Search results for: speech processing

Authors: Ashly Joseph, Jithu Paulose

Abstract:

The increased usage of cloud computing has revolutionized the IT landscape, but it has also raised new security concerns. DevSecOps emerged as a way for tackling these difficulties by integrating security into the software development process. However, the rising complexity and sophistication of cyber threats need more advanced solutions. This paper looks into the usage of artificial intelligence (AI) techniques in the DevSecOps framework to increase cloud security. This study uses quantitative and qualitative techniques to assess the usefulness of AI approaches such as machine learning, natural language processing, and deep learning in reducing security issues. This paper thoroughly examines the symbiotic relationship between AI and DevSecOps, concentrating on how AI may be seamlessly integrated into the continuous integration and continuous delivery (CI/CD) pipeline, automated security testing, and real-time monitoring methods. The findings emphasize AI's huge potential to improve threat detection, risk assessment, and incident response skills. Furthermore, the paper examines the implications and challenges of using AI in DevSecOps workflows, considering factors like as scalability, interpretability, and adaptability. This paper adds to a better understanding of AI's revolutionary role in cloud security and provides valuable insights for practitioners and scholars in the field.

Keywords: Cloud Security, DevSecOps, Artificial Intelligence, AI, Machine Learning, Natural Language Processing, NLP, cybersecurity, AI-driven Security.

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Authors: Akhilesh G. Naik, Dipankar Pal

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In today’s scenario, the complexity of digital signal processing (DSP) applications and various microcontroller architectures have been increasing to such an extent that the traditional approaches to multiplier design in most processors are becoming outdated for being comparatively slow. Modern processing applications require suitable pipelined approaches, and therefore, algorithms that are friendlier with pipelined architectures. Traditional algorithms like Wallace Tree, Radix-4 Booth, Radix-8 Booth, Dadda architectures have been proven to be comparatively slow for pipelined architectures. These architectures, therefore, need to be optimized or combined with other architectures amongst them to enhance its performances and to be made suitable for pipelined hardware/architectures. Recently, Vedic algorithm mathematically has proven to be efficient by appearing to be less complex and with fewer steps for its output establishment and have assumed renewed importance. This paper describes and shows how the Vedic algorithm can be better suited for pipelined architectures and also can be combined with traditional architectures and algorithms for enhancing its ability even further. In this paper, we also established that for complex applications on DSP and other microcontroller architectures, using Vedic approach for multiplication proves to be the best available and efficient option.

Keywords: Wallace tree, Radix-4 Booth, Radix-8 Booth, Dadda, Vedic, Single-Stage Karatsuba, Looped Karatsuba.

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Authors: Nhon Do, Thuong Huynh, An Pham

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Nowadays, organizing a repository of documents and resources for learning on a special field as Information Technology (IT), together with search techniques based on domain knowledge or document-s content is an urgent need in practice of teaching, learning and researching. There have been several works related to methods of organization and search by content. However, the results are still limited and insufficient to meet user-s demand for semantic document retrieval. This paper presents a solution for the organization of a repository that supports semantic representation and processing in search. The proposed solution is a model which integrates components such as an ontology describing domain knowledge, a database of document repository, semantic representation for documents and a file system; with problems, semantic processing techniques and advanced search techniques based on measuring semantic similarity. The solution is applied to build a IT learning materials management system of a university with semantic search function serving students, teachers, and manager as well. The application has been implemented, tested at the University of Information Technology, Ho Chi Minh City, Vietnam and has achieved good results.

Keywords: document retrieval system, knowledgerepresentation, document representation, semantic search, ontology.

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Authors: Ritu Vijay, Rekha Govil

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The design of a complete expansion that allows for compact representation of certain relevant classes of signals is a central problem in signal processing applications. Achieving such a representation means knowing the signal features for the purpose of denoising, classification, interpolation and forecasting. Multilayer Neural Networks are relatively a new class of techniques that are mathematically proven to approximate any continuous function arbitrarily well. Radial Basis Function Networks, which make use of Gaussian activation function, are also shown to be a universal approximator. In this age of ever-increasing digitization in the storage, processing, analysis and communication of information, there are numerous examples of applications where one needs to construct a continuously defined function or numerical algorithm to approximate, represent and reconstruct the given discrete data of a signal. Many a times one wishes to manipulate the data in a way that requires information not included explicitly in the data, which is done through interpolation and/or extrapolation. Tidal data are a very perfect example of time series and many statistical techniques have been applied for tidal data analysis and representation. ANN is recent addition to such techniques. In the present paper we describe the time series representation capabilities of a special type of ANN- Radial Basis Function networks and present the results of tidal data representation using RBF. Tidal data analysis & representation is one of the important requirements in marine science for forecasting.

