Search results for: automated fibre placement

Authors: Bruce Small, Martin Espig, Alyssa Ryan

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In the agricultural sector, the rapid expansion of herbicide resistant weeds is a major threat to the global sustainability of food and fibre production. Efforts to avoid herbicide resistance have primarily focused on new technologies and farmer education. Yet, despite decades of advice to growers from agricultural scientists and extension professionals of the need for management strategies for herbicide use, herbicide resistance continues to increase. Technological options are running out and current extension efforts to change farmer behaviour are failing to curb the problem. As part of a five-year, government funded, research programme to address herbicide resistance in New Zealand, social science theory and practice are being utilised to investigate the complexities of managing herbicide use and controlling resistance. As an initial step, we are utilising a transdisciplinary, multi-level systems approach to examine the problem definition, knowledge beliefs, attitudes and values of different important actors in the agri-business sector. In this paper, we report early project results from qualitative research examining the similarities and contrasts in the perceptions of scientists, farmer/growers, and rural professionals.

Keywords: behaviour change, herbicide resistant weeds, knowledge beliefs, systems perspective

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Authors: Warda Khan, Remo Lachmann, Adarsh S. Garakahally

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The increasing complexity of software and its applicability in a wide range of industries, e.g., automotive, call for enhanced quality assurance techniques. Test automation is one option to tackle the prevailing challenges by supporting test engineers with fast, parallel, and repetitive test executions. A high degree of test automation allows for a shift from mundane (manual) testing tasks to a more analytical assessment of the software under test. However, a high initial investment of test resources is required to establish test automation, which is, in most cases, a limitation to the time constraints provided for quality assurance of complex software systems. Hence, a computer-aided creation of automated test cases is crucial to increase the benefit of test automation. This paper proposes the application of machine learning for the generation of automated test cases. It is based on supervised learning to analyze test specifications and existing test implementations. The analysis facilitates the identification of patterns between test steps and their implementation with test automation components. For the test case generation, this approach exploits historical data of test automation projects. The identified patterns are the foundation to predict the implementation of unknown test case specifications. Based on this support, a test engineer solely has to review and parameterize the test automation components instead of writing them manually, resulting in a significant time reduction for establishing test automation. Compared to other generation approaches, this ML-based solution can handle different writing styles, authors, application domains, and even languages. Furthermore, test automation tools require expert knowledge by means of programming skills, whereas this approach only requires historical data to generate test cases. The proposed solution is evaluated using various multi-label evaluation criteria (EC) and two small-sized real-world systems. The most prominent EC is ‘Subset Accuracy’. The promising results show an accuracy of at least 86% for test cases, where a 1:1 relationship (Multi-Class) between test step specification and test automation component exists. For complex multi-label problems, i.e., one test step can be implemented by several components, the prediction accuracy is still at 60%. It is better than the current state-of-the-art results. It is expected the prediction quality to increase for larger systems with respective historical data. Consequently, this technique facilitates the time reduction for establishing test automation and is thereby independent of the application domain and project. As a work in progress, the next steps are to investigate incremental and active learning as additions to increase the usability of this approach, e.g., in case labelled historical data is scarce.

Keywords: machine learning, multi-class, multi-label, supervised learning, test automation

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Authors: Rohana Abdullah, Md Nizam Abd Rahman, Seri Rahayu Kamat

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Operator efficiency aspect is gaining importance in ensuring optimized usage of resources especially in the semi-automated manufacturing environment. This paper addresses a case study done to solve operator efficiency and line balancing issue at a semiconductor assembly and test manufacturing. A Man-to-Machine (M2M) work study technique is used to study operator current utilization and determine the optimum allocation of the operators to the machines. Critical factors such as operator activity, activity frequency and operator competency level are considered to gain insight on the parameters that affects the operator utilization. Equipment standard time and overall equipment efficiency (OEE) information are also gathered and analyzed to achieve a balanced and optimized production.

