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Elliptic flow due to charged hadrons for Au+Au collisions at RHIC energy 62.4 GeV

AIP Conference Proceedings 2016年第1期1728卷

作者： Somani Ajit Kumar Bhardwaj Sudhir Agnihotri Ashish 1Department of Physics Suresh Gyan Vihar University Jaipur Rajasthan INDIA (Presently working at Govt. Polytechnic College Hanumangarh Rajasthan INDIA) 2Govt. College of Engineering & Technology Bikaner Rajasthan INDIA 3Department of Physics SBCET Jaipur Rajasthan INDIA

Elliptic flow is an important observable in search of Quark Gluon Plasma. The elliptic flow parameter dependence on centrality due to charged hadrons were studied using events generated by event generator AMPT at center of mass energy of 62.4 GeV per nucleon pair for Au+Au collisions. This study performed for pseudorapidity range from −0.35 to 0.35 and transverse momentum bins pt = 0.2 to 1 GeV/c and 1 to 2 GeV/c. We compared the results obtained from simulated data and RHIC-PHENIX data.

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An improved method of audio denoising based on wavelet transform

An improved method of audio denoising based on wavelet trans...

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International Conference on Power, Instrumentation, Control and Computing (PICC)

作者： M. A. Ali P. M. Shemi Dept. of Electronics M E S College Marampally Ernakulam Kerala India Department of Computer Applications Govt. Engineering College Thrissur Kerala India

The recovery of original signals from the communication channel without any noise is a difficult task. Many denoising techniques have been proposed for the removal of noises from a digital signal. Wavelet denoising using threshold algorithm is a powerful method for suppressing noise in digital signals. In this paper, an audio denoising technique based on double-density dual-tree discrete wavelet transform (DDDTWT) using a level dependent threshold algorithm is implemented. Audio signal contaminated with Additive White Gaussian Noise is chosen for the implementation. The results in terms of signal to noise ratio (SNR) and root mean square error (RMSE) are compared with the values of dual-tree discrete wavelet transform (DTDWT) and double-density discrete wavelet transform (DDDWT) methods and also with global thresholding method. The results of MATLAB simulations show that the proposed method is more effective and gives better performance for denoising audio signals in terms of both SNR and RMSE.

关键词： Conferences Instruments 5G mobile communication

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Design and evaluation of performance of printed English Characters and Numerals system using a New Feature Extraction Technique 14

Design and evaluation of performance of printed English Char...

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International Conference on Information and Communication Technology for Competitive Strategies, ICTCS 2014

作者： Singh, Kavita Soni, Rituraj Department of Computer Engineering Govt. Engineering College Bikaner Bikaner India

ISBN: (纸本)9781450332163

Character Recognition is the process of detecting and recognizing characters from an input image. It can improve the interface between human and machine in various applications and contributes vastly to the advancement of an automation process. In this paper, we are presenting a New Feature Extraction Technique for recognizing English Characters and Numerals in printed text. In this approach, first, we have preprocessed the input image so as to make it ready for line segmentation. After that we have extracted the connected components in whole image (line segmentation).Then characters have been extracted in each line (character segmentation). Finally extracted characters have been matched with templates characters so as to recognize the characters. We are also presenting the comparison of our approach with some of the previous character recognition approaches with accuracy and error rate. Our approach successfully recognizes 36 characters with 26 uppercase letters and 10 digits. All the implementation and experimental work has been done in MATLAB R2008a using general Matlab tool box and image processing tool box. Experimental results show that our approach is very robust and gives maximum recognition rate of 99%in comparison to other methods that are previously reported.

关键词： Feature extraction

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Detection and classification technique of Yellow Vein Mosaic Virus disease in okra leaf images using leaf vein extraction and Naive Bayesian classifier

Detection and classification technique of Yellow Vein Mosaic...

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International Conference on Soft Computing Techniques and Implementations (ICSCTI)

作者： Dhiman Mondal Aruna Chakraborty Dipak Kumar Kole D. Dutta Majumder Computer Science & Engineering Jalpaiguri Govt. Engg. College Jalpaiguri India Department of Computer Science and Engineering Inst. of Cybernetics Systems & Info. Technology West Bengal India Indian Statistical Institute Institute of Cybernetics Systems and Information Technology Kolkata

Okra (Abelmoschus esculentus (L) Moench), is widely grown all over tropical, subtropical and warm temperature regions of the world. It is a popular crop in India due to its ease of cultivation and adaptability to varying moisture conditions. But the crop is prone to damage by various diseases caused by various insects, fungi, nematodes and viruses. The most common disease of okra is Yellow Vein Mosaic Virus (YVMV), spread by white fly (Bemisiatabaci). This paper presents an efficient technique to detect and classify the presence of YVMV disease in okra leaf with the joint use of image processing, K-means and Naive Bayesian classifier. The proposed technique is experimented on 79 standard diseased and non-diseased okra leaf images. The input leaf images are of four classes, namely Highly Susceptible (HS), Moderately Susceptible (MS), Tolerable (T) and Resistive (R), depending upon the severity of the YVMV infection. The proposed technique achieves 87% success rate using 10 features only.