Keywords: ANN, RBF, Tidal Data.

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Authors: Nermine Ahmed Hendy, Hania Farag

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Emotion recognition is an important research field that finds lots of applications nowadays. This work emphasizes on recognizing different emotions from speech signal. The extracted features are related to statistics of pitch, formants, and energy contours, as well as spectral, perceptual and temporal features, jitter, and shimmer. The Artificial Neural Networks (ANN) was chosen as the classifier. Working on finding a robust and fast ANN classifier suitable for different real life application is our concern. Several experiments were carried out on different ANN to investigate the different factors that impact the classification success rate. Using a database containing 7 different emotions, it will be shown that with a proper and careful adjustment of features format, training data sorting, number of features selected and even the ANN type and architecture used, a success rate of 85% or even more can be achieved without increasing the system complicity and the computation time

Keywords: Classification, emotion recognition, features extraction, feature selection, neural network

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Authors: Abhijit Mitra

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Different pseudo-random or pseudo-noise (PN) as well as orthogonal sequences that can be used as spreading codes for code division multiple access (CDMA) cellular networks or can be used for encrypting speech signals to reduce the residual intelligence are investigated. We briefly review the theoretical background for direct sequence CDMA systems and describe the main characteristics of the maximal length, Gold, Barker, and Kasami sequences. We also discuss about variable- and fixed-length orthogonal codes like Walsh- Hadamard codes. The equivalence of PN and orthogonal codes are also derived. Finally, a new PN sequence is proposed which is shown to have certain better properties than the existing codes.

Keywords: Code division multiple access, pseudo-noise codes, maximal length, Gold, Barker, Kasami, Walsh-Hadamard, autocorrelation, crosscorrelation, figure of merit.

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Authors: Mohsin T. Mohammed, Zahid A. Khan, Arshad N. Siddiquee

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The field of biomedical materials plays an imperative requisite and a critical role in manufacturing a variety of biological artificial replacements in a modern world. Recently, titanium (Ti) materials are being used as biomaterials because of their superior corrosion resistance and tremendous specific strength, free- allergic problems and the greatest biocompatibility compared to other competing biomaterials such as stainless steel, Co-Cr alloys, ceramics, polymers, and composite materials. However, regardless of these excellent performance properties, Implantable Ti materials have poor shear strength and wear resistance which limited their applications as biomaterials. Even though the wear properties of Ti alloys has revealed some improvements, the crucial effectiveness of biomedical Ti alloys as wear components requires a comprehensive deep understanding of the wear reasons, mechanisms, and techniques that can be used to improve wear behavior. This review examines current information on the effect of thermal and thermomechanical processing of implantable Ti materials on the long-term prosthetic requirement which related with wear behavior. This paper focuses mainly on the evolution, evaluation and development of effective microstructural features that can improve wear properties of bio grade Ti materials using thermal and thermomechanical treatments.

Keywords: Wear Resistance, Heat Treatment, Thermomechanical Processing, Biomedical Titanium Materials.

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Authors: Chen Zhang, Bernhard Schwarz-Röhr, Alexander Härting

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To acquire accurate ship motions at the center of gravity, a single low-cost inertial sensor is utilized and applied on board to measure ship oscillating motions. As observations, the three axes accelerations and three axes rotational rates provided by the sensor are used. The mathematical model of processing the observation data includes determination of the distance vector between the sensor and the center of gravity in x, y, and z directions. After setting up the transfer matrix from sensor’s own coordinate system to the ship’s body frame, an extended Kalman filter is applied to deal with nonlinearities between the ship motion in the body frame and the observation information in the sensor’s frame. As a side effect, the method eliminates sensor noise and other unwanted errors. Results are not only roll and pitch, but also linear motions, in particular heave and surge at the center of gravity. For testing, we resort to measurements recorded on a small vessel in a well-defined sea state. With response amplitude operators computed numerically by a commercial software (Seaway), motion characteristics are estimated. These agree well with the measurements after processing with the suggested method.

