Search results for: machine defect frequency
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3004

Search results for: machine defect frequency

2524 A Machine Learning Approach for Anomaly Detection in Environmental IoT-Driven Wastewater Purification Systems

Authors: Giovanni Cicceri, Roberta Maisano, Nathalie Morey, Salvatore Distefano

Abstract:

The main goal of this paper is to present a solution for a water purification system based on an Environmental Internet of Things (EIoT) platform to monitor and control water quality and machine learning (ML) models to support decision making and speed up the processes of purification of water. A real case study has been implemented by deploying an EIoT platform and a network of devices, called Gramb meters and belonging to the Gramb project, on wastewater purification systems located in Calabria, south of Italy. The data thus collected are used to control the wastewater quality, detect anomalies and predict the behaviour of the purification system. To this extent, three different statistical and machine learning models have been adopted and thus compared: Autoregressive Integrated Moving Average (ARIMA), Long Short Term Memory (LSTM) autoencoder, and Facebook Prophet (FP). The results demonstrated that the ML solution (LSTM) out-perform classical statistical approaches (ARIMA, FP), in terms of both accuracy, efficiency and effectiveness in monitoring and controlling the wastewater purification processes.

Keywords: EIoT, machine learning, anomaly detection, environment monitoring.

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2523 Particle Swarm Optimization Based PID Power System Stabilizer for a Synchronous Machine

Authors: Gowrishankar Kasilingam

Abstract:

This paper proposes a swarm intelligence method that yields optimal Proportional-Integral-Derivative (PID) Controller parameters of a power system stabilizer (PSS) in a single machine infinite bus system. The proposed method utilizes the Particle Swarm Optimization (PSO) algorithm approach to generate the optimal tuning parameters. The paper is modeled in the MATLAB Simulink Environment to analyze the performance of a synchronous machine under several load conditions. At the same operating point, the PID-PSS parameters are also tuned by Ziegler-Nichols method. The dynamic performance of proposed controller is compared with the conventional Ziegler-Nichols method of PID tuning controller to demonstrate its advantage. The analysis reveals the effectiveness of the proposed PSO based PID controller.

Keywords: Particle Swarm Optimization, PID Controller, Power System Stabilizer.

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2522 Tuning of Power System Stabilizers in a Multi- Machine Power System using C-Catfish PSO

Authors: M. H. Moradi, S. M. Moosavi, A. R. Reisi

Abstract:

The main objective of this paper is to investigate the enhancement of power system stability via coordinated tuning of Power System Stabilizers (PSSs) in a multi-machine power system. The design problem of the proposed controllers is formulated as an optimization problem. Chaotic catfish particle swarm optimization (C-Catfish PSO) algorithm is used to minimize the ITAE objective function. The proposed algorithm is evaluated on a two-area, 4- machines system. The robustness of the proposed algorithm is verified on this system under different operating conditions and applying a three-phase fault. The nonlinear time-domain simulation results and some performance indices show the effectiveness of the proposed controller in damping power system oscillations and this novel optimization algorithm is compared with particle swarm optimization (PSO).

Keywords: Power system stabilizer, C-Catfish PSO, ITAE objective function, Power system control, Multi-machine power system

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2521 Design of Power System Stabilizer Based on Sliding Mode Control Theory for Multi- Machine Power System

Authors: Hossein Shahinzadeh, Ladan Darougaran, Ebrahim Jalili Sani, Hamed Yavari, Mahdi Mozaffari Legha

Abstract:

This paper present a new method for design of power system stabilizer (PSS) based on sliding mode control (SMC) technique. The control objective is to enhance stability and improve the dynamic response of the multi-machine power system. In order to test effectiveness of the proposed scheme, simulation will be carried out to analyze the small signal stability characteristics of the system about the steady state operating condition following the change in reference mechanical torque and also parameters uncertainties. For comparison, simulation of a conventional control PSS (lead-lag compensation type) will be carried out. The main approach is focusing on the control performance which later proven to have the degree of shorter reaching time and lower spike.

