Search results for: automated teller machine

Authors: Mette Pedersen

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This paper outlines the criteria that assessment specialists use when they design the 'Persuasive Essay' task for the four Advanced Placement World Language and Culture Exams (AP French, German, Italian, and Spanish). The 'Persuasive Essay' is a free-response, source-based, standardized measure of presentational writing. Each 'Persuasive Essay' item consists of three sources (an article, a chart, and an audio) and a prompt, which is a statement of the topic phrased as an interrogative sentence. Due to its richness of source materials and due to the amount of time that test takers are given to prepare for and write their responses (a total of 55 minutes), the 'Persuasive Essay' is the free-response task on the AP World Language and Culture Exams that goes to the greatest lengths to unleash the test takers' proficiency potential. The author focuses on the work that goes into designing the 'Persuasive Essay' task, outlining best practices for the selection of topics and sources, the interplay that needs to be present among the sources and the thinking behind the articulation of prompts for the 'Persuasive Essay' task. Using released 'Persuasive Essay' items from the AP World Language and Culture Exams and accompanying data on test taker performance, the author shows how different passages, and features of passages, have succeeded (and sometimes not succeeded) in eliciting writing proficiency among test takers over time. Data from approximately 215.000 test takers per year from 2014 to 2017 and approximately 35.000 test takers per year from 2012 to 2013 form the basis of this analysis. The conclusion of the study is that test taker performance improves significantly when the sources that test takers are presented with express directly opposing viewpoints. Test taker performance also improves when the interrogative prompt that the test takers respond to is phrased as a yes/no question. Finally, an analysis of linguistic difficulty and complexity levels of the printed sources reveals that test taker performance does not decrease when the complexity level of the article of the 'Persuasive Essay' increases. This last text complexity analysis is performed with the help of the 'ETS TextEvaluator' tool and the 'Complexity Scale for Information Texts (Scale)', two tools, which, in combination, provide a rubric and a fully-automated technology for evaluating nonfiction and informational texts in English translation.

Keywords: advanced placement world language and culture exams, designing presentational writing assessments, large-scale standardized assessments of written language proficiency, source-based language testing

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Authors: Ming-Jong Tsai, T. M. Wu, R. C. Chu

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The purpose of this study is to develop an Advanced linear calibration Technique for air flow sensing by using CTA-based Hot wire Anemometry. It contains a host PC with Human Machine Interface, a wind tunnel, a wind speed controller, an automatic data acquisition module, and nonlinear calibration model. To improve the fitting error by using single fitting polynomial, this study proposes a Multiple three-order Polynomial Fitting Method (MPFM) for fitting the non-linear output of a CTA-based Hot wire Anemometry. The CTA-based anemometer with built-in fitting parameters is installed in the wind tunnel, and the wind speed is controlled by the PC-based controller. The Hot-Wire anemometer's thermistor resistance change is converted into a voltage signal or temperature differences, and then sent to the PC through a DAQ card. After completion measurements of original signal, the Multiple polynomial mathematical coefficients can be automatically calculated, and then sent into the micro-processor in the Hot-Wire anemometer. Finally, the corrected Hot-Wire anemometer is verified for the linearity, the repeatability, error percentage, and the system outputs quality control reports.

Keywords: flow rate sensing, hot wire, constant temperature anemometry (CTA), linear calibration, multiple three-order polynomial fitting method (MPFM), temperature compensation

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Authors: Yavuz Unal, Kemal Polat, H. Erdinc Kocer

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In this study, a decision support system comprising three stages has been proposed to detect the disc abnormalities of the lumbar region. In the first stage named the feature extraction, T2-weighted sagittal and axial Magnetic Resonance Images (MRI) were taken from 55 people and then 27 appearance and shape features were acquired from both sagittal and transverse images. In the second stage named the feature weighting process, k-means clustering based feature weighting (KMCBFW) proposed by Gunes et al. Finally, in the third stage named the classification process, the classifier algorithms including multi-layer perceptron (MLP- neural network), support vector machine (SVM), Naïve Bayes, and decision tree have been used to classify whether the subject has lumbar disc or not. In order to test the performance of the proposed method, the classification accuracy (%), sensitivity, specificity, precision, recall, f-measure, kappa value, and computation times have been used. The best hybrid model is the combination of k-means clustering based feature weighting and decision tree in the detecting of lumbar disc disease based on both sagittal and axial MR images.

Keywords: lumbar disc abnormality, lumbar MRI, lumbar spine, hybrid models, hybrid features, k-means clustering based feature weighting

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Authors: Mu-Yen Chen, Min-Hsuan Fan, Chia-Chen Chen, Siang-Yu Jhong

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In recent years, real estate prediction or valuation has been a topic of discussion in many developed countries. Improper hype created by investors leads to fluctuating prices of real estate, affecting many consumers to purchase their own homes. Therefore, scholars from various countries have conducted research in real estate valuation and prediction. With the back-propagation neural network that has been popular in recent years and the orthogonal array in the Taguchi method, this study aimed to find the optimal parameter combination at different levels of orthogonal array after the system presented different parameter combinations, so that the artificial neural network obtained the most accurate results. The experimental results also demonstrated that the method presented in the study had a better result than traditional machine learning. Finally, it also showed that the model proposed in this study had the optimal predictive effect, and could significantly reduce the cost of time in simulation operation. The best predictive results could be found with a fewer number of experiments more efficiently. Thus users could predict a real estate transaction price that is not far from the current actual prices.