Keywords: Extended Kalman filter, nonlinear estimation, sea trial, ship motion estimation.

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Authors: Nazim Uddin, Yohiko Nakaura, Kazutaka Yamamoto

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Compote (fruit in syrup) of pineapple (Ananas comosus L. Merrill) is expected to have a high market potential as one of convenient ready-to-eat (RTE) foods worldwide. High hydrostatic pressure (HHP) in combination with low temperature (LT) was applied to the processing of pineapple compote as well as medium HHP (MHHP) in combination with medium-high temperature (MHT) since both processes can enhance liquid impregnation and inactivate microbes. MHHP+MHT (55 or 65 °C) process, as well as the HHP+LT process, has successfully inactivated the microbes in the compote to a non-detectable level. Although the compotes processed by MHHP+MHT or HHP+LT have lost the fresh texture as in a similar manner as those processed solely by heat, it was indicated that the texture degradations by heat were suppressed under MHHP. Degassing process reduced the hardness, while calcium (Ca) contributed to be retained hardness in MHT and MHHP+MHT processes. Electrical impedance measurement supported the damage due to degassing and heat. The color, Brix, and appearance were not affected by the processing methods significantly. MHHP+MHT and HHP+LT processes may be applicable to produce high-quality, safe RTE pineapple compotes. Further studies on the optimization of packaging and storage condition will be indispensable for commercialization.

Keywords: Compote of pineapple, ready-to-eat, medium high hydrostatic pressure, postharvest loss, and texture.

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Authors: Yu Luan

Abstract:

The bone-conducted objective occlusion effect (OE) is characterized by a discomforting sensation of fullness experienced in an occluded ear. This phenomenon arises from various external stimuli, such as human speech, chewing, and walking, which generate vibrations transmitted through the body to the ear canal walls. The bone-conducted OE occurs due to the pressure build-up inside the occluded ear caused by sound radiating into the ear canal cavity from its walls. In the hearing aid industry, artificial ears are utilized as a tool for developing hearing aids. However, the currently available commercial artificial ears primarily focus on pure acoustics measurements, neglecting the bone-conducted vibration aspect. This research endeavors to develop an artificial ear specifically designed for bone-conducted occlusion measurements. Finite Element Analysis (FEA) modeling has been employed to gain insights into the behavior of the artificial ear.

Keywords: Artificial ear, bone conducted vibration, occlusion measurement, Finite Element Modeling.

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Authors: Seok Hong Min, Jung Ho Moon, Woo Young Jung, Tae Kwon Ha

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The hot deformation behavior of high strength low alloy (HSLA) steels with different chemical compositions under hot working conditions in the temperature range of 900 to 1100℃ and strain rate range from 0.1 to 10 s-1 has been studied by performing a series of hot compression tests. The dynamic materials model has been employed for developing the processing maps, which show variation of the efficiency of power dissipation with temperature and strain rate. Also the Kumar-s model has been used for developing the instability map, which shows variation of the instability for plastic deformation with temperature and strain rate. The efficiency of power dissipation increased with decreasing strain rate and increasing temperature in the steel with higher Cr and Ti content. High efficiency of power dissipation over 20 % was obtained at a finite strain level of 0.1 under the conditions of strain rate lower than 1 s-1 and temperature higher than 1050 ℃ . Plastic instability was expected in the regime of temperatures lower than 1000 ℃ and strain rate lower than 0.3 s-1. Steel with lower Cr and Ti contents showed high efficiency of power dissipation at higher strain rate and lower temperature conditions.

Keywords: High strength low alloys steels, hot workability, Dynamic materials model, Processing maps.

