Search results for: machining accuracy.
1476 Exercise and Cognitive Function: Time Course of the Effects
Authors: Simon B. Cooper, Stephan Bandelow, Maria L. Nute, John G. Morris, Mary E. Nevill
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Previous research has indicated a variable effect of exercise on adolescents’ cognitive function. However, comparisons between studies are difficult to make due to differences in: the mode, intensity and duration of exercise employed; the components of cognitive function measured (and the tests used to assess them); and the timing of the cognitive function tests in relation to the exercise. Therefore, the aim of the present study was to assess the time course (10 and 60min post-exercise) of the effects of 15min intermittent exercise on cognitive function in adolescents. 45 adolescents were recruited to participate in the study and completed two main trials (exercise and resting) in a counterbalanced crossover design. Participants completed 15min of intermittent exercise (in cycles of 1 min exercise, 30s rest). A battery of computer based cognitive function tests (Stroop test, Sternberg paradigm and visual search test) were completed 30 min pre- and 10 and 60min post-exercise (to assess attention, working memory and perception respectively).The findings of the present study indicate that on the baseline level of the Stroop test, 10min following exercise response times were slower than at any other time point on either trial (trial by session time interaction, p = 0.0308). However, this slowing of responses also tended to produce enhanced accuracy 10min post-exercise on the baseline level of the Stroop test (trial by session time interaction, p = 0.0780). Similarly, on the complex level of the visual search test there was a slowing of response times 10 min post-exercise (trial by session time interaction, p = 0.0199). However, this was not coupled with an improvement in accuracy (trial by session time interaction, p = 0.2349). The mid-morning bout of exercise did not affect response times or accuracy across the morning on the Sternberg paradigm. In conclusion, the findings of the present study suggest an equivocal effect of exercise on adolescents' cognitive function. The mid-morning bout of exercise appears to cause a speed-accuracy trade off immediately following exercise on the Stroop test (participants become slower but more accurate), whilst slowing response times on the visual search test and having no effect on performance on the Sternberg paradigm. Furthermore, this work highlights the importance of the timing of the cognitive function tests relative to the exercise and the components of cognitive function examined in future studies.
Keywords: Adolescents, cognitive function, exercise.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 31241475 Introductory Design Optimisation of a Machine Tool using a Virtual Machine Concept
Authors: Johan Wall, Johan Fredin, Anders Jönsson, Göran Broman
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Designing modern machine tools is a complex task. A simulation tool to aid the design work, a virtual machine, has therefore been developed in earlier work. The virtual machine considers the interaction between the mechanics of the machine (including structural flexibility) and the control system. This paper exemplifies the usefulness of the virtual machine as a tool for product development. An optimisation study is conducted aiming at improving the existing design of a machine tool regarding weight and manufacturing accuracy at maintained manufacturing speed. The problem can be categorised as constrained multidisciplinary multiobjective multivariable optimisation. Parameters of the control and geometric quantities of the machine are used as design variables. This results in a mix of continuous and discrete variables and an optimisation approach using a genetic algorithm is therefore deployed. The accuracy objective is evaluated according to international standards. The complete systems model shows nondeterministic behaviour. A strategy to handle this based on statistical analysis is suggested. The weight of the main moving parts is reduced by more than 30 per cent and the manufacturing accuracy is improvement by more than 60 per cent compared to the original design, with no reduction in manufacturing speed. It is also shown that interaction effects exist between the mechanics and the control, i.e. this improvement would most likely not been possible with a conventional sequential design approach within the same time, cost and general resource frame. This indicates the potential of the virtual machine concept for contributing to improved efficiency of both complex products and the development process for such products. Companies incorporating such advanced simulation tools in their product development could thus improve its own competitiveness as well as contribute to improved resource efficiency of society at large.Keywords: Machine tools, Mechatronics, Non-deterministic, Optimisation, Product development, Virtual machine
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19551474 Data Mining Applied to the Predictive Model of Triage System in Emergency Department
Authors: Wen-Tsann Lin, Yung-Tsan Jou, Yih-Chuan Wu, Yuan-Du Hsiao
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The Emergency Department of a medical center in Taiwan cooperated to conduct the research. A predictive model of triage system is contracted from the contract procedure, selection of parameters to sample screening. 2,000 pieces of data needed for the patients is chosen randomly by the computer. After three categorizations of data mining (Multi-group Discriminant Analysis, Multinomial Logistic Regression, Back-propagation Neural Networks), it is found that Back-propagation Neural Networks can best distinguish the patients- extent of emergency, and the accuracy rate can reach to as high as 95.1%. The Back-propagation Neural Networks that has the highest accuracy rate is simulated into the triage acuity expert system in this research. Data mining applied to the predictive model of the triage acuity expert system can be updated regularly for both the improvement of the system and for education training, and will not be affected by subjective factors.Keywords: Back-propagation Neural Networks, Data Mining, Emergency Department, Triage System.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22941473 Mathematical Modeling Experimental Approach of the Friction on the Tool-Chip Interface of Multicoated Carbide Turning Inserts
