ELM and K-nn machine learning in classification of breath sounds signals

The acquisition of Breath sounds (BS) signals from a human respiratory system with an electronic stethoscope, provide and offer prominent information which helps the doctors to diagnosis and classification of pulmonary diseases. Unfortunately, this BS signals with other biological signals have a non-stationary nature according to the variation of the lung volume, and this nature makes it difficult to analyze and classify between several diseases. In this study, we were focused on comparing the ability of the extreme learning machine (ELM) and k-nearest neighbour (K-nn) machine learning algorithms in the classification of adventitious and normal breath sounds. To do so, the empirical mode decomposition (EMD) was used in this work to analyze BS, this method is rarely used in the breath sounds analysis. After the EMD decomposition of the signals into Intrinsic Mode Functions (IMFs), the Hjorth descriptors (Activity) and Permutation Entropy (PE) features were extracted from each IMFs and combined for classification stage. The study has found that the combination of features (activity and PE) yielded an accuracy of 90.71%, 95% using ELM and K-nn respectively in binary classification (normal and abnormal breath sounds), and 83.57%, 86.42% in multiclass classification (five classes)

Robust Automatic Speech recognition System Implemented in a Hybrid Design DSP-FPGA

The aim of this work is to reduce the burden task on the DSP processor by transferring a parallel computation part on a configurable circuits FPGA, in automatic speech recognition module design, signal pre-processing, feature selection and optimization, models construction and finally classification phase are necessary. LMS filter algorithm that contains more parallelism and more MACs (multiply and Accumulate) operations is implemented on FPGA Virtex 5 by Xilings, MFCCs features extraction and DTW ( dynamic time wrapping) method is used as a classifier. Major contribution of this work are hybrid solution DSP and FPGA in real time speech recognition system design, the optimization of number of MAC-core within the FPGA this result is obtained by sharing MAC resources between two operation phases: computation of output filter and updating LMS filter coefficients. The paper also provides a hardware solution of the filter with detailed description of asynchronous interface of FPGA circuit and TMS320C6713-EMIF component. The results of simulation shows an improvement in time computation and by optimizing the implementation on the FPGA a gain in space consumption is obtained

“ANALISIS PENGARUH HASIL PRODUKSI BUDIDAYA UDANG VANNAMEI TERHADAP PENINGKATAN EKONOMI MASYARAKAT DALAM PERSPEKTIF EKONOMI ISLAM” (Studi Pada Tambak Udang Desa Bratasena Adiwarna Kecamatan Dente Teladas Kabupaten Tulang Bawang Tahun 2017-2020)

“ANALISIS PENGARUH HASIL PRODUKSI BUDIDAYA UDANG VANNAMEI TERHADAP PENINGKATAN EKONOMI MASYARAKAT DALAM PERSPEKTIF EKONOMI ISLAM (Studi Pada tambak Udang Desa Bratasena Adiwarna Kecamatan Dente Teladas Kabupaten Tulang Bawang Tahun 2017-2020)” ABSTRAK Usaha tambak merupakan suatu kegiatan usaha ekonomis, dimana manusia mengusahakan, mengelola, dan mengendalikan sumberdaya hayati perikanan untuk mendapatkan keuntungan yang lebih demi meningkatkan pendapatan dan kesejahteraan pembudidaya. Pembangunan usaha tambak diarahkan untuk memperbaiki usaha budidaya perikanan yang sederhana menjadi budidaya yang maju. Untuk menyelesaikan permasalahan tersebut, maka rumusan masalahnya adalah.1. Bagaimana proses produksi dan faktor-faktor produksi budidaya udang vannamei di desa Bratasena Adiwarna Kecamatan Dente Teladas Kabupaten Tulang Bawang Tahun 2017-2020? 2. Bagaimana produksi udang vannamei dalam mempengaruhi peningkatan perekonomian petambak udang? 3. Bagaimana hasil produksi budidaya udang vannamei dalam mempengaruhi peningkatan perekonomian petambak udang dalam perspektif ekonomi Islam? Penelitian ini menggunakan jenis penelitian lapangan (field research) dengan metode kualitatif dan pendekatan berfikir deduktif. Pengumpulan data yang digunakan adalah data primer yang dikumpulkan melalui interview/wawancara, observasi, dan dokumentasi . Hasil penelitian menunjukan bahwa Proses produksi yang dilakukan petambak udang vannamei sudah optimal, dimana petambak memanfaatkan tanah, tenaga kerja, modal untuk menjalankan budidaya udang agar dapat meningkatkan perekonomian masyarakat. Pengaruh hasil produksi budidaya udang vannamei sudah sangat berperan penting dalam peningkatan ekonomi masyarakat khususnya masyarakat desa bratasena adiwarna kecamatan dente teladas. Karena hal ini merupakan kesempatan usaha para petambak dan masyarakat sebagai mata pencaharian sampingan dan sehari-hari yang sangat menjanjikan. Proses budidaya Budidaya udang vannamei yang dilakukan oleh masyarakat Desa Bratasena adiwarna sudah sesuai dengan prinsip ekonomi Islam. Dimana masyarakat memproduksi dan mendistribusikan udang vannamei sesuai dengan proses yang harus di jalani, yaitu dengan bersikap adil, jujur dan tidak ada unsur riba ataupun gharar demi tercapainya kepedulian sosial guna menegakkan kesejahteraan dunia maupun akhirat dan pengaruh hasil produksi budidaya udang vannamei terhadap peningkatkan ekonomi masyarakat dalam perspektif ekonomi Islam di desa bratasena adiwarna kecamatan dente teladas, sangat efektif dan berperan penting dalam kegiatan ekonomi. Dikarenakan dengan adanya budidaya udang vannamei, para petambak dan masyarakat dapat memperbaiki keadaan ekonomi untuk kesejahteraan keluarganya dan berperan penting guna memenuhi kebutuhan masyarakat untuk mengkonsumsi udang vannamei sehari-hari. Kata Kunci : Pengaruh Hasil Produksi Budidaya Udang Vannamei, Peningkatan Ekonomi Masyaraka