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Authors: Nickson Kipng’etich Lang’at, Thomas Thoruwa, John Abraham, John Wanyoko

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Green tea is made from the top two leaves and buds of a shrub, Camellia sinensis, of the family Theaceae and the order Theales. The green tea leaves are picked and immediately sent to be dried or steamed to prevent fermentation. Fluid bed drying technique is a common drying method used in drying green tea because of its ease in design and construction and fluidization of fine tea particles. Major problems in this method are significant loss of chemical content of the leaf and green appearance of tea, retention of high moisture content in the leaves and bed channeling and defluidization. The energy associated with the drying technology has been shown to be a vital factor in determining the quality of green tea. As part of the implementation, prototype dryer was built that facilitated sequence of operations involving steaming, cooling, pre-drying and final drying. The major findings of the project were in terms of quality characteristics of tea leaves and energy consumption during processing. The optimal design achieved a moisture content of 4.2 ± 0.84%. With the optimum drying temperature of 100 ºC, the specific energy consumption was 1697.8 kj.Kg^-1 and evaporation rate of 4.272 x 10^-4 Kg.m^-2.s^-1. The energy consumption in a fluidized system can be further reduced by focusing on energy saving designs.

Keywords: Evaporation rate, fluid bed dryer, maceration, specific energy consumption.

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Authors: H. Ali, A. Whitehead

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Providing a panoramic view of famous landmarks around the world offers artistic and historic value for historians, tourists, and researchers. Exploring the history of famous landmarks by presenting a comprehensive view of a temporal panorama merged with geographical and historical information presents a unique challenge of dealing with images that span a long period, from the 1800’s up to the present. This work presents the concept of temporal panorama through a timeline display of aligned historic and modern images for many famous landmarks. Utilization of this panorama requires a collection of hundreds of thousands of landmark images from the Internet comprised of historic images and modern images of the digital age. These images have to be classified for subset selection to keep the more suitable images that chronologically document a landmark’s history. Processing of historic images captured using older analog technology under various different capturing conditions represents a big challenge when they have to be used with modern digital images. Successful processing of historic images to prepare them for next steps of temporal panorama creation represents an active contribution in cultural heritage preservation through the fulfillment of one of UNESCO goals in preservation and displaying famous worldwide landmarks.

Keywords: Cultural heritage, image registration, image subset selection, registered image similarity, temporal panorama, timescapes.

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Authors: Sangamesh G. Sakri, Akash N. Patil, Sadashivappa M. Kotli

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Agro based industries in India are considered as the micro, small and medium enterprises (MSME). In India, MSMEs contribute approximately 8 percent of the country’s GDP, 42 percent of the manufacturing output and 40 percent of exports. The toor dal (scientific name Cajanus cajan, commonly known as yellow gram, pigeon pea) is the second largest pulse crop in India accounting for about 20% of total pulse production. The toor dal milling industry in India is one of the major agro-processing industries in the country. Most of the dal mills are concentrated in pulse producing areas, which are spread all over the country. In Karnataka state, Gulbarga is a district, where toor dal is the main crop and is grown extensively. There are more than 500 dal mills in and around the Gulbarga district to process dal. However, the majority of these dal milling units use traditional methods of processing which are energy and capital intensive. There exists a huge energy saving potential in these mills. An energy audit is conducted on a dal mill in Gulbarga to understand the energy consumption pattern to assess the energy saving potential, and an economic analysis is conducted to identify energy conservation opportunities.

Keywords: Conservation, demand side management, load curve, toor dal.

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Authors: Miljan B. Petrović, Dušan B. Petrović, Goran S. Nikolić

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This paper describes a method for AWGN (Additive White Gaussian Noise) variance estimation in noisy stochastic signals, referred to as Multiplicative-Noising Variance Estimation (MNVE). The aim was to develop an estimation algorithm with minimal number of assumptions on the original signal structure. The provided MATLAB simulation and results analysis of the method applied on speech signals showed more accuracy than standardized AR (autoregressive) modeling noise estimation technique. In addition, great performance was observed on very low signal-to-noise ratios, which in general represents the worst case scenario for signal denoising methods. High execution time appears to be the only disadvantage of MNVE. After close examination of all the observed features of the proposed algorithm, it was concluded it is worth of exploring and that with some further adjustments and improvements can be enviably powerful.

Keywords: Noise, signal-to-noise ratio, stochastic signals, variance estimation.

