Search results for: machine repair

Authors: Ahmed A.D. Sarhan, Chong Feng Duan, Mum Wai Yip, M. Sayuti

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Rapid Prototyping (RP) technologies enable physical parts to be produced from various materials without depending on the conventional tooling. Fused Deposition Modeling (FDM) is one of the famous RP processes used at present. Tensile strength and compressive strength resistance will be identified for different sample structures and different layer orientations of ABS rapid prototype solid models. The samples will be fabricated by a FDM rapid prototyping machine in different layer orientations with variations in internal geometrical structure. The 0° orientation where layers were deposited along the length of the samples displayed superior strength and impact resistance over all the other orientations. The anisotropic properties were probably caused by weak interlayer bonding and interlayer porosity.

Keywords: building orientation, compression strength, rapid prototyping, tensile strength

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Authors: Shingo Murakami, Shinichi Enoki

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In structures, stress concentration is a factor of fatigue fracture. Basically, the stress concentration is a phenomenon that should be avoided. However, it is difficult to avoid the stress concentration. Therefore, relaxation of the stress concentration is important. The stress concentration arises from notches and circular holes. There is a relaxation method that a composite patch covers a notch and a circular hole. This relaxation method is used to repair aerial wings, but it is not systematized. Composites are more expensive than single materials. Accordingly, we propose the relaxation method that a single material patch covers a notch and a circular hole, and aim to systematize this relaxation method. We performed FEA (Finite Element Analysis) about an object by using a three-dimensional FEA model. The object was that a patch adheres to a plate with a circular hole. And, a uniaxial tensile load acts on the patched plate with a circular hole. In the three-dimensional FEA model, it is not easy to model the adhesion layer. Basically, the yield stress of the adhesive is smaller than that of adherents. Accordingly, the adhesion layer gets to plastic deformation earlier than the adherents under the yield load of adherents. Therefore, we propose the three-dimensional FEA model which is applied a nonlinear elastic region to the adhesion layer. The nonlinear elastic region was calculated by a bilinear approximation. We compared the analysis results with the tensile test results to confirm whether the analysis model has usefulness. As a result, the analysis results agreed with the tensile test results. And, we confirmed that the analysis model has usefulness. As a result that the three-dimensional FEA model was used to the analysis, it was confirmed that an out-of-plane deformation occurred to the patched plate with a circular hole. The out-of-plane deformation causes stress increase of the patched plate with a circular hole. Therefore, we investigated that the out-of-plane deformation affects relaxation of the stress concentration in the plate with a circular hole on this relaxation method. As a result, it was confirmed that the out-of-plane deformation inhibits relaxation of the stress concentration on the plate with a circular hole.

Keywords: stress concentration, patch, out-of-plane deformation, Finite Element Analysis

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Authors: Eric Shannon, Mark J. McGuire, John P. Parmigiani

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A hazard associated with the use of timber harvesters is chain shot. Harvester saw chain is subjected to large dynamic mechanical stresses which can cause it to fracture. The resulting open loop of saw chain can fracture a second time and create a projectile consisting of several saw-chain links referred to as a chain shot. Its high kinetic energy enables it to penetrate operator enclosures and be a significant hazard. Accurate data on projectile composition, mass, and speed are needed for the design of both operator enclosures resistant to projectile penetration and for saw chain resistant to fracture. The work presented here contributes to providing this data through the use of a test machine designed and built at Oregon State University. The machine’s enclosure is a standard shipping container. To safely contain any anticipated chain shot, the container was lined with both 9.5 mm AR500 steel plates and 50 mm high-density polyethylene (HDPE). During normal operation, projectiles are captured virtually undamaged in the HDPE enabling subsequent analysis. Standard harvester components are used for bar mounting and chain tensioning. Standard guide bars and saw chains are used. An electric motor with flywheel drives the system. Testing procedures follow ISO Standard 11837. Chain speed at break was approximately 45.5 m/s. Data was collected using both a 75 cm solid bar (Oregon 752HSFB149) and 90 cm solid bar (Oregon 902HSFB149). Saw chains used were 89 Drive Link .404”-18HX loops made from factory spools. Standard 16-tooth sprockets were used. Projectile speed was measured using both a high-speed camera and a chronograph. Both rotational and translational kinetic energy are calculated. For this study 50 chain shot events were executed. Results showed that projectiles consisted of a variety combinations of drive links, tie straps, and cutter links. Most common (occurring in 60% of the events) was a drive-link / tie-strap / drive-link combination having a mass of approximately 10.33 g. Projectile mass varied from a minimum of 2.99 g corresponding to a drive link only to a maximum of 18.91 g corresponding to a drive-link / tie-strap / drive-link / cutter-link / drive-link combination. Projectile translational speed was measured to be approximately 270 m/s and rotational speed of approximately 14000 r/s. The calculated translational and rotational kinetic energy magnitudes each average over 600 J. This study provides useful information for both timber harvester manufacturers and saw chain manufacturers to design products that reduce the hazards associated with timber harvesting.