Keywords: artificial neural network, Taguchi method, real estate valuation model, investors

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Authors: Aleksandr I. Korobov, Natalia V. Shirgina, Aleksey I. Kokshaiskiy, Vyacheslav M. Prokhorov

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The paper presents the results of an experimental study of the effect of reverse mechanical load-unloading on the mechanical, linear, and nonlinear elastic properties of n-AMg6/C60 nanocomposite. Samples for experimental studies of n-AMg6/C60 nanocomposite were obtained by grinding AMg6 polycrystalline alloy in a planetary mill with 0.3 wt % of C60 fullerite in an argon atmosphere. The resulting product consisted of 200-500-micron agglomerates of nanoparticles. X-ray coherent scattering (CSL) method has shown that the average nanoparticle size is 40-60 nm. The resulting preform was extruded at high temperature. Modifications of C60 fullerite interferes the process of recrystallization at grain boundaries. In the samples of n-AMg6/C60 nanocomposite, the load curve is measured: the dependence of the mechanical stress σ on the strain of the sample ε under its multi-cycle load-unloading process till its destruction. The hysteresis dependence σ = σ(ε) was observed, and insignificant residual strain ε < 0.005 were recorded. At σ≈500 MPa and ε≈0.025, the sample was destroyed. The destruction of the sample was fragile. Microhardness was measured before and after destruction of the sample. It was found that the loading-unloading process led to an increase in its microhardness. The effect of the reversible mechanical stress on the linear and nonlinear elastic properties of the n-AMg6/C60 nanocomposite was studied experimentally by ultrasonic method on the automated complex Ritec RAM-5000 SNAP SYSTEM. In the n-AMg6/C60 nanocomposite, the velocities of the longitudinal and shear bulk waves were measured with the pulse method, and all the second-order elasticity coefficients and their dependence on the magnitude of the reversible mechanical stress applied to the sample were calculated. Studies of nonlinear elastic properties of the n-AMg6/C60 nanocomposite at reversible load-unloading of the sample were carried out with the spectral method. At arbitrary values of the strain of the sample (up to its breakage), the dependence of the amplitude of the second longitudinal acoustic harmonic at a frequency of 2f = 10MHz on the amplitude of the first harmonic at a frequency f = 5MHz of the acoustic wave is measured. Based on the results of these measurements, the values of the nonlinear acoustic parameter in the n-AMg6/C60 nanocomposite sample at different mechanical stress were determined. The obtained results can be used in solid-state physics, materials science, for development of new techniques for nondestructive testing of structural materials using methods of nonlinear acoustic diagnostics. This study was supported by the Russian Science Foundation (project №14-22-00042).

Keywords: nanocomposite, generation of acoustic harmonics, nonlinear acoustic parameter, hysteresis

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Authors: R. Dangtungee, A. Rattanapan, S. Siengchin

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Waste silicon carbide (waste SiC) filled high-density polyethylene (HDPE) with and without surface modifiers were studied. Two types of surface modifiers namely; high-density polyethylene-grafted-maleic anhydride (HDPE-g-MA) and 3-aminopropyltriethoxysilane have been used in this study. The composites were produced using a two roll mill, extruder and shaped in a hydraulic compression molding machine. The mechanical properties of polymer composites such as flexural strength and modulus, impact strength, tensile strength, stiffness and hardness were investigated over a range of compositions. It was found that, flexural strength and modulus, tensile modulus and hardness increased, whereas impact strength and tensile strength decreased with the increasing in filler contents, compared to the neat HDPE. At similar filler content, the effect of both surface modifiers increased flexural modulus, impact strength, tensile strength and stiffness but reduced the flexural strength. Morphological investigation using SEM revealed that the improvement in mechanical properties was due to enhancement of the interfacial adhesion between waste SiC and HDPE.

Keywords: high-density polyethylene, HDPE-g-MA, mechanical properties, morphological properties, silicon carbide, waste silicon carbide

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Authors: Suresh Vidyasagar Chevuri, D. B. Karunakar Chevuri

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The main advantages of 'Metal Matrix Nano Composites (MMNCs)' include excellent mechanical performance, good wear resistance, low creep rate, etc. The method of fabrication of MMNCs is quite a challenge, which includes processing techniques like Spark Plasma Sintering (SPS), etc. The objective of the present work is to fabricate aluminum based MMNCs with the addition of small amounts of yttrium using Spark Plasma Sintering and to evaluate their mechanical and microstructure properties. Samples of 2024 AA with yttrium ranging from 0.1% to 0.5 wt% keeping 1 wt% TiB2 constant are fabricated by Spark Plasma Sintering (SPS). The mechanical property like hardness is determined using Vickers hardness testing machine. The metallurgical characterization of the samples is evaluated by Optical Microscopy (OM), Field Emission Scanning Electron Microscopy (FE-SEM) and X-Ray Diffraction (XRD). Unreinforced 2024 AA sample is also fabricated as a benchmark to compare its properties with that of the composite developed. It is found that the yttrium addition increases the above-mentioned properties to some extent and then decreases gradually when yttrium wt% increases beyond a point between 0.3 and 0.4 wt%. High density is achieved in the samples fabricated by spark plasma sintering when compared to any other fabrication route, and uniform distribution of yttrium is observed.

