Search results for: modular wound rotor synchronous machine

Authors: Zain Ul Hassan, Muhammad Zain Ul Abadin, Muhammad Zubair Khan

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Unmanned aerial vehicles (UAVs) have now become of predominant importance for various operations, and an immense amount of work is going on in this specific category. The structural stability and life of these UAVs is key factor that should be considered while deploying them to different intelligent operations as their failure leads to loss of sensitive real-time data and cost. This paper presents an applied research on the development of a structural health monitoring system for a UAV designed and fabricated by deploying modular approach. Firstly, a modular UAV has been designed which allows to dismantle and to reassemble the components of the UAV without effecting the whole assembly of UAV. This novel approach makes the vehicle very sustainable and decreases its maintenance cost to a significant value by making possible to replace only the part leading to failure. Then the SHM for the designed architecture of the UAV had been specified as a combination of wings integrated with strain gauges, on-board data logger, bridge circuitry and the ground station. For the research purpose sensors have only been attached to the wings being the most load bearing part and as per analysis was done on ANSYS. On the basis of analysis of the load time spectrum obtained by the data logger during flight, fatigue life of the respective component has been predicted using fracture mechanics techniques of Rain Flow Method and Miner’s Rule. Thus allowing us to monitor the health of a specified component time to time aiding to avoid any failure.

Keywords: fracture mechanics, rain flow method, structural health monitoring system, unmanned aerial vehicle

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Authors: Liang Zhao, Chong-quan Zhong

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In order to improve the control performance of vector inverter, an improved parameter identification solution for induction motor is proposed in this paper. Dc or AC voltage is applied to the induction motor using the SVPWM through the inverter. Then stator resistance, stator leakage inductance, rotor resistance, rotor leakage inductance and mutual inductance are obtained according to the signal response. The discrete Fourier transform (DFT) is used to deal with the noise and harmonic. The impact on parameter identification caused by delays in the inverter switch tube, tube voltage drop and dead-time is avoided by effective compensation measures. Finally, the parameter identification experiment is conducted based on the vector inverter which using TMS320F2808 DSP as the core processor and results show that the strategy is verified.

Keywords: vector inverter, parameter identification, SVPWM; DFT, dead-time compensation

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Authors: Norah Mohammed Alshahrani, Abdulaziz Almaleh

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Autism Spectrum Disorder (ASD) is a condition related to issues with brain development that affects how a person recognises and communicates with others which results in difficulties with interaction and communication socially and it is constantly growing. Early recognition of ASD allows children to lead safe and healthy lives and helps doctors with accurate diagnoses and management of conditions. Therefore, it is crucial to develop a method that will achieve good results and with high accuracy for the measurement of ASD in children. In this paper, ASD datasets of toddlers and children have been analyzed. We employed the following machine learning techniques to attempt to explore ASD and they are Random Forest (RF), Decision Tree (DT), Na¨ıve Bayes (NB) and Support Vector Machine (SVM). Then Feature selection was used to provide fewer attributes from ASD datasets while preserving model performance. As a result, we found that the best result has been provided by the Support Vector Machine (SVM), achieving 0.98% in the toddler dataset and 0.99% in the children dataset.

Keywords: autism spectrum disorder, machine learning, feature selection, support vector machine

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Authors: Chetna Dhand, Venkatesh Mayandi, Silvia Marrero Diaz, Roger W. Beuerman, Seeram Ramakrishna, Rajamani Lakshminarayanan

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Sturdy Insect Cuticle Sclerotization, Incredible Substrate independent Mussel’s bioadhesion, Tanning of Leather are some of catechol(amine)s mediated natural processes. Chemical contemplation spots toward a mechanism instigated with the formation of the quinone moieties from the respective catechol(amine)s, via oxidation, followed by the nucleophilic addition of the amino acids/proteins/peptides to this quinone leads to the development of highly strong, cross-linked and water-resistant proteinacious structures. Inspired with this remarkable catechol(amine)s chemistry towards amino acids/proteins/peptides, we attempted to design highly stable and water-resistant antifungal wound dressing mats with exceptional durability using collagen (protein), dopamine (catecholamine) and antifungal drugs (Amphotericin B and Caspofungin) as the key materials. Electrospinning technique has been used to fabricate desired nanofibrous mat including Collagen (COLL), COLL/Dopamine (COLL/DP) and calcium incorporated COLL/DP (COLL-DP-Ca2+). The prepared protein-based scaffolds have been studied for their microscopic investigations (SEM, TEM, and AFM), structural analysis (FT-IR), mechanical properties, water wettability characteristics and aqueous stability. Biocompatibility of these scaffolds has been analyzed for dermal fibroblast cells using MTS assay, Cell TrackerTM Green CMFDA and confocal imaging. Being the winner sample, COLL-DP-Ca2+ scaffold has been selected for incorporating two antifungal drugs namely Caspofungin (Peptide based) and Amphotericin B (Non-Peptide based). Antifungal efficiency of the designed mats has been evaluated for eight diverse fungal strains employing different microbial assays including disc diffusion, cell-viability assay, time kill kinetics etc. To confirm the durability of these mats, in term of their antifungal activity, drug leaching studies has been performed and monitored using disc diffusion assay each day. Ex-vivo fungal infection model has also been developed and utilized to validate the antifungal efficacy of the designed wound dressings. Results clearly reveal dopamine mediated crosslinking within COLL-antifungal scaffolds that leads to the generation of highly stable, mechanical tough, biocompatible wound dressings having the zone of inhabitation of ≥ 2 cm for almost all the investigated fungal strains. Leaching studies and Ex-vivo model has confirmed the durability of these wound dressing for more than 3 weeks and certified their suitability for commercialization. A model has also been proposed to enlighten the chemical mechanism involved for the development of these antifungal wound dressings with exceptional robustness.

