main functions of AI were explained: identify songs, solve mathematical problems, and recognize plants. As a result, it was obtained that 50% still do not know the characteristics of AI, 50% still believe song recognition is not always correct, 41.7% believe that math problems are usually accurate and 91.7% believes the plant detection tool is working properly.

Keywords: artificial intelligence, scanning, Snapchat, machine learning

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1648 Design and Implementation of Wireless Syncronized AI System for Security

Authors: Saradha Priya

Abstract:

Developing virtual human is very important to meet the challenges occurred in many applications where human find difficult or risky to perform the task. A robot is a machine that can perform a task automatically or with guidance. Robotics is generally a combination of artificial intelligence and physical machines (motors). Computational intelligence involves the programmed instructions. This project proposes a robotic vehicle that has a camera, PIR sensor and text command based movement. It is specially designed to perform surveillance and other few tasks in the most efficient way. Serial communication has been occurred between a remote Base Station, GUI Application, and PC.

Keywords: Zigbee, camera, pirsensor, wireless transmission, DC motor

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1647 Educase–Intelligent System for Pedagogical Advising Using Case-Based Reasoning

Authors: Elionai Moura, José A. Cunha, César Analide

Abstract:

This work introduces a proposal scheme for an Intelligent System applied to Pedagogical Advising using Case-Based Reasoning, to find consolidated solutions before used for the new problems, making easier the task of advising students to the pedagogical staff. We do intend, through this work, introduce the motivation behind the choices for this system structure, justifying the development of an incremental and smart web system who learns bests solutions for new cases when it’s used, showing technics and technology.

Keywords: case-based reasoning, pedagogical advising, educational data-mining (EDM), machine learning

Procedia PDF Downloads 411
1646 Comparison of Anterolateral Thigh Flap with or without Acellular Dermal Matrix in Repair of Hypopharyngeal Squamous Cell Carcinoma Defect: A Retrospective Study

Authors: Yaya Gao, Bing Zhong, Yafeng Liu, Fei Chen

Abstract:

Aim: The purpose of this study was to explore the difference between acellular dermal matrix (ADM) combined with anterolateral thigh (ALT) flap and ALT flap alone. Methods: HSCC patients were treated and divided into group A (ALT) and group B (ALT+ADM) between January 2014 and December 2018. We compared and analyzed the intraoperative information and postoperative outcomes of the patients. Results: There were 21 and 17 patients in group A and group B, respectively. The operation time, blood loss, defect size and anastomotic vessel selection showed no significant difference between two groups. The postoperative complications, including wound bleeding (n=0 vs. 1, p=0.459), wound dehiscence (n=0 vs. 1, p=0.459), wound infection (n=5vs.3, p=0.709), pharyngeal fistula (n=5vs.4, p=1.000) and hypoproteinemia (n=11 vs. 12, p=0.326) were comparable between the groups. Dysphagia at 6 months (number of liquid diets=0vs. 0; number of partial tube feedings=1vs. 1; number of total tube feedings=1vs. 0, p=0.655) also showed no significant differences. However, significant differences was observed in dysphagia at 12 months (number of liquid diets=0vs. 0; number of partial tube feedings=3 vs. 1; number of total tube feedings=10vs. 1, p=0.006). Conclusion: For HSCC patients, the use of the ALT flap combined ADM, compared to ALT treatment, showed better swallowing function at 12 months. The ALT flap combined ADM may serve as a safe and feasible alternative for selected HSCC patients.

Keywords: hypopharyngeal squamous cell carcinoma, anterolateral thigh free flap, acellular dermal matrix, reconstruction, dysphagia

Procedia PDF Downloads 74
1645 Automata-Based String Analysis for Detecting Malware in Android Programs

Authors: Assad Maalouf, Lunjin Lu, James Lynott

Abstract:

We design and implement a precise model of string operations using finite state machine transformers and state transformers to approximate the values string variables can take throughout the execution of the program.We use our model to analyze Android program string variables. Our experimental results show that our string analysis is very efficient at detecting the contextual effect of string operations on the string variables. Our model proved to be very useful when it came to verifying statements about the string variables of the program.