Keywords: spark plasma sintering, 2024 AA, yttrium addition, microstructure characterization, mechanical properties

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Authors: Mahadehe Hassan

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In most countries manufacturing, trading and distribution of gasoline and diesel fuels belongs to the most important sectors of national economy. For Bangladesh, a robust, well-functioning, secure and smartly managed national fuel distribution chain is an essential precondition for achieving Government top priorities in development and modernization of transportation infrastructure, protection of national environment and population health as well as, very importantly, securing due tax revenue for the State Budget. Bangladesh is a developing country with complex fuel supply network, high fuel taxes incidence and – till now - limited possibilities in application of modern, automated technologies for Government national fuel market control. Such environment allows dishonest physical and legal persons and organized criminals to build and profit from illegal fuel distribution schemes and fuel illicit trade. As a result, the market transparency and the country attractiveness for foreign investments, law-abiding economic operators, national consumers, State Budget and the Government ability to finance development projects, and the country at large suffer significantly. Research shows that over 50% of retail petrol stations in major agglomerations of Bangladesh sell adulterated fuels and/or cheat customers on the real volume of the fuel pumped into their vehicles. Other forms of detected fuel illicit trade practices include misdeclaration of fuel quantitative and qualitative parameters during internal transit and selling of non-declared and smuggled fuels. The aim of the study is to recommend the implementation of a National Fuel Distribution Integrity Program (FDIP) in Bangladesh to address and resolve fuel adulteration and illicit trade problems. The program should be customized according to the specific needs of the country and implemented in partnership with providers of advanced technologies. FDIP should enable and further enhance capacity of respective Bangladesh Government authorities in identification and elimination of all forms of fuel illicit trade swiftly and resolutely. FDIP high-technology, IT and automation systems and secure infrastructures should be aimed at the following areas (1) fuel adulteration, misdeclaration and non-declaration; (2) fuel quality and; (3) fuel volume manipulation at retail level. Furthermore, overall concept of FDIP delivery and its interaction with the reporting and management systems used by the Government shall be aligned with and support objectives of the Vision 2041 and Smart Bangladesh Government programs.

Keywords: fuel adulteration, octane, kerosene, diesel, petrol, pollution, carbon emissions

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Authors: Jiaqi Dong, Qing-Hua Qin, Yi Xiao

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Some of the most fundamental challenges of elastic metamaterials (EMMs) optimization can be attributed to the high consumption of computational power resulted from finite element analysis (FEA) simulations that render the optimization process inefficient. Furthermore, due to the inherent mesh dependence of FEA, minuscule geometry features, which often emerge during the later stages of optimization, induce very fine elements, resulting in enormously high time consumption, particularly when repetitive solutions are needed for computing the objective function. In this study, a surrogate modelling algorithm is developed to reduce computational time in structural optimization of EMMs. The surrogate model is constructed based on a multilayer feedforward artificial neural network (ANN) architecture, trained with prepopulated eigenfrequency data prepopulated from FEA simulation and optimized through regime selection with genetic algorithm (GA) to improve its accuracy in predicting the location and width of the primary elastic band gap. With the optimized ANN surrogate at the core, a Nelder-Mead (NM) algorithm is established and its performance inspected in comparison to the FEA solution. The ANNNM model shows remarkable accuracy in predicting the band gap width and a reduction of time consumption by 47%.

Keywords: artificial neural network, machine learning, mechanical metamaterials, Nelder-Mead optimization

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Authors: Aragorn Joaquin Pineda Dela Cruz

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Road traffic congestion is continually deteriorating in Hong Kong. The largest contributing factor is the increase in vehicle fleet size, resulting in higher competition over the utilisation of road space. This study proposes a project that can process closed-circuit television images and videos to provide real-time traffic detection and prediction capabilities. Specifically, a deep-learning model involving computer vision techniques for video and image-based vehicle counting, then a separate model to detect and predict traffic congestion levels based on said data. State-of-the-art object detection models such as You Only Look Once and Faster Region-based Convolutional Neural Networks are tested and compared on closed-circuit television data from various major roads in Hong Kong. It is then used for training in long short-term memory networks to be able to predict traffic conditions in the near future, in an effort to provide more precise and quicker overviews of current and future traffic conditions relative to current solutions such as navigation apps.

Keywords: intelligent transportation system, vehicle detection, traffic analysis, deep learning, machine learning, computer vision, traffic prediction

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Authors: S. Sharan Sundar, Nithish B. Moudhgalya, Nidhi Bhandari, Vineeth Vijayaraghavan

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Automatic Short Answer Grading is one of the prime applications of artificial intelligence in education. Several approaches involving the utilization of selective handcrafted features, graphical matching techniques, concept identification and mapping, complex deep frameworks, sentence embeddings, etc. have been explored over the years. However, keeping in mind the real-world application of the task, these solutions present a slight overhead in terms of computations and resources in achieving high performances. In this work, a simple and effective solution making use of elemental features based on statistical, linguistic properties, and word-based similarity measures in conjunction with tree-based classifiers and regressors is proposed. The results for classification tasks show improvements ranging from 1%-30%, while the regression task shows a stark improvement of 35%. The authors attribute these improvements to the addition of multiple similarity scores to provide ensemble of scoring criteria to the models. The authors also believe the work could reinstate that classical natural language processing techniques and simple machine learning models can be used to achieve high results for short answer grading.