Keywords: catecholamine chemistry, electrospinning technique, antifungals, wound dressings, collagen

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Authors: Oladimeji Adetona Adeyeye, Emmanuel Rotimi Sadiku, Oluwaseun Olayinka Adeyeye

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In order to resuscitate soybean production and post-harvest processing especially, in term of threshing, there is need to develop an affordable threshing machine which will reduce drudgery associated with manual soybean threshing. Soybean thresher was fabricated and evaluated at Institute of Agricultural Research and Training IAR&T Apata Ibadan. The machine component includes; hopper, threshing unit, shaker, cleaning unit and the seed outlet, all working together to achieve the main objective of threshing and cleaning. TGX1835 - 10E variety was used for evaluation because of its high resistance to pests, rust and pustules. The final moisture content of the used sample was about 15%. The sample was weighed and introduced into the machine. The parameters evaluated includes moisture content, threshing efficiency, cleaning efficiency, machine capacity and speed. The threshing efficiency and capacity are 74% and 65.9kg/hr respectively. All materials used were sourced locally which makes the cost of production of the machine extremely cheaper than the imported soybean thresher.

Keywords: efficiency, machine capacity, speed, soybean, threshing

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Authors: Rodrigo Aguiar, Adelino Ferreira

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Road traffic accidents are the leading cause of unnatural death and injuries worldwide, representing a significant problem of road safety. In this context, the use of artificial intelligence with advanced machine learning techniques has gained prominence as a promising approach to predict traffic accidents. This article investigates the application of machine learning algorithms to develop traffic accident frequency prediction models. Models are evaluated based on performance metrics, making it possible to do a comparative analysis with traditional prediction approaches. The results suggest that machine learning can provide a powerful tool for accident prediction, which will contribute to making more informed decisions regarding road safety.

Keywords: machine learning, artificial intelligence, frequency of accidents, road safety

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Authors: Hyun-Woo Jun, In-Gun Kim, Hyun Seok Hong, Dong-Woo Kang, Ju Lee

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In high-speed SPMSM design, the rotor-retaining sleeve is inserted into rotor to prevent permanent magnet’s damage. It is quite efficient way considering manufacturability, but the sleeve becomes major source of ohm loss in high-speed operation. In this paper, the high-speed motor for turbo-blower at the rating of 100kW was introduced. To improve its efficiency, the retaining sleeve’s optimal design was needed. Within the range of satisfies the mechanical safety, sleeve’s some design variables have been changed. The effect of changing design variables of the sleeve was studied. This paper presents the optimized sleeve’s advantages in electrical efficiency from the result of electromagnetic FEA (finite element analysis) software. Finally, it suggests the optimal sleeve design to reduce eddy current loss, which is related to motor shape.

Keywords: SPMSM, sleeve, eddy current, high efficiency

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Authors: K. K. Saijaand, K. Prabhakaran Nair

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This study aims to determine change in optimal lo-cations of dual trailing-edge flaps for various thrust coefficient to solidity (Ct /σ) ratios of helicopter to achieve minimum hub vibration levels, with low penalty in terms of required trailing-edge flap control power. Polynomial response functions are used to approximate hub vibration and flap power objective functions. Single objective and multi-objective optimization is carried with the objective of minimizing hub vibration and flap power. The optimization results shows that the inboard flap location at low Ct/σ ratio move farther from the baseline value and at high Ct/σ ratio move towards the root of the blade for minimizing hub vibration.

Keywords: helicopter rotor, trailing-edge flap, thrust coefficient to solidity (Ct /σ) ratio, optimization

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Authors: Dmitriy Yu. Korulkin, Raissa A. Muzychkina

