Intelligent Biomedical Electrocardiogram Signal Processing for Cardiovascular Disease Diagnosis

Automatic biomedical signal recognition is an important process for several disease diagnoses. Particularly, Electrocardiogram (ECG) is commonly used to identify cardiovascular diseases. The professionals can determine the existence of cardiovascular diseases using the morphological patterns of the ECG signals. In order to raise the diagnostic accuracy and reduce the diagnostic time, automated computer aided diagnosis model is necessary. With the advancements of artificial intelligence (AI) techniques, large quantity of biomedical datasets can be easily examined for decision making. In this aspect, this paper presents an intelligent biomedical ECG signal processing (IBECG-SP) technique for CVD diagnosis. The proposed IBECG-SP technique examines the ECG signals for decision making. In addition, gated recurrent unit (GRU) model is used for the feature extraction of the ECG signals. Moreover, earthworm optimization (EWO) algorithm is utilized to optimally tune the hyperparameters of the GRU model. Lastly, softmax classifier is employed to allot appropriate class labels to the applied ECG signals. For examining the enhanced outcomes of the proposed IBECG-SP technique, an extensive simulation analysis take place on the PTB-XL database. The experimental results portrayed the supremacy of the IBECG-SP technique over the recent state of art techniques.     

Performance-Enhanced Bolometric Terahertz Detectors Based on V<Subscript>2</Subscript>O<Subscript>5</Subscript> for 15 to 30 THz

Terahertz (THz) radiation perception using uncooled detectors are gaining importance due to the increasing demands in the areas of military, space, and industrial, medical, and surveillance applications. In spite of the efforts of researchers to fill the THz gap, there exists a need for detectors in the range between 15 THz and 30 THz. In this paper, we discuss the development of bolometric detectors whose performance is enhanced by an optical immersion technique and their characterization in the aforesaid range of frequencies. These detectors are characterized by high specific detectivity (D*) of 1.28?×?10⁹ cmHz^1/2 W^?1 and high radiometric resolution (noise-equivalent temperature difference?=?26 mK) and are fast enough for bolometric detectors (time constant?=?1.7 ms), which make them suitable for spectroscopic and imaging applications.     

Mössbauer and XRD studies on the effect of doping iron in KCaY(PO4)2

The effect of doping iron at the yttrium site in hexagonal KCaY(PO₄)₂ is studied for various concentrations ofx (0≤x≤1), of iron using Mössbauer and X-ray diffraction methods. For low iron concentrations, very little changes in structure are seen but atx≈0·1, onset of new peaks in the XRD pattern is observed. The Mössbauer study of the doped samples reveals that iron has a solubility of up to 2·5% in the parent phase with any excess iron precipitating out to form a new and unknown phase. From a detailed analysis of the X-ray diffraction pattern (corresponding tox=1) of the latter phase, it is found that this phase is rhombohedral with the possible space groupR3.     

Synthesis of phenetidine-based telechelics and subsequent reactions with water-based curing reagents

The development of soluble telechelics based on aniline are highly desirable due to numerous applications that are possible, especially in the coatings and adhesive industry. Control of molecular length and ease of synthesis lends o-ethoxyaniline to be an ideal candidate for the synthesis of amino-terminated telechelic oligomers. Combined with the higher solubility and reactivity, curing of these functionally reactive oligomers has been accomplished using aqueous formaldehyde, as well as water-dispersed epoxy resins. Spectroscopic studies have been done to characterize the prepolymers, as well as the cured materials. © 1998 John Wiley & Sons, Inc. J Appl Polym Sci 67:1811–1817, 1998     

Java-MaC: A Run-Time Assurance Approach for Java Programs

We describe Java-MaC, a prototype implementation of the Monitoring and Checking (MaC) architecture for Java programs. The MaC architecture provides assurance that the target program is running correctly with respect to a formal requirements specification by monitoring and checking the execution of the target program at run-time. MaC bridges the gap between formal verification, which ensures the correctness of a design rather than an implementation, and testing, which does not provide formal guarantees about the correctness of the system.Use of formal requirement specifications in run-time monitoring and checking is the salient aspect of the MaC architecture. MaC is a lightweight formal method solution which works as a viable complement to the current heavyweight formal methods. In addition, analysis processes of the architecture including instrumentation of the target program, monitoring, and checking are performed fully automatically without human direction, which increases the accuracy of the analysis. Another important feature of the architecture is the clear separation between monitoring implementation-dependent low-level behaviors and checking high-level behaviors, which allows the reuse of a high-level requirement specification even when the target program implementation changes. Furthermore, this separation makes the architecture modular and allows the flexibility of incorporating third party tools into the architecture. The paper presents an overview of the MaC architecture and a prototype implementation Java-MaC.     