Keywords: chain shot, timber harvesters, safety, testing

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Authors: Andrew Kurochkin, Kostiantyn Bokhan

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In this study, a new meme dataset of ~650K meme instances was created, a technology of meme generation based on the state of the art deep learning technique - GPT-2 model was researched, a comparative analysis of machine-generated memes and human-created was conducted. We justified that Amazon Mechanical Turk workers can be used for the approximate estimating of users' behavior in a social network, more precisely to measure engagement. It was shown that generated memes cause the same engagement as human memes that produced low engagement in the social network (historically). Thus, generated memes are less engaging than random memes created by humans.

Keywords: content generation, computational social science, memes generation, Reddit, social networks, social media interaction

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Authors: Carlos Huertas, Reyes Juarez-Ramirez

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Public health is one of the most critical issues today; therefore, there is great interest to improve technologies in the area of diseases detection. With machine learning and feature selection, it has been possible to aid the diagnosis of several diseases such as cancer. In this work, we present an extension to the Heat Map Based Feature Selection algorithm, this modification allows automatic threshold parameter selection that helps to improve the generalization performance of high dimensional data such as mass spectrometry. We have performed a comparison analysis using multiple cancer datasets and compare against the well known Recursive Feature Elimination algorithm and our original proposal, the results show improved classification performance that is very competitive against current techniques.

Keywords: biomarker discovery, cancer, feature selection, mass spectrometry

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Authors: Jose D. Herrera, Mario A. Rios

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This paper deals with the coordinated tuning of the Power System Stabilizer (PSS) controller and Power Oscillation Damping (POD) Controller of Flexible AC Transmission System (FACTS) in a multi-machine power systems. The coordinated tuning is based on the critical eigenvalues of the power system and a model reduction technique where the Hankel Singular Value method is applied. Through the linearized system model and the parameter-constrained nonlinear optimization algorithm, it can compute the parameters of both controllers. Moreover, the parameters are optimized simultaneously obtaining the gains of both controllers. Then, the nonlinear simulation to observe the time response of the controller is performed.

Keywords: electromechanical oscillations, power system stabilizers, power oscillation damping, hankel singular values

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Authors: Mohamed Moustafa Mahmoud Sedky

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In line start permanent magnet synchronous motor, eccentricity is a common fault that can make it necessary to remove the motor from the production line. However, because the motor may be inaccessible, diagnosing the fault is not easy. This paper presents an FEM that identifies different models, static eccentricity, dynamic eccentricity, and mixed eccentricity, at no load and full load. The method overcomes the difficulty of applying FEMs to transient behavior. It simulates motor speed, torque and flux density distribution along the air gap for SE, DE, and ME. This paper represents the various effects of different eccentricities types on the transient performance.

Keywords: line start permanent magnet, synchronous machine, static eccentricity, dynamic eccentricity, mixed eccentricity

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Authors: Jaskirat Singh, Roshan Lal Virdi, Khushdeep Goyal

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The purpose of this paper is to perform a microstructural analysis of Friction Stir Welded joints of aluminum alloys 6063 and 5083, also to check the properties of the weld zone by SEM analysis. FSW experiments were carried on CNC Vertical milling machine. The tools used for welding were the round cylindrical pin shape and square pin shape. It is found that Microstructure shows the uniformly distributed material with minimum heat affected zone and dense welded zone without any defect. Microstructures indicate that the weld material is defect free. The SEM shows the diffusion of material with base metal with proper bonding without any defect.