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The last decade the growth of severe and disseminated forms of inflammatory diseases is observed in Kazakhstan, in particular, septic shock, which progresses on 3-15% of patients with infectious complications of postnatal period. In terms of the rate of occurrence septic shock takes third place after hemorrhagic and cardiovascular shock, in terms of lethality it takes first place. The structure of obstetric sepsis has significantly changed. Currently the first place is taken by postabortive sepsis (40%) that is connected with usage of imperfect methods of artificial termination of pregnancy in late periods (intraamnial injection of sodium chloride, glucose). The second place is taken by postnatal sepsis (32%); the last place is taken by septic complications of caesarean section (28%). In this connection, search for and assessment of effectiveness of new medicines for treatment of postoperative infectious complications, having biostimulating effect and speeding up regeneration processes, is very promising and topical. Essential oil was obtained by the method hydrodistillation air-dry aerial part of Sedum L. plants using Clevenger apparatus. Pilot batch of plant medicinal product based on Sedum essential oils was produced by Chimpharm JSC, Santo Member of Polpharma Group (Kazakhstan). During clinical test of the plant medicinal product based on Sedum L. essential oils 37 female patients at the age from 35 to 57 with clinical signs of complicated postoperative processes and 12 new mothers with clinical signs of inflammatory process on sutures on anterior abdominal wall after caesarean section and partial disruption of surgical suture line on perineum were examined. Medicine usage methods - surgical wound treatment 2 times a day, treatment with other medicines of local action was not performed. Before and after treatment general clinical test, determination of immune status, bacterioscopic test of wound fluid was performed to all women, medical history data was taken into account, wound cleansing and healing time, full granulations, side effects and complications, satisfaction with the used medicine was assessed. On female patients with inflammatory infiltration and partial disruption of surgical suture line anesthetic wound healing effect of plant medicinal product based on Sedum L. essential oils was observed as early as on the second day after beginning of using it, wound cleansing took place, as a rule, within the first row days. Hyperemia in the area of suture line also was not observed for 2-3-d day of usage of medicine, good constant course was observed. The absence of clinical effect on this group of patients was not registered. The represented data give evidence of that clinical effect was accompanied with normalization of changed laboratory findings. No allergic responses or side effects were observed during usage of the plant medicinal products based on Sedum L. essential oils.

Keywords: antiinflammatory, bioactive substances, essential oils, isolation, sedum L., wound healing

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Authors: Seongjun Kim, Sanghoon Shim, Jinwooung Kim, Jaehwan Jung, Sung-Ah Kim

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As the development of information and communication technology, the convergence of machine learning of the ICT area and design is attempted. In this way, it is possible to grasp the correlation between various design elements, which was difficult to grasp, and to reflect this in the design result. In architecture, there is an attempt to predict the performance, which is difficult to grasp in the past, by finding the correlation among multiple factors mainly through machine learning. In architectural design area, some attempts to predict the performance affected by various factors have been tried. With machine learning, it is possible to quickly predict performance. The aim of this study is to propose a model that predicts performance according to the block arrangement of apartment housing through machine learning and the design alternative which satisfies the performance such as the daylight hours in the most similar form to the alternative proposed by the designer. Through this study, a designer can proceed with the design considering various design alternatives and accurate performances quickly from the early design stage.

Keywords: apartment housing, machine learning, multi-objective optimization, performance prediction

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Authors: Elizalde D. Bana

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Healing restores continuity and form through cell replication; hence, conserving structural integrity. In response to the worldwide pressing problem of chronic wounds in the healthcare delivery system, the researcher aims to provide effective intervention to preserve the structural integrity of the person. The wound healing effects of cryopreserved and lyophilized amniotic membrane (AM) of a term fetus embedded into two (2) concentrations (1.5 % and 1.0 %) of absorption-based ointment has been evaluated in vivo using the excision wound healing model 1x1 cm size. The total protein concentration in full term fetus was determined by the Biuret and Bradford methods, which are based on UV-visible spectroscopy. The percentages of protein presence in 9.5 mg (Mass total sample) of Amniotic membrane ranges between 14.77 – 14.46 % in Bradford method, while slightly lower to 13.78 – 13.80 % concentration in Biuret method, respectively. Bradford method evidently showed higher sensitivity for proteins than Biuret test. Overall, the amniotic membrane is composed principally of proteins in which a copious amount of literature substantially proved its healing abilities. After which, an area of 1 cm by 1 cm skin tissue was excised to its full thickness from the dorsolateral aspect of the isogenic mice and was applied twice a day with the ointment formulation having two (2) concentrations for the diabetic group and non-diabetic group. The wounds of each animal were left undressed and its area was measured every other day by a standard measurement formula from day 2,4,6,8,10,12 and 14. By the 14th day, the ointment containing 1.5 % of AM in absorption-based ointment applied to non-diabetic and diabetic group showed 100 % healing. The wound areas in the animals treated with the standard antibiotic, Mupirocin Ointment (Brand X) showed a 100% healing by the 14th day but with traces of scars, indicating that AM prepared from cryopreservation and lyophilization, at that given concentration, had a better wound healing property than the standard antibiotic. Four (4) multivariate tests were used which showed a significant interaction between days and treatments, meaning that the ointments prepared in two differing concentrations and induced in different groups of the mice had a significant effect on the percent of contraction over time. Furthermore, the evaluations of its effectiveness to wound healing were all significant although in differing degrees. It is observed that the higher the concentrations of amniotic membrane, the more effective are the results.

