Effect of bandwidth modifications on the quality of speech imitated by Alexandrine and Indian Ringneck parrots

Alexandrine and Indian Ringneck parrots are known for imitating the voice of other animals. The objective of this paper is to estimate the spectral limits of the imitated sounds produced by parrots and quantify the quality. The investigations showed that 500–3000 Hz spectral band is adequate for retaining the important perceptual information in the phrases uttered by human speakers and imitated by parrots. Investigations confirmed that the Indian Ringneck parrots are capable of following the formant structure and pitch contour of the phrases uttered by the human subjects. The dynamic range of the pitch of Indian Ringneck parrots was observed as higher than that of the human subjects. A rise of about 1000 Hz in the formant F1 of the parrots was observed, indicating the tongue height small and beak opening, relatively large, as compared to that of human subjects. The quality of some of the synthesized and processed phrases was found slightly better as compared to that of the original phrases because of the inherent enhancement capability of the Harmonic plus noise model (HNM). The average Mean opinion score (MOS) score of the Indian Ringnech parrots for the original, synthesized, and processed phrases was observed as 2.65, 2.59, and 2.77, respectively. The investigations may be beneficial for studying the behavior of endangered birds, defense related activities, safeguarding the crashes with aero planes, and safeguard of the birds from wind power generator etc.     

Nanoindentation and Wear Characteristics of Al 5083/SiC_p Nanocomposites Synthesized by High Energy Ball Milling and Spark Plasma Sintering

Al 5083/10 wt% SiC p nano composites have been synthesized by means of high energy ball milling followed by spark plasma sintering (SPS). Nano composites produced via this method exhibited near-theoretical density while retaining the nano-grained features. X-ray diffraction (XRD) analysis indicated that the crystalline size of the ball milled Al 5083 matrix was observed to be ～25 nm and it was coarsened up to ～30 nm after SPS. Nano indentation results of nano composites demonstrated a high hardness of ～280 HV with an elastic modulus of 126 GPa. Wear and friction characteristics with addition of SiC p reinforcement exhibited significant improvement in terms of coefficient of friction and specific wear rate to that of nano structured Al 5083 alloy. The reduction in specific wear rate in the nanocomposite was mainly due to the change of wear mechanism from adhesive to abrasive wear with the addition of SiC p which resulted in high hardness associated with nano-grained microstructure.     

Implication of molecular orientation on charge transport and gas sensing characteristics of cobalt–phthalocyanine thin films

Charge transport and gas sensing characteristics of cobalt phthalocyanine films deposited along (ATB) and perpendicular (PTB) to the natural twin boundaries of (0 0 1) LaAlO₃ substrate have been investigated. The charge carrier mobility of ATB films (∼5 cm² V⁻¹ s⁻¹) is five orders of magnitude higher compared to that of PTB films (∼7 × 10⁻⁵ cm² V⁻¹ s⁻¹), suggesting that twin boundaries acts like a template for ordering of molecules. The ATB films on exposure to ammonia showed a reversible increase of resistance, with fast response and recovery. In contrast PTB films showed same sensitivity, but exhibits base resistance drift along with sluggish response.     

Enhancing the efficiency of alternating current driven organic light-emitting devices by optimizing the operation frequency

We report efficient and bright organic light-emitting devices operated by capacitive energy coupling. In this approach, the organic layers are enclosed between sputter-deposited hafnium dioxide layers to prevent charge carrier injection. When a sinusoidal voltage signal is applied to the electrodes, the devices emit bright green light whereas no detectable emission is generated upon application of a constant voltage. The efficiency of the process depends heavily on the frequency of the applied voltage signal. By optimizing the driving scheme, a record luminous efficacy for AC driven OLEDs of 2.7 lm/W at 500 cd/m² is achieved.     

Oxime-Modified Aluminum(III) Isopropoxide: A Promising Sol–Gel Precursor for Corrosion Resistive Nano-Alumina Coating on an Aluminum Alloy

Protection of Metals and Physical Chemistry of Surfaces - Dense alumina coatings were fabricated over aluminum alloy via dip coating method using oxime-modified aluminum(III) isopropoxide as a...     

CAMP: cluster aided multi-path routing protocol for wireless sensor networks

Wireless Networks - In this article, we propose a novel routing algorithm for wireless sensor network, which achieves uniform energy depletion across all the nodes and thus leading to prolonged...     

A multilevel hybrid anomaly detection scheme for industrial wireless sensor networks

Real-time sensing plays an important role in ensuring the reliability of industrial wireless sensor networks (IWSNs). Sensor nodes in IWSNs have inherent limitations that give rise to different anomalies in the network. These anomalies can lead to disastrous and harmful situations or even serious system failures. This article presents a formulation to the design of an anomaly detection scheme for detecting the anomalous node along with the type of anomaly. The proposed scheme is divided into two major parts. First, spatiotemporal correlation within a cluster is obtained for the normal and anomalous behavior of sensor nodes. Second, the multilevel hybrid classifier is used by combining the sequential minimal optimization support vector machine (SMO-SVM) as a binary classifier with optimally pruned extreme learning machine (OP-ELM) as a multiclass classifier for detection of an anomalous node and type of anomalies, respectively. Mahalanobis distance-based lightweight K-Medoid clustering is used to build a new set of training datasets that represents the original training dataset, by significantly reducing the training time of a multilevel hybrid classifier. Results are analyzed using standard WSN datasets. The proposed model shows high accuracy, i.e., 94.79% and detection rate, i.e., 94.6% with a reduced false positive rate as compared to existing hybrid methods.