Dispersed beamforming approach for secure communication in UDN

Wireless communication systems are prone to many security breaches due to open nature of the medium and exponential a rise in subscribers. Hence, physical layer security (PLS) has emerged as one of the dominant low complexity alternatives to overcome the impact of eavesdropping by managing the physical characteristics of the medium. In this paper, we ensure PLS to moving users which tends to experience rise in handover, as a result of proximity between users and base station. This study is based on ultra-dense network (UDN). To tackle this challenge, novel secure beamforming named as beam broadening and beam merging have been proposed. Besides, we propose a synchronization approach called synchronized mobility clustering for UDN to reduce the overheads generated due to the exchange of information about moving users. More specifically, we derive an analytical expression for secrecy outage probability—an important security metric. The effect of proposed approaches have been validated through numerical results and the results show the effectiveness of the proposed approaches against eavesdropping. Finally, the performance of the proposed scheme is evaluated and compared with the conventional beamforming approach. However, this proposed approach works well for a varied density of users and location to be targeted.

     

Simulation Techniques in Electromyography

A motor unit action potential (MUAP) recorded in clinical electromyography (EMG) is the spatial and temporal summation of the action potentials (AP's) from all muscle fibers in a motor unit (MU). An important determinant of MUAP waveform characteristics is the size of the recording electrode. In this paper, we have described the use of a modified line source model of single muscle fiber action potentials to simulate MUAP's as recorded by single fiber (SF) EMG, concentric needle (CN) EMG, and macro-EMG electrodes. Results indicate that SFEMG recordings from a normal MU contain mainly the AP's of the closest one to three muscle fibers of the MU. The amplitude, area, and duration of the simulated CNEMG MUAP's are determined mainly by the number and size of muscle fibers within a semicircular territory of 0.5, 1.5, and 2.5 mm, respectively, around the tip of the electrode. The amplitude and area of simulated macro-EMG MUAP's increase with the number of muscle fibers in the MU.     

A selected-area CVD method for deposition of sensing films onmonolithically integrated gas detectors

A novel method for deposition of thin transducing films on geometrically well-defined areas is reported. The films represent the front-end of monolithically integrated microelectronic gas detectors. These devices contain a 1 μm thick dielectric window equipped with four-point probe electrodes and a boron-diffused silicon heater underneath the window. The central region of the window can be instantaneously switched from room temperature to several hundred °C while maintaining excellent thermal uniformity within a 350×350 μm area. Thermally activated CVD of Pt is realized on the heated region by raising the temperature of the central region into the regime of thermal decomposition of Pt precursors such as Pt(PF₃)₄. The growth of thin Pt films is monitored in situ by measuring film resistance, and film growth is terminated once desired film resistance values are reached by cutting off the heater current. This allows to optimize film properties for gas sensing applications. The deposited films are characterized ex situ by optical microscopy and scanning electron microscopy to correlate film morphology with resistance. This method can be easily extended to deposition of other films of interest such as TiO₂     

An Efficient Variant of Fully-Convolutional Network for Segmenting Lung Fields from Chest Radiographs

Wireless Personal Communications - Automatic analysis of chest radiographs using computer-aided diagnosis (CAD) systems is pivotal to perform mass screening and detect early signs of various...     

Green IoT: A Short Survey on Technical Evolution & Techniques

The Internet of Things (IoT) embodies the confluence of the virtual & physical world. IoT will play an important role in managing the managing depleting resource such as water, fuel, food, etc. However, to realize these applications enormous IoT devices will communicate with each other. This massive connectivity will directly or indirectly aid in Green House Gas emissions. Hence, to admissibly reduce this environmental impact of IoT, it must be greened in terms of energy consumption. Green IoT will reduce environmental exploitation by slashing carbon emission effectively and thus will help in achieving sustainability of the planet. This paper describes the journey of IoT to Green IoT. Along with this, the survey on recent Green-IoT techniques that will effectively help in reducing required energy consumption is presented. Along with this ability of unmanned aerial vehicle (UAV) technology to provide Green IoT and survey on recent energy-efficient UAV assisted communication is presented. In addition to this, a dual battery enabled Unmanned Aerial vehicle base station, an energy-efficient clustering algorithm, has also been proposed to prolong the battery life.

     

Analysis and modelling the effects of mobility,Churn rate,node’s life span,intermittent bandwidth and stabilization cost of finger table in structured mobile P2P networks

Today P2P (Peer-to-Peer) networks are gaining popularity for sharing the contents. Due to massive spreading of Internet, these networks are also growing fast. MP2P (Mobile P2P) networks are attracting many users due to increase in the Internet-based mobile applications. These networks suffer from many challenges which are not considered for analysis and modelling adequately. We focus on few challenges like mobility of users, churn rate, intermittent bandwidth, shorter life span of mobile nodes, stabilization of finger table, etc. in this paper. We analytically analyse these challenges and define the effects of different parameters over the performance. Traditional P2P protocols are designed for wired networks and when these are implemented for mobile networks then mobility effect of users adds more challenge for researchers. We select two types of mobility models namely FF (Fluid Flow) and RWP (Random Waypoint) models to model the users’ mobility. The churn rate of the mobile nodes makes network overlay management and content searching more difficult in MP2P networks. We select finger table-based protocols which are widely deployed in the P2P networks. But these protocols can’t perform well in the mobile P2P networks due to mobility of the users. The mobility of the users and churn rate of the mobile nodes create failure in lookup of finger table and induce more cost to update the finger table. We consider these challenges and quantify the failure rate of mobile nodes, life span of mobile nodes, available bandwidth, cost of stabilization of finger table per node, etc. in this proposal. The proposed model is useful for modelling the performance of MP2P networks performance in various wireless environments like Mobile Ad hoc Networks (MANETs), Wireless Mesh Networks (WMNs), Wireless Sensor Networks (WSNs), Vehicular Ad hoc Networks (VANETs), Wireless LAN (WLAN), Wireless MAN (WMAN), etc.