Keywords: wounds, healing, amniotic membrane ointments, biomedical, stem cell

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Authors: W. Mohammedsaeed, A. J. Mcbain, S. M. Cruickshank, C. A. O’Neill

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Many studies have demonstrated the importance of probiotics and their potential therapeutic effects within the gut. Recently, the possible therapeutic effects of probiotics in other tissues have also begun to be investigated. Comparatively few studies have evaluated the use of topical probiotics in relation to the skin. In this study, we have conducted preliminary investigations into whether a well-known probiotic, Lactobacillus rhamnosus GG (LGG), can increase the rate of re-epithelialization in a model wound. Full-thickness skin was obtained from individuals undergoing elective cosmetic surgery. This skin was wounded using excisional punch and cultured using a serum-free medium, either in the presence or absence of L. rhamnosus GG lysate. Histological staining of the sections was performed with Haematoxylin& Eosin E to quantify “epithelial tongue length”. This is the length of the new epithelial ‘tongue’ that grows and covers the exposed dermis at the inner wound edges. The length of the new epithelial ‘tongue’ was compared in untreated section and section treated with and L. rhamnosus GG made using108CFU/ml bacterial cells. L. rhamnosus GG lysate enhanced significantly the re-epithelialisation of treated wounds compared with that of untreated wounds (P=0.005, n=3). Tongue length, at day 1 was 7.55μm 0.15, at day 3 it was 18.5μm 0.25 and at day 7 was 22.9μm 0.35. These results can be compared with untreated cultures in which tongue length was 3.25μm 0.35, day 3 was 9.65μm 0.25 and day 7 was 13.5μm 0.15 post-wounding. In ex-vivo proliferation and migration cells were measured by determining the expression of nuclear proliferation marker Ki-67 and the expression of Phosphorylated cortactin respectively demonstrated that L. rhamnosus GG significantly increased NHEK proliferation and migration rates relative to controls. However, the dominant mechanism was migration because in ex-vivo skin treated with the L. rhamnosus GG up-regulated the gene expression of the chemokine receptor and ligands CXCR2 and CXCL2 comparing with controls (P=0.02, P=0.03 respectively, n=3). High levels of CXCL2/CXCL2 have already been implicated in multiple aspects of stimulation of wound healing through activation of keratinocyte migration. These data demonstrate that lysates from Lactobacillus rhamnosus GG increase re-epithelialization by stimulation of keratinocyte migration. The current study identifies the partial mechanism that contribute to stimulating the wound-healing process ex vivo in response to L. rhamnosus GG lysate is an increase in the production of CXCL2/ CXCR2 in ex vivo models. The use of probiotic lysates potentially offers new options to develop treatments that could improve wound healing.

Keywords: Lactobacillus rhamnosus GG, wounds, migration, lysate

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Authors: Francis Ojo Ologunagba, Monday Olatunbosun Ale, Lewis A. Olutayo

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The economic successes of commercial development of agricultural product processing depend upon the adaptability of each processing stage to mechanization. In maize processing, one of its post-harvest operations that is still facing a major challenge is dehusking. Therefore, a maize dehusking machine that could replace the prevalent traditional method of dehusking maize in developing countries, especially Nigeria was designed, constructed and tested at the Department of Agricultural and Bio-Environmental Engineering Technology, Rufus Giwa Polytechnic, Owo. The basic features of the machine are feeding unit (hopper), housing frame, dehusking unit, drive mechanism and discharge outlets. The machine was tested with maize of 50mm average diameter at 13% moisture content and 2.5mm machine roller clearance. Test results showed appreciable performance with the dehusking efficiency of 92% and throughput capacity of 200 Kg/hr at a machine speed of 400rpm. The estimated production cost of the machine at the time of construction is forty-five thousand, one hundred and eighty nairas (₦45,180) excluding the cost of the electric motor. It is therefore recommended for small and medium-scale maize farmers and processors in Nigeria.

Keywords: construction, dehusking, design, efficiency, maize

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Authors: Yanmeng Liu

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This article analyzes and compares the linguistic differences between machine translation and manual translation, through a case study of the book Gone with the Wind. As an important carrier of human feeling and thinking, the literature translation poses a huge difficulty for machine translation, and it is supposed to expose distinct translation features apart from manual translation. In order to display linguistic features objectively, tentative uses of computerized and statistical evidence to the systematic investigation of large scale translation corpora by using quantitative methods have been deployed. This study compiles bilingual corpus with four versions of Chinese translations of the book Gone with the Wind, namely, Piao by Chunhai Fan, Piao by Huairen Huang, translations by Google Translation and Baidu Translation. After processing the corpus with the software of Stanford Segmenter, Stanford Postagger, and AntConc, etc., the study analyzes linguistic data and answers the following questions: 1. How does the machine translation differ from manual translation linguistically? 2. Why do these deviances happen? This paper combines translation study with the knowledge of corpus linguistics, and concretes divergent linguistic dimensions in translated text analysis, in order to present linguistic deviances in manual and machine translation. Consequently, this study provides a more accurate and more fine-grained understanding of machine translation products, and it also proposes several suggestions for machine translation development in the future.