Authors: Samy E. Oraby, Ayman M. Alaskari
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The importance of machining process in today-s industry requires the establishment of more practical approaches to clearly represent the intimate and severe contact on the tool-chipworkpiece interfaces. Mathematical models are developed using the measured force signals to relate each of the tool-chip friction components on the rake face to the operating cutting parameters in rough turning operation using multilayers coated carbide inserts. Nonlinear modeling proved to have high capability to detect the nonlinear functional variability embedded in the experimental data. While feedrate is found to be the most influential parameter on the friction coefficient and its related force components, both cutting speed and depth of cut are found to have slight influence. Greater deformed chip thickness is found to lower the value of friction coefficient as the sliding length on the tool-chip interface is reduced.Keywords: Mathematical modeling, Cutting forces, Frictionforces, Friction coefficient and Chip ratio.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 31121472 Manufacturing of Twist-Free Surfaces by Magnetism Aided Machining Technologies
Authors: Zs. Kovács, Zs. J. Viharos, J. Kodácsy
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As a well-known conventional finishing process, the grinding is commonly used to manufacture seal mating surfaces and bearing surfaces, but is also creates twisted surfaces. The machined surfaces by turning or grinding usually have twist structure on the surfaces, which can convey lubricants such as conveyor screw. To avoid this phenomenon, have to use special techniques or machines, for example start-stop turning, tangential turning, ultrasonic protection or special toll geometries. All of these solutions have high cost and difficult usability. In this paper, we describe a system and summarize the results of the experimental research carried out mainly in the field of Magnetic Abrasive Polishing (MAP) and Magnetic Roller Burnishing (MRB). These technologies are simple and also green while able to produce twist-free surfaces. During the tests, C45 normalized steel was used as workpiece material which was machined by simple and Wiper geometrical turning inserts in a CNC turning lathe. After the turning, the MAP and MRB technologies can be used directly to reduce the twist of surfaces. The evaluation was completed by advanced measuring and IT equipment.
Keywords: Magnetism, finishing, polishing, roller burnishing, twist-free.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11671471 The Optimization of an Intelligent Traffic Congestion Level Classification from Motorists- Judgments on Vehicle's Moving Patterns
Authors: Thammasak Thianniwet, Satidchoke Phosaard, Wasan Pattara-Atikom
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We proposed a technique to identify road traffic congestion levels from velocity of mobile sensors with high accuracy and consistent with motorists- judgments. The data collection utilized a GPS device, a webcam, and an opinion survey. Human perceptions were used to rate the traffic congestion levels into three levels: light, heavy, and jam. Then the ratings and velocity were fed into a decision tree learning model (J48). We successfully extracted vehicle movement patterns to feed into the learning model using a sliding windows technique. The parameters capturing the vehicle moving patterns and the windows size were heuristically optimized. The model achieved accuracy as high as 99.68%. By implementing the model on the existing traffic report systems, the reports will cover comprehensive areas. The proposed method can be applied to any parts of the world.Keywords: intelligent transportation system (ITS), traffic congestion level, human judgment, decision tree (J48), geographic positioning system (GPS).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18091470 WebAppShield: An Approach Exploiting Machine Learning to Detect SQLi Attacks in an Application Layer in Run-Time
Authors: Ahmed Abdulla Ashlam, Atta Badii, Frederic Stahl
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In recent years, SQL injection attacks have been identified as being prevalent against web applications. They affect network security and user data, which leads to a considerable loss of money and data every year. This paper presents the use of classification algorithms in machine learning using a method to classify the login data filtering inputs into "SQLi" or "Non-SQLi,” thus increasing the reliability and accuracy of results in terms of deciding whether an operation is an attack or a valid operation. A method as a Web-App is developed for auto-generated data replication to provide a twin of the targeted data structure. Shielding against SQLi attacks (WebAppShield) that verifies all users and prevents attackers (SQLi attacks) from entering and or accessing the database, which the machine learning module predicts as "Non-SQLi", has been developed. A special login form has been developed with a special instance of the data validation; this verification process secures the web application from its early stages. The system has been tested and validated, and up to 99% of SQLi attacks have been prevented.