Keywords: operator efficiency, optimized production, line balancing, industrial and manufacturing engineering

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Authors: T. Ahilan, V. Aswin Adityan, S. Kailash

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UAV’s are small remote operated or automated aerial surveillance systems without a human pilot aboard. UAV’s generally finds its use in military and special operation application, a recent growing trend in UAV’s finds its application in several civil and non military works such as inspection of power or pipelines. The objective of this paper is the augmentation of a UAV in order to replace the existing expensive sonar (sound navigation and ranging) based equipment amongst small scale fisherman, for whom access to sonar equipment are restricted due to limited economic resources. The surveillance equipment’s present in the UAV will relay data and GPS location onto a receiver on the fishing boat using RF signals, using which the location of the schools of fishes can be found. In addition to this, an emergency beacon system is present for rescue operations and drone recovery.

Keywords: UAV, Surveillance, RF signals, fishing, sonar, GPS, video stream, school of fish

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Authors: B. H. Aitchanov, Sh. K. Aitchanova, O. A. Baimuratov

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This paper is focused on dynamic pulse-frequency modulation (DPFM) control systems. Currently, the control law based on DPFM control signals is widely used in direct digital control subsystems introduced in the automated control systems of technological processes. Statistical analysis of automatic control systems is reduced to its construction of functional relationships between the statistical characteristics of the errors processes and input processes. Structural and dynamic Volterra models of digital pulse-frequency control systems can be used to develop methods for generating the dependencies, differing accuracy, requiring the amount of information about the statistical characteristics of input processes and computing labor intensity of their use.

Keywords: digital dynamic pulse-frequency control systems, dynamic pulse-frequency modulation, control object, discrete filter, impulse device, microcontroller

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Authors: Jamison Duckworth, Shankarachary Ragi

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Detection and segmentation of wildfire smoke plumes from remote sensing imagery are being pursued as a solution for early fire detection and response. Smoke plume detection can be automated and made robust by the application of artificial intelligence methods. Specifically, in this study, the deep learning approach Mask Region-based Convolutional Neural Network (RCNN) is being proposed to learn smoke patterns across different spectral bands. This method is proposed to separate the smoke regions from the background and return masks placed over the smoke plumes. Multispectral data was acquired using NASA’s Earthdata and WorldView and services and satellite imagery. Due to the use of multispectral bands along with the three visual bands, we show that Mask R-CNN can be applied to distinguish smoke plumes from clouds and other landscape features that resemble smoke.

Keywords: deep learning, mask-RCNN, smoke plumes, spectral bands

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Authors: Norfishah Mat Rabi, Rosma Osman, Norziana Mat Rabi

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It is difficult for autistic children to mix with and be around with other people. Language difficulties are a problem that affects their social life. A lack of knowledge and ability in language are factors that greatly influence their behavior, and their ability to communicate and interact. Autistic children need to be assisted to improve their language abilities through the use of suitable learning resources. This study is conducted to identify weather graphic animation resources can help autistic children learn and use transitive verbs more effectively. The study was conducted in a rural secondary school in Penang, Malaysia. The research subject comprised of three autistic students ranging in age from 14 years to 16 years. The 14-year-old student is placed in A Class and two 16-year-old students placed in B Class. The class placement of the subjects is based on the diagnostic test results conducted by the teacher and not based on age. Data collection is done through observation and interviews for the duration of five weeks; with the researcher allocating 30 minutes for every learning activity carried out. The research finding shows that the subjects learn transitive verbs better using graphic animation compared to static pictures. It is hoped that this study will give a new perspective towards the learning processes of autistic children.

Keywords: graphic animation, autistic children, language learning, teaching

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Authors: C. O. Agu, C. C. Okafor

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Maize and soybean flours were produced using different methods of processing which include fermentation (FWF), roasting (RWF) and malting (MWF). Products from the different methods were mixed in the ratio 60:40 maize/soybean, respectively. These composites mixed with other ingredients such as sugar, vegetable oil, vanilla flavour and vitamin mix were analyzed for proximate composition, physical/functional, sensory and nutritional properties. The results for the protein content ranged between 6.25% and 16.65% with sample RWF having the highest value. Crude fibre values ranged from 3.72 to 10.0%, carbohydrate from 58.98% to 64.2%, ash from 1.27 to 2.45%. Physical and functional properties such as bulk density, wettability, gelation capacity have values between 0.74 and 0.76g/ml, 20.33 and 46.33 min and 0.73 to 0.93g/ml, respectively. On the sensory quality colour, flavour, taste, texture and general acceptability were determined. In terms of colour and flavour there was no significant difference (P < 0.05) while the values for taste ranged between 4.89 and 7.1 l, texture 5.50 to 8.38 and general acceptability 6.09 and 7.89. Nutritionally there is no significant difference (P < 0.05) between sample RWF and the control in all parameters considered. Samples FWF and MWF showed significantly (P < 0.5) lower values in all parameters determined. In the light of the above findings, roasting method is highly recommend in the production of weaning foods.