Keywords: artificial intelligence, intelligent systems, natural language processing, text mining

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Authors: Justyna Humięcka-Jakubowska

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1. Background in music analysis. Traditionally, when we think about a composer’s sketches, the chances are that we are thinking in terms of the working out of detail, rather than the evolution of an overall concept. Since music is a “time art’, it follows that questions of a form cannot be entirely detached from considerations of time. One could say that composers tend to regard time either as a place gradually and partially intuitively filled, or they can look for a specific strategy to occupy it. In my opinion, one thing that sheds light on Stockhausen's compositional thinking is his frequent use of 'form schemas', that is often a single-page representation of the entire structure of a piece. 2. Background in music technology. Sonic Visualiser is a program used to study a musical recording. It is an open source application for viewing, analysing, and annotating music audio files. It contains a number of visualisation tools, which are designed with useful default parameters for musical analysis. Additionally, the Vamp plugin format of SV supports to provide analysis such as for example structural segmentation. 3. Aims. The aim of my paper is to show how SV may be used to obtain a better understanding of the specific musical work, and how the compositional strategy does impact on musical structures and musical surfaces. I want to show that ‘traditional” music analytic methods don’t allow to indicate interrelationships between musical surface (which is perceived) and underlying musical/acoustical structure. 4. Main Contribution. Stockhausen had dealt with the most diverse musical problems by the most varied methods. A characteristic which he had never ceased to be placed at the center of his thought and works, it was the quest for a new balance founded upon an acute connection between speculation and intuition. In the case with Mikrophonie I (1964) for tam-tam and 6 players Stockhausen makes a distinction between the "connection scheme", which indicates the ground rules underlying all versions, and the form scheme, which is associated with a particular version. The preface to the published score includes both the connection scheme, and a single instance of a "form scheme", which is what one can hear on the CD recording. In the current study, the insight into the compositional strategy chosen by Stockhausen was been compared with auditory image, that is, with the perceived musical surface. Stockhausen's musical work is analyzed both in terms of melodic/voice and timbre evolution. 5. Implications The current study shows how musical structures have determined of musical surface. My general assumption is this, that while listening to music we can extract basic kinds of musical information from musical surfaces. It is shown that an interactive strategies of musical structure analysis can offer a very fruitful way of looking directly into certain structural features of music.

Keywords: automated analysis, composer's strategy, mikrophonie I, musical surface, stockhausen

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Authors: C. Fernanda da S. Sampaio, M. Gabriela Sadith Perez Paredes, V. Antonio de O. Martins

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Today the transport sector is undergoing a revolution, with the rise of Advanced Driver Assistance Systems (ADAS), industry and society itself will undergo a major transformation. However, the technological development of these applications is a challenge that requires new techniques and great machine learning and artificial intelligence. The study proposes to develop a vehicular perception system called Veibra, which consists of two front cameras for day/night viewing and an embedded device capable of working with Yolov2 image processing algorithms with low computational cost. The strategic version for the market is to assist the driver on the road with the detection of day/night objects, such as road signs, pedestrians, and animals that will be viewed through the screen of the phone or tablet through an application. The system has the ability to perform real-time driver detection and recognition to identify muscle movements and pupils to determine if the driver is tired or inattentive, analyzing the student's characteristic change and following the subtle movements of the whole face and issuing alerts through beta waves to ensure the concentration and attention of the driver. The system will also be able to perform tracking and monitoring through GSM (Global System for Mobile Communications) technology and the cameras installed in the vehicle.

Keywords: advanced driver assistance systems, tracking, traffic signal detection, vehicle perception system

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Authors: Prashant Parhad, Vinayak Dakre, Ajay Likhite, Jatin Bhatt

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This work mainly focuses on machinability studies of Austempered Ductile Iron (ADI). The Ductile Iron (DI) was austempered at 250 oC for different durations and the process window for austempering was established by studying the microstructure. The microstructural characterization of the material was done using optical microscopy, SEM and XRD. The samples austempered as per the process window were then subjected to turning using a TiAlN-coated tungsten carbide insert to study the effect of cutting parameters, namely the cutting speed and the depth of cut. The effect was investigated in terms of cutting forces required as well as the surface roughness obtained. The turning was conducted on a CNC turning machine and primary (Fx), radial (Fy) and feed (Fz) cutting forces were quantified with a three-component dynamometer. It was observed that the magnitude of radial force was more than that of primary cutting force for all cutting speed and for various depths of cut studied. It has also been seen that increasing the cutting speed improves the surface quality. The observed machinability behaviour was investigated in light of the microstructure of the material obtained under the given austempering conditions and a structure-property- co-relation was established between the two. For all cutting speed and depth of cut, the best machining response in terms of cutting forces and surface quality was obtained towards the centre of process window.