Keywords: SQL injection, attacks, web application, accuracy, database, WebAppShield.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4161469 Hybrid Anomaly Detection Using Decision Tree and Support Vector Machine
Authors: Elham Serkani, Hossein Gharaee Garakani, Naser Mohammadzadeh, Elaheh Vaezpour
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Intrusion detection systems (IDS) are the main components of network security. These systems analyze the network events for intrusion detection. The design of an IDS is through the training of normal traffic data or attack. The methods of machine learning are the best ways to design IDSs. In the method presented in this article, the pruning algorithm of C5.0 decision tree is being used to reduce the features of traffic data used and training IDS by the least square vector algorithm (LS-SVM). Then, the remaining features are arranged according to the predictor importance criterion. The least important features are eliminated in the order. The remaining features of this stage, which have created the highest level of accuracy in LS-SVM, are selected as the final features. The features obtained, compared to other similar articles which have examined the selected features in the least squared support vector machine model, are better in the accuracy, true positive rate, and false positive. The results are tested by the UNSW-NB15 dataset.
Keywords: Intrusion detection system, decision tree, support vector machine, feature selection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12211468 Iraqi Short Term Electrical Load Forecasting Based On Interval Type-2 Fuzzy Logic
Authors: Firas M. Tuaimah, Huda M. Abdul Abbas
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Accurate Short Term Load Forecasting (STLF) is essential for a variety of decision making processes. However, forecasting accuracy can drop due to the presence of uncertainty in the operation of energy systems or unexpected behavior of exogenous variables. Interval Type 2 Fuzzy Logic System (IT2 FLS), with additional degrees of freedom, gives an excellent tool for handling uncertainties and it improved the prediction accuracy. The training data used in this study covers the period from January 1, 2012 to February 1, 2012 for winter season and the period from July 1, 2012 to August 1, 2012 for summer season. The actual load forecasting period starts from January 22, till 28, 2012 for winter model and from July 22 till 28, 2012 for summer model. The real data for Iraqi power system which belongs to the Ministry of Electricity.
Keywords: Short term load forecasting, prediction interval, type 2 fuzzy logic systems.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18771467 An Evaluation of the Oxide Layers in Machining Swarfs to Improve Recycling
Authors: J. Uka, B. McKay, T. Minton, O. Adole, R. Lewis, S. J. Glanvill, L. Anguilano
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Effective heat treatment conditions to obtain maximum aluminium swarf recycling are investigated in this work. Aluminium swarf briquettes underwent treatments at different temperatures and cooling times to investigate the improvements obtained in the recovery of aluminium metal. The main issue for the recovery of the metal from swarfs is to overcome the constraints due to the oxide layers present in high concentration in the swarfs since they have a high surface area. Briquettes supplied by Renishaw were heat treated at 650, 700, 750, 800 and 850 ℃ for 1-hour and then cooled at 2.3, 3.5 and 5 ℃/min. The resulting material was analysed using SEM EDX to observe the oxygen diffusion and aluminium coalescence at the boundary between adjacent swarfs. Preliminary results show that, swarf needs to be heat treated at a temperature of 850 ℃ and cooled down slowly at 2.3 ℃/min to have thin and discontinuous alumina layers between the adjacent swarf and consequently allowing aluminium coalescence. This has the potential to save energy and provide maximum financial profit in preparation of swarf briquettes for recycling.