     

A Novel Ensemble Method for PTB Classification in CXRs

Pulmonary tuberculosis (PTB) is a contagious disease that affects the lung region. PTB is a life-threatening disease if it is detected late or left untreated. To perform the initial screening of PTB, the World Health Organization has recommended chest radiograph. Till now, the screening process requires either the patients to come to secondary health centers from rural areas or the radiologists to go the remote locations. This process is rejuvenated with the introduction of computer-aided diagnosis (CAD) systems. CAD systems reduce the need for expert radiologists in the screening process. However, the development and deployment are still in the early phases as new methods are being developed to improve the performance of CAD systems in terms of accuracy, specificity and sensitivity. In this study, a deep learning-based PTB classification system has been presented that achieves the state-of-the-art performance for TB classification. Firstly, a proposed architecture based on the blocks is presented and then it is used to create an ensemble. In the proposed ensemble, two standard architectures namely AlexNet, and ResNet have also been used in addition to the proposed architecture. All the architectures are trained and evaluated on a combined dataset formed using publicly available standard datasets. The proposed ensemble attains the accuracy of 90.00% and area under the curve equal to 0.96, which is better than the performance of the existing methods.

     

Impact of Megha-Tropiques SAPHIR radiances in T574L64 global data assimilation and forecasting system at NCMRWF

The Sounder for Probing Vertical Profiles of Humidity (SAPHIR) is a sounding instrument of Megha-Tropiques (Indo-French joint satellite); launched by the Indian Space Research Organization on 12 October 2011 with six channels near the absorption band of water vapour at 183 GHz. In the framework of this work, the assimilation scheme has been first modified to enable the SAPHIR radiance observations being used as additional observation type, and second, a methodology has been prepared to remove the radiance pixels significantly affected by clouds. The impact of SAPHIR radiances on analysis as well as forecasts of the National Centre for Medium Range Weather Forecasting-Global Forecast System (NGFS) at T574L64 resolution has been investigated through data assimilation. Measurements from SAPHIR are incorporated into the Gridpoint Statistical Interpolation three-dimensional variational assimilation system to provide the improved initial conditions. To find out the impact, analysis/forecast cycling experiments with and without SAPHIR radiances are performed during the period 10–29 November 2013. The impact of the improvement in term of root mean square error has been clearly evaluated for five parameters, namely, relative humidity, temperature, wind, geopotential height, and specific humidity. It is demonstrated that the assimilation of SAPHIR observations results in a considerable improvement for the five parameters over the global region. During the study period, two tropical cyclones (HELEN, 19–22 November and LEHAR, 23–28 November) were formed over the North Indian Ocean. Impact on specific humidity and track forecast errors of tropical cyclone are also examined. Overall, initial results show the usefulness of SAPHIR radiances in the NGFS.     

What about Privacy of My OSN Data?

In the arena of internet of things, everyone has the ability to share every aspect of their lives with other people. Social media is the most popular and effective medium to provide communication. Social media has gripped our lives in a dramatic way. Privacy of users data lying with the service providers needs to be preserved when published for the purpose of research as the release of sensitive personal information of an individual may pose security threats. This has become an important research area nowadays. To some extent, the concepts of anonymization that were earlier used to preserve privacy of relational microdata have been applied to preserve privacy of social networks data. Anonymizing social networks data is challenging as it is a complex structure with users connected to one another graphically and the most important is to preserve the structural properties of the graph depicting the social network relationships while applying such concepts. Recent studies based upon K-anonymity and L-diversity help to preserve privacy of online social networks data and subsequently identify attacks that arise while applying these techniques in different scenarios. K-anonymity equalizes the degree of the nodes to prevent the data from identity disclosure but it cannot preserve sensitive information and also cannot handle attacks arising due to background knowledge and homogeneity. To cope up with the drawbacks of K anonymity, L-diversity was introduced that protects the sensitive labels of the users. In this paper, a novel technique has been proposed which implements the combined features of K-anonymity and L-diversity. Our proposed approach has been validated using the data of real time social network–Twitter (most popular microblogging network). The performance of the proposed technique has been measured by the metrics, such as average path length, average change in sensitive labels, and remaining ratio of top influential users. It thus becomes evident from the results that the values of these parameters attained with the proposed technique for the anonymized graph has minimal variation to that of original structural graph. So, it is possible to retain the utility without compromising privacy while publishing social networks data. Further, the performance of the proposed technique has been discussed by calculating the information loss that addresses the concern of preserving privacy with the least variation of actual content viz info loss.     

Wide range-low jitter PLL design for serializer

The paper presents the wide range phase-locked loop design for serializer. Serializer converts the 16 bit parallel data into serial, thus 16 times fast clock is required to synchronize the parallel data and serial data. PLL generates 16× serial clock from the parallel clock by frequency multiplication. PLL is simulated with 0.18 µm CMOS process. Major challenge of PLL design is to achieve large dynamic range. The PLL design for large dynamic range suffers from a high jitter at lower frequency and linearity issues. Advance CSVCO has been simulated with source degeneration technique and achieve wide linear range from 14 MHz to 1.05 GHz with 99.2 % linearity. The PVT Corners simulation shows 16 MHz to 1.04 GHz output range. Average power dissipation of the proposed PLL design is 2.7 mW. Worst case Peak to peak period jitter is 13.4 ps and rms jitter is 2.6 ps for 800 MHz output frequency.