Keywords: abstract interpretation, android, static analysis, string analysis

Procedia PDF Downloads 176
1644 Self-Help Adaptation to Flooding in Low-Income Settlements in Chiang Mai, Thailand

Authors: Nachawit Tikul

Abstract:

This study aimed to determine low-income housing adaptations for flooding, which causes living problems and housing damage, and the results from improvement. Three low-income settlements in Chiang Mai which experienced different flood types, i.e. flash floods in Samukeepattana, drainage floods in Bansanku, and river floods in Kampangam, were chosen for the study. Almost all of the residents improved their houses to protect the property from flood damage by changing building materials to flood damage resistant materials for walls, floors, and other parts of the structure that were below the base of annual flood elevation. They could only build some parts of their own homes, so hiring skilled workers or contractors was still important. Building materials which have no need for any special tools and are easy to access and use for construction, as well as low cost, are selected for construction. The residents in the three slums faced living problems for only a short time and were able to cope with them. This may be due to the location of the three slums near the city where assistance is readily available. But the housing and the existence in the slums can endure only the regular floods and residence still have problems in unusual floods, which have been experienced 1-2 times during the past 10 years. The residents accept the need for evacuations and prepare for them. When faced with extreme floods, residence have evacuated to the nearest safe place such as schools and public building, and come back to repair the houses after the flood. These are the distinguishing characteristics of low-income living which can withstand serious situations due to the simple lifestyle. Therefore, preparation of living areas for use during severe floods and encouraging production of affordable flood resistant materials should be areas of concern when formulating disaster assistance policies for low income people.

Keywords: flooding, low-income settlement, housing, adaptation

Procedia PDF Downloads 232
1643 PPRA Regulates DNA Replication Initiation and Cell Morphology in Escherichia coli

Authors: Ganesh K. Maurya, Reema Chaudhary, Neha Pandey, Hari S. Misra

Abstract:

PprA, a pleiotropic protein participating in radioresistance, has been reported for its roles in DNA replication initiation, genome segregation, cell division and DNA repair in polyextremophile Deinococcus radiodurans. Interestingly, expression of deinococcal PprA in E. coli suppresses its growth by reducing the number of colony forming units and provides better resistance against γ-radiation than control. We employed different biochemical and cell biology studies using PprA and its DNA binding/polymerization mutants (K133E & W183R) in E. coli. Cells expressing wild type PprA or its K133E mutant showed reduction in the amount of genomic DNA as well as chromosome copy number in comparison to W183R mutant of PprA and control cells, which suggests the role of PprA protein in regulation of DNA replication initiation in E. coli. Further, E. coli cells expressing PprA or its mutants exhibited different impact on cell morphology than control. Expression of PprA or K133E mutant displayed a significant increase in cell length upto 5 folds while W183R mutant showed cell length similar to uninduced control cells. We checked the interaction of deinococcal PprA and its mutants with E. coli DnaA using Bacterial two-hybrid system and co-immunoprecipitation. We observed a functional interaction of EcDnaA with PprA and K133E mutant but not with W183R mutant of PprA. Further, PprA or K133E mutant has suppressed the ATPase activity of EcDnaA but W183R mutant of PprA failed to do so. These observations suggested that PprA protein regulates DNA replication initiation and cell morphology of surrogate E. coli.

Keywords: DNA replication, radioresistance, protein-protein interaction, cell morphology, ATPase activity

Procedia PDF Downloads 61
1642 Fabrication of Drug-Loaded Halloysite Nanotubes Containing Sodium Alginate/Gelatin Composite Scaffolds

Authors: Masoumeh Haghbin Nazarpak, Hamidreza Tolabi, Aryan Ekhlasi

Abstract:

Bone defects are mentioned as one of the most challenging clinical conditions, affecting millions of people each year. A fracture, osteoporosis, tumor, or infection usually causes these defects. At present, autologous and allogeneic grafts are used to correct bone defects, but these grafts have some difficulties, such as limited access, infection, disease transmission, and immune rejection. Bone tissue engineering is considered a new strategy for repairing bone defects. However, problems with scaffolds’ design with unique structures limit their clinical applications. In addition, numerous in-vitro studies have been performed on the behavior of bone cells in two-dimensional environments. Still, cells grow in physiological situations in the human body in a three-dimensional environment. As a result, the controlled design of porous structures with high structural complexity and providing the necessary flexibility to meet specific needs in bone tissue repair is beneficial. For this purpose, a three-dimensional composite scaffold based on gelatin and sodium alginate hydrogels is used in this research. In addition, the antibacterial drug-loaded halloysite nanotubes were introduced into the hydrogel scaffold structure to provide a suitable substrate for controlled drug release. The presence of halloysite nanotubes improved hydrogel’s properties, while the drug eliminated infection and disease transmission. Finally, it can be acknowledged that the composite scaffold prepared in this study for bone tissue engineering seems promising.