Keywords: Aluminium, swarf, oxide layers, recycle, reuse.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5471466 Process Optimisation for Internal Cylindrical Rough Turning of Nickel Alloy 625 Weld Overlay
Authors: Lydia Chan, Islam Shyha, Dale Dreyer, John Hamilton, Phil Hackney
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Nickel-based superalloys are generally known to be difficult to cut due to their strength, low thermal conductivity, and high work hardening tendency. Superalloy such as alloy 625 is often used in the oil and gas industry as a surfacing material to provide wear and corrosion resistance to components. The material is typically applied onto a metallic substrate through weld overlay cladding, an arc welding technique. Cladded surfaces are always rugged and carry a tough skin; this creates further difficulties to the machining process. The present work utilised design of experiment to optimise the internal cylindrical rough turning for weld overlay surfaces. An L27 orthogonal array was used to assess effects of the four selected key process variables: cutting insert, depth of cut, feed rate, and cutting speed. The optimal cutting conditions were determined based on productivity and the level of tool wear.Keywords: Cylindrical turning, nickel superalloy, turning of overlay, weld overlay.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9171465 Neural Network Control of a Biped Robot Model with Composite Adaptation Low
Authors: Ahmad Forouzantabar
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this paper presents a novel neural network controller with composite adaptation low to improve the trajectory tracking problems of biped robots comparing with classical controller. The biped model has 5_link and 6 degrees of freedom and actuated by Plated Pneumatic Artificial Muscle, which have a very high power to weight ratio and it has large stoke compared to similar actuators. The proposed controller employ a stable neural network in to approximate unknown nonlinear functions in the robot dynamics, thereby overcoming some limitation of conventional controllers such as PD or adaptive controllers and guarantee good performance. This NN controller significantly improve the accuracy requirements by retraining the basic PD/PID loop, but adding an inner adaptive loop that allows the controller to learn unknown parameters such as friction coefficient, therefore improving tracking accuracy. Simulation results plus graphical simulation in virtual reality show that NN controller tracking performance is considerably better than PD controller tracking performance.Keywords: Biped robot, Neural network, Plated Pneumatic Artificial Muscle, Composite adaptation
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18361464 Surface Roughness and MRR Effect on Manual Plasma Arc Cutting Machining
Authors: R. Bhuvenesh, M.H. Norizaman, M.S. Abdul Manan
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Industrial surveys shows that manufacturing companies define the qualities of thermal removing process based on the dimension and physical appearance of the cutting material surface. Therefore, the roughness of the surface area of the material cut by the plasma arc cutting process and the rate of the removed material by the manual plasma arc cutting machine was importantly considered. Plasma arc cutter Selco Genesis 90 was used to cut Standard AISI 1017 Steel of 200 mm x100 mm x 6 mm manually based on the selected parameters setting. The material removal rate (MRR) was measured by determining the weight of the specimens before and after the cutting process. The surface roughness (SR) analysis was conducted using Mitutoyo CS-3100 to determine the average roughness value (Ra). Taguchi method was utilized to achieve optimum condition for both outputs studied. The microstructure analysis in the region of the cutting surface is performed using SEM. The results reveal that the SR values are inversely proportional to the MRR values. The quality of the surface roughness depends on the dross peak that occurred after the cutting process.Keywords: Material removal rate, plasma arc cutting, surface roughness, Taguchi method
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 56561463 Prediction of Dissolved Oxygen in Rivers Using a Wang-Mendel Method – Case Study of Au Sable River
Authors: Mahmoud R. Shaghaghian
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Amount of dissolve oxygen in a river has a great direct affect on aquatic macroinvertebrates and this would influence on the region ecosystem indirectly. In this paper it is tried to predict dissolved oxygen in rivers by employing an easy Fuzzy Logic Modeling, Wang Mendel method. This model just uses previous records to estimate upcoming values. For this purpose daily and hourly records of eight stations in Au Sable watershed in Michigan, United States are employed for 12 years and 50 days period respectively. Calculations indicate that for long period prediction it is better to increase input intervals. But for filling missed data it is advisable to decrease the interval. Increasing partitioning of input and output features influence a little on accuracy but make the model too time consuming. Increment in number of input data also act like number of partitioning. Large amount of train data does not modify accuracy essentially, so, an optimum training length should be selected.
Keywords: Dissolved oxygen, Au Sable, fuzzy logic modeling, Wang Mendel.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18751462 Vibration, Lubrication and Machinery Consideration for a Mixer Gearbox Related to Iran Oil Industries
Authors: Omid A. Zargar
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In this paper, some common gearboxes vibration analysis methods and condition monitoring systems are explained. In addition, an experimental gearbox vibration analysis is discussed through a critical case history for a mixer gearbox related to Iran oil industry. The case history also consists of gear manufacturing (machining) recommendations, lubrication condition of gearbox and machinery maintenance activities that caused reduction in noise and vibration of the gearbox. Besides some of the recent patents and innovations in gearboxes, lubrication and vibration monitoring systems explained. Finally micro pitting and surface fatigue in pinion and bevel of mentioned horizontal to vertical gearbox discussed in details.