Navigation pour robot avec garantie de sécurité basée sur la théorie de la viabilité

Guaranteeing safe, i.e. collision-free, motion for robotic systems is usually tackled in the InevitableCollision State framework. This paper explores the use of the more general Viability theory as analternative when safe motion involves multiple motion constraints and not just collision avoidance. Centralto Viability is the so-called viability kernel, i.e. the set of states of the robotic system for which there isat least one trajectory that satisfies the motion constraints forever. The paper presents an algorithm thatcomputes off-line an approximation of the viability kernel that is both conservative and able to handletime-varying constraints such as moving obstacles. Then it demonstrates, for different robotic scenarios involvingmultiple motion constraints (collision avoidance, visibility, velocity), how to use the viability kernelcomputed off-line within an on-line reactive navigation scheme that can drive the robotic system withoutever violating the motion constraints at hand.La garantie de mouvement sans collision pour les systèmes robotiques est généralement abordéedans le cadre des Etats de Collision Inévitable. Cet article explore l’utilisation de la théorie plusgénérale de la Viabilité comme alternative lorsque le mouvement implique des contraintes de mouvementautres que l’évitement de collision. Le noyau de viabilité, i.e. l’ensemble des états du systèmerobotique pour lequel il existe au moins une trajectoire qui satisfait à jamais les contraintes de mouvement,est un élément central de la théorie de la viabilité. Cet article présente un algorithme qui calculehors ligne une approximation du noyau de viabilité qui est à la fois conservative et capable de gérer descontraintes dynamiques telles que des obstacles mobiles. Ensuite, il démontre, pour différents scénariosrobotiques impliquant plusieurs contraintes de mouvement (évitement de collision, visibilité, vitesse),comment utiliser le noyau de viabilité calculé hors ligne dans un schéma de navigation réactive en lignecapable de piloter le système robotique sans jamais violer les différentes contraintes de mouvement

Viability-Based Guaranteed Safe Robot Navigation

International audienceGuaranteeing safe, i.e. collision-free, motion for robotic systems is usually tackled in the Inevitable Collision State (ICS) framework. This paper explores the use of the more general Viability theory as an alternative when safe motion involves multiple motion constraints and not just collision avoidance. Central to Viability is the so-called viability kernel, i.e. the set of states of the robotic system for which there is at least one trajectory that satisfies the motion constraints forever. The paper presents an algorithm that computes off-line an approximation of the viability kernel that is both conservative and able to handle time-varying constraints such as moving obstacles. Then it demonstrates, for different robotic scenarios involving multiple motion constraints (collision avoidance, visibility, velocity), how to use the viability kernel computed off-line within an on-line reactive navigation scheme that can drive the robotic system without ever violating the motion constraints at hand

An Improved GMM-SVM System based on Distance Metric for Voice Pathology Detection

As acoustic signal generated from vocal folds is directly affected by vocal tract pathologies, it can be an effective tool for diagnosis purpose. In this work, we present an efficient method for voice pathology detection based on speech signal processing and machine learning techniques. In the proposed method, we used MFCC to represent the signal features, and we chose to combine GMM and SVMclassifiers to benefit from their generative and discriminative natures respectively. That is to exploit the similarity function of the RBF kernel to separate the GMM models representing normal and pathological voices. To further improve the separation, we used modified versions of the well known Kullback-leibler and Bhattacharyya distances. The modified distances, unlike the classical ones, do satisfy all metric axioms. As a result, we obtained an improvement of 2 % and 4 % in terms of sensitivity compared to using the classical Kullback-leibler and Bhattacharyya distances respectively. The Receiver Operating Curve (ROC) does illustrate the efficiency of the proposed method