Keywords: Power system stabilizer (PSS), multi-machine power system, sliding mode control

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2520 Decoy-pulse Protocol for Frequency-coded Quantum Key Distribution

Authors: Sudeshna Bhattacharya, Pratyush Pandey, Pradeep Kumar K

Abstract:

We propose a decoy-pulse protocol for frequency-coded implementation of B92 quantum key distribution protocol. A direct extension of decoy-pulse method to frequency-coding scheme results in security loss as an eavesdropper can distinguish between signal and decoy pulses by measuring the carrier photon number without affecting other statistics. We overcome this problem by optimizing the ratio of carrier photon number of decoy-to-signal pulse to be as close to unity as possible. In our method the switching between signal and decoy pulses is achieved by changing the amplitude of RF signal as opposed to modulating the intensity of optical signal thus reducing system cost. We find an improvement by a factor of 100 approximately in the key generation rate using decoy-state protocol. We also study the effect of source fluctuation on key rate. Our simulation results show a key generation rate of 1.5×10-4/pulse for link lengths up to 70km. Finally, we discuss the optimum value of average photon number of signal pulse for a given key rate while also optimizing the carrier ratio.

Keywords: B92, decoy-pulse, frequency-coding, quantum key distribution.

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2519 An Improvement of Flow Forming Process for Pressure Vessels by Four Rollers Machine

Authors: P. Sawitri, S. Cdr. Sittha, T. Kritsana

Abstract:

Flow forming is widely used in many industries, especially in defence technology industries. Pressure vessels requirements are high precision, light weight, seamless and optimum strength. For large pressure vessels, flow forming by 3 rollers machine were used. In case of long range rocket motor case flow forming and welding of pressure vessels have been used for manufacturing. Due to complication of welding process, researchers had developed 4 meters length pressure vessels without weldment by 4 rollers flow forming machine. Design and preparation of preform work pieces are performed. The optimization of flow forming parameter such as feed rate, spindle speed and depth of cut will be discussed. The experimental result shown relation of flow forming parameters to quality of flow formed tube and prototype pressure vessels have been made.

Keywords: Flow forming, Pressure vessel, four rollers, feed rate, spindle speed, cold work.

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2518 Image Compression Using Hybrid Vector Quantization

Authors: S.Esakkirajan, T. Veerakumar, V. Senthil Murugan, P.Navaneethan

Abstract:

In this paper, image compression using hybrid vector quantization scheme such as Multistage Vector Quantization (MSVQ) and Pyramid Vector Quantization (PVQ) are introduced. A combined MSVQ and PVQ are utilized to take advantages provided by both of them. In the wavelet decomposition of the image, most of the information often resides in the lowest frequency subband. MSVQ is applied to significant low frequency coefficients. PVQ is utilized to quantize the coefficients of other high frequency subbands. The wavelet coefficients are derived using lifting scheme. The main aim of the proposed scheme is to achieve high compression ratio without much compromise in the image quality. The results are compared with the existing image compression scheme using MSVQ.

Keywords: Lifting Scheme, Multistage Vector Quantization and Pyramid Vector Quantization.

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2517 Novel Schemes of Pilot-Aided Integer Frequency Offset Estimation for OFDM-Based DVB-T Systems

Authors: Youngyoon Lee, Dahae Chong, Myungsoo Lee, Seongho Chae, Seokho Yoon

Abstract:

This paper proposes two novel schemes for pilot-aided integer frequency offset (IFO) estimation in orthogonal frequency division multiplexing (OFDM)-based digital video broadcastingterrestrial (DVB-T) systems. The conventional scheme proposed for estimating the IFO uses only partial information of combinations that pilots can provide, which stems from a rigorous assumption that the channel responses of pilots used for estimating the IFO change very rapidly. Thus, in this paper, we propose the novel IFO estimation schemes exploiting all information of combinations that pilots can provide to improve the performance of IFO estimation. The simulation results show that the proposed schemes are highly accurate in terms of the IFO detection probability.