Keywords: Gear box, condition monitoring, time wave form (TWF), fast Fourier transform (FFT), gear mesh frequency (GMF), Shock Pulse measurement (SPM), bearing condition unit (BCU), pinion, bevel gear, micro pitting, surface fatigue.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 42731461 Experimental Study of the Metal Foam Flow Conditioner for Orifice Plate Flowmeters
Authors: B. Manshoor, N. Ihsak, Amir Khalid
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The sensitivity of orifice plate metering to disturbed flow (either asymmetric or swirling) is a subject of great concern to flow meter users and manufacturers. The distortions caused by pipe fittings and pipe installations upstream of the orifice plate are major sources of this type of non-standard flows. These distortions can alter the accuracy of metering to an unacceptable degree. In this work, a multi-scale object known as metal foam has been used to generate a predetermined turbulent flow upstream of the orifice plate. The experimental results showed that the combination of an orifice plate and metal foam flow conditioner is broadly insensitive to upstream disturbances. This metal foam demonstrated a good performance in terms of removing swirl and producing a repeatable flow profile within a short distance downstream of the device. The results of using a combination of a metal foam flow conditioner and orifice plate for non-standard flow conditions including swirling flow and asymmetric flow show this package can preserve the accuracy of metering up to the level required in the standards.Keywords: Metal foam flow conditioner, flow measurement, orifice plate.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20461460 Age–Related Changes of the Sella Turcica Morphometry in Adults Older Than 20-25 Years
Authors: Yu. I. Pigolkin, M. A. Garcia Corro
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Age determination of unknown dead bodies in forensic personal identification is a complicated process which involves the application of numerous methods and techniques. Skeletal remains are less exposed to influences of environmental factors. In order to enhance the accuracy of forensic age estimation additional properties of bones correlating with age are required to be revealed. Material and Methods: Dimensional examination of the sella turcica was carried out on cadavers with the cranium opened by a circular vibrating saw. The sample consisted of a total of 90 Russian subjects, ranging in age from two months and 87 years. Results: The tendency of dimensional variations throughout life was detected. There were no observed gender differences in the morphometry of the sella turcica. The shared use of the sella turcica depth and length values revealed the possibility to categorize an examined sample in a certain age period. Conclusions: Based on the results of existing methods of age determination, the morphometry of the sella turcica can be an additional characteristic, amplifying the received values, and accordingly, increasing the accuracy of forensic biological age diagnosis.Keywords: Age–related changes in bone structures, forensic personal identification, Sella turcica morphometry, body identification.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13551459 Performances Comparison of Neural Architectures for On-Line Speed Estimation in Sensorless IM Drives
Authors: K.Sedhuraman, S.Himavathi, A.Muthuramalingam
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The performance of sensor-less controlled induction motor drive depends on the accuracy of the estimated speed. Conventional estimation techniques being mathematically complex require more execution time resulting in poor dynamic response. The nonlinear mapping capability and powerful learning algorithms of neural network provides a promising alternative for on-line speed estimation. The on-line speed estimator requires the NN model to be accurate, simpler in design, structurally compact and computationally less complex to ensure faster execution and effective control in real time implementation. This in turn to a large extent depends on the type of Neural Architecture. This paper investigates three types of neural architectures for on-line speed estimation and their performance is compared in terms of accuracy, structural compactness, computational complexity and execution time. The suitable neural architecture for on-line speed estimation is identified and the promising results obtained are presented.Keywords: Sensorless IM drives, rotor speed estimators, artificial neural network, feed- forward architecture, single neuron cascaded architecture.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14401458 A Force-directed Graph Drawing based on the Hierarchical Individual Timestep Method
Authors: T. Matsubayashi, T. Yamada