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Authors: Farhad Asadi, Hossein Sadati

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In fields such as neuroscience and especially in cognition modeling of mental processes, uncertainty processing in temporal zone of signal is vital. In this paper, Bayesian online inferences in estimation of change-points location in signal are constructed. This method separated the observed signal into independent series and studies the change and variation of the regime of data locally with related statistical characteristics. We give conditions on simulations of the method when the data characteristics of signals vary, and provide empirical evidence to show the performance of method. It is verified that correlation between series around the change point location and its characteristics such as Signal to Noise Ratios and mean value of signal has important factor on fluctuating in finding proper location of change point. And one of the main contributions of this study is related to representing of these influences of signal statistical characteristics for finding abrupt variation in signal. There are two different structures for simulations which in first case one abrupt change in temporal section of signal is considered with variable position and secondly multiple variations are considered. Finally, influence of statistical characteristic for changing the location of change point is explained in details in simulation results with different artificial signals.

Keywords: Time series, fluctuation in statistical characteristics, optimal learning.

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Authors: D. Beziakina, E. Bulgakova

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The paper deals with cross-gender and cross-linguistic comparison of pitch characteristics for Tuvinian with two other Turkic languages - Uzbek and Azerbaijani, based on the results of statistical analysis of pitch parameter values and intonation patterns used by male and female speakers.

The main goal of our work is to obtain the ranges of pitch parameter values typical for Tuvinian speakers for the purpose of automatic language identification. We also propose a cross-gender analysis of declarative intonation in the poorly studied Tuvinian language.

The ranges of pitch parameter values were obtained by means of specially developed software that deals with the distribution of pitch values and allows us to obtain statistical language-specific pitch intervals.

Keywords: Speech analysis, Statistical analysis, Speaker recognition, Identification of person.

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Authors: Farhad Alizadeh, Alireza Faregh Gharamaleki, Mojtaba Jalilzadeh, Houshang Gholami, Ali Akhoundzadeh

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This study presented hybrid pre-processing approach along with a conceptual model to enhance the accuracy of river discharge prediction. In order to achieve this goal, Ensemble Empirical Mode Decomposition algorithm (EEMD), Discrete Wavelet Transform (DWT) and Mutual Information (MI) were employed as a hybrid pre-processing approach conjugated to Least Square Support Vector Machine (LSSVM). A conceptual strategy namely multi-station model was developed to forecast the Souris River discharge more accurately. The strategy used herein was capable of covering uncertainties and complexities of river discharge modeling. DWT and EEMD was coupled, and the feature selection was performed for decomposed sub-series using MI to be employed in multi-station model. In the proposed feature selection method, some useless sub-series were omitted to achieve better performance. Results approved efficiency of the proposed DWT-EEMD-MI approach to improve accuracy of multi-station modeling strategies.

Keywords: River stage-discharge process, LSSVM, discrete wavelet transform (DWT), ensemble empirical decomposition mode (EEMD), multi-station modeling.

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Authors: Hee-Jeong Ahn, Kee-Won Kim, Seung-Hoon Kim

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The knowledge of the relationship between characters can help readers to understand the overall story or plot of the literary fiction. In this paper, we present a method for extracting the specific relationship between characters from a Korean literary fiction. Generally, methods for extracting relationships between characters in text are statistical or computational methods based on the sentence distance between characters without considering Korean linguistic features. Furthermore, it is difficult to extract the relationship with direction from text, such as one-sided love, because they consider only the weight of relationship, without considering the direction of the relationship. Therefore, in order to identify specific relationships between characters, we propose a statistical method considering linguistic features, such as syntactic patterns and speech verbs in Korean. The result of our method is represented by a weighted directed graph of the relationship between the characters. Furthermore, we expect that proposed method could be applied to the relationship analysis between characters of other content like movie or TV drama.

Keywords: Data mining, Korean linguistic feature, literary fiction, relationship extraction.