Keywords: halloysite nanotubes, bone tissue engineering, composite scaffold, controlled drug release

Procedia PDF Downloads 59
1641 PPRA Controls DNA Replication and Cell Growth in Escherichia Coli

Authors: Ganesh K. Maurya, Reema Chaudhary, Neha Pandey, Hari S. Misra

Abstract:

PprA, a pleiotropic protein participating in radioresistance, has been reported for its roles in DNA replication initiation, genome segregation, cell division and DNA repair in polyextremophile Deinococcus radiodurans. Interestingly, expression of deinococcal PprA in E. coli suppresses its growth by reducing the number of colony forming units and provide better resistance against γ-radiation than control. We employed different biochemical and cell biology studies using PprA and its DNA binding/polymerization mutants (K133E & W183R) in E. coli. Cells expressing wild type PprA or its K133E mutant showed reduction in the amount of genomic DNA as well as chromosome copy number in comparison to W183R mutant of PprA and control cells, which suggests the role of PprA protein in regulation of DNA replication initiation in E. coli. Further, E. coli cells expressing PprA or its mutants exhibited different impact on cell morphology than control. Expression of PprA or K133E mutant displayed a significant increase in cell length upto 5 folds while W183R mutant showed cell length similar to uninduced control cells. We checked the interaction of deinococcal PprA and its mutants with E. coli DnaA using Bacterial two-hybrid system and co-immunoprecipitation. We observed a functional interaction of EcDnaA with PprA and K133E mutant but not with W183R mutant of PprA. Further, PprA or K133E mutant has suppressed the ATPase activity of EcDnaA but W183R mutant of PprA failed to do so. These observations suggested that PprA protein regulates DNA replication initiation and cell morphology of surrogate E. coli.

Keywords: DNA replication, radioresistance, protein-protein interaction, cell morphology, ATPase activity

Procedia PDF Downloads 62
1640 The Association of Anthropometric Measurements, Blood Pressure Measurements, and Lipid Profiles with Mental Health Symptoms in University Students

Authors: Ammaarah Gamieldien

Abstract:

Depression is a very common and serious mental illness that has a significant impact on both the social and economic aspects of sufferers worldwide. This study aimed to investigate the association between body mass index (BMI), blood pressure, and lipid profiles with mental health symptoms in university students. Secondary objectives included the associations between the variables (BMI, blood pressure, and lipids) with themselves, as they are key factors in cardiometabolic disease. Sixty-three (63) students participated in the study. Thirty-two (32) were assigned to the control group (minimal-mild depressive symptoms), while 31 were assigned to the depressive group (moderate to severe depressive symptoms). Montgomery-Asberg Depression Rating Scale (MADRS) and Beck Depression Inventory (BDI) were used to assess depressive scores. Anthropometric measurements such as weight (kg), height (m), waist circumference (WC), and hip circumference were measured. Body mass index (BMI) and ratios such as waist-to-hip ratio (WHR) and waist-to-height ratio (WtHR) were also calculated. Blood pressure was measured using an automated AfriMedics blood pressure machine, while lipids were measured using a CardioChek plus analyzer machine. Statistics were analyzed via the SPSS statistics program. There were no significant associations between anthropometric measurements and depressive scores (p > 0.05). There were no significant correlations between lipid profiles and depression when running a Spearman’s rho correlation (P > 0.05). However, total cholesterol and LDL-C were negatively associated with depression, and triglycerides were positively associated with depression after running a point-biserial correlation (P < 0.05). Overall, there were no significant associations between blood pressure measurements and depression (P > 0.05). However, there was a significant moderate positive correlation between systolic blood pressure and MADRS scores in males (P < 0.05). Depressive scores positively and strongly correlated to how long it takes participants to fall asleep. There were also significant associations with regard to the secondary objectives. This study indicates the importance of determining the prevalence of depression among university students in South Africa. If the prevalence and factors associated with depression are addressed, depressive symptoms in university students may be improved.