Keywords: process window, cutting speed, depth of cut, surface roughness

Procedia PDF Downloads 367

Authors: John Cheferson R. De Belen, John Paul G. Elizares, Ronald John G. Raz, Janina Elyse A. Reyes, Charie G. Salengua, Aristotle L. Soriano

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Plastic is a type of synthetic or man-made polymer that can readily be molded into a variety of products. Its usage over the past century has enabled society to make huge technological advances. The workers of United Asia International Plastics Corporation (UAIPC), a plastic manufacturing company performs manual packaging which causes fatigue and stress on their arm, neck, and legs due to extended periods of standing and repetitive motions. With the use of the Fishbone Diagram, Five-Why Analysis, Rapid Entire Body Assessment (REBA), and Anthropometry, the stressful tasks and activities were identified and analyzed. Given the anthropometric measurements obtained from the workers, improved dimensions for the tables and chairs should be used and provide a new packaging machine. The validation of this proposal shall follow after its implementation. By eliminating fatigue during working hours in the production, the workers will be at ease at performing their work properly; productivity will increase that will lead to more profit. Further areas for study include measurement and comparison of the worker’s anthropometric measurement with the industry standard.

Keywords: anthropometry, fishbone diagram, five-why analysis, rapid entire body assessment

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Authors: Waleed A. Basuliman, Khalid S. AlSaleh, Mohamed Z. Ramadan

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Applying the anthropometric dimensions is considered one of the important factors when designing any human-machine system. In this study, the estimation of anthropometric dimensions has been improved by developing artificial neural network that aims to predict the anthropometric measurements of the male in Saudi Arabia. A total of 1427 Saudi males from age 6 to 60 participated in measuring twenty anthropometric dimensions. These anthropometric measurements are important for designing the majority of work and life applications in Saudi Arabia. The data were collected during 8 months from different locations in Riyadh City. Five of these dimensions were used as predictors variables (inputs) of the model, and the remaining fifteen dimensions were set to be the measured variables (outcomes). The hidden layers have been varied during the structuring stage, and the best performance was achieved with the network structure 6-25-15. The results showed that the developed Neural Network model was significantly able to predict the body dimensions for the population of Saudi Arabia. The network mean absolute percentage error (MAPE) and the root mean squared error (RMSE) were found 0.0348 and 3.225 respectively. The accuracy of the developed neural network was evaluated by compare the predicted outcomes with a multiple regression model. The ANN model performed better and resulted excellent correlation coefficients between the predicted and actual dimensions.

Keywords: artificial neural network, anthropometric measurements, backpropagation, real anthropometric database

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Authors: Bowei Yuan, Shi Li, Liuyang Song, Huaqing Wang, Lingli Cui

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Convolutional neural networks (CNN) have received extensive attention in the field of fault diagnosis. Many fault diagnosis methods use CNN for fault type identification. However, when the amount of raw data collected by sensors is massive, the neural network needs to perform a time-consuming classification task. In this paper, a mechanical fault diagnosis method based on vibration signal down-sampling and the improved one-dimensional convolutional neural network is proposed. Through the robust principal component analysis, the low-rank feature matrix of a large amount of raw data can be separated, and then down-sampling is realized to reduce the subsequent calculation amount. In the improved one-dimensional CNN, a smaller convolution kernel is used to reduce the number of parameters and computational complexity, and regularization is introduced before the fully connected layer to prevent overfitting. In addition, the multi-connected layers can better generalize classification results without cumbersome parameter adjustments. The effectiveness of the method is verified by monitoring the signal of the centrifugal pump test bench, and the average test accuracy is above 98%. When compared with the traditional deep belief network (DBN) and support vector machine (SVM) methods, this method has better performance.

Keywords: fault diagnosis, vibration signal down-sampling, 1D-CNN

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Authors: S. Valarmathi, P. B. Harathi, R. Sridhar, S. Balasubramanian

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Machine learning tools in medical diagnosis is increasing due to the improved effectiveness of classification and recognition systems to help medical experts in diagnosing breast cancer. In this study, ID3 chooses the splitting attribute with the highest gain in information, where gain is defined as the difference between before the split versus after the split. It is applied for age, location, taluk, stage, year, period, martial status, treatment, heredity, sex, and habitat against Very Serious (VS), Very Serious Moderate (VSM), Serious (S) and Not Serious (NS) to calculate the gain of information. The ranked histogram gives the gain of each field for the breast cancer data. The doctors use TNM staging which will decide the risk level of the breast cancer and play an important decision making field in fuzzy logic for perception based measurement. Spatial risk area (taluk) of the breast cancer is calculated. Result clearly states that Coimbatore (North and South) was found to be risk region to the breast cancer than other areas at 20% criteria. Weighted value of taluk was compared with criterion value and integrated with Map Object to visualize the results. ID3 algorithm shows the high breast cancer risk regions in the study area. The study has outlined, discussed and resolved the algorithms, techniques / methods adopted through soft computing methodology like ID3 algorithm for prognostic decision making in the seriousness of the breast cancer.