Keywords: friction stir welding, aluminum alloy, microstructure, SEM analysis

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Authors: T. Thein, S. Kalyar Myo

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Human uses visual information for understanding the speech contents in noisy conditions or in situations where the audio signal is not available. The primary advantage of visual information is that it is not affected by the acoustic noise and cross talk among speakers. Using visual information from the lip movements can improve the accuracy and robustness of automatic speech recognition. However, a major challenge with most automatic lip reading system is to find a robust and efficient method for extracting the linguistically relevant speech information from a lip image sequence. This is a difficult task due to variation caused by different speakers, illumination, camera setting and the inherent low luminance and chrominance contrast between lip and non-lip region. Several researchers have been developing methods to overcome these problems; the one is lip reading. Moreover, it is well known that visual information about speech through lip reading is very useful for human speech recognition system. Lip reading is the technique of a comprehensive understanding of underlying speech by processing on the movement of lips. Therefore, lip reading system is one of the different supportive technologies for hearing impaired or elderly people, and it is an active research area. The need for lip reading system is ever increasing for every language. This research aims to develop a visual teaching method system for the hearing impaired persons in Myanmar, how to pronounce words precisely by identifying the features of lip movement. The proposed research will work a lip reading system for Myanmar Consonants, one syllable consonants (င (Nga)၊ ည (Nya)၊ မ (Ma)၊ လ (La)၊ ၀ (Wa)၊ သ (Tha)၊ ဟ (Ha)၊ အ (Ah) ) and two syllable consonants ( က(Ka Gyi)၊ ခ (Kha Gway)၊ ဂ (Ga Nge)၊ ဃ (Ga Gyi)၊ စ (Sa Lone)၊ ဆ (Sa Lain)၊ ဇ (Za Gwe) ၊ ဒ (Da Dway)၊ ဏ (Na Gyi)၊ န (Na Nge)၊ ပ (Pa Saug)၊ ဘ (Ba Gone)၊ ရ (Ya Gaug)၊ ဠ (La Gyi) ). In the proposed system, there are three subsystems, the first one is the lip localization system, which localizes the lips in the digital inputs. The next one is the feature extraction system, which extracts features of lip movement suitable for visual speech recognition. And the final one is the classification system. In the proposed research, Two Dimensional Discrete Cosine Transform (2D-DCT) and Linear Discriminant Analysis (LDA) with Active Contour Model (ACM) will be used for lip movement features extraction. Support Vector Machine (SVM) classifier is used for finding class parameter and class number in training set and testing set. Then, experiments will be carried out for the recognition accuracy of Myanmar consonants using the only visual information on lip movements which are useful for visual speech of Myanmar languages. The result will show the effectiveness of the lip movement recognition for Myanmar Consonants. This system will help the hearing impaired persons to use as the language learning application. This system can also be useful for normal hearing persons in noisy environments or conditions where they can find out what was said by other people without hearing voice.

Keywords: feature extraction, lip reading, lip localization, Active Contour Model (ACM), Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), Two Dimensional Discrete Cosine Transform (2D-DCT)

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Authors: Hyung Jun Ahn

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With the growing importance of social media, it is imperative to analyze it to understand the users. Users share useful information and their experience through social media, where much of what is shared is in the form of texts. This study focused on blogs and aimed to test whether the psycho-linguistic characteristics of blog texts vary with the subject or the type of experience of the texts. For this goal, blog texts about four different types of experience, Go, skiing, reading, and musical were collected through the search API of the Tistory blog service. The analysis of the texts showed that various psycholinguistic characteristics of the texts are different across the four categories of the texts. Moreover, the machine learning experiment using the characteristics for automatic text classification showed significant performance. Specifically, the ensemble method, based on functional tree and bagging appeared to be most effective in classification.

Keywords: blog, social media, text analysis, psycholinguistics

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Authors: Rupan Preet Kaur

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This article reviewed the potential of artificial intelligence in the field of identity and access management (IAM) and identity governance and administration (IGA), the most critical pillars of any organization. The power of leveraging AI in the most complex and huge user base environment was outlined by simplifying and streamlining the user access approvals and re-certifications without any impact on the user productivity and at the same time strengthening the overall compliance of IAM landscape. Certain challenges encountered in the current state were detailed where majority of organizations are still lacking maturity in the data integrity aspect. Finally, this paper concluded that within the realm of possibility, users and application owners can reap the benefits of unified approach provided by AI to improve the user experience, improve overall efficiency, and strengthen the risk posture.

Keywords: artificial intelligence, machine learning, user access review, access approval

Procedia PDF Downloads 83

Authors: Shilpi Malik, Ramneek Kaur, Archita Gupta, Deepshikha Yadav, Ashwani Mathur, Manisha Singh