Keywords: depression, blood pressure, body mass index, lipid profiles, mental health symptoms

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1639 Evaluation of Cytotoxic Effect of Mitoxantrone Conjugated Magnetite Nanoparticles and Graphene Oxide-Magnetite Nanocomposites on Mesenchymal Stem Cells

Authors: Abbas Jafarizad, Duygu Ekinci

Abstract:

In this work targeted drug delivery is proposed to decrease adverse effect of drugs with concomitant reduces in consumption and treatment outgoings. Nanoparticles (NPs) can be prepared from a variety of materials such as lipid, biodegradable polymer that prevent the drugs cytotoxicity in healthy cells, etc. One of the most important drugs used in chemotherapy is mitoxantrone (MTX) which prevents cell proliferation by inhibition of topoisomerase II and DNA repair; however, it is not selective and has some serious side effects. In this study, mentioned aim is achieved by using several nanocarriers like magnetite (Fe3O4) and their composites with magnetic graphene oxide (Fe3O4@GO). Also, cytotoxic potential of Fe3O4, Fe3O4-MTX, and Fe3O4@GO-MTX nanocomposite were evaluated on mesenchymal stem cells (MSCs). In this study, we reported the synthesis of monodisperse Fe3O4 NPs and Fe3O4@GO nanocomposite and their structures were investigated by using field emission scanning electron microscope (FESEM), Fourier transform infrared (FTIR) spectra, atomic force microscopy (AFM), Brauneur Emmet Teller (BET) isotherm and contact angle studies. Moreover, we used 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay to evaluate cytotoxic effects of MTX, Fe3O4 NPs, Fe3O4-MTX and Fe3O4@GO-MTX nanocomposite on MSCs. The in-vitro MTT results indicated that all concentrations of MTX and Fe3O4@GO-MTX nanocomposites showed cytotoxic effects while all concentrations of Fe3O4 NPs and Fe3O4-MTX NPs did not show any cytotoxic effect on stem cells. The results from this study indicated that using Fe3O4 NPs as anticancer drug delivery systems could be a trustworthy method for cancer treatment. But for reaching excellent and accurate results, further investigation is necessary.

Keywords: mitoxantrone, magnetite, magnetic graphene oxide, MTT assay, mesenchymal stem cells

Procedia PDF Downloads 269
1638 Comparison between Classical and New Direct Torque Control Strategies of Induction Machine

Authors: Mouna Essaadi, Mohamed Khafallah, Abdallah Saad, Hamid Chaikhy

Abstract:

This paper presents a comparative analysis between conventional direct torque control (C_DTC), Modified direct torque control (M_DTC) and twelve sectors direct torque control (12_DTC).Those different strategies are compared by simulation in term of torque, flux and stator current performances. Finally, a summary of the comparative analysis is presented.

Keywords: C_DTC, M_DTC, 12_DTC, torque dynamic, stator current, flux, performances

Procedia PDF Downloads 610
1637 Simultaneous Bilateral Patella Tendon Rupture: A Systematic Review

Authors: André Rui Coelho Fernandes, Mariana Rufino, Divakar Hamal, Amr Sousa, Emma Fossett, Kamalpreet Cheema

Abstract:

Aim: A single patella tendon rupture is relatively uncommon, but a simultaneous bilateral event is a rare occurrence and has been scarcely reviewed in the literature. This review was carried out to analyse the existing literature on this event, with the aim of proposing a standardised approach to the diagnosis and management of this injury. Methods: A systematic review was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Three independent reviewers conducted searches in PubMed, OvidSP for Medline and Embase, as well as Cochrane Library using the same search strategy. From a total of 183 studies, 45 were included, i.e. 90 patellas. Results: 46 patellas had a Type 1 Rupture equating to 51%, with Type 3 being the least common, with only 7 patellas sustaining this injury. The mean Insall-Salvio ratio for each knee was 1.62 (R) and 1.60 (L) Direct Primary Repair was the most common surgical technique compared to Tendon Reconstruction, with End to End and Transosseous techniques split almost equally. Brace immobilisation was preferred over cast, with a mean start to weight-bearing of 3.23 weeks post-op. Conclusions: Bilateral patellar tendon rupture is a rare injury that should be considered in patients with knee extensor mechanism disruption. The key limitation of this study was the low number of patients encompassed by the eligible literature. There is space for a higher level of evidence study, specifically regarding surgical treatment choice and methods, as well as post-operative management, which could potentially improve the outcomes in the management of this injury.