Keywords: fermentation, malting, ratio, roasting, wettability

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Authors: Li Hui, Riyadh Hindi

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Concrete structures frequently suffer from crack formation, a critical issue that can significantly reduce their lifespan by allowing damaging agents to enter. Traditional methods of crack detection depend on manual visual inspections, which heavily relies on the experience and expertise of inspectors using tools. In this study, a more efficient, computer vision-based approach is introduced by using the lightweight MobileNetV2 neural network. A dataset of 40,000 images was used to develop a specialized crack evaluation algorithm. The analysis indicates that MobileNetV2 matches the accuracy of traditional CNN methods but is more efficient due to its smaller size, making it well-suited for mobile device applications. The effectiveness and reliability of this new method were validated through experimental testing, highlighting its potential as an automated solution for crack detection in concrete structures.

Keywords: Concrete crack, computer vision, deep learning, MobileNetV2 neural network

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Authors: Maulik Parmar, Sumeet Sandhu

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The online fashion industry experiences high product return rates. Many returns are because of size/fit mismatches -the size scale on labels can vary across brands, the size parameters may not capture all fit measurements, or the product may have manufacturing defects. Warehouse quality check of garment sizes can be semi-automated to improve speed and accuracy. This paper presents an approach for automatically measuring garment sizes from a single image of the garment -using Deep Learning to learn garment keypoints. The paper focuses on the waist size measurement of jeans and can be easily extended to other garment types and measurements. Experimental results show that this approach can greatly improve the speed and accuracy of today’s manual measurement process.

Keywords: convolutional neural networks, deep learning, distortion, garment measurements, image warping, keypoints

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Authors: Noha Seddik, Sherine Youssef, Mohamed Kholeif

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

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

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Authors: Hitesh Tahbildar

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The cost of test data generation for a program is computationally very high. In general case, no algorithm to generate test data for all types of algorithms has been found. The cost of generating test data for different types of algorithm is different. Till date, people are emphasizing the need to generate test data for different types of programming constructs rather than different types of algorithms. The test data generation methods have been implemented to find heuristics for different types of algorithms. Some algorithms that includes divide and conquer, backtracking, greedy approach, dynamic programming to find the minimum cost of test data generation have been tested. Our experimental results say that some of these types of algorithm can be used as a necessary condition for selecting heuristics and programming constructs are sufficient condition for selecting our heuristics. Finally we recommend the different heuristics for test data generation to be selected for different types of algorithms.

Keywords: ongest path, saturation point, lmax, kL, kS

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Authors: K. O. Igwe, E. N. Onyeike, A. A. Uwakwe

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Comparative proximate composition of selected edible vegetables (Abelmoschus esculentus, Telfairia occidentalis, vernonia amygdalina and Talinum triangulare ) harvested in farmland nearby oil impacted sites in Rivers State was investigated. The result obtained was compared to the proximate composition of similar edible vegetables harvested from non oil producing areas in Imo State. Values from the study areas indicated vegetables with high moisture levels (highest values in Abelmoschus esculentus and Telfairia occidentalis; 6.07±0.11% and 4.10±0.12%) low ash contents (lowest value in Telfairia occidentalis 9.80±0.08%) low crude protein (lowest value in Talinum triangulare 8.15±0.06 %) high lipid content (highest value in Talinum triangulare 4.12± 0.20%) lower crude fibre (lowest value in Abelmoschus esculentus 9.58±0.08 %) and higher Carbohydrate contents (highest value in vernonia amygdalina 62.18± 0.67%). Values obtained indicated vegetables with lower quality in the study areas.