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Glucosamine (GS) is the most abundant naturally occurring amino monosaccharide and is normally produced in human body via cellular glucose metabolism. It is regarded as the building block of cartilage matrix and is also an essential component of cartilage matrix repair mechanism. Besides that, it can also be explored for its prebiotic potential as many bacterial species are known to utilize the amino sugar by acquiring them to form peptidoglycans and lipopolysaccharides in the bacterial cell wall. Glucosamine can therefore be considered for its fermentation by bacterial species present in the gut. Current study is focused on exploring the potential of glucosamine as prebiotic. The studies were done to optimize considerable concentration of GS to reach GI tract and being fermented by the complex gut microbiota and food grade GS was added to various Simulated Fluids of Gastro-Intestinal Tract (GIT) such as Simulated Saliva, Gastric Fluid (Fast and Fed State), Colonic fluid, etc. to detect its degradation. Since it was showing increase in microbial growth (CFU) with time, GS was Further, encapsulated to increase its residential time in the gut, which exhibited improved resistance to the simulated Gut conditions. Moreover, prepared microspehres were optimized and characterized for their encapsulation efficiency and toxicity. To further substantiate the prebiotic activity of Glucosamine, studies were also performed to determine the effect of Glucosamine on the known probiotic bacterial species, i.e. Lactobacillus delbrueckii (MTCC 911) and Bifidobacteriumbifidum (MTCC 5398). Culture conditions for glucosamine will be added in MRS media in anaerobic tube at 0.20%, 0.40%, 0.60%, 0.80%, and 1.0%, respectively. MRS media without GS was included in this experiment as the control. All samples were autoclaved at 118° C for 15 min. Active culture was added at 5% (v/v) to each anaerobic tube after cooling to room temperature and incubated at 37° C then determined biomass and pH and viable count at incubation 18h. The experiment was completed in triplicate and the results were presented as Mean ± SE (Standard error).The experimental results are conclusive and suggest Glucosamine to hold prebiotic properties.

Keywords: gastro intestinal tract, microspheres, peptidoglycans, simulated fluid

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Authors: Sayor Ajfar Aaron, Mushfiqur Rahman, Sajjat Hossain Abir, Ashif Newaz

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This study delves into the development of an artificial intelligence application designed for real-time emotion recognition from human vocal patterns. Utilizing advanced machine learning algorithms, including deep learning and neural networks, the paper highlights both the technical challenges and potential opportunities in accurately interpreting emotional cues from speech. Key findings demonstrate the critical role of diverse training datasets and the impact of ambient noise on recognition accuracy, offering insights into future directions for improving robustness and applicability in real-world scenarios.

Keywords: artificial intelligence, convolutional neural network, emotion recognition, vocal patterns

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Authors: Mohammad Mahdi Hajiali

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Many of construction projects estimated in Iran have been influenced by the limitations of financial resources. As for Iran, a country that is developing, and to follow this development-oriented approach which many numbers of projects each year run in, if we can reduce the cost of projects by applying a method we will help greatly to minimize the cost of major construction projects and therefore projects will finish faster and more efficiently. One of the components of transportation infrastructure are roads that are considered to have a considerable share of the country budget. In addition, major budget of the related ministry is spending to repair, improve and maintain roads. Value Engineering is a simple and powerful methodology over the past six decades that has been successful in reducing the cost of many projects. Specific solution for using value engineering in the stage of project implementation is called value engineering change proposal (VECP). It was tried in this research to apply VECP in one of the road-building projects in Iran in order to enhance the value of this kind of projects and reduce their cost. In this case study after applying VECP, an idea was raised. It was about use of concrete pavement instead of hot mixed asphalt (HMA) and also using fiber in order to improve concrete pavement performance. VE group team made a decision that for choosing the best alternatives, get expert’s opinions in pavement systems and use Fuzzy TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) for ranking opinions of the experts. Finally, Jointed Plain Concrete Pavement (JPCP) was selected. Group also experimented concrete samples with available fibers in Iran and the results of experiments showed a significant increment in concrete specifications such as flexural strength. In the end, it was shown that by using of fiber-reinforced concrete pavement instead of asphalt pavement, we can achieve a significant saving in cost, time and also increment in quality, durability, and longevity.

Keywords: road-building projects, value engineering change proposal (VECP), Jointed Plain Concrete Pavement (JPCP), Fuzzy TOPSIS, fiber-reinforced concrete

Procedia PDF Downloads 184

Authors: Santhosh Kumat T., Priya E.

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The control of a doubly fed induction generator by fuzzy is described. The active and reactive power can be controlled by rotor and grid side converters with fuzzy controller. The main objective is to maintain constant voltage and frequency at the output of the generator. However the Line Side Converter (LSC) can be controlled to supply up to 50% of the required reactive current. When the crowbar is not activated the DFIG can supply reactive power from the rotor side through the machine as well as through the LSC.

