Voice Activity Detection (VAD) is considered as an important pre-processing step in speech processing systems such as speech enhancement, speech recognition, gender and age identification. VAD helps in reducing the time required to process speech data and to improve final system accuracy by focusing the work on the voiced part of the speech. An automatic technique for VAD using Fuzzy-Neuro technique (FN-AVAD) is presented in this paper. The aim of this work is to alleviate the problem of choosing the best threshold value in traditional VAD methods and achieves automaticity by combining fuzzy clustering and machine learning techniques. Four features are extracted from each speech segment, which are short term energy, zero-crossing rate, autocorrelation, and log energy. A modified version of fuzzy C-Means is then used to cluster speech segments into three clusters; two clusters for voice and one for unvoiced. After that, three feed forward neural networks are trained to adjust their weights, in which each network represents one cluster. To make the final decision regarding the class type of a given speech segment, the membership degrees of this segment in all clusters along with neural networks' decisions are given to a defuzzification step which finally gives the class type of that segment. The proposed FN-AVAD is tested on the public multimodal emotion database, Surrey AudioVisual Expressed Emotion (SAVEE), and the error rate was 2.08%. The achieved results are comparable to the results achieved by the current published works in the literature.
In present work, new tetra-dentate ligand, titled 3,5-bis ((E)-5-Bromo-2-hydroxy benzylidene amino) benzoic acid (H3L), was prepared via an acid-catalyzed condensation process. New four metallic ligand complexes with Co(II), Ni(II), Cu(II) and Zn(II) ions, were also prepared from the refluxing of equivalent moles. Ligand's structure and its complexes; were confirmed by numerous characterization methods, including Ultraviolet-Visible, Infrared, Mass Spectrometer, 1H and 13C Nuclear Magnetic Resonance spectra, atomic absorption, magnetic moments, and molar conductivity measurements. The results of the spectroscopic analyzes proved that the prepared ligand acts as tetradentate bi-ionic ligand and it was bond
... Show MoreA group of derivatives for compounds 2-Amino-3-carboxy-4,5,6,7-tetra hydrobenz -othiophene bearing different heterocyclic moieties such as Schiff bases. B-Lactum, 4-thiazolidinone.1,3-oxazepan. The newly synthesized derivatives have been supported by spectral data FT-IR, H1-NMR. All the synthesized compounds were screened for their antimicrobial activities against gram-positive and gram-negative bacteria as reference.
There is a great risk of cardiovascular disease (CVD) and vascular thrombosis in patients with End-Stage Renal Disease (ESRD). These patients exhibit numerous abnormalities in coagulation, fibrinolytic, inhibitory protein abnormalities in multiple levels. The study aimed to assess hypercoagulable changes by measuring the levels of antithrombin, plasma fibrinogen and FXII activity in patients with ESRD, and to find their correlation with Hemoglobin (Hb) level, WBC count, reticulocyte percentage and platelet count. This study was conducted at Al-Hayat center, Al Karama Teaching Hospital on 50 ESRD patients aged < 60 years of both genders. In addition, 20 apparently healthy individuals were included as a control group. The mean Hb level, total
... Show MoreSchiff base (methyl 6-(2- (4-hydroxyphenyl) -2- (1-phenyl ethyl ideneamino) acetamido) -3, 3-dimethyl-7-oxo-4-thia-1-azabicyclo[3.2.0] heptane-2-carboxylate)Co(II), Ni(II), Cu (II), Zn (II), and Hg(II)] ions were employed to make certain complexes. Metal analysis M percent, elemental chemical analysis (C.H.N.S), and other standard physico-chemical methods were used. Magnetic susceptibility, conductometric measurements, FT-IR and UV-visible Spectra were used to identified. Theoretical treatment of the generated complexes in the gas phase was performed using the (hyperchem-8.07) program for molecular mechanics and semi-empirical computations. The (PM3) approach was used to determine the heat of formation (ΔH˚f), binding energy (ΔEb), an
... Show MoreThis study was carried out to evaluate the antioxidant activity of Iraqi sumac seeds (Rhus coriaria. L) (Anacardiaceae). Total phenolic compounds and flavoniods were determined in three different sumac seed extracts (SSE) (aqueous,ethanolic and methanolic extract). For extraction Antioxidant activity of SSE were evaluated by various antioxidant assays, including total antioxidant capacity, reducing power,by using 1,1-diphenyl-2-picryl hydrazyl (DPPH) radical scavenging, nitric oxide scavenging, Hydroxyl radical scavenging, and metal ion chelating activities. These various antioxidant activities were compared with ascorbic acid as a standard antioxidant.The results showed that the three(SSE), contained large amounts of phenolic and flavonio
... Show MoreBackground/Objectives: The purpose of this study was to classify Alzheimer’s disease (AD) patients from Normal Control (NC) patients using Magnetic Resonance Imaging (MRI). Methods/Statistical analysis: The performance evolution is carried out for 346 MR images from Alzheimer's Neuroimaging Initiative (ADNI) dataset. The classifier Deep Belief Network (DBN) is used for the function of classification. The network is trained using a sample training set, and the weights produced are then used to check the system's recognition capability. Findings: As a result, this paper presented a novel method of automated classification system for AD determination. The suggested method offers good performance of the experiments carried out show that the
... Show MoreImitation learning is an effective method for training an autonomous agent to accomplish a task by imitating expert behaviors in their demonstrations. However, traditional imitation learning methods require a large number of expert demonstrations in order to learn a complex behavior. Such a disadvantage has limited the potential of imitation learning in complex tasks where the expert demonstrations are not sufficient. In order to address the problem, we propose a Generative Adversarial Network-based model which is designed to learn optimal policies using only a single demonstration. The proposed model is evaluated on two simulated tasks in comparison with other methods. The results show that our proposed model is capable of completing co
... Show MoreThis paper examines the change in planning pattern In Lebanon, which relies on vehicles as a semi-single mode of transport, and directing it towards re-shaping the city and introducing concepts of "smooth or flexible" mobility in its schemes; the concept of a "compact city" with an infrastructure based on a flexible mobility culture. Taking into consideration environmental, economical and health risks of the existing model, the paper focuses on the four foundations of the concepts of "city based on culture flexible mobility, "and provides a SWOT analysis to encourage for a shift in the planning methodology.
Mobile ad-hoc networks (MANETs) are composed of mobile nodes communicating through wireless medium, without any fixed centralized infrastructure. Providing quality of service (QoS) support to multimedia streaming applications over MANETs is vital. This paper focuses on QoS support, provided by the stream control transmission protocol (SCTP) and the TCP-friendly rate control (TFRC) protocol to multimedia streaming applications over MANETs. In this study, three QoS parameters were considered jointly: (1) packet delivery ratio (PDR), (2) end-to-end delay, (3) and throughput. Specifically, the authors analyzed and compared the simulated performance of the SCTP and TFRC transport protocols for delivering multimedia streaming over MANETs.
... Show More This paper describes the application of consensus optimization for Wireless Sensor Network (WSN) system. Consensus algorithm is usually conducted within a certain number of iterations for a given graph topology. Nevertheless, the best Number of Iterations (NOI) to reach consensus is varied in accordance with any change in number of nodes or other parameters of . graph topology. As a result, a time consuming trial and error procedure will necessary be applied
to obtain best NOI. The implementation of an intellig ent optimization can effectively help to get the optimal NOI. The performance of the consensus algorithm has considerably been improved by the inclusion of Particle Swarm Optimization (PSO). As a case s