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In this paper, we propose a fast and efficient method for drawing very large-scale graph data. The conventional force-directed method proposed by Fruchterman and Rheingold (FR method) is well-known. It defines repulsive forces between every pair of nodes and attractive forces between connected nodes on a edge and calculates corresponding potential energy. An optimal layout is obtained by iteratively updating node positions to minimize the potential energy. Here, the positions of the nodes are updated every global timestep at the same time. In the proposed method, each node has its own individual time and time step, and nodes are updated at different frequencies depending on the local situation. The proposed method is inspired by the hierarchical individual time step method used for the high accuracy calculations for dense particle fields such as star clusters in astrophysical dynamics. Experiments show that the proposed method outperforms the original FR method in both speed and accuracy. We implement the proposed method on the MDGRAPE-3 PCI-X special purpose parallel computer and realize a speed enhancement of several hundred times.Keywords: visualization, graph drawing, Internet Map
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18361457 Multimedia Data Fusion for Event Detection in Twitter by Using Dempster-Shafer Evidence Theory
Authors: Samar M. Alqhtani, Suhuai Luo, Brian Regan
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Data fusion technology can be the best way to extract useful information from multiple sources of data. It has been widely applied in various applications. This paper presents a data fusion approach in multimedia data for event detection in twitter by using Dempster-Shafer evidence theory. The methodology applies a mining algorithm to detect the event. There are two types of data in the fusion. The first is features extracted from text by using the bag-ofwords method which is calculated using the term frequency-inverse document frequency (TF-IDF). The second is the visual features extracted by applying scale-invariant feature transform (SIFT). The Dempster - Shafer theory of evidence is applied in order to fuse the information from these two sources. Our experiments have indicated that comparing to the approaches using individual data source, the proposed data fusion approach can increase the prediction accuracy for event detection. The experimental result showed that the proposed method achieved a high accuracy of 0.97, comparing with 0.93 with texts only, and 0.86 with images only.Keywords: Data fusion, Dempster-Shafer theory, data mining, event detection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17891456 Predicting Protein-Protein Interactions from Protein Sequences Using Phylogenetic Profiles
Authors: Omer Nebil Yaveroglu, Tolga Can
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In this study, a high accuracy protein-protein interaction prediction method is developed. The importance of the proposed method is that it only uses sequence information of proteins while predicting interaction. The method extracts phylogenetic profiles of proteins by using their sequence information. Combining the phylogenetic profiles of two proteins by checking existence of homologs in different species and fitting this combined profile into a statistical model, it is possible to make predictions about the interaction status of two proteins. For this purpose, we apply a collection of pattern recognition techniques on the dataset of combined phylogenetic profiles of protein pairs. Support Vector Machines, Feature Extraction using ReliefF, Naive Bayes Classification, K-Nearest Neighborhood Classification, Decision Trees, and Random Forest Classification are the methods we applied for finding the classification method that best predicts the interaction status of protein pairs. Random Forest Classification outperformed all other methods with a prediction accuracy of 76.93%Keywords: Protein Interaction Prediction, Phylogenetic Profile, SVM , ReliefF, Decision Trees, Random Forest Classification
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16001455 Appraisal of Relativistic Effects on GNSS Receiver Positioning
Authors: I. Yakubu, Y. Y. Ziggah, E. A. Gyamera
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The Global Navigation Satellite System (GNSS) started with the launch of the United State Department of Defense Global Positioning System (GPS). GNSS systems has grown over the years to include: GLONASS (Russia); Galileo (European Union); BeiDou (China). Any GNSS architecture consists of three major segments: Space, Control and User Segments. Errors such as; multipath, ionospheric and tropospheric effects, satellite clocks, receiver noise and orbit errors (relativity effect) have significant effects on GNSS positioning. To obtain centimeter level accuracy, the impacts of the relative motion of the satellites and earth need to be taken into account. This paper discusses the relevance of the theory of relativity as a source of error for GNSS receivers for position fix based on available relevant literature. Review of relevant literature reveals that due to relativity; Time dilation, Gravitational frequency shift and Sagnac effect cause significant influence on the use of GNSS receivers for positioning by an error range of ± 2.5 m based on pseudo-range computation.