Keywords: corpus-based analysis, linguistic deviances, machine translation, statistical evidence

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Authors: Mohammad Syed Ali Molla, Mohammed Azim, Mohammad Esharuzzaman

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Centrifugal-casting machine is used in manufacturing special machine components like multi-layer journal bearing used in all internal combustion engine, steam, gas turbine and air craft turboengine where isotropic properties and high precisions are desired. Moreover, this machine can be used in manufacturing thin wall hightech machine components like cylinder liners and piston rings of IC engine and other machine parts like sleeves, and bushes. Heavy-duty machine component like railway wheel can also be prepared by centrifugal casting. A lot of technological developments are required in casting process for production of good casted machine body and machine parts. Usually defects like blowholes, surface roughness, chilled surface etc. are found in sand casted machine parts. But these can be removed by centrifugal casting machine using rotating metallic die. Moreover, die rotation, its temperature control, and good pouring practice can contribute to the quality of casting because of the fact that the soundness of a casting in large part depends upon how the metal enters into the mold or dies and solidifies. Poor pouring practice leads to variety of casting defects such as temperature loss, low quality casting, excessive turbulence, over pouring etc. Besides these, handling of molten metal is very unsecured and dangerous for the workers. In order to get rid of all these problems, the need of an automatic pouring device arises. In this research work, a robot assisted pouring device and a centrifugal casting machine are designed, developed constructed and tested experimentally which are found to work satisfactorily. The robot assisted pouring device is further modified and developed for using it in actual metal casting process. Lot of settings and tests are required to control the system and ultimately it can be used in automation of centrifugal casting machine to produce high-tech machine parts with desired precision.

Keywords: bearing, centrifugal casting, cylinder liners, robot

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Authors: Mark McGuire, Eric Shannon, John Parmigiani

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Timber harvesting increasingly involves mechanized equipment. This has increased the efficiency of harvesting, but has also introduced worker-safety concerns. One such concern arises from the use of harvesters. During operation, harvesters subject saw chain to large dynamic mechanical stresses. These stresses can, under certain conditions, cause the saw chain to fracture. The high speed of harvester saw chain can cause the resulting open chain loop to fracture a second time due to the dynamic loads placed upon it as it travels through space. If a second fracture occurs, it can result in a projectile consisting of one-to-several chain links. This projectile is referred to as a chain shot. It has speeds similar to a bullet but typically has greater mass and is a significant safety concern. Numerous examples exist of chain shots penetrating bullet-proof barriers and causing severe injury and death. Improved harvester-cab barriers can help prevent injury however a comprehensive scientific understanding of chain shot is required to consistently reduce or prevent it. Obtaining this understanding requires a test machine with the capability to cause chain shot to occur under carefully controlled conditions and accurately measure the response. Worldwide few such test machine exist. Those that do focus on validating the ability of barriers to withstand a chain shot impact rather than obtaining a scientific understanding of the chain shot event itself. The purpose of this paper is to describe the design, fabrication, and use of a test machine capable of a comprehensive scientific investigation of chain shot. The capabilities of this machine are to test all commercially-available saw chains and bars at chain tensions and speeds meeting and exceeding those typically encountered in harvester use and accurately measure the corresponding key technical parameters. The test machine was constructed inside of a standard shipping container. This provides space for both an operator station and a test chamber. In order to contain the chain shot under any possible test conditions, the test chamber was lined with a base layer of AR500 steel followed by an overlay of HDPE. To accommodate varying bar orientations and fracture-initiation sites, the entire saw chain drive unit and bar mounting system is modular and capable of being located anywhere in the test chamber. The drive unit consists of a high-speed electric motor with a flywheel. Standard Ponsse harvester head components are used to bar mounting and chain tensioning. Chain lubrication is provided by a separate peristaltic pump. Chain fracture is initiated through ISO standard 11837. Measure parameters include shaft speed, motor vibration, bearing temperatures, motor temperature, motor current draw, hydraulic fluid pressure, chain force at fracture, and high-speed camera images. Results show that the machine is capable of consistently causing chain shot. Measurement output shows fracture location and the force associated with fracture as a function of saw chain speed and tension. Use of this machine will result in a scientific understanding of chain shot and consequently improved products and greater harvester operator safety.

Keywords: chain shot, safety, testing, timber harvesters

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Authors: Yukiko Sasaki Alam

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This research aims at finding out the causes that led to wrong lexical selections in machine translation (MT) rather than categorizing lexical errors, which has been a main practice in error analysis. By manually examining and analyzing lexical errors outputted by a MT system, it suggests what knowledge would help the system reduce lexical errors.