Localization of angiotensin AT1 receptors in the rat heart conduction system

We characterized angiotensin II receptor subtypes in the conduction system of the rat heart using quantitative autoradiography. In both the sinoatrial and atrioventricular nodes, binding could be totally displaced by losartan, and was insensitive to PD 123177, indicating that angiotensin II receptors in the conduction system of the rat heart belong to the AT1 subtype. Angiotensin AT1 receptors could play a direct role in the regulation of the heart chronotropic properties.     

Effect of stress and temperature on the creep and rupture behavior of a 1.25 Pct chromium—0.5 Pct molybdenum steel

The creep and stress rupture behavior of a normalized 1.25 pct chromium-0.5 pct molybdenum steel has been investigated over a temperature (T) range of 510 to 620°C and a stress(σ) range of 65 to 425 MN/m². The creep rate ( ) and time to rupture (t _r ) data have been analyzed in terms of the general expression ort _r -A σⁿ exp (Q/RT), whereA is a constant,n is the power exponent of stress,Q is an empirical activation energy for the rate controlling process andR is the universal gas constant. At each temperature, the logarithmic plots of creep rate and time to rupture as functions of stress consist of two linear segments, separating the data into low stress and high stress regimes. The stress exponent has approximate values of 4 and 10 in the low stress and high stress regimes respectively in the appropriate expressions for both creep rate and for time to rupture. The activation energy has values of 367 and 420 kJ/mole in the low stress regime for time to rupture and creep rate respectively. In the high stress regime, the respective values of activation energy are 581 and 670 kJ/mole. Fractographic observations show that the changes from low stress to high stress behavior in creep rate and time to rupture approximately coincide with the transition in fracture mode from intergranular to transgranular cracking as well as with the transition in the rupture ductility from a region of linear variation with stress to one of constant ductility. These observations suggest that the transition from low stress to high stress behavior may be associated with a change in deformation mode from predominantly grain boundary sliding at low stress to transgranular matrix deformation at high stress. Analysis of the creep rate data based on this premise enables calculation of the ratio of the contributions of the grain boundary sliding mode to the total deformation (ε _gb /ε _T ) at various values of stress and temperature. Results of this analysis are consistent with numerous experimental observations reported in the literature.     

Energy-Efficient Thermal-Aware Autonomic Management of Virtualized HPC Cloud Infrastructure

Virtualized datacenters and clouds are being increasingly considered for traditional High-Performance Computing (HPC) workloads that have typically targeted Grids and conventional HPC platforms. However, maximizing energy efficiency and utilization of datacenter resources, and minimizing undesired thermal behavior while ensuring application performance and other Quality of Service (QoS) guarantees for HPC applications requires careful consideration of important and extremely challenging tradeoffs. Virtual Machine (VM) migration is one of the most common techniques used to alleviate thermal anomalies (i.e., hotspots) in cloud datacenter servers as it reduces load and, hence, the server utilization. In this article, the benefits of using other techniques such as voltage scaling and pinning (traditionally used for reducing energy consumption) for thermal management over VM migrations are studied in detail. As no single technique is the most efficient to meet temperature/performance optimization goals in all situations, an autonomic approach that performs energy-efficient thermal management while ensuring the QoS delivered to the users is proposed. To address the problem of VM allocation that arises during VM migrations, an innovative application-centric energy-aware strategy for Virtual Machine (VM) allocation is proposed. The proposed strategy ensures high resource utilization and energy efficiency through VM consolidation while satisfying application QoS by exploiting knowledge obtained through application profiling along multiple dimensions (CPU, memory, and network bandwidth utilization). To support our arguments, we present the results obtained from an experimental evaluation on real hardware using HPC workloads under different scenarios.