Keywords: GNSS, relativistic effects, pseudo-range, accuracy.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3441454 Partially Knowing of Least Support Orthogonal Matching Pursuit (PKLS-OMP) for Recovering Signal
Authors: Israa Sh. Tawfic, Sema Koc Kayhan
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Given a large sparse signal, great wishes are to reconstruct the signal precisely and accurately from lease number of measurements as possible as it could. Although this seems possible by theory, the difficulty is in built an algorithm to perform the accuracy and efficiency of reconstructing. This paper proposes a new proved method to reconstruct sparse signal depend on using new method called Least Support Matching Pursuit (LS-OMP) merge it with the theory of Partial Knowing Support (PSK) given new method called Partially Knowing of Least Support Orthogonal Matching Pursuit (PKLS-OMP). The new methods depend on the greedy algorithm to compute the support which depends on the number of iterations. So to make it faster, the PKLS-OMP adds the idea of partial knowing support of its algorithm. It shows the efficiency, simplicity, and accuracy to get back the original signal if the sampling matrix satisfies the Restricted Isometry Property (RIP). Simulation results also show that it outperforms many algorithms especially for compressible signals.
Keywords: Compressed sensing, Lest Support Orthogonal Matching Pursuit, Partial Knowing Support, Restricted isometry property, signal reconstruction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22221453 Mathematical Analysis of Stock Prices Prediction in a Financial Market Using Geometric Brownian Motion Model
Authors: Edikan E. Akpanibah, Ogunmodimu Dupe Catherine
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The relevance of geometric Brownian motion (GBM) in modelling the behaviour of stock market prices (SMP) cannot be over emphasized taking into consideration the volatility of the SMP. Consequently, there is need to investigate how GBM models are being estimated and used in financial market to predict SMP. To achieve this, the GBM estimation and its application to the SMP of some selected companies are studied. The normal and log-normal distributions were used to determine the expected value, variance and co-variance. Furthermore, the GBM model was used to predict the SMP of some selected companies over a period of time and the mean absolute percentage error (MAPE) were calculated and used to determine the accuracy of the GBM model in predicting the SMP of the four companies under consideration. It was observed that for all the four companies, their MAPE values were within the region of acceptance. Also, the MAPE values of our data were compared to an existing literature to test the accuracy of our prediction with respect to time of investment. Finally, some numerical simulations of the graphs of the SMP, expectations and variance of the four companies over a period of time were presented using MATLAB programming software.
Keywords: Stock Market, Geometric Brownian Motion, normal and log-normal distribution, mean absolute percentage error.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2331452 Experimental Determination of Large Strain Localization in Cut Steel Chips
Authors: A. Simoneau
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Metal cutting is a severe plastic deformation process involving large strains, high strain rates, and high temperatures. Conventional analysis of the chip formation process is based on bulk material deformation disregarding the inhomogeneous nature of the material microstructure. A series of orthogonal cutting tests of AISI 1045 and 1144 steel were conducted which yielded similar process characteristics and chip formations. With similar shear angles and cut chip thicknesses, shear strains for both chips were found to range from 2.0 up to 2.8. The manganese-sulfide (MnS) precipitate in the 1144 steel has a very distinct and uniform shape which allows for comparison before and after chip formation. From close observations of MnS precipitates in the cut chips it is shown that the conventional approach underestimates plastic strains in metal cutting. Experimental findings revealed local shear strains around a value of 6. These findings and their implications are presented and discussed.Keywords: Machining, metal cutting, microstructure, plastic strains, local strain.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21051451 Implementation of Edge Detection Based on Autofluorescence Endoscopic Image of Field Programmable Gate Array
Authors: Hao Cheng, Zhiwu Wang, Guozheng Yan, Pingping Jiang, Shijia Qin, Shuai Kuang
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Autofluorescence Imaging (AFI) is a technology for detecting early carcinogenesis of the gastrointestinal tract in recent years. Compared with traditional white light endoscopy (WLE), this technology greatly improves the detection accuracy of early carcinogenesis, because the colors of normal tissues are different from cancerous tissues. Thus, edge detection can distinguish them in grayscale images. In this paper, based on the traditional Sobel edge detection method, optimization has been performed on this method which considers the environment of the gastrointestinal, including adaptive threshold and morphological processing. All of the processes are implemented on our self-designed system based on the image sensor OV6930 and Field Programmable Gate Array (FPGA), The system can capture the gastrointestinal image taken by the lens in real time and detect edges. The final experiments verified the feasibility of our system and the effectiveness and accuracy of the edge detection algorithm.
