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EMG is the recording of electrical activity of the muscles that can be used in diagnosing muscular diseases like myopathy and neuropathy and in generating control signals for operating artificial prosthetic arms and limbs. Various forms of artifacts get introduced into the EMG during the acquisition process that limits its proper analysis and characterization. This paper proposes a novel noise suppression method for EMG signals employing orthogonal Wave Atom Transform (WAT) followed by statistical modelling of wavelet coefficients by using a Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model with maximum a-posteriori (MAP) estimator for signal recovery from noisy EMG signals. The proposed algorithm was evaluated on signals taken from the standard Physionet ATM database that was manually corrupted by different levels of Additive White Gaussian Noise (AWGN) noise. The efficiency of the proposed algorithm is studied using the standard metrics namely, Signal to Noise Ratio (SNR) in dB, and Percent Root Mean Square Deviation (PRD). Results indicate that the hybrid denoising scheme was able to reduce noise from EMG signals more effectively quantified by average SNR of 22.98 dB and PRD of 0.00029, across different datasets, in comparison with the currently employed noise reduction algorithms. [ABSTRACT FROM AUTHOR]

Software-Defined Network (SDN) and Network Function Virtualization (NFV) are key enablers for provisioning dynamic, virtual security services on demand. This article, presents a novel Group Key Management scheme for Low-Resource Devices (GKM-LRD) with SDN aided trusted key management server as a central server to provide key management service to groups formed in Internet of Things (IoT) applications. In addition to the group key management scheme, a lightweight packet key-based communication system is proposed to make the data traffic reliable. Packet keys are short sized keys acquiring the lifetime of a packet. Even though the key is short sized, the security strength comes from its short lifetime. The proposed GKM-LRD is evaluated in terms of computation load, communication load, storage and scalability in comparison with the existing group key management schemes. The computation load, communication load and storage load is reduced by 80%, 17.25% and 20% respectively in comparison with the existing system assuring the scheme as lightweight and applicable for IoT devices. The proposed packet key-based communication scheme is compared with an existing Diffie-Hellman based packet key system. The results show the system is comparatively lightweight with computation load reduced by 74.8%. The security analysis of the proposed scheme proves that the scheme ensures forward secrecy, backward secrecy and resistance to man-in-the-middle and replay attacks. • Resistance to man-in-the-middle-attack, and replay attack in group communication. • Lightweight in terms of computation and communication cost. • Data traffic is made more reliable using packet keys using IoT. • The scheme is scalable with sustainable energy monitoring. [ABSTRACT FROM AUTHOR]

The vast majority of people in rural Andhra Pradesh depend on employment for their primary source of income. Therefore, success in terms of improving employment opportunities can lead to success in reducing poverty and raising living standards. Simply having access to employment is not enough. Labour force participation rates are generally high across the districts in the state of Andhra Pradesh and yet large numbers of employed people cannot lift their families out of poverty. Therefore, reducing poverty requires a joint emphasis on the quality and quantity of employment. The greater the employment focus, the more the effective economic growth in fighting poverty. However, economic growth alone cannot be counted on to generate significant improvement in the quality and quantity of employment opportunities. What is needed is an employment-centred approach to growth and development. The link between employment and living standards is straightforward. However, one has to be clear on what one means by employment in the context of rural Andhra Pradesh. Often labour market policy recommendations assume a wage employment relationship as the dominant framework for understanding the employment dynamics. Equilibrium earnings are determined by an interaction between the supply and demand for labour in a wage labour market. It is critical to understand the structure of employment in rural Andhra Pradesh if appropriate employment policies are to be formulated. [ABSTRACT FROM AUTHOR]

The amount of data and computing power has drastically increased over the last decade, which leads to the development of several new fronts in the field of Natural Language Processing (NLP). In addition to that, the entanglement of embeddings and large pre-trained models have pushed the field forward, covering a wide variety of tasks starting from machine translation to more complex tasks such as contextual text classification. This paper covers the underlying idea behind all embeddings and pre-trained models and provides an insight into fundamental strategies and implementation details of innovative embeddings. Further, it imparts the pros and cons of each specific embedding design and the associated impact on the result. It also comprehends the comparison of all the different strategies, datasets, architectures discussed in different papers with the help of standard metrics used in NLP. The content covered in this review work aims to shed light on different milestones reached in NLP, allowing the reader to deepen their understanding of NLP, which would motivate to explore the field further. [ABSTRACT FROM AUTHOR]

This study was conducted to measure the basal metabolic rate of athletes during three different phases of training; Transition (TP), Pre-competition (PP) and Competition (CP). Twelve national level male athletes, aged between 18 and 20 years were recruited. Anthropometry, body composition and BMR were measured. The quantification of training was done by time allocation pattern combined with measurements of oxygen consumption, heart rate and mechanical power output relationships in all three phases. The results showed an increase of 1.2 folds in training intensity and 2 folds in training duration from transition to competition phase of training. These training changes resulted in a 1.5 kg weight gain, 1.6 kg LBM gain and 9% increase in 24-hour BMR. There was also an increase in 1.5 Kcal/kg body weight (2.8 Kcal/M⊃ and 1.7 Kcal/kg LBM when expressed in terms of BMR) and 12 L/min in MVE Max from TP to CP of training. This study concludes that the BMR varies with the quantum of training and hence it must be measured periodically to identify energy needs. From the data of this study an attempt was made to provide phase wise prediction equations of BMR for athletes. [ABSTRACT FROM AUTHOR]

This study describes the changes in body composition profile and in turn the relationship to maximal work performance across three phases of athlete training. Ten national level male distance runners aged between 18 and 22 years from Sports Authority of Andhra Pradesh were studied during their transition (TP), Pre-competition (PP) and Competition (CP) phases of training. Body height, weight and circumferences were measured. Body composition was assessed by using skin-fold thickness at four sites. Physiological parameters such as VO2max (by means of indirect calorimetry) and maximal work performance (WRmax) were estimated from treadmill running using the Bruce protocol. Quantification of training was done by the Time Allocation Pattern (TAP) and heart rate-work rate relationships. The results indicated a significant (P<0.001) increase in Lean Body mass (LBM) by 4.7%, VO2max (18%) and maximal work performance (WRmax) by 37% from TP to CP. The change in training during this phase transition was 1.6 fold for intensity and 2 fold for duration. In addition, there were high significant correlations between LBM and VO2max, and WRmax and VO2max. Thus, this study suggests that the body composition is an important component in training-induced adaptations, and may influence various physiological parameters resulting in an enhanced maximal work performance. [ABSTRACT FROM AUTHOR]