Hand posture recognition using HOW and homogenous kernel

In this paper, we present a static hand gestures recognition system of Arabic Sign Language alphabets. The proposed method uses Histogram Of visual Words (HOW) descriptor and Support Vector Machine (SVM). First, the images of static hand gestures are converted into HOW features and grouped using k-means clustering to create histograms. Then they are converted from non linear space into linear space using Chi-squared kernel. The result is fed into One-vs-All SVM classifier to build signs models. Training and test stages of this technique are implemented on hand postures images using cluttered backgrounds for different lighting conditions, scales and rotations. The proposed method shows a satisfactory recognition rate and achieves good real-time performance regardless of the image resolution.Keywords: arabic sign language - static hand gesture – how - one-vs-all support vector machine (svm

Navigation pour robot avec garantie de sécurité basée sur la théorie de la viabilité

Guaranteeing safe, i.e. collision-free, motion for robotic systems is usually tackled in the InevitableCollision State framework. This paper explores the use of the more general Viability theory as analternative when safe motion involves multiple motion constraints and not just collision avoidance. Centralto Viability is the so-called viability kernel, i.e. the set of states of the robotic system for which there isat least one trajectory that satisfies the motion constraints forever. The paper presents an algorithm thatcomputes off-line an approximation of the viability kernel that is both conservative and able to handletime-varying constraints such as moving obstacles. Then it demonstrates, for different robotic scenarios involvingmultiple motion constraints (collision avoidance, visibility, velocity), how to use the viability kernelcomputed off-line within an on-line reactive navigation scheme that can drive the robotic system withoutever violating the motion constraints at hand.La garantie de mouvement sans collision pour les systèmes robotiques est généralement abordéedans le cadre des Etats de Collision Inévitable. Cet article explore l’utilisation de la théorie plusgénérale de la Viabilité comme alternative lorsque le mouvement implique des contraintes de mouvementautres que l’évitement de collision. Le noyau de viabilité, i.e. l’ensemble des états du systèmerobotique pour lequel il existe au moins une trajectoire qui satisfait à jamais les contraintes de mouvement,est un élément central de la théorie de la viabilité. Cet article présente un algorithme qui calculehors ligne une approximation du noyau de viabilité qui est à la fois conservative et capable de gérer descontraintes dynamiques telles que des obstacles mobiles. Ensuite, il démontre, pour différents scénariosrobotiques impliquant plusieurs contraintes de mouvement (évitement de collision, visibilité, vitesse),comment utiliser le noyau de viabilité calculé hors ligne dans un schéma de navigation réactive en lignecapable de piloter le système robotique sans jamais violer les différentes contraintes de mouvement

Station hybride (DSP/FPGA) pour un système rapide de reconnaissance automatique de la parole: Hybrid station (DSP/FPGA) for fast automatic speech recognition system

La reconnaissance automatique de la parole (RAP) a fait l’objet de plusieurs investigations depuis le début des années 50. La nature complexe de la parole oblige, l’auditeur humain à utiliser plusieurs niveaux de traitement pour ce domaine. Le 1er niveau est la détermination des caractéristiques du signal de la parole lui-même, c'est-à-dire l’analyse acoustique. Les niveaux phonétique, lexical et sémantique, etc. c’est dire combien chez l’être humain la reconnaissance et la compréhension de la parole sont fortement liées. Le but du présent travail est la réalisation d’un système embarqué (DSP/FPGA) pour le domaine de RAP fonctionnant en temps réel. Pour atteindre ce but, nous avons matérialisé quelques parties du système RAP implémenté sur DSP comme le filtre LMS et le coeur de la distance DTW (accélérateurs matériels) sur FPGA. Cette implantation nous permet d’accélérer le processus de la reconnaissance donc une augmentation considérable du dictionnaire de références. The automatic speech recognition (ASR) has been the subject of several research studies since the early 50s. And because of the complex nature of speech, human listener uses several levels of treatment for this domain. The first level is the determination of the speech signal characteristics itself, i.e the acoustic analysis. Then comes the phonetics, lexical and semantic levels,etc. This shows how human’s recognition and speech understanding are strongly related. The purpose of this work is to design an embedded ASR system based on (DSP/FPGA) functioning/operating in real time. To achieve this goal, we have materialized and implemented some parts of the ASR system on DSP and other parts such as the LMS filter and the core of the DTW distance (hardware accelerators) on FPGA, this hybrid implementation allows us to accelerate the process of automatic speech recognition, so it can be used on real time applications to help us reach a considerable increase amount of words in the reference dictionary