Keywords: trauma and orthopaedic surgery, bilateral patella, tendon rupture, trauma

Procedia PDF Downloads 128
1636 A Deep Learning Approach for the Predictive Quality of Directional Valves in the Hydraulic Final Test

Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

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The increasing use of deep learning applications in production is becoming a competitive advantage. Predictive quality enables the assurance of product quality by using data-driven forecasts via machine learning models as a basis for decisions on test results. The use of real Bosch production data along the value chain of hydraulic valves is a promising approach to classifying the leakage of directional valves.

Keywords: artificial neural networks, classification, hydraulics, predictive quality, deep learning

Procedia PDF Downloads 233
1635 Artificial Intelligence in Patient Involvement: A Comprehensive Review

Authors: Igor A. Bessmertny, Bidru C. Enkomaryam

Abstract:

Active involving patients and communities in health decisions can improve both people’s health and the healthcare system. Adopting artificial intelligence can lead to more accurate and complete patient record management. This review aims to identify the current state of researches conducted using artificial intelligence techniques to improve patient engagement and wellbeing, medical domains used in patient engagement context, and lastly, to assess opportunities and challenges for patient engagement in the wellness process. A search of peer-reviewed publications, reviews, conceptual analyses, white papers, author’s manuscripts and theses was undertaken. English language literature published in 2013– 2022 period and publications, report and guidelines of World Health Organization (WHO) were also assessed. About 281 papers were retrieved. Duplicate papers in the databases were removed. After application of the inclusion and exclusion criteria, 41 papers were included to the analysis. Patient counseling in preventing adverse drug events, in doctor-patient risk communication, surgical, drug development, mental healthcare, hypertension & diabetes, metabolic syndrome and non-communicable chronic diseases are implementation areas in healthcare where patient engagement can be implemented using artificial intelligence, particularly machine learning and deep learning techniques and tools. The five groups of factors that potentially affecting patient engagement in safety are related to: patient, health conditions, health care professionals, tasks and health care setting. Active involvement of patients and families can help accelerate the implementation of healthcare safety initiatives. In sub-Saharan Africa, using digital technologies like artificial intelligence in patient engagement context is low due to poor level of technological development and deployment. The opportunities and challenges available to implement patient engagement strategies vary greatly from country to country and from region to region. Thus, further investigation will be focused on methods and tools using the potential of artificial intelligence to support more simplified care that might be improve communication with patients and train health care professionals.

Keywords: artificial intelligence, patient engagement, machine learning, patient involvement

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1634 A Textile-Based Scaffold for Skin Replacements

Authors: Tim Bolle, Franziska Kreimendahl, Thomas Gries, Stefan Jockenhoevel

Abstract:

The therapeutic treatment of extensive, deep wounds is limited. Autologous split-skin grafts are used as a so-called ‘gold standard’. Most common deficits are the defects at the donor site, the risk of scarring as well as the limited availability and quality of the autologous grafts. The aim of this project is a tissue engineered dermal-epidermal skin replacement to overcome the limitations of the gold standard. A key requirement for the development of such a three-dimensional implant is the formation of a functional capillary-like network inside the implant to ensure a sufficient nutrient and gas supply. Tailored three-dimensional warp knitted spacer fabrics are used to reinforce the mechanically week fibrin gel-based scaffold and further to create a directed in vitro pre-vascularization along the parallel-oriented pile yarns within a co-culture. In this study various three-dimensional warp knitted spacer fabrics were developed in a factorial design to analyze the influence of the machine parameters such as the stitch density and the pattern of the fabric on the scaffold performance and further to determine suitable parameters for a successful fibrin gel-incorporation and a physiological performance of the scaffold. The fabrics were manufactured on a Karl Mayer double-bar raschel machine DR 16 EEC/EAC. A fine machine gauge of E30 was used to ensure a high pile yarn density for sufficient nutrient, gas and waste exchange. In order to ensure a high mechanical stability of the graft, the fabrics were made of biocompatible PVDF yarns. Key parameters such as the pore size, porosity and stress/strain behavior were investigated under standardized, controlled climate conditions. The influence of the input parameters on the mechanical and morphological properties as well as the ability of fibrin gel incorporation into the spacer fabric was analyzed. Subsequently, the pile yarns of the spacer fabrics were colonized with Human Umbilical Vein Endothelial Cells (HUVEC) to analyze the ability of the fabric to further function as a guiding structure for a directed vascularization. The cells were stained with DAPI and investigated using fluorescence microscopy. The analysis revealed that the stitch density and the binding pattern have a strong influence on both the mechanical and morphological properties of the fabric. As expected, the incorporation of the fibrin gel was significantly improved with higher pore sizes and porosities, whereas the mechanical strength decreases. Furthermore, the colonization trials revealed a high cell distribution and density on the pile yarns of the spacer fabrics. For a tailored reinforcing structure, the minimum porosity and pore size needs to be evaluated which still ensures a complete incorporation of the reinforcing structure into the fibrin gel matrix. That will enable a mechanically stable dermal graft with a dense vascular network for a sufficient nutrient and oxygen supply of the cells. The results are promising for subsequent research in the field of reinforcing mechanically weak biological scaffolds and develop functional three-dimensional scaffolds with an oriented pre-vascularization.