关键词： Veins Diseases Feature extraction Correlation Standards Entropy Agriculture

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"diagnostics of induction motor based on spectral analysis of stator current signal using fast fourier transform and genetically tuned interval type-2 fuzzy classifier methods"

Advances in Modelling and Analysis B

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Advances in Modelling and Analysis B 2014年第1期57卷 47-67页

作者： Manoj, Jha Kulkarni, A.G. Qureshi, M.F. Department of Applied Mathematics Rungta Engineering College Raipur492099 India Department of Electronics and Telecommunication Rungta Engineering College Raipur492099 India Department of Electrical Engg. Govt. Polytechnic Janjgir-Champa 495668 India

A novel diagnostics method of induction motor based on spectral analysis of stator current signal using Fast Fourier Transform (FFT) and genetically tuned interval type-2 fuzzy classifier (GA+IT2FC) is proposed in this paper. New implementation of diagnostics of imminent failure conditions of induction motor was presented. System of current recognition is based on a study of the frequency spectrum of stator using FFT current signal. Interval type-2 Fuzzy classifier was applied. The studies were carried out for four imminent failure conditions of induction motor. The results confirm that the system can be useful for detecting damage and protect the engines. The failure identification techniques applied for condition monitoring of the motor and finally to design an Online condition monitoring system with interval type-2 fuzzy logic controller is studied. The modeling of three-phase induction motor in three phase reference frame using MATLAB 7 version software and designing an intelligent system for condition monitoring of the induction motor is proposed.

关键词： Fast Fourier transforms

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Notice of Removal: Reduced out-of-band radiation-based filter optimization for UFMC systems in 5G - Withdrawn

Notice of Removal: Reduced out-of-band radiation-based filte...

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IEEE Conference on Vehicular Technology (VTC)

作者： Mithun Mukherjee Vikas Kumar Gagnesh Kumar Prashant Kumar Rakesh Matam Department of Electronics and Communication Engineering National Institute of Technology Hamirpur India A Govt. of India Enterprise Bharat Sanchar Nigam Limited Patna India Department of Electronics and Communication Engineering Birla Institute of Technology Patna India Department of Computer Science Engineering Indian Institute of Information Technology Guwahati India

Universal-filtered multi-carrier (UFMC) technique is considered as a potential candidate for future communication systems due to its robustness against inter-carrier interference (ICI), suitability for non-contiguous fragmented available spectrum resources and low latency scenario in 5G network. In this work, we present a novel pulse shaping approach in UFMC to reduce the spectral leakage to nearby subbands used for same or other users with low complexity and high throughput. In the proposed scheme, we apply Bohman filter-based pulse shaping with combination of antipodal symbol-pairs to the edgesubcarriers of the subbands, and consequently reduce the outof-band radiation. We further optimize the filter co-efficients, which outperforms the current state-of-the art. This scheme offers better signal-to-interference ratio (SIR) to improve the robustness against carrier frequency offset (CFO) for energy saving in loosely synchronized scenario. In addition, we validate the proposed scheme by hardware prototype on a field programmable gate array (FPGA) chip.

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Random forest algorithm for improving the performance of speech/non-speech detection 1

Random forest algorithm for improving the performance of spe...

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2014 1st International Conference on Computational Systems and Communications, ICCSC 2014

作者： Thambi, Sincy V. Sreekumar, K.T. Santhosh Kumar, C. Reghu Raj, P.C. Department of Computer Science and Engineering Govt. Engineering College Palakkad Kerala India Machine Intelligence Research Lab Department of Electronics and Communication Engineering Amrita Vishwa Vidyapeetham Coimbatore Tamil Nadu India

ISBN: (纸本)9781479960132

Speech/non-speech detection (SND) distinguishes between speech and non-speech segments in recorded audio and video documents. SND systems can help reduce the storage space required when only speech segments from the audio documents are required, for example content analysis, spoken language identification, etc. In this work, we experimented with the use of time domain, frequency domain and cepstral domain features for short time frames of 20 ms. size along with their mean and standard deviation for segments of size 200 ms. We then analysed if selecting a subset of the features can help improve the performance of the SND system. Towards this, we experimented with different feature selection algorithms, and observed that correlation based feature selection gave the best results. Further, we experimented with different decision tree classification algorithms, and note that random forest algorithm outperformed other decision tree algorithms. We further improved the SND system performance by smoothing the decisions over 5 segments of 200 ms. each. Our baseline system has 272 features, a classification accuracy of 94.45 % and the final system with 8 features has a classification accuracy of 97.80 %. © 2014 IEEE.