Keywords: edible vegetables, proximate composition, oil spill, farmland

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Authors: Abdelrahman A. Ramzy, Bassel S. Abdallah, Mohamed E. Bahgat, Sarah M. Abdelkader, Sherif H. ElGohary

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Attention-Deficit/Hyperactivity Disorder (ADHD), epilepsy, and autism affect millions of children worldwide, many of which are undiagnosed despite the fact that all of these disorders are detectable in early childhood. Late diagnosis can cause severe problems due to the late treatment and to the misconceptions and lack of awareness as a whole towards these disorders. Moreover, electroencephalography (EEG) has played a vital role in the assessment of neural function in children. Therefore, quantitative EEG measurement will be utilized as a tool for use in the evaluation of patients who may have ADHD, epilepsy, and autism. We propose a screening tool that uses EEG signals and machine learning algorithms to detect these disorders at an early age in an automated manner. The proposed classifiers used with epilepsy as a step taken for the work done so far, provided an accuracy of approximately 97% using SVM, Naïve Bayes and Decision tree, while 98% using KNN, which gives hope for the work yet to be conducted.

Keywords: ADHD, autism, epilepsy, EEG, SVM

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Authors: Mostefa Hamrat, Bensaid Boulekbache, Mohamed Chemrouk, Sofiane Amziane

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The paper presents the results of an experimental work on the flexural behaviour of two types of concrete in terms of the progressive cracking process until failure and the crack opening, and beam deflection, using Digital Image Correlation (DIC) technique. At serviceability limit states, comparisons of the building code equations and the equations developed by some researchers for the short-term deflections and crack widths have been made using the reinforced concrete test beams. The experimental results show that the addition of steel fibers increases the first cracking load and amplify the number of cracks that conducts to a remarkable decreasing in the crack width with an increasing in ductility. This study also shows that there is a good agreement between the deflection values for RC beams predicted by the major codes (Eurocode2, ACI 318, and the CAN/CSA-S806) and the experimental results for beams with steel fibers at service load. The most important added benefit of the DIC technique is that it allows detecting the first crack with a high precision easily measures the crack opening and follows the progressive cracking process until failure of reinforced concrete members.

Keywords: beams, digital image correlation (DIC), deflection, crack width, serviceability, codes provisions

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Authors: M. Abdullah Al Faruque, Ram Balachandar

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An experimental study with four different types of bed conditions was carried out to understand the effect of roughness in open channel flow at two different Reynolds numbers. The bed conditions include a smooth surface and three different roughness conditions which were generated using sand grains with a median diameter of 2.46 mm. The three rough conditions include a surface with distributed roughness, a surface with continuously distributed roughness and a sand bed with a permeable interface. A commercial two-component fibre-optic LDA system was used to conduct the velocity measurements. The variables of interest include the mean velocity, turbulence intensity, the correlation between the streamwise and the wall normal turbulence, Reynolds shear stress and velocity triple products. Quadrant decomposition was used to extract the magnitude of the Reynolds shear stress of the turbulent bursting events. The effect of roughness was evident throughout the flow depth. The results show that distributed roughness has the greatest roughness effect followed by the sand bed and the continuous roughness. Compared to the smooth bed, the streamwise turbulence intensity reduces but the vertical turbulence intensity increases at a location very close to the bed due to the introduction of roughness. Although the same sand grain is used to create the three different rough bed conditions, the difference in the turbulence intensity is an indication that the specific geometry of the roughness has an influence on turbulence structure.

Keywords: open channel flow, smooth and rough bed, Reynolds number, turbulence

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Authors: Kolade Olawande Owoeye, George R. S. Weir

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The widespread of terrorism and extremism activities on the internet has become a major threat to the government and national securities due to their potential dangers which have necessitated the need for intelligence gathering via web and real-time monitoring of potential websites for extremist activities. However, the manual classification for such contents is practically difficult or time-consuming. In response to this challenge, an automated classification system called composite technique was developed. This is a computational framework that explores the combination of both semantics and syntactic features of textual contents of a web. We implemented the framework on a set of extremist webpages dataset that has been subjected to the manual classification process. Therein, we developed a classification model on the data using J48 decision algorithm, this is to generate a measure of how well each page can be classified into their appropriate classes. The classification result obtained from our method when compared with other states of arts, indicated a 96% success rate in classifying overall webpages when matched against the manual classification.