Keywords: ID3 algorithm, breast cancer, fuzzy logic, MATLAB

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Authors: M. K. Yusuf, W. O. Hamman, U. E. Umana, S. B. Oladele

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Background: Dilatation of the inferior vena cava (IVC) is used as the ultrasonic diagnostic feature in patients suspected of congestive heart failure. The IVC diameter has been reported to vary among the various body mass indexes (BMI) and body shape indexes (ABSI). Knowledge of these variations is useful in precision diagnoses of CHF by imaging scientists. Aim: The study aimed to establish an equation for predicting the ultrasonic mean diameter of the IVC among the various BMI/ABSI of inhabitants of Azare, Bauchi State-Nigeria. Methodology: Two hundred physically healthy adult subjects of both sexes were classified into under, normal, over, and obese weights using their BMIs after selection using a structured questionnaire following their informed consent for an abdominal ultrasound scan. The probe was placed on the midline of the body, halfway between the xiphoid process and the umbilicus, with the marker on the probe directed towards the patient's head to obtain a longitudinal view of the IVC. The maximum IVC diameter was measured from the subcostal view using the electronic caliper of the scan machine. The mean value of each group was obtained, and the results were analysed. Results: A novel equation {(IVC Diameter = 1.04 +0.01(X) where X= BMI} has been generated for determining the IVC diameter among the populace. Conclusion: An equation for predicting the IVC diameter from individual BMI values in apparently healthy subjects has been established.

Keywords: equation, ultrasonic, IVC diameter, body adiposities

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Authors: P. Kavuma, J. Mukasa, M. Lusunku

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Background and Problem: The widespread poverty in Africa- together with the negative impacts of climate change-are two great global challenges that call for everyone’s involvement including Architects. This in particular places serious challenges on architects to have additional skills in both Entrepreneurship and Environmental Design (SEED). Regrettably, while Architectural Training in most African Universities including those from Uganda lack comprehensive implementation of SEED in their curricula, regulatory bodies have not contributed towards the effective integration of SEED in their professional practice. In response to these challenges, Nkumba University (NU) under Architect Kavuma Paul supported by the Uganda Chambers of Architects– initiated the SEED integration in the undergraduate Architectural curricula to cultivate SEED know-how and examples of best practices. Main activities: Initiated in 2007, going beyond the traditional Architectural degree curriculum, the NU Architect department offers SEED courses including provoking passions for creating desirable positive changes in communities. Learning outcomes are assessed theoretically and practically through field projects. The first set of SEED graduates came out in 2012. As part of the NU post-graduation and alumni survey, in October 2014, the pioneer SEED graduates were contacted through automated reminder emails followed by individual, repeated personal follow-ups via email and phone. Out of the 36 graduates who responded to the survey, 24 have formed four (4) private consortium agencies of 5-7 graduates all of whom have pioneered Ugandan-own-cultivated Architectural social projects that include: fishing farming in shipping containers; solar powered mobile homes in shipping containers, solar powered retail kiosks in rural and fishing communities, and floating homes in the flood-prone areas. Primary outcomes: include being business self –reliant in creating the social change the architects desired in the communities. Examples of the SEED project returns to communities reported by the graduates include; employment creation via fabrication, retail business, marketing, improved diets, safety of life and property, decent shelter in the remote mining and oil exploration areas. Negative outcomes-though not yet evaluated include the disposal of used-up materials. Conclusion: The integration of SEED in Architectural Training has established a baseline benchmark and a replicable model based on best practice projects.

Keywords: architectural training, entrepreneurship, environment, integration

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Authors: Ashok Kalagura

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This paper presents a data-mining model for fault-zone identification of flexible AC transmission systems (FACTS)-based transmission line including a thyristor-controlled series compensator (TCSC) and unified power-flow controller (UPFC), using ensemble decision trees. Given the randomness in the ensemble of decision trees stacked inside the random forests model, it provides an effective decision on the fault-zone identification. Half-cycle post-fault current and voltage samples from the fault inception are used as an input vector against target output ‘1’ for the fault after TCSC/UPFC and ‘1’ for the fault before TCSC/UPFC for fault-zone identification. The algorithm is tested on simulated fault data with wide variations in operating parameters of the power system network, including noisy environment providing a reliability measure of 99% with faster response time (3/4th cycle from fault inception). The results of the presented approach using the RF model indicate the reliable identification of the fault zone in FACTS-based transmission lines.

Keywords: distance relaying, fault-zone identification, random forests, RFs, support vector machine, SVM, thyristor-controlled series compensator, TCSC, unified power-flow controller, UPFC

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Authors: Bin Liu

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MicroRNAs (miRNAs) are small non-coding RNA molecules, functioning in transcriptional and post-transcriptional regulation of gene expression. The discrimination of the real pre-miRNAs from the false ones (such as hairpin sequences with similar stem-loops) is necessary for the understanding of miRNAs’ role in the control of cell life and death. Since both their small size and sequence specificity, it cannot be based on sequence information alone but requires structure information about the miRNA precursor to get satisfactory performance. Kmers are convenient and widely used features for modeling the properties of miRNAs and other biological sequences. However, Kmers suffer from the inherent limitation that if the parameter K is increased to incorporate long range effects, some certain Kmer will appear rarely or even not appear, as a consequence, most Kmers absent and a few present once. Thus, the statistical learning approaches using Kmers as features become susceptible to noisy data once K becomes large. In this study, we proposed a Gapped k-mer approach to overcome the disadvantages of Kmers, and applied this method to the field of miRNA prediction. Combined with the structure status composition, a classifier called imiRNA-GSSC was proposed. We show that compared to the original imiRNA-kmer and alternative approaches. Trained on human miRNA precursors, this predictor can achieve an accuracy of 82.34 for predicting 4022 pre-miRNA precursors from eleven species.