Keywords: machine translation, error analysis, lexical errors, evaluation

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Authors: Lebogang L. R. Mphahlele, Bruce B. Sithole

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Chicken meat is the highest consumed meat in south Africa, with a per capita consumption of >33 kg yearly. Hence, South Africa produces over 250 million kg of waste chicken feathers each year, the majority of which is landfilled or incinerated. The discarded feathers have caused environmental pollution and natural protein resource waste. Therefore, the valorisation of waste chicken feathers is measured as a more environmentally friendly and cost-effective treatment. Feather contains 91% protein, the main component being beta-keratin, a fibrous and insoluble structural protein extensively cross linked by disulfide bonds. Keratin is usually converted it into nanofibers via electrospinning for a variety of applications. keratin nanofiber composites have many potential biomedical applications for their attractive features, such as high surface-to-volume ratio and very high porosity. The application of nanofibers in the biomedical wound dressing requires antimicrobial properties for materials. One approach is incorporating inorganic nanoparticles, among which silver nanoparticles played an important alternative antibacterial agent and have been studied against many types of microbes. The objective of this study is to combine synthetic polymer, chicken feather keratin, and antibacterial nanoparticles to develop novel electrospun antibacterial nanofibrous composites for possible wound dressing application. Furthermore, this study will converting a two-dimensional electrospun nanofiber membrane to three-dimensional fiber networks that resemble the structure of the extracellular matrix (ECM)

Keywords: chicken feather keratin, nanofibers, nanoparticles, nanocomposites, wound dressing

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Authors: Carlos Roncero-Parra, Alfonso Parreño-Torres, Jorge Mateo Sotos, Alejandro L. Borja

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In this research, different methods based on machine/deep learning algorithms are presented for the classification and diagnosis of patients with mental disorders such as alzheimer. For this purpose, the signals obtained from 32 unipolar electrodes identified by non-invasive EEG were examined, and their basic properties were obtained. More specifically, different well-known machine learning based classifiers have been used, i.e., support vector machine (SVM), Bayesian linear discriminant analysis (BLDA), decision tree (DT), Gaussian Naïve Bayes (GNB), K-nearest neighbor (KNN) and Convolutional Neural Network (CNN). A total of 668 patients from five different hospitals have been studied in the period from 2011 to 2021. The best accuracy is obtained was around 93 % in both ADM and ADA classifications. It can be concluded that such a classification will enable the training of algorithms that can be used to identify and classify different mental disorders with high accuracy.

Keywords: alzheimer, machine learning, deep learning, EEG

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Authors: Anli Du Preez, James Bekker

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Data is currently one of the most critical and influential emerging technologies. However, the true potential of data is yet to be exploited since, currently, about 1% of generated data are ever actually analyzed for value creation. There is a data gap where data is not explored due to the lack of data analytics infrastructure and the required data analytics skills. This study developed a decision support framework for data analytics by following Jabareen’s framework development methodology. The study focused on machine learning algorithms, which is a subset of data analytics. The developed framework is designed to assist data analysts with little experience, in choosing the appropriate machine learning algorithm given the purpose of their application.

Keywords: Data analytics, Industrial engineering, Machine learning, Value creation

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Authors: Abdellah Boualouch, Ahmed Essadki, Tamou Nasser, Ali Boukhriss, Abdellatif Frigui

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This paper presents a power control for a Doubly Fed Induction Generator (DFIG) using in Wind Energy Conversion System (WECS) connected to the grid. The proposed control strategy employs two nonlinear controllers, Backstipping (BSC) and sliding-mode controller (SMC) scheme to directly calculate the required rotor control voltage so as to eliminate the instantaneous errors of active and reactive powers. In this paper the advantages of BSC and SMC are presented, the performance and robustness of this two controller’s strategy are compared between them. First, we present a model of wind turbine and DFIG machine, then a synthesis of the controllers and their application in the DFIG power control. Simulation results on a 1.5MW grid-connected DFIG system are provided by MATLAB/Simulink.

Keywords: backstipping, DFIG, power control, sliding-mode, WESC

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Authors: Peter Adekunle, Clinton Aigbavboa, Matthew Ikuabe, Opeoluwa Akinradewo

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The future of machine learning (ML) in building may seem like a distant idea that will take decades to materialize, but it is actually far closer than previously believed. In reality, the built environment has been progressively increasing interest in machine learning. Although it could appear to be a very technical, impersonal approach, it can really make things more personable. Instead of eliminating humans out of the equation, machine learning allows people do their real work more efficiently. It is therefore vital to evaluate the factors influencing the implementation and challenges of implementing machine learning techniques in the South African built environment. The study's design was one of a survey. In South Africa, construction workers and professionals were given a total of one hundred fifty (150) questionnaires, of which one hundred and twenty-four (124) were returned and deemed eligible for study. Utilizing percentage, mean item scores, standard deviation, and Kruskal-Wallis, the collected data was analyzed. The results demonstrate that the top factors influencing the adoption of machine learning are knowledge level and a lack of understanding of its potential benefits. While lack of collaboration among stakeholders and lack of tools and services are the key hurdles to the deployment of machine learning within the South African built environment. The study came to the conclusion that ML adoption should be promoted in order to increase safety, productivity, and service quality within the built environment.