Keywords: AFI, edge detection, adaptive threshold, morphological processing, OV6930, FPGA.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6421450 Construction of Large Scale UAVs Using Homebuilt Composite Techniques
Authors: Brian J. Kozak, Joshua D. Shipman, Peng Hao Wang, Blake Shipp
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The unmanned aerial system (UAS) industry is growing at a rapid pace. This growth has increased the demand for low cost, custom made and high strength unmanned aerial vehicles (UAV). The area of most growth is in the area of 25 kg to 200 kg vehicles. Vehicles this size are beyond the size and scope of simple wood and fabric designs commonly found in hobbyist aircraft. These high end vehicles require stronger materials to complete their mission. Traditional aircraft construction materials such as aluminum are difficult to use without machining or advanced computer controlled tooling. However, by using general aviation composite aircraft homebuilding techniques and materials, a large scale UAV can be constructed cheaply and easily. Furthermore, these techniques could be used to easily manufacture cost made composite shapes and airfoils that would be cost prohibitive when using metals. These homebuilt aircraft techniques are being demonstrated by the researchers in the construction of a 75 kg aircraft.
Keywords: Composite aircraft, homebuilding, unmanned aerial system, unmanned aerial vehicles.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7961449 A 3D Approach for Extraction of the Coronaryartery and Quantification of the Stenosis
Authors: Mahdi Mazinani, S. D. Qanadli, Rahil Hosseini, Tim Ellis, Jamshid Dehmeshki
Abstract:
Segmentation and quantification of stenosis is an important task in assessing coronary artery disease. One of the main challenges is measuring the real diameter of curved vessels. Moreover, uncertainty in segmentation of different tissues in the narrow vessel is an important issue that affects accuracy. This paper proposes an algorithm to extract coronary arteries and measure the degree of stenosis. Markovian fuzzy clustering method is applied to model uncertainty arises from partial volume effect problem. The algorithm employs: segmentation, centreline extraction, estimation of orthogonal plane to centreline, measurement of the degree of stenosis. To evaluate the accuracy and reproducibility, the approach has been applied to a vascular phantom and the results are compared with real diameter. The results of 10 patient datasets have been visually judged by a qualified radiologist. The results reveal the superiority of the proposed method compared to the Conventional thresholding Method (CTM) on both datasets.Keywords: 3D coronary artery tree extraction, segmentation, quantification, fuzzy clustering, and Markov random field
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15731448 Digital Control Algorithm Based on Delta-Operator for High-Frequency DC-DC Switching Converters
Authors: Renkai Wang, Tingcun Wei
Abstract:
In this paper, a digital control algorithm based on delta-operator is presented for high-frequency digitally-controlled DC-DC switching converters. The stability and the controlling accuracy of the DC-DC switching converters are improved by using the digital control algorithm based on delta-operator without increasing the hardware circuit scale. The design method of voltage compensator in delta-domain using PID (Proportion-Integration- Differentiation) control is given in this paper, and the simulation results based on Simulink platform are provided, which have verified the theoretical analysis results very well. It can be concluded that, the presented control algorithm based on delta-operator has better stability and controlling accuracy, and easier hardware implementation than the existed control algorithms based on z-operator, therefore it can be used for the voltage compensator design in high-frequency digitally- controlled DC-DC switching converters.
Keywords: Digitally-controlled DC-DC switching converter, finite word length, control algorithm based on delta-operator, high-frequency, stability.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12491447 A Local Invariant Generalized Hough Transform Method for Integrated Circuit Visual Positioning
Authors: Fei Long Wei, Hua Yang, Hai Tao Zhang, Zhou Ping Yin
Abstract:
In this study, an local invariant generalized Houghtransform (LI-GHT) method is proposed for integrated circuit (IC) visual positioning. The original generalized Hough transform (GHT) is robust to external noise; however, it is not suitable for visual positioning of IC chips due to the four-dimensionality (4D) of parameter space which leads to the substantial storage requirement and high computational complexity. The proposed LI-GHT method can reduce the dimensionality of parameter space to 2D thanks to the rotational invariance of local invariant geometric feature and it can estimate the accuracy position and rotation angle of IC chips in real-time under noise and blur influence. The experiment results show that the proposed LI-GHT can estimate position and rotation angle of IC chips with high accuracy and fast speed. The proposed LI-GHT algorithm was implemented in IC visual positioning system of radio frequency identification (RFID) packaging equipment.
Keywords: Integrated Circuit Visual Positioning, Generalized Hough Transform, Local invariant Generalized Hough Transform, ICpacking equipment.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2197