Keywords: Doubly Fed Induction Generator (DFIG), Rotor Side Converter (RSC), Grid Side Converter (GSC), Wind Energy Conversion Systems (WECS)

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Authors: Shiva Abdoli, Daniel T.Semere

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Several researches have been conducted to study consumption of energy in cutting process. Most of these researches are focusing to measure the consumption and propose consumption reduction methods. In this work, the relation between the cutting parameters and the consumption is investigated in order to establish a generalized energy consumption model that can be used for process and production planning in real production lines. Using the generalized model, the process planning will be carried out by taking into account the energy as a function of the selected process parameters. Similarly, the generalized model can be used in production planning to select the right operational parameters like batch sizes, routing, buffer size, etc. in a production line. The description and derivation of the model as well as a case study are given in this paper to illustrate the applicability and validity of the model.

Keywords: process parameters, cutting process, energy efficiency, Material Removal Rate (MRR)

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Authors: S. Kherchaoui, A. Houacine

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This paper presents a facial expression recognition system. It performs identification and classification of the seven basic expressions; happy, surprise, fear, disgust, sadness, anger, and neutral states. It consists of three main parts. The first one is the detection of a face and the corresponding facial features to extract the most expressive portion of the face, followed by a normalization of the region of interest. Then calculus of curvelet coefficients is performed with dimensionality reduction through principal component analysis. The resulting coefficients are combined with two ratios; mouth ratio and face edge ratio to constitute the whole feature vector. The third step is the classification of the emotional state using the SVM method in the feature space.

Keywords: facial expression identification, curvelet coefficient, support vector machine (SVM), recognition system

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Authors: Hassina Gheribi, Salim Boukebbab

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The measurement of the parts manufactured on CMM (coordinate measuring machine) is based on the association of a surface of perfect geometry to the group of dots palpated via a mathematical calculation of the distances between the palpated points and itself surfaces. Surfaces not being never perfect, they are measured by a number of points higher than the minimal number necessary to define them mathematically. However, the central problems of three-dimensional metrology are the estimate of, the orientation parameters, location and intrinsic of this surface. Including the numerical uncertainties attached to these parameters help the metrologist to make decisions to be able to declare the conformity of the part to specifications fixed on the design drawing. During this paper, we will present a data-processing model in Visual Basic-6 which makes it possible automatically to determine the whole of these parameters, and their uncertainties.

Keywords: coordinate measuring machines (CMM), associated surface, uncertainties of measurement, acquisition and modeling

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Authors: R. Naveen, E. Vanitha, S. Gayathri

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The use of Sandwich composite materials in aerospace and civil infrastructure application has been increasing especially due to their enormously low weight that leads to a reduction in the total weight and fuel consumption, high flexural and transverse shear stiffness, and corrosion resistance. The essential properties of sandwich materials vary according to the application area of the structure. The objectives of this study are to identify the mechanical behaviour and failure mechanisms of sandwich structures made of bamboo, V- board and metal (Aluminium as face sheet and Foam as Core material). The three-point bending test and UTM (Universal testing machine) experimental tests are done for three specimens for each type of sandwich composites. From the experiment results of three sandwich composites, bamboo shows high Young’s modulus of elasticity and low density.

Keywords: bamboo sandwich composite, metal sandwich composite, sandwich composite, v-board sandwich composite

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Authors: Tim Farrelly

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In recent years, AI-powered object detection systems have opened the doors for innovative new applications and products, especially those operating in the real world or ‘on edge’ – namely, in sport. This paper investigates the viability of an ultra-low parameter convolutional neural network specially designed for the detection of footballs on ‘on the edge’ devices. The main contribution of this paper is the exploration of integrating new design features (depth-wise separable convolutional blocks and squeezed and excitation modules) into an ultra-low parameter network and demonstrating subsequent improvements in performance. The results show that tracking the ball from Full HD images with negligibly high accu-racy is possible in real-time.

Keywords: deep learning, object detection, machine vision applications, sport, network design

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Authors: Misarah Abdelaziz, L Djenidi, Mergen H. Ghayesh, Rey Chin

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Measurements of a turbulent boundary layer over 3D sinusoidal roughness are performed for friction Reynolds numbers ranging from 650 < Reτ < 2700. This surface was fabricated by a Multicam CNC Router machine of an acrylic sheet to have an amplitude of k/2 = 0.8 mm and an equal wavelength of 8k in both streamwise and spanwise directions, a 0.6 mm stepover and 12 mm ball nose cutter was used. Single hotwire anemometry measurements are done at one location x=1.5 m downstream at different freestream velocities under zero-pressure gradient conditions. As expected, the roughness causes a downward shift on the wall-unit normalised streamwise mean velocity profile when compared to the smooth wall profile. The shift is increasing with increasing Reτ, 1.8 < ∆U+ < 6.2. The coefficient of friction is almost constant at all cases Cf = 0.0042 ± 0.0002. The results show a gradual reduction in the inner peak of profiles with increasing Reτ until fully destruction at Reτ of 2700.