Keywords: gapped k-mer, imiRNA-GSSC, microRNA precursor, support vector machine

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Authors: Raphael Tuor, Denis Lalanne

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The ATM research community is missing suitable tools to design, test, and validate new UI prototypes. Important stakes underline the implementation of both DSS and XAI methods into current systems. ML-based DSS are gaining in relevance as ATFM becomes increasingly complex. However, these systems only prove useful if a human can understand them, and thus new XAI methods are needed. The human-machine dyad should work as a team and should understand each other. We present xSky, a configurable benchmark tool that allows us to compare different versions of an ATC interface in conflict detection tasks. Our main contributions to the ATC research community are (1) a conflict detection task simulator (xSky) that allows to test the applicability of visual prototypes on scenarios of varying difficulty and outputting relevant operational metrics (2) a theoretical approach to the explanations of AI-driven trajectory predictions. xSky addresses several issues that were identified within available research tools. Researchers can configure the dimensions affecting scenario difficulty with a simple CSV file. Both the content and appearance of the XAI elements can be customized in a few steps. As a proof-of-concept, we implemented an XAI prototype inspired by the maritime field.

Keywords: air traffic control, air traffic simulation, conflict detection, explainable artificial intelligence, explainability, human-automation collaboration, human factors, information visualization, interpretability, trajectory prediction

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Authors: Thiago Viana

Abstract:

Eventually train accidents occur on railways and for some specific cases it is necessary to use a train rescue with a crane positioned under a platform wagon. These tumbled machines are collected and sent to the machine shop or scrap yard. In one of these cranes that were being used to rescue a wagon, occurred a fall of hoist due to fracture of two large pins. The two pins were collected and sent for failure analysis. This work investigates the main cause and the secondary causes for the initiation of the fatigue crack. All standard failure analysis procedures were applied, with careful evaluation of the characteristics of the material, fractured surfaces and, mainly, metallographic tests using an optical microscope to compare the geometry of the peaks and valleys of the thread of the pins and their respective seats. By metallographic analysis, it was concluded that the fatigue cracks were started from a notch (stress concentration) in the valley of the threads of the pin applied to the right side of the crane (pin 1). In this, it was verified that the peaks of the threads of the pin seat did not have proper geometry, with sharp edges being present that caused such notches. The visual analysis showed that fracture of the pin on the left side of the crane (pin 2) was brittle type, being a consequence of the fracture of the first one. Recommendations for this and other railway cranes have been made, such as nondestructive testing, stress calculation, design review, quality control and suitability of the mechanical forming process of the seat threads and pin threads.

Keywords: crane, fracture, pin, railway

Procedia PDF Downloads 106

Authors: Smah Almotiri

Abstract:

One of the most common fields of natural language processing (NLP) is sentimental analysis. The inferred feeling in the text can be successfully mined for various events using sentiment analysis. Twitter is viewed as a reliable data point for sentimental analytics studies since people are using social media to receive and exchange different types of data on a broad scale during the COVID-19 epidemic. The processing of such data may aid in making critical decisions on how to keep the situation under control. The aim of this research is to look at how sentimental states differed in a single geographic region during the lockdown at two different times.1162 tweets were analyzed related to the COVID-19 pandemic lockdown using keywords hashtags (lockdown, COVID-19) for the first sample tweets were from March 23, 2020, until April 23, 2020, and the second sample for the following year was from March 1, 2020, until April 4, 2020. Natural language processing (NLP), which is a form of Artificial intelligence, was used for this research to calculate the sentiment value of all of the tweets by using AFINN Lexicon sentiment analysis method. The findings revealed that the sentimental condition in both different times during the region's lockdown was positive in the samples of this study, which are unique to the specific geographical area of New Zealand. This research suggests applying machine learning sentimental methods such as Crystal Feel and extending the size of the sample tweet by using multiple tweets over a longer period of time.

Keywords: sentiment analysis, Twitter analysis, lockdown, Covid-19, AFINN, NodeJS

Procedia PDF Downloads 189

Authors: Songul Cinaroglu

Abstract:

Background: Random Forest is an efficient, multi-class machine learning method using for classification, regression and other tasks. This method is operating by constructing each tree using different bootstrap sample of the data. Determining the number of trees in random forests is an open question in the literature for studies about improving classification performance of random forests. Aim: The aim of this study is to analyze whether there is an optimal number of trees in Random Forests and how performance of Random Forests differ according to increase in number of trees using sample health data sets in R programme. Method: In this study we analyzed the performance of Random Forests as the number of trees grows and doubling the number of trees at every iteration using “random forest” package in R programme. For determining minimum and optimal number of trees we performed Mc Nemar test and Area Under ROC Curve respectively. Results: At the end of the analysis it was found that as the number of trees grows, it does not always means that the performance of the forest is better than forests which have fever trees. In other words larger number of trees only increases computational costs but not increases performance results. Conclusion: Despite general practice in using random forests is to generate large number of trees for having high performance results, this study shows that increasing number of trees doesn’t always improves performance. Future studies can compare different kinds of data sets and different performance measures to test whether Random Forest performance results change as number of trees increase or not.