Keywords: OFDM, DVB-T, pilot, IFO, estimation

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2516 Large Vibration Amplitude of Circular Functionally Graded Plates Resting on Pasternak Foundations

Authors: El Kaak Rachid, El Bikri Khalid, Benamar Rhali

Abstract:

In the present study, the problem of geometrically nonlinear free vibrations of functionally graded circular plates (FGCP) resting on Pasternak elastic foundation with immovable ends was studied. The material properties of the functionally graded composites examined were assumed to be graded in the thickness direction and estimated through the rule of mixture. The theoretical model is based on the classical Plate theory and the Von Kármán geometrical nonlinearity assumptions. Hamilton’s principle is applied and a multimode approach is derived to calculate the fundamental nonlinear frequency parameters, which are found to be in a good agreement with the published results dealing with the problem of functionally graded plates. On the other hand, the influence of the foundation parameters on the nonlinear frequency to the linear frequency ratio of the FGCP has been studied. The effect of the linear and shearing foundations is to decrease the frequency ratio, where it increases with the effect of the nonlinear foundation stiffness. 

Keywords: Non-linear vibrations, Circular plates, Pasternak foundation, functionally graded materials.

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2515 Characterization and Modeling of Piezoelectric Integrated Micro Speakers for Audio Acoustic Actuation

Authors: J. Mendoza-López, S. Sánchez-Solano, J. L. Huertas-Díaz

Abstract:

An array of piezoelectric micro actuators can be used for radiation of an ultrasonic carrier signal modulated in amplitude with an acoustic signal, which yields audio frequency applications as the air acts as a self-demodulating medium. This application is known as the parametric array. We propose a parametric array with array elements based on existing piezoelectric micro ultrasonic transducer (pMUT) design techniques. In order to reach enough acoustic output power at a desired operating frequency, a proper ratio between number of array elements and array size needs to be used, with an array total area of the order of one cm square. The transducers presented are characterized via impedance, admittance, noise figure, transducer gain and frequency responses.

Keywords: Pizeoelectric, Microspeaker, MEMS, pMUT, Parametric Array

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2514 Investigation of Grid Supply Harmonic Effects in Wound Rotor Induction Machines

Authors: Nur Sarma, Paul M. Tuohy, Siniša Djurović

Abstract:

This paper presents an in-depth investigation of the effects of several grid supply harmonic voltages on the stator currents of an example wound rotor induction machine. The observed effects of higher order grid supply harmonics are identified using a finite element time stepping transient model, as well as a time-stepping electromagnetic model. In addition, a number of analytical equations to calculate the spectral content of the stator currents are presented in the paper. The presented equations are validated through comparison with the obtained spectra predicted using the finite element and electromagnetic models. The presented study provides a better understanding of the origin of supply harmonic effects identified in the stator currents of the example wound rotor induction machine. Furthermore, the study helps to understand the effects of higher order supply harmonics on the harmonic emissions of the wound rotor induction machine.  

Keywords: Wound rotor induction machine, supply harmonics, current spectrum, power spectrum, power quality, harmonic emissions, finite element analysis.

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2513 Secured Mutual Authentication Protocol for Radio Frequency Identification Systems

Authors: C. Kalamani, S. Sowmiya, S. Dheivambigai, G. Harihara Sudhan

Abstract:

Radio Frequency Identification (RFID) is a blooming technology which uses radio frequency to track the objects. This technology transmits signals between tag and reader to fetch information from the tag with a unique serial identity. Generally, the drawbacks of RFID technology are high cost, high consumption of power and weak authentication systems between a reader and a tag. The proposed protocol utilizes less dynamic power using reversible truncated multipliers which are implemented in RFID tag-reader with mutual authentication protocol system to reduce both leakage and dynamic power consumption. The proposed system was simulated using Xilinx and Cadence tools.