Keywords: hotwire, roughness, TBL, ZPG

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Authors: Sun-Ki Hong, Ki-Seok Kim, Yong-Ho Jo

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Lots of motors have been being used in industry. Therefore many researchers have studied about the failure diagnosis of motors. In this paper, the effect of measuring environment for diagnosis of gear fault connected to a motor shaft is studied. The fault diagnosis is executed through the comparison of normal gear and abnormal gear. The measured FFT data are compared with the normal data and analyzed for q-axis current, noise and vibration. For bad and good environment, the diagnosis results are compared. From these, it is shown that the bad measuring environment may not be able to detect exactly the motor gear fault. Therefore it is emphasized that the measuring environment should be carefully prepared.

Keywords: motor fault, diagnosis, FFT, vibration, noise, q-axis current, measuring environment

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Authors: Marc Sader, Michiel Stock, Bernard De Baets

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Considering a large amount of adsorption data of adsorbate gases on adsorbent materials in literature, it is interesting to predict such adsorption data without experimentation. A quantitative structure-activity relationship (QSAR) is developed to correlate molecular characteristics of gases and existing knowledge of materials with their respective adsorption properties. The application of Random Forest, a machine learning method, on a set of adsorption isotherms at a wide range of partial pressures and concentrations is studied. The predicted adsorption isotherms are fitted to several adsorption equations to estimate the adsorption properties. To impute the adsorption properties of desired gases on desired materials, leave-one-out cross-validation is employed. Extensive experimental results for a range of settings are reported.

Keywords: adsorption, predictive modeling, QSAR, random forest

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Authors: Antonio Montes, Antonio Cozar, Clara Pereyra, Diego Valor, Enrique Martinez de la Ossa

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Tissues and organs can be damaged because of traumatism, congenital illnesses, or cancer and the traditional therapeutic alternatives, such as surgery, cannot usually completely repair the damaged tissues. Tissue engineering allows regeneration of the patient's tissues, reducing the problems caused by the traditional methods. Scaffolds, polymeric structures with interconnected porosity, can be promoted the proliferation and adhesion of the patient’s cells in the damaged area. Furthermore, by means of impregnation of the scaffold with beneficial active substances, tissue regeneration can be induced through a drug delivery process. The objective of the work is the fabrication of a PVA scaffold coated with Gallic Acid and polypyrrole through a one-step foaming and impregnation process using the SSI technique (Supercritical Solvent Impregnation). In this technique, supercritical CO₂ penetrates into the polymer chains producing the plasticization of the polymer. In the depressurization step a CO₂ cellular nucleation and growing to take place to an interconnected porous structure of the polymer. The foaming process using supercritical CO₂ as solvent and expansion agent presents advantages compared to the traditional scaffolds’ fabrication methods, such as the polymer’s high solubility in the solvent or the possibility of carrying out the process at a low temperature, avoiding the inactivation of the active substance. In this sense, the supercritical CO₂ avoids the use of organic solvents and reduces the solvent residues in the final product. Moreover, this process does not require long processing time that could cause the stratification of substance inside the scaffold reducing the therapeutic efficiency of the formulation. An experimental design has been carried out to optimize the SSI technique operating conditions, as well as a study of the morphological characteristics of the scaffold for its use in tissue engineerings, such as porosity, conductivity or the release profiles of the active substance. It has been proved that the obtained scaffolds are partially porous, conductors of electricity and are able to release Gallic Acid in the long term.

Keywords: scaffold, foaming, supercritical, PVA, polypyrrole, gallic acid

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Authors: Akhil Raj Pushparajan, Ranjit Ramachandran, Jijimole Gopi Reji, Ajay Kumar Ramakrishnan