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Authors: Nagesha, G. Hemantha Kumar

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Although the level crossing concept has been the subject of intensive investigation over the last few years, certain problems of great interest remain unsolved. One of these concern is distribution of threshold levels. This paper presents a new threshold level allocation schemes for level crossing based on nonuniform sampling. Intuitively, it is more reasonable if the information rich regions of the signal are sampled finer and those with sparse information are sampled coarser. To achieve this objective, we propose non-linear quantization functions which dynamically assign the number of quantization levels depending on the importance of the given amplitude range. Two new approaches to determine the importance of the given amplitude segment are presented. The proposed methods are based on exponential and logarithmic functions. Various aspects of proposed techniques are discussed and experimentally validated. Its efficacy is investigated by comparison with uniform sampling.

Keywords: speech signals, sampling, signal reconstruction, asynchronousdelta modulation, non-linear quantization.

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Authors: V. Balanica, W. I. D. Rae, M. Caramihai, S. Acho, C. P. Herbst

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Mammographic images and data analysis to facilitate modelling or computer aided diagnostic (CAD) software development should best be done using a common database that can handle various mammographic image file formats and relate these to other patient information. This would optimize the use of the data as both primary reporting and enhanced information extraction of research data could be performed from the single dataset. One desired improvement is the integration of DICOM file header information into the database, as an efficient and reliable source of supplementary patient information intrinsically available in the images. The purpose of this paper was to design a suitable database to link and integrate different types of image files and gather common information that can be further used for research purposes. An interface was developed for accessing, adding, updating, modifying and extracting data from the common database, enhancing the future possible application of the data in CAD processing. Technically, future developments envisaged include the creation of an advanced search function to selects image files based on descriptor combinations. Results can be further used for specific CAD processing and other research. Design of a user friendly configuration utility for importing of the required fields from the DICOM files must be done.

Keywords: Database Integration, Mammogram Classification, Tumour Classification, Computer Aided Diagnosis.

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Authors: Adrienne Kline, Jaydip Desai

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Electroencephalogram (EEG) is a noninvasive technique that registers signals originating from the firing of neurons in the brain. The Emotiv EEG Neuroheadset is a consumer product comprised of 14 EEG channels and was used to record the reactions of the neurons within the brain to two forms of stimuli in 10 participants. These stimuli consisted of auditory and visual formats that provided directions of ‘right’ or ‘left.’ Participants were instructed to raise their right or left arm in accordance with the instruction given. A scenario in OpenViBE was generated to both stimulate the participants while recording their data. In OpenViBE, the Graz Motor BCI Stimulator algorithm was configured to govern the duration and number of visual stimuli. Utilizing EEGLAB under the cross platform MATLAB®, the electrodes most stimulated during the study were defined. Data outputs from EEGLAB were analyzed using IBM SPSS Statistics® Version 20. This aided in determining the electrodes to use in the development of a brain-machine interface (BMI) using real-time EEG signals from the Emotiv EEG Neuroheadset. Signal processing and feature extraction were accomplished via the Simulink® signal processing toolbox. An Arduino™ Duemilanove microcontroller was used to link the Emotiv EEG Neuroheadset and the right and left Mecha TE™ Hands.

Keywords: Brain-machine interface, EEGLAB, emotiv EEG neuroheadset, openViBE, simulink.

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Authors: Anam Rafique, Syed Sohail Ahmed

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One of the essential components of much of DSP application is noise cancellation. Changes in real time signals are quite rapid and swift. In noise cancellation, a reference signal which is an approximation of noise signal (that corrupts the original information signal) is obtained and then subtracted from the noise bearing signal to obtain a noise free signal. This approximation of noise signal is obtained through adaptive filters which are self adjusting. As the changes in real time signals are abrupt, this needs adaptive algorithm that converges fast and is stable. Least mean square (LMS) and normalized LMS (NLMS) are two widely used algorithms because of their plainness in calculations and implementation. But their convergence rates are small. Adaptive averaging filters (AFA) are also used because they have high convergence, but they are less stable. This paper provides the comparative study of LMS and Normalized NLMS, AFA and new enhanced average adaptive (Average NLMS-ANLMS) filters for noise cancelling application using speech signals.

Keywords: AFA, ANLMS, LMS, NLMS.