Keywords: fibrin-gel, skin replacement, spacer fabric, pre-vascularization

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1633 Cluster Analysis and Benchmarking for Performance Optimization of a Pyrochlore Processing Unit

Authors: Ana C. R. P. Ferreira, Adriano H. P. Pereira

Abstract:

Given the frequent variation of mineral properties throughout the Araxá pyrochlore deposit, even if a good homogenization work has been carried out before feeding the processing plants, an operation with quality and performance’s high variety standard is expected. These results could be improved and standardized if the blend composition parameters that most influence the processing route are determined, and then the types of raw materials are grouped by them, finally presenting a great reference with operational settings for each group. Associating the physical and chemical parameters of a unit operation through benchmarking or even an optimal reference of metallurgical recovery and product quality reflects in the reduction of the production costs, optimization of the mineral resource, and guarantee of greater stability in the subsequent processes of the production chain that uses the mineral of interest. Conducting a comprehensive exploratory data analysis to identify which characteristics of the ore are most relevant to the process route, associated with the use of Machine Learning algorithms for grouping the raw material (ore) and associating these with reference variables in the process’ benchmark is a reasonable alternative for the standardization and improvement of mineral processing units. Clustering methods through Decision Tree and K-Means were employed, associated with algorithms based on the theory of benchmarking, with criteria defined by the process team in order to reference the best adjustments for processing the ore piles of each cluster. A clean user interface was created to obtain the outputs of the created algorithm. The results were measured through the average time of adjustment and stabilization of the process after a new pile of homogenized ore enters the plant, as well as the average time needed to achieve the best processing result. Direct gains from the metallurgical recovery of the process were also measured. The results were promising, with a reduction in the adjustment time and stabilization when starting the processing of a new ore pile, as well as reaching the benchmark. Also noteworthy are the gains in metallurgical recovery, which reflect a significant saving in ore consumption and a consequent reduction in production costs, hence a more rational use of the tailings dams and life optimization of the mineral deposit.

Keywords: mineral clustering, machine learning, process optimization, pyrochlore processing

Procedia PDF Downloads 140
1632 Decoding Kinematic Characteristics of Finger Movement from Electrocorticography Using Classical Methods and Deep Convolutional Neural Networks

Authors: Ksenia Volkova, Artur Petrosyan, Ignatii Dubyshkin, Alexei Ossadtchi

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Brain-computer interfaces are a growing research field producing many implementations that find use in different fields and are used for research and practical purposes. Despite the popularity of the implementations using non-invasive neuroimaging methods, radical improvement of the state channel bandwidth and, thus, decoding accuracy is only possible by using invasive techniques. Electrocorticography (ECoG) is a minimally invasive neuroimaging method that provides highly informative brain activity signals, effective analysis of which requires the use of machine learning methods that are able to learn representations of complex patterns. Deep learning is a family of machine learning algorithms that allow learning representations of data with multiple levels of abstraction. This study explores the potential of deep learning approaches for ECoG processing, decoding movement intentions and the perception of proprioceptive information. To obtain synchronous recording of kinematic movement characteristics and corresponding electrical brain activity, a series of experiments were carried out, during which subjects performed finger movements at their own pace. Finger movements were recorded with a three-axis accelerometer, while ECoG was synchronously registered from the electrode strips that were implanted over the contralateral sensorimotor cortex. Then, multichannel ECoG signals were used to track finger movement trajectory characterized by accelerometer signal. This process was carried out both causally and non-causally, using different position of the ECoG data segment with respect to the accelerometer data stream. The recorded data was split into training and testing sets, containing continuous non-overlapping fragments of the multichannel ECoG. A deep convolutional neural network was implemented and trained, using 1-second segments of ECoG data from the training dataset as input. To assess the decoding accuracy, correlation coefficient r between the output of the model and the accelerometer readings was computed. After optimization of hyperparameters and training, the deep learning model allowed reasonably accurate causal decoding of finger movement with correlation coefficient r = 0.8. In contrast, the classical Wiener-filter like approach was able to achieve only 0.56 in the causal decoding mode. In the noncausal case, the traditional approach reached the accuracy of r = 0.69, which may be due to the presence of additional proprioceptive information. This result demonstrates that the deep neural network was able to effectively find a representation of the complex top-down information related to the actual movement rather than proprioception. The sensitivity analysis shows physiologically plausible pictures of the extent to which individual features (channel, wavelet subband) are utilized during the decoding procedure. In conclusion, the results of this study have demonstrated that a combination of a minimally invasive neuroimaging technique such as ECoG and advanced machine learning approaches allows decoding motion with high accuracy. Such setup provides means for control of devices with a large number of degrees of freedom as well as exploratory studies of the complex neural processes underlying movement execution.