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Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), is one of the leading causes of death by an infectious disease. In spite of the availability of effective drugs and a vaccine, TB is a major health concern and was declared a global emergency by the World Health Organization (WHO). The success of intracellular pathogens like Mtb depends on its ability to overcome the challenging environment in the host. Gene regulation controlled by transcriptional regulators (TRs) plays a crucial role for the bacteria to adapt to the host environment. In vitro studies on gene regulatory mechanisms during dormancy and reactivation have provided insights into the adaptations employed by Mtb to survive in the host. Here we present our efforts to functionally characterize Rv1019, a putative TR of Mtb H37Rv which was found to be present at significantly varying levels during dormancy and reactivation in vitro. The expression of this protein in the dormancy-reactivation model was validated by qRT-PCR and western blot. By DNA- protein interaction studies and reporter assays we found that under normal laboratory conditions of growth this protein behaves as an auto-repressor and tetracycline was found to abrogate this repression by interfering with its ability to bind DNA. Further, by cDNA analysis, we found that this TR is co-transcribed with its downstream genes Rv1020 (mfd) and Rv1021 (mazG) which are involved in DNA damage response in Mtb. Constitutive expression of this regulator in the surrogate host M. smegmatis showed downregulation of the orthologues of downstream genes suggested that Rv1019 could negatively regulate these genes. Our finds also show that M. smegmatis expressing Rv1019 is sensitive to DNA damage suggests the role of this protein in regulating DNA damage response induced by oxidative stress. Because of its role in regulating DNA damage response which may help in the persistence of Mtb, Rv1019 could be used as a prospective target for therapeutic intervention to fight TB.

Keywords: auto-repressor, DNA repair, mycobacterium smegmatis, mycobacterium tuberculosis, tuberculosis

Procedia PDF Downloads 124

Authors: Debjit Ray

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Horizontal gene transfer (HGT) and recombination leads to the emergence of bacterial antibiotic resistance and pathogenic traits. HGT events can be identified by comparing a large number of fully sequenced genomes across a species or genus, define the phylogenetic range of HGT, and find potential sources of new resistance genes. In-depth comparative phylogenomics can also identify subtle genome or plasmid structural changes or mutations associated with phenotypic changes. Comparative phylogenomics requires that accurately sequenced, complete and properly annotated genomes of the organism. Assembling closed genomes requires additional mate-pair reads or “long read” sequencing data to accompany short-read paired-end data. To bring down the cost and time required of producing assembled genomes and annotating genome features that inform drug resistance and pathogenicity, we are analyzing the performance for genome assembly of data from the Illumina NextSeq, which has faster throughput than the Illumina HiSeq (~1-2 days versus ~1 week), and shorter reads (150bp paired-end versus 300bp paired end) but higher capacity (150-400M reads per run versus ~5-15M) compared to the Illumina MiSeq. Bioinformatics improvements are also needed to make rapid, routine production of complete genomes a reality. Modern assemblers such as SPAdes 3.6.0 running on a standard Linux blade are capable in a few hours of converting mixes of reads from different library preps into high-quality assemblies with only a few gaps. Remaining breaks in scaffolds are generally due to repeats (e.g., rRNA genes) are addressed by our software for gap closure techniques, that avoid custom PCR or targeted sequencing. Our goal is to improve the understanding of emergence of pathogenesis using sequencing, comparative genomics, and machine learning analysis of ~1000 pathogen genomes. Machine learning algorithms will be used to digest the diverse features (change in virulence genes, recombination, horizontal gene transfer, patient diagnostics). Temporal data and evolutionary models can thus determine whether the origin of a particular isolate is likely to have been from the environment (could it have evolved from previous isolates). It can be useful for comparing differences in virulence along or across the tree. More intriguing, it can test whether there is a direction to virulence strength. This would open new avenues in the prediction of uncharacterized clinical bugs and multidrug resistance evolution and pathogen emergence.

Keywords: genomics, pathogens, genome assembly, superbugs

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Authors: Mayandi Ramanathan

Abstract:

Gas turbine blades see the most aggressive thermal stress conditions within the engine, due to Turbine Entry Temperatures in the range of 1500 to 1600°C, but in synchronization with other functional components, they must readily deliver efficient performance, whilst incurring minimal overhaul and repair costs during its service life up to 5 million flying miles. The blades rotate at very high rotation rates and remove significant amount of thermal power from the gas stream. At high temperatures the major component failure mechanism is creep. During its service over time under high temperatures and loads, the blade will deform, lengthen and rupture. High strength and stiffness in the longitudinal direction up to elevated service temperatures are certainly the most needed properties of turbine blades. The proposed advanced Ti alloy material needs a process that provides strategic orientation of metallic ordering, uniformity in composition and high metallic strength. 25% Ta/(Al+Ta) ratio ensures TaAl3 phase formation, where as 51% Al/(Al+Ti) ratio ensures formation of α-Ti3Al and γ-TiAl mixed phases fand the three phase combination ensures minimal Al excess (~1.4% Al excess), unlike Ti-47Al-2Cr-2Nb which has significant excess Al (~5% Al excess) that could affect the service life of turbine blades. This presentation will involve the summary of additive manufacturing and heat treatment process conditions to fabricate turbine blade with Ti-43Al matrix alloyed with optimized amount of refractory Ta metal. Summary of thermo-mechanical test results such as high temperature tensile strength, creep strain rate, thermal expansion coefficient and fracture toughness will be presented. Improvement in service temperature of the turbine blades and corrosion resistance dependence on coercivity of the alloy material will be reported. Phase compositions will be quantified, and a summary of its correlation with creep strain rate will be presented.