Keywords: machine learning, implementation, built environment, construction stakeholders

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Authors: Chaouch Souad, Abdou Latifa, Larbi Chrifi Alaoui

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This paper deals with sensorless backstepping control of induction motor using MRAS technique associated to sliding mode approach. A high order genetic algorithm structure is used to approximate a control law designed by the Backstepping technique, and to find the best parameters globally optimized. However, the Backstepping control approach is unsuitable for high performance applications because the need of a speed sensor for increased accuracy and the absence of any error decay mechanism. In this paper a nonlinear observer, obtained by combining sliding mode structure and model reference adaptive system (MRAS), is designed for the rotor flux and rotor speed estimations. To validate the proposed method, the results are presented for showing the improved drive characteristics and performances.

Keywords: Backstepping Control, Induction Motor, Genetic Algorithm, Sliding Mode observer

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Authors: Magdy Al Shourbagi

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Diabetes mellitus is the commonest cause of neuropathy. The common pattern is a distal symmetrical sensory polyneuropathy, associated with autonomic disturbances. Less often, Diabetes mellitus is responsible for a focal or multifocal neuropathy. Common causes for non-healing of diabetic foot are the infection and ischemia. Diabetes mellitus is associated with a defective cellular and humoral immunity. Particularly, decreased phagocytosis, decreased chemotaxis, impaired bacterial killing and abnormal lymphocytic function resulting in a reduced inflammatory reaction and defective wound healing. Hyperbaric oxygen therapy is defined by the Undersea and Hyperbaric Medical Society as a treatment in which a patient intermittently breathes 100% oxygen and the treatment chamber is pressurized to a pressure greater than sea level (1 atmosphere absolute). The pressure increase may be applied in mono-place (single person) or multi-place chambers. Multi-place chambers are pressurized with air, with oxygen given via face mask or endotracheal tube; while mono-place chambers are pressurized with oxygen. Oxygen gas plays an important role in the physiology of wound healing. Hyperbaric oxygen therapy can raise tissue oxygen tensions to levels where wound healing can be expected. HBOT increases the killing ability of leucocytes also it is lethal for certain anaerobic bacteria and inhibits toxin formation in many other anaerobes. Multiple anecdotal reports and studies in HBO therapy in diabetic patients report that HBO can be an effective adjunct therapy in the management of diabetic foot wounds and is associated with better functional outcomes.

Keywords: hyperbari oxygen therapy, diabetic foot, neuropathy, multiplace chambers

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Authors: Stephen Kyakulumbye, Vivian Kobusingye

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Generally, World over, COVID-19 has had adverse effects on all sectors but with more debilitating effects on the education sector. After reactive lockdowns, education institutions that could continue teaching and learning had to go a distance mediated by digital technological tools. In Uganda, the Ministry of Education thereby issued COVID-19 Online Distance E-learning (ODeL) emergent guidelines. Despite such guidelines, academic institutions in Uganda and similar developing contexts with academically constrained resource environments were caught off-guard and ill-prepared to transform from face-to-face learning to online distance learning mode. Most academic institutions that migrated spontaneously did so with no deliberate tools, systems, strategies, or software to cause active, meaningful, and engaging learning for students. By experience, most of these academic institutions shifted to Zoom and WhatsApp and instead conducted online teaching in real-time than blended synchronous and asynchronous tools. This paper provides students’ experiences while blending synchronous and asynchronous content-creating and learning tools within a technological resource-constrained environment to navigate in such a challenging Uganda context. These conceptual case-based findings, using experience from Uganda Christian University (UCU), point at the design of learning activities with two certain characteristics, the enhancement of synchronous learning technologies with asynchronous ones to mitigate the challenge of system breakdown, passive learning to active learning, and enhances the types of presence (social, cognitive and facilitatory). The paper, both empirical and experiential in nature, uses online experiences from third-year students in Bachelor of Business Administration student lectured using asynchronous text, audio, and video created with Open Broadcaster Studio software and compressed with Handbrake, all open-source software to mitigate disk space and bandwidth usage challenges. The synchronous online engagements with students were a blend of zoom or BigBlueButton, to ensure that students had an alternative just in case one failed due to excessive real-time traffic. Generally, students report that compared to their previous face-to-face lectures, the pre-recorded lectures via Youtube provided them an opportunity to reflect on content in a self-paced manner, which later on enabled them to engage actively during the live zoom and/or BigBlueButton real-time discussions and presentations. The major recommendation is that lecturers and teachers in a resource-constrained environment with limited digital resources like the internet and digital devices should harness this approach to offer students access to learning content in a self-paced manner and thereby enabling reflective active learning through reflective and high-order thinking.

Keywords: synchronous learning, asynchronous learning, active learning, reflective learning, resource-constrained environment

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Authors: Guang Yang, Zhiwei Bai, Bo Sun

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This paper analyzes the influence of failure mode and harmfulness of rotative machine according to FMECA (Failure Mode, Effects, and Criticality Analysis) method, and finds out the weak links that affect the reliability of this equipment. Also in this paper, fault tree analysis software is used for quantitative and qualitative analysis, pointing out the main factors of failure of this equipment. Based on the experimental results, this paper puts forward corresponding measures for prevention and improvement, and fundamentally improves the inherent reliability of this rotative machine, providing the basis for the formulation of technical conditions for the safe operation of industrial applications.