Keywords: Mutual authentication, protocol, reversible gates, RFID.

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2512 Enhancing Word Meaning Retrieval Using FastText and NLP Techniques

Authors: Sankalp Devanand, Prateek Agasimani, V. S. Shamith, Rohith Neeraje

Abstract:

Machine translation has witnessed significant advancements in recent years, but the translation of languages with distinct linguistic characteristics, such as English and Sanskrit, remains a challenging task. This research presents the development of a dedicated English to Sanskrit machine translation model, aiming to bridge the linguistic and cultural gap between these two languages. Using a variety of natural language processing (NLP) approaches including FastText embeddings, this research proposes a thorough method to improve word meaning retrieval. Data preparation, part-of-speech tagging, dictionary searches, and transliteration are all included in the methodology. The study also addresses the implementation of an interpreter pattern and uses a word similarity task to assess the quality of word embeddings. The experimental outcomes show how the suggested approach may be used to enhance word meaning retrieval tasks with greater efficacy, accuracy, and adaptability. Evaluation of the model's performance is conducted through rigorous testing, comparing its output against existing machine translation systems. The assessment includes quantitative metrics such as BLEU scores, METEOR scores, Jaccard Similarity etc.

Keywords: Machine translation, English to Sanskrit, natural language processing, word meaning retrieval, FastText embeddings.

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2511 A Procedure for Post-Earthquake Damage Estimation Based on Detection of High-Frequency Transients

Authors: Aleksandar Zhelyazkov, Daniele Zonta, Helmut Wenzel, Peter Furtner

Abstract:

In the current research structural health monitoring is considered for addressing the critical issue of post-earthquake damage detection. A non-standard approach for damage detection via acoustic emission is presented - acoustic emissions are monitored in the low frequency range (up to 120 Hz). Such emissions are termed high-frequency transients. Further a damage indicator defined as the Time-Ratio Damage Indicator is introduced. The indicator relies on time-instance measurements of damage initiation and deformation peaks. Based on the time-instance measurements a procedure for estimation of the maximum drift ratio is proposed. Monitoring data is used from a shaking-table test of a full-scale reinforced concrete bridge pier. Damage of the experimental column is successfully detected and the proposed damage indicator is calculated.

Keywords: Acoustic emission, Damage detection, Shaking table test, Structural health monitoring, High-frequency transients.

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2510 Hybrid Neuro Fuzzy Approach for Automatic Generation Control of Two -Area Interconnected Power System

Authors: Gayadhar Panda, Sidhartha Panda, C. Ardil

Abstract:

The main objective of Automatic Generation Control (AGC) is to balance the total system generation against system load losses so that the desired frequency and power interchange with neighboring systems is maintained. Any mismatch between generation and demand causes the system frequency to deviate from its nominal value. Thus high frequency deviation may lead to system collapse. This necessitates a very fast and accurate controller to maintain the nominal system frequency. This paper deals with a novel approach of artificial intelligence (AI) technique called Hybrid Neuro-Fuzzy (HNF) approach for an (AGC). The advantage of this controller is that it can handle the non-linearities at the same time it is faster than other conventional controllers. The effectiveness of the proposed controller in increasing the damping of local and inter area modes of oscillation is demonstrated in a two area interconnected power system. The result shows that intelligent controller is having improved dynamic response and at the same time faster than conventional controller.

Keywords: Automatic Generation Control (AGC), Dynamic Model, Two-area Power System, Fuzzy Logic Controller, Neural Network, Hybrid Neuro-Fuzzy(HNF).

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2509 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.