Keywords: gas turbine, aerospace, specific strength, creep, high temperature materials, alloys, phase optimization

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Authors: Guofan Shao, Lina Tang, Hao Zhang

Abstract:

The values of image classification accuracy are affected by class size distributions and classification schemes, making it difficult to compare the performance of classification algorithms across different remote sensing data sources and classification systems. Based on the term efficacy from medicine and pharmacology, we have developed the metrics of image classification efficacy at the map and class levels. The novelty of this approach is that a baseline classification is involved in computing image classification efficacies so that the effects of class statistics are reduced. Furthermore, the image classification efficacies are interpretable and comparable, and thus, strengthen the assessment of image data classification methods. We use real-world and hypothetical examples to explain the use of image classification efficacies. The metrics of image classification efficacy meet the critical need to rectify the strategy for the assessment of image classification performance as image classification methods are becoming more diversified.

Keywords: accuracy assessment, efficacy, image classification, machine learning, uncertainty

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Authors: Chonlakorn Wiboonsiriruk, Ekachai Phaisangittisagul, Chadchai Srisurangkul, Itsuo Kumazawa

Abstract:

Public transportation is a crucial aspect of passenger transportation, with buses playing a vital role in the transportation service. Passenger counting is an essential tool for organizing and managing transportation services. However, manual counting is a tedious and time-consuming task, which is why computer vision algorithms are being utilized to make the process more efficient. In this study, different object detection algorithms combined with passenger tracking are investigated to compare passenger counting performance. The system employs the EfficientDet algorithm, which has demonstrated superior performance in terms of speed and accuracy. Our results show that the proposed system can accurately count passengers in varying conditions with an accuracy of 94%.

Keywords: computer vision, object detection, passenger counting, public transportation

Procedia PDF Downloads 133

Authors: Henning Lahmann, Benjamyn I. Scott, Bart Custers

Abstract:

Suboptimal adoption of AI in defence organisations carries risks for the protection of the freedom, safety, and security of society. Despite the vast opportunities that defence AI-technology presents, there are also a variety of ethical, legal, and societal concerns. To ensure the successful use of AI technology by the military, ethical, legal, and societal aspects (ELSA) need to be considered, and their concerns continuously addressed at all levels. This includes ELSA considerations during the design, manufacturing and maintenance of AI-based systems, as well as its utilisation via appropriate military doctrine and training. This raises the question how defence organisations can remain strategically competitive and at the edge of military innovation, while respecting the values of its citizens. This paper will explain the set-up and share preliminary results of a 4-year research project commissioned by the National Research Council in the Netherlands on the ethical, legal, and societal aspects of AI in defence. The project plans to develop a future-proof, independent, and consultative ecosystem for the responsible use of AI in the defence domain. In order to achieve this, the lab shall devise a context-dependent methodology that focuses on the ‘analysis’, ‘design’ and ‘evaluation’ of ELSA of AI-based applications within the military context, which include inter alia unmanned aircraft. This is bolstered as the Lab also recognises and complements the existing methods in regards to human-machine teaming, explainable algorithms, and value-sensitive design. Such methods will be modified for the military context and applied to pertinent case-studies. These case-studies include, among others, the application of autonomous robots (incl. semi- autonomous) and AI-based methods against cognitive warfare. As the perception of the application of AI in the military context, by both society and defence personnel, is important, the Lab will study how these perceptions evolve and vary in different contexts. Furthermore, the Lab will monitor – as they may influence people’s perception – developments in the global technological, military and societal spheres. Although the emphasis of the research project is on different forms of AI in defence, it focuses on several case studies. One of these case studies is on unmanned aircraft, which will also be the focus of the paper. Hence, ethical, legal, and societal aspects of unmanned aircraft in the defence domain will be discussed in detail, including but not limited to privacy issues. Typical other issues concern security (for people, objects, data or other aircraft), privacy (sensitive data, hindrance, annoyance, data collection, function creep), chilling effects, PlayStation mentality, and PTSD.

Keywords: autonomous weapon systems, unmanned aircraft, human-machine teaming, meaningful human control, value-sensitive design

Procedia PDF Downloads 85