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Authors: Sepideh Fazeli, Fariba Bahrami

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Investigating language acquisition is one of the most challenging problems in the area of studying language. Syllable learning as a level of language acquisition has a considerable significance since it plays an important role in language acquisition. Because of impossibility of studying language acquisition directly with children, especially in its developmental phases, computer models will be useful in examining language acquisition. In this paper a computer model of early language learning for syllable learning is proposed. It is guided by a conceptual model of syllable learning which is named Directions Into Velocities of Articulators model (DIVA). The computer model uses simple associational and reinforcement learning rules within neural network architecture which are inspired by neuroscience. Our simulation results verify the ability of the proposed computer model in producing phonemes during babbling and early speech. Also, it provides a framework for examining the neural basis of language learning and communication disorders.

Keywords: Brain modeling, computer models, language acquisition, reinforcement learning.

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Authors: Aicha Majda, Abdelhamid El Hassani

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Lung CT image segmentation is a prerequisite in lung CT image analysis. Most of the conventional methods need a post-processing to deal with the abnormal lung CT scans such as lung nodules or other lesions. The simplest similarity measure in the standard Graph Cuts Algorithm consists of directly comparing the pixel values of the two neighboring regions, which is not accurate because this kind of metrics is extremely sensitive to minor transformations such as noise or other artifacts problems. In this work, we propose an improved version of the standard graph cuts algorithm based on the Patch-Based similarity metric. The boundary penalty term in the graph cut algorithm is defined Based on Patch-Based similarity measurement instead of the simple intensity measurement in the standard method. The weights between each pixel and its neighboring pixels are Based on the obtained new term. The graph is then created using theses weights between its nodes. Finally, the segmentation is completed with the minimum cut/Max-Flow algorithm. Experimental results show that the proposed method is very accurate and efficient, and can directly provide explicit lung regions without any post-processing operations compared to the standard method.

Keywords: Graph cuts, lung CT scan, lung parenchyma segmentation, patch based similarity metric.

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Authors: Kgatla T.E, Howard S.S., Hiss D.C.

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Prickly pear (Opuntia spp) fruit has received renewed interest since it contains a betalain pigment that has an attractive purple colour for the production of juice. Prickly pear juice was prepared by homogenizing the fruit and treating the pulp with 48 g of pectinase from Aspergillus niger. Titratable acidity was determined by diluting 10 ml prickly pear juice with 90 ml deionized water and titrating to pH 8.2 with 0.1 N NaOH. Brix was measured using a refractometer and ascorbic acid content assayed spectrophotometrically. Colour variation was determined colorimetrically (Hunter L.a.b.). Hunter L.a.b. analysis showed that the red purple colour of prickly pear juice had been affected by juice treatments. This was indicated by low light values of colour difference meter (CDML*), hue, CDMa* and CDMb* values. It was observed that non-treated prickly pear juice had a high (colour difference meter of light) CDML* of 3.9 compared to juice treatments (range 3.29 to 2.14). The CDML* significantly (p<0.05) decreased as the juice was preserved. Spectrophotometric colour analysis showed that browning was low in all treated prickly juice samples as indicated by high values at 540 nm and low values at 476 nm (browning index). The brightness of prickly pear had been affected by acidification compared to other juice treatments. This study presents evidence that processing has a positive effect on the colour quality attribute that offers a clear advantage for the production of red-purple prickly pear juice.

Keywords: Colour, Hunter L.a.b, Prickly pear juice, processing, physicochemical.

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Authors: Nieto Bernal Wilson, Carmona Suarez Edgar

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The organizations have structured and unstructured information in different formats, sources, and systems. Part of these come from ERP under OLTP processing that support the information system, however these organizations in OLAP processing level, presented some deficiencies, part of this problematic lies in that does not exist interesting into extract knowledge from their data sources, as also the absence of operational capabilities to tackle with these kind of projects.  Data Warehouse and its applications are considered as non-proprietary tools, which are of great interest to business intelligence, since they are repositories basis for creating models or patterns (behavior of customers, suppliers, products, social networks and genomics) and facilitate corporate decision making and research. The following paper present a structured methodology, simple, inspired from the agile development models as Scrum, XP and AUP. Also the models object relational, spatial data models, and the base line of data modeling under UML and Big data, from this way sought to deliver an agile methodology for the developing of data warehouses, simple and of easy application. The methodology naturally take into account the application of process for the respectively information analysis, visualization and data mining, particularly for patterns generation and derived models from the objects facts structured.