Keywords: classification methods, decision trees, number of trees, random forest

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Authors: Fereshteh Zarei, Mahdi Kohandel

Abstract:

The aim of this study was investigate and compare plyometric and vibration exercises on muscle explosive power in non-athlete female students. For this purpose, 45 female students from non-athletes selected target then divided in to the three groups, two experimental and one control groups. From all groups were getting pre-tested. Experimental A did whole-body vibration exercises involved standing on one of machine vibration with frequency 30 Hz, amplitude 10 mm and in 5 different postures. Training for each position was 40 seconds with 60 seconds rest between it, and each season 5 seconds was added to duration of each body condition, until time up to 2 minutes for each postures. Exercises were done three times a week for 2 month. Experimental group B did plyometric exercises that include jumping, such as horizontal, vertical, and skipping .They included 10 times repeat for 5 set in each season. Intensity with increasing repetitions and sets were added. At this time, asked from control group that keep a daily activity and avoided strength training, explosive power and. after do exercises by groups we measured factors again. One-way analysis of variance and paired t statistical methods were used to analyze the data. There was significant difference in the amount of explosive power between the control and vibration groups (p=0/048) there was significant difference between the control and plyometric groups (019/0 = p). But between vibration and plyometric groups didn't observe significant difference in the amount of explosive power.

Keywords: vibration, plyometric, exercises, explosive power, non-athlete

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Authors: A. Luft, S. Bremen, N. Balc

Abstract:

The task of flexibility planning and design, just like factory planning, for example, is to create the long-term systemic framework that constitutes the restriction for short-term operational management. This is a strategic challenge since, due to the decision defect character of the underlying flexibility problem, multiple types of flexibility need to be considered over the course of various scenarios, production programs, and production system configurations. In this context, an evaluation model has been developed that integrates both conventional and additive resources on a basic task level and allows the quantification of flexibility enhancement in terms of mix and volume flexibility, complexity reduction, and machine capacity. The model helps companies to decide in early decision-making processes about the potential gains of implementing additive manufacturing technologies on a strategic level. For companies, it is essential to consider both additive and conventional manufacturing beyond pure unit costs. It is necessary to achieve an integrative view of manufacturing that incorporates both additive and conventional manufacturing resources and quantifies their potential with regard to flexibility and manufacturing complexity. This also requires a structured process for the strategic production systems design that spans the design of various scenarios and allows for multi-dimensional and comparative analysis. A respective guideline for the planning of additive resources on a strategic level is being laid out in this paper.

Keywords: additive manufacturing, production system design, flexibility enhancement, strategic guideline

Procedia PDF Downloads 122

Authors: Nicolò Vaiana, Mariacristina Spizzuoco, Giorgio Serino

Abstract:

In this paper, the results of experimental tests performed on a Helical Wire Rope Isolator (HWRI) are presented in order to describe the dynamic and static behavior of the selected metal device in three different displacements ranges, namely small, relatively large, and large displacements ranges, without and under the effect of a vertical load. A testing machine, allowing to apply horizontal displacement or load histories to the tested bearing with a constant vertical load, has been adopted to perform the dynamic and static tests. According to the experimental results, the dynamic behavior of the tested device depends on the applied displacement amplitude. Indeed, the HWRI displays a softening and a hardening stiffness at small and relatively large displacements, respectively, and a stronger nonlinear stiffening behavior at large displacements. Furthermore, the experimental tests reveal that the application of a vertical load allows to have a more flexible device with higher damping properties and that the applied vertical load affects much less the dynamic response of the metal device at large displacements. Finally, a decrease in the static to dynamic effective stiffness ratio with increasing displacement amplitude has been observed.

Keywords: base isolation, earthquake engineering, experimental hysteresis loops, wire rope isolators

Procedia PDF Downloads 432

Authors: Idris Idris Sunusi, U.S. Muhammed, N.A. Sale, I.B. Dalha, N.A. Adam

Abstract:

Threshing efficiency and mechanical grain damages are among the important parameters used in rating the performance of agricultural threshers. To be acceptable to farmers, threshers should have high threshing efficiency and low grain. The objective of the research is to evaluate the performances of the thresher using sorghum and millet, the performances parameters considered are; threshing efficiency and mechanical grain damage. For millet, four drum speed levels; 700, 800, 900 and 1000 rpm were considered while for sorghum; 600, 700, 800 and 900 rpm were considered. The feed rate levels were 3, 4, 5 and 6 kg/min for both sorghum and millet; the levels of moisture content were 8.93 and 10.38% for sorghum and 9.21 and 10.81% for millet. For millet the test result showed a maximum of 98.37 threshing efficiencies and a minimum of 0.24% mechanical grain damage while for sorghum the test result indicated a maximum of 99.38 threshing efficiencies, and a minimum of 0.75% mechanical grain damage. In comparison to the previous thresher, the threshing efficiency and mechanical grain damage of the modified machine has improved by 2.01% and 330.56% for millet and 5.31%, 287.64% for sorghum. Also analysis of variance (ANOVA) showed that, the effect of drum speed, feed rate and moisture content were significant on the performance parameters.

Keywords: Threshing Efficiency, Mechanical Grain Damages, Sorghum and Millet, Multi Crop Thresher

Procedia PDF Downloads 348