Keywords: rotative machine, reliability test, fault tree analysis, FMECA

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Authors: Benjamen Nathaniel, Eludiora Safiriyu Ijiyemi, Egume Oneme Lucky

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A review on machine translation systems shows that a lot of computational artefacts has been carried out to translate written or spoken texts from a source language to Yorùbá language through Machine Translation systems. However, there are no work on French to Yorùbá language machine translation system; hence, the study investigated the process involved in the translation of French-to-Yorùbá language equivalent with the view to adopting a rule- based MT approach to build a Machine Translation framework from simple sentences administered through questionnaire. Articles and relevant textbooks were reviewed with key speakers of both languages interviewed to find out the processes involved in the translation of French language and their equivalent in Yorùbálanguage simple sentences using home domain terminologies. Achieving this, a model was formulated using phrase grammar structure, re-write rule, parse tree, automata theory- based techniques, designed and implemented respectively with unified modeling language (UML) and python programming language. Analysing the result, it was observed when carrying out the result that, the Machine Translation system performed 18.45% above Experimental Subject Respondent and 2.7% below Linguistics Expert when analysed with word orthography, sentence syntax and semantic correctness of the sentences. And, when compared with Google Machine Translation system, it was noticed that the developed system performed better on lexicons of the target language.

Keywords: machine translation (MT), rule-based, French language, Yoru`ba´ language

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

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The widespread use of machine learning applications in production is significantly accelerated by improved computing power and increasing data availability. Predictive quality enables the assurance of product quality by using machine learning models as a basis for decisions on test results. The use of real Bosch production data based on geometric gauge blocks from machining, mating data from assembly and hydraulic measurement data from final testing of directional valves is a promising approach to classifying the quality characteristics of workpieces.

Keywords: machine learning, classification, predictive quality, hydraulics, supervised learning

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Authors: Dong-Woo Kang

Abstract:

This paper presents an optimal magnet shape of a spoke-shaped interior permanent magnet synchronous motor by using ferrite magnets. Generally, the permanent magnet motor used the ferrite magnets has lower output power and efficiency than a rare-earth magnet motor, because the ferrite magnet has lower magnetic energy than the rare-earth magnet. Nevertheless, the ferrite magnet motor is used to many industrial products owing to cost effectiveness. In this paper, the authors propose a high power density design of the ferrite permanent magnet synchronous motor. Furthermore, because the motor design has to be taken a manufacturing process into account, the design is simulated by using the finite element method for analyzing the demagnetization, the magnetizing, and the structure stiffness. Especially, the magnet shape and dimensions are decided for satisfying these properties. Finally, the authors design an optimal motor for applying our system. That final design is manufactured and evaluated from experimentations.

Keywords: demagnetization, design optimization, magnetic analysis, permanent magnet motors

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Authors: Mohamed Gouda

Abstract:

Antibacterial wound dressings based on cellulose nanofibers containing different metal nanoparticles (CMC-MNPs) were synthesized using an electrospinning technique. First, the composite of carboxymethyl cellulose containing different metal nanoparticles (CMC/MNPs), such as copper nanoparticles (CuNPs), iron nanoparticles (FeNPs), zinc nanoparticles (ZnNPs), cadmium nanoparticles (CdNPs) and cobalt nanoparticles (CoNPs) were synthesized, and finally, these composites were transferred to the electrospinning process. Synthesized CMC-MNPs were characterized using scanning electron microscopy (SEM) coupled with high-energy dispersive X-ray (EDX) and UV-visible spectroscopy used to confirm nanoparticle formation. The SEM images clearly showed regular flat shapes with semi-porous surfaces. All MNPs were well distributed inside the backbone of the cellulose without aggregation. The average particle diameters were 29-39 nm for ZnNPs, 29-33 nm for CdNPs, 25-33 nm for CoNPs, 23-27 nm for CuNPs and 22-26 nm for FeNPs. Surface morphology, water uptake and release of MNPs from the nanofibers in water and antimicrobial efficacy were studied. SEM images revealed that electrospun CMC-MNPs nanofibers are smooth and uniformly distributed without bead formation with average fiber diameters in the range of 300 to 450 nm. Fiber diameters were not affected by the presence of MNPs. TEM images showed that MNPs are present in/on the electrospun CMC-MNPs nanofibers. The diameter of the electrospun nanofibers containing MNPs was in the range of 300–450 nm. The MNPs were observed to be spherical in shape. The CMC-MNPs nanofibers showed good hydrophilic properties and had excellent antibacterial activity against the Gram-negative bacteria Escherichia coli and the Gram-positive bacteria Staphylococcus aureus.

Keywords: electrospinning technique, metal nanoparticles, cellulosic nanofibers, wound dressing

Procedia PDF Downloads 303