Keywords: extremist, web pages, classification, semantics, posit

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Authors: D. R. Ambika, K. R. Radhika, D. Seshachalam

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Unconstrained authentication is an important component for personal automated systems and human-computer interfaces. Existing solutions mostly use face as the primary object of analysis. The performance of face-based systems is largely determined by the extent of deformation caused in the facial region and amount of useful information available in occluded face images. Periocular region is a useful portion of face with discriminative ability coupled with resistance to deformation. A reliable portion of periocular area is available for occluded images. The present work demonstrates that joint representation of periocular texture and periocular structure provides an effective expression and poses invariant representation. The proposed methodology provides an effective and compact description of periocular texture and shape. The method is tested over four benchmark datasets exhibiting varied acquisition conditions.

Keywords: periocular authentication, Zernike moments, LBP variance, shape and texture fusion

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Authors: Marek Dlapa

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The algebraic approach is applied to the control of the HiMAT (Highly Maneuverable Aircraft Technology). The objective is to find a robust controller which guarantees robust stability and decoupled control of longitudinal model of a scaled remotely controlled vehicle version of the advanced fighter HiMAT. Control design is performed by decoupling the nominal MIMO (multi-input multi-output) system into two identical SISO (single-input single-output) plants which are approximated by a 4th order transfer function. The algebraic approach is then used for pole placement design, and the nominal closed-loop poles are tuned so that the peak of the µ-function is minimal. As an optimization tool, evolutionary algorithm Differential Migration is used in order to overcome the multimodality of the cost function yielding simple controller with decoupling for nominal plant which is compared with the D-K iteration through simulations of standard longitudinal manoeuvres documenting decoupled control obtained from algebraic approach for nominal plant as well as worst case perturbation.

Keywords: algebraic approach, evolutionary computation, genetic algorithms, HiMAT, robust control, structured singular value

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Authors: Oday Al-Mamoori, J. Enrique Martinez-Rueda

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'C' shape yielding devices (C-devices) are effective tools for introducing supplemental sources of energy dissipation by hysteresis. Studies have shown that C-devices made of mild steel can be successfully applied as integral parts of seismic retrofitting schemes. However, explicit modelling of these devices can become cumbersome, expensive and time consuming. The device under study in this article has been previously used in non-invasive dissipative bracing for seismic retrofitting. The device is cut from a mild steel plate and has an overall shape that resembles that of a rectangular portal frame with circular interior corner transitions to avoid stress concentration and to control the extension of the dissipative region of the device. A number of inelastic finite element (FE) analyses using either inelastic 2D plane stress elements or inelastic fibre frame elements are reported and used to calibrate a 1D equivalent inelastic spring model that effectively reproduces the cyclic response of the device. The more elaborate FE model accounts for the frictional forces developed between the steel plate and the bolts used to connect the C-device to structural members. FE results also allow the visualization of the inelastic regions of the device where energy dissipation is expected to occur. FE analysis results are in a good agreement with experimental observations.

Keywords: C-device, equivalent nonlinear spring, FE analyses, reversed cyclic tests

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Authors: A. Latif Karimi, M. K. Shrimali

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Seismic design is a critical stage in the process of design and construction of a building. It includes strategies for designing earthquake-resistant buildings to ensure health, safety, and security of the building occupants and assets. Hence, it becomes very important to understand the behavior of structural members precisely, for construction of buildings that can yield a better response to seismic forces. This paper investigates the behavior of a typical structure when subjected to ground motion. The corresponding mode shapes and modal frequencies are studied to interpret the response of an actual structure using different fabricated models and 3D visual models. In this study, three different structural configurations are subjected to horizontal ground motion, and the effect of “stiffness eccentricity” and placement of infill walls are checked to determine how each parameter contributes in a building’s response to dynamic forces. The deformation data from lab experiments and the analysis on SAP2000 software are reviewed to obtain the results. This study revealed that seismic response in a building can be improved by introducing higher deformation capacity in the building. Also, proper design of infill walls and maintaining a symmetrical configuration in a building are the key factors in building stability during the earthquake.