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2508 A ZVS Flyback DC-DC Converter using Multilayered Coreless Printed-Circuit Board(PCB) Step-down Power Transformer

Authors: Hari Babu Kotte, Radhika Ambatipudi, Dr. Kent Bertilsson

Abstract:

The experimental and theoretical results of a ZVS (Zero Voltage Switching) isolated flyback DC-DC converter using multilayered coreless PCB step down 2:1 transformer are presented. The performance characteristics of the transformer are shown which are useful for the parameters extraction. The measured energy efficiency of the transformer is found to be more than 94% with the sinusoidal input voltage excitation. The designed flyback converter has been tested successfully upto the output power level of 10W, with a switching frequency in the range of 2.7MHz-4.3MHz. The input voltage of the converter is varied from 25V-40V DC. Frequency modulation technique is employed by maintaining constant off time to regulate the output voltage of the converter. The energy efficiency of the isolated flyback converter circuit under ZVS condition in the MHz frequency region is found to be approximately in the range of 72-84%. This paper gives the comparative results in terms of the energy efficiency of the hard switched and soft switched flyback converter in the MHz frequency region.

Keywords: Coreless PCB step down transformer, DC-DCconverter, Flyback, Hard Switched Converter, MHz frequencyregion, Multilayered PCB transformer, Zero Voltage Switching

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2507 Challenges for Interface Designers in Designing Sensor Dashboards in the Context of Industry 4.0

Authors: Naveen Kumar, Shyambihari Prajapati

Abstract:

Industry 4.0 is the fourth industrial revolution that focuses on interconnectivity of machine to machine, human to machine and human to human via Internet of Things (IoT). Technologies of industry 4.0 facilitate communication between human and machine through IoT and forms Cyber-Physical Production System (CPPS). In CPPS, multiple shop floors sensor data are connected through IoT and displayed through sensor dashboard to the operator. These sensor dashboards have enormous amount of information to be presented which becomes complex for operators to perform monitoring, controlling and interpretation tasks. Designing handheld sensor dashboards for supervision task will become a challenge for the interface designers. This paper reports emerging technologies of industry 4.0, changing context of increasing information complexity in consecutive industrial revolutions and upcoming design challenges for interface designers in context of Industry 4.0. Authors conclude that information complexity of sensor dashboards design has increased with consecutive industrial revolutions and designs of sensor dashboard causes cognitive load on users. Designing such complex dashboards interfaces in Industry 4.0 context will become main challenges for the interface designers.

Keywords: Industry 4.0, sensor dashboard design, Cyber-physical production system, Interface designer.

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2506 Automatic Inspection of Percussion Caps by Means of Combined 2D and 3D Machine Vision Techniques

Authors: A. Tellaeche, R. Arana, I.Maurtua

Abstract:

The exhaustive quality control is becoming more and more important when commercializing competitive products in the world's globalized market. Taken this affirmation as an undeniable truth, it becomes critical in certain sector markets that need to offer the highest restrictions in quality terms. One of these examples is the percussion cap mass production, a critical element assembled in firearm ammunition. These elements, built in great quantities at a very high speed, must achieve a minimum tolerance deviation in their fabrication, due to their vital importance in firing the piece of ammunition where they are built in. This paper outlines a machine vision development for the 100% inspection of percussion caps obtaining data from 2D and 3D simultaneous images. The acquisition speed and precision of these images from a metallic reflective piece as a percussion cap, the accuracy of the measures taken from these images and the multiple fabrication errors detected make the main findings of this work.

Keywords: critical tolerance, high speed decision makingsimultaneous 2D/3D machine vision.