关键词： Feature Selection

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Towards improving the performance of language identification system for Indian languages 1

Towards improving the performance of language identification...

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2014 1st International Conference on Computational Systems and Communications, ICCSC 2014

作者： Anto, Abitha Sreekumar, K.T. Santhosh Kumar, C. Reghu Raj, P.C. Department of Computer Science and Engineering Govt. Engineering College Palakkad Kerala India Machine Intelligence Research Lab Department of Electronics and Communication Engineering Amrita Vishwa Vidyapeetham Coimbatore Tamil Nadu India

ISBN: (纸本)9781479960132

In this paper, we present the details of a phonotactic language identification (LID) system developed for five Indian languages, English (Indian), Hindi, Malayalam, Tamil and Kan-nada. Since there are no publicly available speech databases for English, Malayalam and Kannada, we developed the database for each of the target languages by downloading the audio files from YouTube videos and removing the non-speech signals manually. The system was tested using a test data set consisting of 40 utterances with duration of 30, 10, and 3 sees, in each of 5 target languages. The performance evaluation was done separately accordingly to the NIST benchmarking sessions, for 30s, 10s and 3s segments separately. For the baseline system, we got an overall EER of 10.41 %, 19.56 % and 31.45 % for 30, 10, and 3 sees segments when tested with a 3-gram language model. The use of 4-gram language model has helped enhance the performance of the LID system to 9.81 %, 19.38 % and 32.77% respectively for 30,10 and 3 sees test segments. Further, by using the n-gram smoothing, we were able to improve the EER of the LID system, 9.02 %, 18.70 % and 29.24 % for 3-gram language models and 8.88 %, 16.46 % and 32.03 % for 4-gram language models, respectively for 30,10, and 3 sec test segments. The study shows that the use of 4-gram language models can help enhance the performance of LID systems for Indian languages. © 2014 IEEE.

关键词： Benchmarking

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Towards improving the performance of speaker recognition systems 1

Towards improving the performance of speaker recognition sys...

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2014 1st International Conference on Computational Systems and Communications, ICCSC 2014

作者： Johnson, Neethu George, Kuruvachan K. Santhosh Kumar, C. Reghu Raj, P.C. Department of Computer Science and Engineering Govt. Engineering College Palakkad Kerala India Machine Intelligence Research Lab Department of Electronics and Communication Engineering Amrita Vishwa Vidyapeetham Coimbatore Tamil Nadu India

ISBN: (纸本)9781479960132

This paper studies the contribution of different phones in speech data towards improving the performance of text/language independent speaker recognition systems. This work is motivated by the fact that the removal of silence segments from the speech data improves the system performance significantly as it does not contain any speaker-specific information. It is also clear from the literature that not all the phones in the speech data contains equal amount of speaker-specific information in it and the performance of the speaker recognition systems depends on this information. In addition to the silence segments, our work empirically finds 18 other diluent phones that has minimum speaker discrimination capability. We propose to use a preprocessing stage that identifies all non-informative set of phones recursively and removes them along with silence segments. Results show that using phones removed preprocessed data in state-of-the-art i-vector system outperforms the baseline i-vector system. We report absolute improvements of 1%, 1%, 2%, 2% and 1% in EER for test set collected through channels of Digital Voice Recorder, Headset, Mobile Phone 1, Mobile Phone 2 and Tablet PC respectively on IITG-MV database. © 2014 IEEE.

关键词： Cellular telephones

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Multi-objective optimization approach for cost management during product design at the conceptual phase

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Journal of Industrial engineering International 2014年第1期10卷 1-12页

作者： Durga Prasad, K.G. Venkata Subbaiah, K. Narayana Rao, K. Department of Mechanical Engineering School of Engineering G.V.P. Technical Campus Gayatri Vidya Parishad College for Degree and P.G. Courses Vishakhapatnam India Department of Mechanical Engineering Andhra University Vishakhapatnam India Department of Mechanical Engineering Govt. Polytechnic Paderu India

The effective cost management during the conceptual design phase of a product is essential to develop a product with minimum cost and desired quality. The integration of the methodologies of quality function deployment (QFD), value engineering (VE) and target costing (TC) could be applied to the continuous improvement of any product during product development. To optimize customer satisfaction and total cost of a product, a mathematical model is established in this paper. This model integrates QFD, VE and TC under multi-objective optimization frame work. A case study on domestic refrigerator is presented to show the performance of the proposed model. Goal programming is adopted to attain the goals of maximum customer satisfaction and minimum cost of the product. © 2014, The Author(s).

关键词： Cost management Goal programming Multi-objective optimization Product design Quality function deployment Target costing Value engineering

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