Keywords: eccentricity, seismic response, mode shape, building configuration, building dynamics

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Authors: Rangoli Goyal, Rama Bhargava

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The triple diffusive boundary layer flow of nanofluid under the action of constant magnetic field over a non-linear stretching sheet has been investigated numerically. The model includes the effect of Brownian motion, thermophoresis, and cross-diffusion; slip mechanisms which are primarily responsible for the enhancement of the convective features of nanofluid. The governing partial differential equations are transformed into a system of ordinary differential equations (by using group theory transformations) and solved numerically by using variational finite element method. The effects of various controlling parameters, such as the magnetic influence number, thermophoresis parameter, Brownian motion parameter, modified Dufour parameter, and Dufour solutal Lewis number, on the fluid flow as well as on heat and mass transfer coefficients (both of solute and nanofluid) are presented graphically and discussed quantitatively. The present study has industrial applications in aerodynamic extrusion of plastic sheets, coating and suspensions, melt spinning, hot rolling, wire drawing, glass-fibre production, and manufacture of polymer and rubber sheets, where the quality of the desired product depends on the stretching rate as well as external field including magnetic effects.

Keywords: FEM, thermophoresis, diffusiophoresis, Brownian motion

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Authors: M. M. Akhmediev, J. R. Ashrapov, T. M. Akhmediev

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Hydrocephalus frequently occurs with spina bifida, and up to 80% of such patients need to be shunted. Objective: It’s sought to improve the results of the surgical treatment of hydrocephalus in children with spina bifida. Methods: We have analyzed the results of the surgical treatment of 80 patients aged between 1 month and 1,5-year-old with hydrocephalus and myelomeningocele. All patients underwent surgery in the period of 2013-2018. Results: In all patients, spina bifida was associated with hydrocephalus with a predominant extension of the posterior horns of the lateral ventricles in the form of colpocephaly, Chiari malformation type 2. Based on the method “Choose right shunt” the determination of the point of critical deformation of the ventricular system was established, 47 (58.8%) patients for the 1st stage underwent ventriculoperitoneal (VP) shunt surgery with a low-pressure valve, 28 (35.0%) patients with medium pressure and 5 (6.2%) with high-pressure valve. Under or over drainage complications were not observed in the postoperative period. The 2nd stage of surgery for myelomeningocele repair was planned in 1-2 months with the follow-up head ultrasonography and electromyography study. Conclusion: The implantable shunt systems parameters chosen before surgery in the surgical management of hydrocephalus in children with myelomeningocele are important in the causes of under or over drainage states, cerebrospinal fluid leakage from the myelomeningocele sac. Management of hydrocephalus should be performed by considering myelomeningocele affecting craniospinal compliance.

Keywords: hydrocephalus, spina bifida, myelomeningocele, ventriculoperitoneal (VP) shunt

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Authors: Kar Lin Nyam, Phey Yee Lim

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The aim of this study was to determine the antioxidant potential, nutritional composition, and functional properties of kenaf leaves powder. Besides, the effect of kenaf leaves powder in bread qualities, properties, and consumer acceptability were evaluated. Different formulations of bread fortified with 0%, 4% and 8% kenaf leaves powder, respectively were produced. Physical properties of bread, such as loaf volume, dough expansion, crumb colour, and bread texture, were determined. Nine points hedonic scale was utilized in sensory evaluation to determine the best formulation (the highest overall acceptability). Proximate composition, calcium content, and antioxidant properties were also determined for the best formulation. 4% leaves powder bread was the most preferred by the panelists followed by control bread, and the least preferred was being 8% leaves powder bread. 4% leaves powder bread had significantly higher value of DPPH radical scavenging capacity (8.05 mg TE/100g), total phenolic content (12.88 mg GAE/100g) and total flavonoid content (13.26 mg QE/100g) compared to control bread (1.38 mg TE/100g, 8.17 mg GAE/100g, and 8.77 mg QE/100g respectively). Besides, 4% leaves powder bread also showed higher in calcium content and total dietary fiber compared to control bread. Kenaf leaves powder is suitable to be used as a source of natural antioxidant for fortification and nutrient improver in bread.