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2505 Performance Analysis of Traffic Classification with Machine Learning

Authors: Htay Htay Yi, Zin May Aye

Abstract:

Network security is role of the ICT environment because malicious users are continually growing that realm of education, business, and then related with ICT. The network security contravention is typically described and examined centrally based on a security event management system. The firewalls, Intrusion Detection System (IDS), and Intrusion Prevention System are becoming essential to monitor or prevent of potential violations, incidents attack, and imminent threats. In this system, the firewall rules are set only for where the system policies are needed. Dataset deployed in this system are derived from the testbed environment. The traffic as in DoS and PortScan traffics are applied in the testbed with firewall and IDS implementation. The network traffics are classified as normal or attacks in the existing testbed environment based on six machine learning classification methods applied in the system. It is required to be tested to get datasets and applied for DoS and PortScan. The dataset is based on CICIDS2017 and some features have been added. This system tested 26 features from the applied dataset. The system is to reduce false positive rates and to improve accuracy in the implemented testbed design. The system also proves good performance by selecting important features and comparing existing a dataset by machine learning classifiers.

Keywords: False negative rate, intrusion detection system, machine learning methods, performance.

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2504 Determining the Gender of Korean Names for Pronoun Generation

Authors: Seong-Bae Park, Hee-Geun Yoon

Abstract:

It is an important task in Korean-English machine translation to classify the gender of names correctly. When a sentence is composed of two or more clauses and only one subject is given as a proper noun, it is important to find the gender of the proper noun for correct translation of the sentence. This is because a singular pronoun has a gender in English while it does not in Korean. Thus, in Korean-English machine translation, the gender of a proper noun should be determined. More generally, this task can be expanded into the classification of the general Korean names. This paper proposes a statistical method for this problem. By considering a name as just a sequence of syllables, it is possible to get a statistics for each name from a collection of names. An evaluation of the proposed method yields the improvement in accuracy over the simple looking-up of the collection. While the accuracy of the looking-up method is 64.11%, that of the proposed method is 81.49%. This implies that the proposed method is more plausible for the gender classification of the Korean names.

Keywords: machine translation, natural language processing, gender of proper nouns, statistical method

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2503 Gas Detection via Machine Learning

Authors: Walaa Khalaf, Calogero Pace, Manlio Gaudioso

Abstract:

We present an Electronic Nose (ENose), which is aimed at identifying the presence of one out of two gases, possibly detecting the presence of a mixture of the two. Estimation of the concentrations of the components is also performed for a volatile organic compound (VOC) constituted by methanol and acetone, for the ranges 40-400 and 22-220 ppm (parts-per-million), respectively. Our system contains 8 sensors, 5 of them being gas sensors (of the class TGS from FIGARO USA, INC., whose sensing element is a tin dioxide (SnO2) semiconductor), the remaining being a temperature sensor (LM35 from National Semiconductor Corporation), a humidity sensor (HIH–3610 from Honeywell), and a pressure sensor (XFAM from Fujikura Ltd.). Our integrated hardware–software system uses some machine learning principles and least square regression principle to identify at first a new gas sample, or a mixture, and then to estimate the concentrations. In particular we adopt a training model using the Support Vector Machine (SVM) approach with linear kernel to teach the system how discriminate among different gases. Then we apply another training model using the least square regression, to predict the concentrations. The experimental results demonstrate that the proposed multiclassification and regression scheme is effective in the identification of the tested VOCs of methanol and acetone with 96.61% correctness. The concentration prediction is obtained with 0.979 and 0.964 correlation coefficient for the predicted versus real concentrations of methanol and acetone, respectively.

Keywords: Electronic nose, Least square regression, Mixture ofgases, Support Vector Machine.

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2502 Cirrhosis Mortality Prediction as Classification Using Frequent Subgraph Mining

Authors: Abdolghani Ebrahimi, Diego Klabjan, Chenxi Ge, Daniela Ladner, Parker Stride

Abstract:

In this work, we use machine learning and data analysis techniques to predict the one-year mortality of cirrhotic patients. Data from 2,322 patients with liver cirrhosis are collected at a single medical center. Different machine learning models are applied to predict one-year mortality. A comprehensive feature space including demographic information, comorbidity, clinical procedure and laboratory tests is being analyzed. A temporal pattern mining technic called Frequent Subgraph Mining (FSM) is being used. Model for End-stage liver disease (MELD) prediction of mortality is used as a comparator. All of our models statistically significantly outperform the MELD-score model and show an average 10% improvement of the area under the curve (AUC). The FSM technic itself does not improve the model significantly, but FSM, together with a machine learning technique called an ensemble, further improves the model performance. With the abundance of data available in healthcare through electronic health records (EHR), existing predictive models can be refined to identify and treat patients at risk for higher mortality. However, due to the sparsity of the temporal information needed by FSM, the FSM model does not yield significant improvements. Our work applies modern machine learning algorithms and data analysis methods on predicting one-year mortality of cirrhotic patients and builds a model that predicts one-year mortality significantly more accurate than the MELD score. We have also tested the potential of FSM and provided a new perspective of the importance of clinical features.

Keywords: machine learning, liver cirrhosis, subgraph mining, supervised learning

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2501 Digital Encoder Based Power Frequency Deviation Measurement

Authors: Syed Javed Arif, Mohd Ayyub Khan, Saleem Anwar Khan

Abstract:

In this paper, a simple method is presented for measurement of power frequency deviations. A phase locked loop (PLL) is used to multiply the signal under test by a factor of 100. The number of pulses in this pulse train signal is counted over a stable known period, using decade driving assemblies (DDAs) and flip-flops. These signals are combined using logic gates and then passed through decade counters to give a unique combination of pulses or levels, which are further encoded. These pulses are equally suitable for both control applications and display units. The experimental circuit developed gives a resolution of 1 Hz within the measurement period of 20 ms. The proposed circuit is also simulated in Verilog Hardware Description Language (VHDL) and implemented using Field Programing Gate Arrays (FPGAs). A Mixed signal Oscilloscope (MSO) is used to observe the results of FPGA implementation. These results are compared with the results of the proposed circuit of discrete components. The proposed system is useful for frequency deviation measurement and control in power systems.

Keywords: Frequency measurement, digital control, phase locked loop, encoding, Verilog HDL.

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2500 Face Recognition with PCA and KPCA using Elman Neural Network and SVM

Authors: Hossein Esbati, Jalil Shirazi

Abstract:

In this paper, in order to categorize ORL database face pictures, principle Component Analysis (PCA) and Kernel Principal Component Analysis (KPCA) methods by using Elman neural network and Support Vector Machine (SVM) categorization methods are used. Elman network as a recurrent neural network is proposed for modeling storage systems and also it is used for reviewing the effect of using PCA numbers on system categorization precision rate and database pictures categorization time. Categorization stages are conducted with various components numbers and the obtained results of both Elman neural network categorization and support vector machine are compared. In optimum manner 97.41% recognition accuracy is obtained.

Keywords: Face recognition, Principal Component Analysis, Kernel Principal Component Analysis, Neural network, Support Vector Machine.

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2499 Permanent Magnet Machine Can Be a Vibration Sensor for Itself

Authors: M. Barański

Abstract:

This article presents a new vibration diagnostic method designed to (PM) machines with permanent magnets. Those devices are commonly used in small wind and water systems or vehicles drives. The author’s method is very innovative and unique. Specific structural properties of PM machines are used in this method - electromotive force (EMF) generated due to vibrations. There was analysed number of publications which describe vibration diagnostic methods and tests of electrical PM machines and there was no method found to determine the technical condition of such machine basing on their own signals. In this article will be discussed: the method genesis, the similarity of machines with permanent magnet to vibration sensor and simulation and laboratory tests results. The method of determination the technical condition of electrical machine with permanent magnets basing on its own signals is the subject of patent application and it is the main thesis of author’s doctoral dissertation.

Keywords: Electrical vehicle, generator, permanent magnet, traction drive, vibrations.