Keywords: Data warehouse, model data, big data, object fact, object relational fact, process developed data warehouse.

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Authors: Ali Ganoun

Abstract:

This paper proposes evaluation of sound parameterization methods in recognizing some spoken Arabic words, namely digits from zero to nine. Each isolated spoken word is represented by a single template based on a specific recognition feature, and the recognition is based on the Euclidean distance from those templates. The performance analysis of recognition is based on four parameterization features: the Burg Spectrum Analysis, the Walsh Spectrum Analysis, the Thomson Multitaper Spectrum Analysis and the Mel Frequency Cepstral Coefficients (MFCC) features. The main aim of this paper was to compare, analyze, and discuss the outcomes of spoken Arabic digits recognition systems based on the selected recognition features. The results acqired confirm that the use of MFCC features is a very promising method in recognizing Spoken Arabic digits.

Keywords: Speech Recognition, Spectrum Analysis, Burg Spectrum, Walsh Spectrum Analysis, Thomson Multitaper Spectrum, MFCC.

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Authors: Violina R. Angelova, Radka V. Ivanova, Givko M. Todorov, Krasimir I. Ivanov

Abstract:

A field study was conducted to evaluate the efficacy of Salvia sclarea L. for phytoremediation of contaminated soils. The experiment was performed on an agricultural fields contaminated by the Non-Ferrous-Metal Works near Plovdiv, Bulgaria. The content of heavy metals in different parts of Salvia sclarea L. (roots, stems, leaves and inflorescences) was determined by ICP. The essential oil of the Salvia sclarea L. was obtained by steam distillation in laboratory conditions and was analyzed for heavy metals and its chemical composition was determined. Salvia sclarea L. is a plant which is tolerant to heavy metals and can be grown on contaminated soils. Based on the obtained results and using the most common criteria, Salvia sclarea L. can be classified as Pb hyperaccumulator and Cd and Zn accumulators, therefore, this plant has suitable potential for the phytoremediation of heavy metal contaminated soils. Favorable is also the fact that heavy metals do not influence the development of the Salvia sclarea L., as well as on the quality and quantity of the essential oil. For clary sage oil obtained from the processing of clary sage grown on highly contaminated soils, its key odour-determining ingredients meet the quality requirements of the European Pharmacopoeia and BS ISO 7609 regarding Bulgarian clary sage oil and/or have values that are close to the limits of these standards. The possibility of further industrial processing will make Salvia sclarea L. an economically interesting crop for farmers of phytoextraction technology.

Keywords: Clary sage, heavy metals, phytoremediation, polluted soils.

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Authors: Jia-Rong Yeh, Ai-Hsien Li, Jiann-Shing Shieh, Yen-An Su, Chi-Yu Yang

Abstract:

In this paper, an automatic detecting algorithm for QRS complex detecting was applied for analyzing ECG recordings and five criteria for dangerous arrhythmia diagnosing are applied for a protocol type of automatic arrhythmia diagnosing system. The automatic detecting algorithm applied in this paper detected the distribution of QRS complexes in ECG recordings and related information, such as heart rate and RR interval. In this investigation, twenty sampled ECG recordings of patients with different pathologic conditions were collected for off-line analysis. A combinative application of four digital filters for bettering ECG signals and promoting detecting rate for QRS complex was proposed as pre-processing. Both of hardware filters and digital filters were applied to eliminate different types of noises mixed with ECG recordings. Then, an automatic detecting algorithm of QRS complex was applied for verifying the distribution of QRS complex. Finally, the quantitative clinic criteria for diagnosing arrhythmia were programmed in a practical application for automatic arrhythmia diagnosing as a post-processor. The results of diagnoses by automatic dangerous arrhythmia diagnosing were compared with the results of off-line diagnoses by experienced clinic physicians. The results of comparison showed the application of automatic dangerous arrhythmia diagnosis performed a matching rate of 95% compared with an experienced physician-s diagnoses.

Keywords: Signal processing, electrocardiography (ECG), QRS complex, arrhythmia.

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