Keywords: dietary fibre, calcium, total phenolic content, total flavonoid content

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Authors: Mosab Alrashed, Wei Xu, Stephen Abineri, Yifan Zhao, Jörn Mehnen

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Thermographic inspection is a relatively new technique for Non-Destructive Testing (NDT) which has been gathering increasing interest due to its relatively low cost hardware and extremely fast data acquisition properties. This technique is especially promising in the area of rapid automated damage detection and quantification. In collaboration with a major industry partner from the aerospace sector advanced thermography-based NDT software for impact damaged composites is introduced. The software is based on correlation analysis of time-temperature profiles in combination with an image enhancement process. The prototype software is aiming to a) better visualise the damages in a relatively easy-to-use way and b) automatically and quantitatively measure the properties of the degradation. Knowing that degradation properties play an important role in the identification of degradation types, tests and results on specimens which were artificially damaged have been performed and analyzed.

Keywords: NDT, correlation analysis, image processing, damage, inspection

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Authors: Awais Ali, Hesham Ali

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The absence of teeth through either premature loss or developmental absence is a common condition with potentially severe impact on affected individuals. Management of these cases presents a clinical challenge which may be difficult to resolve given the effects of tooth loss or hypodontia over the course of a patient’s lifetime. Treatment of such cases is often best provided by a multi-disciplinary team, where the patient’s expectations and care delivery can be optimally managed. Orthodontic treatment is often used to prepare the dentition in advance of restorative replacement of missing teeth. Conversely, the placement of implants may precede the delivery of orthodontic treatment and indeed may function as an adjunctive orthodontic procedure. We discuss the use of both approaches here and illustrate their clinical implementation with two case reports. The first case demonstrates the use of fixed appliances to prepare the mouth for an opposing implant-retained complete denture. A second case demonstrates the use of implant-retained crowns to provide orthodontic anchorage in a partially dentate patient. We propose that complex cases such as these should always be planned and treated by a multi-disciplinary team in order to optimise the delivery of care, patient experience, and treatment outcome. The presented cases add to the body of evidence in this area.

Keywords: orthodontics, dental implantology, hypodontia, multi-disciplinary

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Authors: Ayesha Anjum, Arbaz Basha

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Active Galactic Nuclei (AGN) are the actively accreting centers of the galaxies that host supermassive black holes. AGN emits radiation in all wavelengths and also shows variability across all the wavelength bands. The analysis of flux variability tells us about the morphology of the site of emission radiation. Some of the major classifications of AGN are (a) Blazars, with featureless spectra. They are subclassified as BLLacertae objects, Flat Spectrum Radio Quasars (FSRQs), and others; (b) Seyferts with prominent emission line features are classified into Broad Line, Narrow Line Seyferts of Type 1 and Type 2 (c) quasars, and other types. Sloan Digital Sky Survey (SDSS) is an optical telescope based in Mexico that has observed and classified billions of objects based on automated photometric and spectroscopic methods. A sample of blazars is obtained from the third Fermi catalog. For variability analysis, we searched for light curves for these objects in Wide-Field Infrared Survey Explorer (WISE) and Near Earth Orbit WISE (NEOWISE) in two bands: W1 (3.4 microns) and W2 (4.6 microns), reducing the final sample to 256 objects. These objects are also classified into 155 BLLacs, 99 FSRQs, and 2 Narrow Line Seyferts, namely, PMNJ0948+0022 and PKS1502+036. Mid-infrared variability studies of these objects would be a contribution to the literature. With this as motivation, the present work is focused on studying a final sample of 256 objects in general and the Seyferts in particular. Owing to the fact that the classification is automated, SDSS has miclassified these objects into quasars, galaxies, and stars. Reasons for the misclassification are explained in this work. The variability analysis of these objects is done using the method of flux amplitude variability and excess variance. The sample consists of observations in both W1 and W2 bands. PMN J0948+0022 is observed between MJD from 57154.79 to 58810.57. PKS 1502+036 is observed between MJD from 57232.42 to 58517.11, which amounts to a period of over six years. The data is divided into different epochs spanning not more than 1.2 days. In all the epochs, the sources are found to be variable in both W1 and W2 bands. This confirms that the object is variable in mid-infrared wavebands in both long and short timescales. Also, the sources are observed for color variability. Objects either show a bluer when brighter trend (BWB) or a redder when brighter trend (RWB). The possible claim for the object to be BWB (present objects) is that the longer wavelength radiation emitted by the source can be suppressed by the high-energy radiation from the central source. Another result is that the smallest radius of the emission source is one day since the epoch span used in this work is one day. The mass of the black holes at the centers of these sources is found to be less than or equal to 108 solar masses, respectively.