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2498 Dissolved Oxygen Prediction Using Support Vector Machine

Authors: Sorayya Malek, Mogeeb Mosleh, Sharifah M. Syed

Abstract:

In this study, Support Vector Machine (SVM) technique was applied to predict the dichotomized value of Dissolved oxygen (DO) from two freshwater lakes namely Chini and Bera Lake (Malaysia). Data sample contained 11 parameters for water quality features from year 2005 until 2009. All data parameters were used to predicate the dissolved oxygen concentration which was dichotomized into 3 different levels (High, Medium, and Low). The input parameters were ranked, and forward selection method was applied to determine the optimum parameters that yield the lowest errors, and highest accuracy. Initial results showed that pH, Water Temperature, and Conductivity are the most important parameters that significantly affect the predication of DO. Then, SVM model was applied using the Anova kernel with those parameters yielded 74% accuracy rate. We concluded that using SVM models to predicate the DO is feasible, and using dichotomized value of DO yields higher prediction accuracy than using precise DO value.

Keywords: Dissolved oxygen, Water quality, predication DO, Support Vector Machine.

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2497 Solving Single Machine Total Weighted Tardiness Problem Using Gaussian Process Regression

Authors: Wanatchapong Kongkaew

Abstract:

This paper proposes an application of probabilistic technique, namely Gaussian process regression, for estimating an optimal sequence of the single machine with total weighted tardiness (SMTWT) scheduling problem. In this work, the Gaussian process regression (GPR) model is utilized to predict an optimal sequence of the SMTWT problem, and its solution is improved by using an iterated local search based on simulated annealing scheme, called GPRISA algorithm. The results show that the proposed GPRISA method achieves a very good performance and a reasonable trade-off between solution quality and time consumption. Moreover, in the comparison of deviation from the best-known solution, the proposed mechanism noticeably outperforms the recently existing approaches.

 

Keywords: Gaussian process regression, iterated local search, simulated annealing, single machine total weighted tardiness.

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2496 Contribution to Active and Passive Control of Flow around a Cylinder

Authors: M. Tahar Bouzaher

Abstract:

This numerical study aims to develop a coupled, passive and active control strategy of the flow around a cylinder of diameter D, and Re=4000. The strategy consists to put a cylindrical rod in front of a deforming cylinder. The quasi- elliptical deformation of cylinder follow a sinusoidal law in order to reduce the drag force. To analyze the evolution of unsteady vortices, the Large Eddy Simulation approach is used in this 2D simulation, carried out using ANSYS – Fluent. The movement of deformation is reproduced using an internal subroutine, introduced in the form of a User Defined Function UDF. Two diameters of the rod were tested for a rod placed at a distance L = 3 ×d, with an amplitudes of deformation A = 5%, A = 25% and A = 50% of the cylinder diameter, the frequency of deformation take the values fd = 1fn, 5fn and 8fn, which fn represents the naturel vortex shedding frequency. The results show substantial changes in the flow behavior and for a rod of 6mm (1% D) with amplitude A = 25%, and with a 2fn frequency, drag reduction of 60% was recorded.

Keywords: CFD, Flow separation, control, Boundary layer, rod, Cylinder.

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2495 Compensation Method Eliminating Voltage Distortions in PWM Inverter

Authors: H. Sediki, S. Djennoune

Abstract:

The switching lag-time and the voltage drop across the power devices cause serious waveform distortions and fundamental voltage drop in pulse width-modulated inverter output. These phenomenons are conspicuous when both the output frequency and voltage are low. To estimate the output voltage from the PWM reference signal it is essential to take account of these imperfections and to correct them. In this paper, on-line compensation method is presented. It needs three simple blocs to add at the ideal reference voltages. This method does not require any additional hardware circuit and off- line experimental measurement. The paper includes experimental results to demonstrate the validity of the proposed method. It is applied, finally, in case of indirect vector controlled induction machine and implemented using dSpace card.

Keywords: Dead time, field-oriented control, Induction motor, PWM inverter, voltage drop.

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