Trends in Cardiac Pacemaker Batteries

Batteries used in Implantable cardiac pacemakers-present unique challenges to their developers and manufacturers in terms of high levels of safety and reliability. In addition, the batteries must have longevity to avoid frequent replacements. Technological advances in leads/electrodes have reduced energy requirements by two orders of magnitude. Micro-electronics advances sharply reduce internal current drain concurrently decreasing size and increasing functionality, reliability, and longevity. It is reported that about 600,000 pacemakers are implanted each year worldwide and the total number of people with various types of implanted pacemaker has already crossed 3 million. A cardiac pacemaker uses half of its battery power for cardiac stimulation and the other half for housekeeping tasks such as monitoring and data logging. The first implanted cardiac pacemaker used nickel-cadmium rechargeable battery, later on zinc-mercury battery was developed and used which lasted for over 2 years. Lithium iodine battery invented and used by Wilson Greatbatch and his team in 1972 made the real impact to implantable cardiac pacemakers. This battery lasts for about 10 years and even today is the power source for many manufacturers of cardiac pacemakers. This paper briefly reviews various developments of battery technologies since the inception of cardiac pacemaker and presents the alternative to lithium iodine battery for the near future

Semi-supervised and Active-learning Scenarios: Efficient Acoustic Model Refinement for a Low Resource Indian Language

We address the problem of efficient acoustic-model refinement (continuous retraining) using semi-supervised and active learning for a low resource Indian language, wherein the low resource constraints are having i) a small labeled corpus from which to train a baseline `seed' acoustic model and ii) a large training corpus without orthographic labeling or from which to perform a data selection for manual labeling at low costs. The proposed semi-supervised learning decodes the unlabeled large training corpus using the seed model and through various protocols, selects the decoded utterances with high reliability using confidence levels (that correlate to the WER of the decoded utterances) and iterative bootstrapping. The proposed active learning protocol uses confidence level based metric to select the decoded utterances from the large unlabeled corpus for further labeling. The semi-supervised learning protocols can offer a WER reduction, from a poorly trained seed model, by as much as 50% of the best WER-reduction realizable from the seed model's WER, if the large corpus were labeled and used for acoustic-model training. The active learning protocols allow that only 60% of the entire training corpus be manually labeled, to reach the same performance as the entire data

Non-Destructive Evaluation—A Pivotal Technology for Qualification of Composite Aircraft Structures

Tremendous advances in composite materials and a deeper understanding of their behavior have been responsible for the increased use of composites in the development of advanced, new generation civil and military aircraft. Composites play an important role in any aircraft development programme and are strong contenders to their metal counterparts due to their significant contributions towards improving strength, stiffness, fatigue properties & weight reduction. As materials, structural design & processing have evolved, strong emphasis is placed on effective & reliable damage detection, durability and damage tolerance. As a consequence, Non-destructive Evaluation (NDE) has also undergone significant advances towards meeting the growing demands of quality assurance. Advanced Composites Division (ACD) of National Aerospace Laboratories (NAL), has been involved in the development of composite structures for both civil and military aircraft for over a decade and a half. Innovative composite processing methods like co-curing/co-bonding have been successfully employed to realize airworthy structures. The role of NDE in the development of these structures has been critical and not limited to damage detection alone. On several occasions, NDE has provided valuable inputs towards improving design and process parameters. In-spite of the complexity of the structures, stringent quality requirements and tight delivery schedules, NDE has been successful in certifying these composite structures for airworthiness. This paper discusses the implementation of key NDE techniques like ultrasonics, radiography, acoustic emission and thermography for reliable flaw detection, characterization and quality assurance of composite aircraft structures

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DESIGN OF AN ERROR DETECTION AND DATA RECOVERY ARCHITECTURE FOR MOTION ESTIMATION TESTING APPLICATIONS

Motion estimation (ME) in a video coding system is the critical role, so testing such a module is of priority concern. While focusing on the testing of ME in a video coding system, this work presents an error detection and data recovery (EDDR) design based on residue -and- quotient (RQ) code. An error in processing elements (PEs) can be detected and recovered effectively by using the proposed EDDR design. Importantly, the proposed EDDR design performs satisfactorily in terms of throughput and reliability for motion estimation (ME) testing applications