Keywords: active galaxies, variability, Seyfert galaxies, SDSS, WISE

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Authors: Saule Mussabekova, Samal Abzhanova

Abstract:

The Kazakh Language Fluency Test, based on the IELTS exam, was implemented in 2012 at Nazarbayev University in Astana, Kazakhstan. We would like to share our experience in developing this exam and some exam results with other language instructors. In this paper, we will cover all these peculiarities and their related issues. The Kazakh Language Fluency Test is a young exam. During its development, we faced many difficulties. One of the goals of the university and the country is to encourage fluency in the Kazakh language for all citizens of the Republic. Nazarbayev University has introduced a Kazakh language program to assist in achieving this goal. This policy is one-step in ensuring that NU students have a thorough understanding of the Kazakh language through a fluency test based on the International English Language Testing System (IELTS). The Kazakh Language Fluency Test exam aims to determine student’s knowledge of Kazakh language. The fact is that there are three types of students at Nazarbayev University: Kazakh-speaking heritage learners, Russian-speaking and English-speaking students. Unfortunately, we have Kazakh students who do not speak Kazakh. All students who finished school with Russian language instruction are given Kazakh Language Fluency Test in order to determine their Kazakh level. After the test exam, all students can choose appropriate Kazakh course: Basic Kazakh, Intermediate Kazakh and Upper-Intermediate Kazakh. The Kazakh Language Fluency Test consists of four parts: Listening, Reading, Writing and Speaking. They are taken on the same day in the abovementioned order.

Keywords: diagnostic test, kazakh language, placement test, test result

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Authors: Ali Motevalli, Shahin Nayyeri Amiri

Abstract:

Cross-Hole Sonic Logging (CSL) is a common type of Non-Destructive Testing (NDT) method, which is currently used to check the integrity of placed drilled shafts. CSL evaluates the integrity of the concrete inside the cage and between the access tubes based on propagation of ultrasonic waves between two or more access tubes. A number of access tubes are installed inside the reinforcing cage prior to concrete placement as guides for sensors. The access tubes can be PVC or steel galvanized based on ASTM6760. The type of the CSL tubes can affect the axial strength of the drilled shaft. The objective of this study is to compare the amount of axial load capacity of drilled shafts due to using a different type of CSL tubes inside the caging. To achieve this, three (3) large-scale drilled shaft samples were built and tested using a hydraulic actuator at the Florida International University’s (FIU) Titan America Structures and Construction Testing (TASCT) laboratory. During the static load test, load-displacement curves were recorded by the data acquisition system (MegaDAC). Three drilled shaft samples were built to evaluate the effect of the type of the CSL tube on the axial load capacity in drilled shaft foundations.

Keywords: drilled shaft foundations, axial load capacity, cage, PVC, galvanized tube, CSL tube

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Authors: M. O. Bayram, H. B. Gencdal, N. O. Fercan, B. Basbug

Abstract:

Liquid limit, which is used as a measure of soil strength, can be detected by Casagrande and fall-cone testing methods. The two methods majorly diverge from each other in terms of operator dependency. The Casagrande method that is applied according to ASTM D4318-17 standards may give misleading results, especially if the calibration process is not performed well. To reveal the effect of calibration for drop height and amount of soil paste placement in the Casagrande cup, a series of tests were carried out by multipoint method as it is specified in the ASTM standards. The tests include the combination of 6 mm, 8 mm, 10 mm, and 12 mm drop heights and under-filled, half-filled, and full-filled Casagrande cups by kaolinite samples. It was observed that during successive tests, the drop height of the cup deteriorated; hence the device was recalibrated before and after each test to provide the accuracy of the results. Besides, the tests by under-filled and full-filled samples for higher drop heights revealed lower liquid limit values than the lower drop heights revealed. For the half-filled samples, it was clearly seen that the liquid limit values didn’t change at all as the drop height increased, and this explains the function of standard specifications.

Keywords: calibration, casagrande cup method, drop height, kaolinite, liquid limit, placing form

Procedia PDF Downloads 151