Keywords: brain-computer interface, deep learning, ECoG, movement decoding, sensorimotor cortex

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1631 Technical Non-Destructive Evaluation of Burnt Bridge at CH. 57+450 Along Abuja-Abaji-Lokoja Road, Nigeria

Authors: Abraham O. Olaniyi, Oluyemi Oke, Atilade Otunla

Abstract:

The structural performance of bridges decreases progressively throughout their service life due to many contributing factors (fatigue, carbonation, fire incidents etc.). Around the world, numerous bridges have attained their estimated service life and many have approached this limit. The structural integrity assessment of the burnt composite bridge located at CH57+450, Koita village along Abuja-Abaji-Lokoja road, Nigeria, is presented as a case study and shall be forthwith referred to as the 'Koita bridge' in this paper. From the technical evaluation, the residual compressive strength of the concrete piers was found to be below 16.0 N/mm2. This value is very low compared to the expected design value of 30.0 N/mm2. The pier capping beam at pier location 1 has a very low residual compressive strength. The cover to the reinforcement of certain capping beams has an outline of reinforcement which signifies poor concrete cover and the mean compressive strength is also less than 20.0 N/mm2. The steel girder indicated black colouration as a result of the fire incident without any significant structural defect like buckling or warping of the steel section. This paper reviews the structural integrity assessment and repair methodology of the Koita bridge; a composite bridge damaged by fire, highlighting the various challenges of limited obtainable guidance documents about the bridge. The objectives are to increase the understanding of processes and versatile equipment required to test and assess a fire-damaged bridge in order to improve the quality of structural appraisal and rehabilitation; thus, eliminating the prejudice associated with current visual inspection techniques.

Keywords: assessment, bridge, rehabilitation, sustainability

Procedia PDF Downloads 361
1630 Attribution Theory and Perceived Reliability of Cellphones for Teaching and Learning

Authors: Mayowa A. Sofowora, Seraphin D. Eyono Obono

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The use of information and communication technologies such as computers, mobile phones and the internet is becoming prevalent in today’s world; and it is facilitating access to a vast amount of data, services, and applications for the improvement of people’s lives. However, this prevalence of ICTs is hampered by the problem of low income levels in developing countries to the point where people cannot timeously replace or repair their ICT devices when damaged or lost; and this problem serves as a motivation for this study whose aim is to examine the perceptions of teachers on the reliability of cellphones when used for teaching and learning purposes. The research objectives unfolding this aim are of two types: objectives on the selection and design of theories and models, and objectives on the empirical testing of these theories and models. The first type of objectives is achieved using content analysis in an extensive literature survey, and the second type of objectives is achieved through a survey of high school teachers from the ILembe and Umgungudlovu districts in the KwaZuluNatal province of South Africa. Data collected from this questionnaire based survey is analysed in SPSS using descriptive statistics and Pearson correlations after checking the reliability and validity of the questionnaire. The main hypothesis driving this study is that there is a relationship between the demographics and the attribution identity of teachers on one hand, and their perceptions on the reliability of cellphones on the other hand, as suggested by existing literature; except that attribution identities are considered in this study under three angles: intention, knowledge and ability, and action. The results of this study confirm that the perceptions of teachers on the reliability of cellphones for teaching and learning are affected by the school location of these teachers, and by their perceptions on learners’ cellphones usage intentions and actual use.

Keywords: attribution, cellphones, e-learning, reliability

Procedia PDF Downloads 395