Controlling a remotely located Robot using Hand Gestures in real time: A DSP implementation

Telepresence is a necessity for present time as we can't reach everywhere and also it is useful in saving human life at dangerous places. A robot, which could be controlled from a distant location, can solve these problems. This could be via communication waves or networking methods. Also controlling should be in real time and smooth so that it can actuate on every minor signal in an effective way. This paper discusses a method to control a robot over the network from a distant location. The robot was controlled by hand gestures which were captured by the live camera. A DSP board TMS320DM642EVM was used to implement image pre-processing and fastening the whole system. PCA was used for gesture classification and robot actuation was done according to predefined procedures. Classification information was sent over the network in the experiment. This method is robust and could be used to control any kind of robot over distance

A Deep Learning Approach to Structured Signal Recovery

In this paper, we develop a new framework for sensing and recovering structured signals. In contrast to compressive sensing (CS) systems that employ linear measurements, sparse representations, and computationally complex convex/greedy algorithms, we introduce a deep learning framework that supports both linear and mildly nonlinear measurements, that learns a structured representation from training data, and that efficiently computes a signal estimate. In particular, we apply a stacked denoising autoencoder (SDA), as an unsupervised feature learner. SDA enables us to capture statistical dependencies between the different elements of certain signals and improve signal recovery performance as compared to the CS approach

Gravitational waves and electroweak baryogenesis in a global study of the extended scalar singlet model

We perform a global fit of the extended scalar singlet model with a fermionic dark matter (DM) candidate. Using the most up-to-date results from the $\mathit{Planck}$ measured DM relic density, direct detection limits from the XENON1T (2018) experiment, electroweak precision observables and Higgs searches at colliders, we constrain the 7-dimensional model parameter space. We also find regions in the model parameter space where a successful electroweak baryogenesis (EWBG) can be viable. This allows us to compute the gravitational wave (GW) signals arising from the phase transition, and discuss the potential discovery prospects of the model at current and future GW experiments. Our global fit places a strong upper $\mathit{and}$ lower limit on the second scalar mass, the fermion DM mass and the scalar-fermion DM coupling. In agreement with previous studies, we find that our model can simultaneously yield a strong first-order phase transition and saturate the observed DM abundance. More importantly, the GW spectra of viable points can often be within reach of future GW experiments such as LISA, DECIGO and BBO.Comment: 42 pages, 10 figures and 2 tables; v2: updated references, submitted to JHEP; v3: corrected typos and updated references, matches version published in JHE

Locality and Availability in Distributed Storage

This paper studies the problem of code symbol availability: a code symbol is said to have $(r, t)$-availability if it can be reconstructed from $t$ disjoint groups of other symbols, each of size at most $r$. For example, $3$-replication supports $(1, 2)$-availability as each symbol can be read from its $t= 2$ other (disjoint) replicas, i.e., $r=1$. However, the rate of replication must vanish like $\frac{1}{t+1}$ as the availability increases. This paper shows that it is possible to construct codes that can support a scaling number of parallel reads while keeping the rate to be an arbitrarily high constant. It further shows that this is possible with the minimum distance arbitrarily close to the Singleton bound. This paper also presents a bound demonstrating a trade-off between minimum distance, availability and locality. Our codes match the aforementioned bound and their construction relies on combinatorial objects called resolvable designs. From a practical standpoint, our codes seem useful for distributed storage applications involving hot data, i.e., the information which is frequently accessed by multiple processes in parallel.Comment: Submitted to ISIT 201

PDA Based Human Motion Recognition System

10.1142/S021819400500218XInternational Journal of Software Engineering and Knowledge Engineering152199-204ISEK

Prediction of the structural and electronic properties of MoxTi1−xS2 monolayers via first principle simulations

Two-dimensional transition metal dichalcogenides have gained great attention because of their peculiar physical properties that make them interesting for a wide range of applications. Lately, alloying between different transition metal dichalcogenides has been proposed as an approach to control two-dimensional phase stability and to obtain compounds with tailored characteristics. In this theoretical study, we predict the phase diagram and the electronic properties of MoxTi1−xS2 at varying stoichiometry and show how the material is metallic, when titanium is the predominant species, while it behaves as a p-doped semiconductor, when approaching pure MoS2 composition. Correspondingly, the thermodynamically most stable phase switches from the tetragonal to the hexagonal one. Further, we present an example which shows how the proposed alloys can be used to obtain new vertical two-dimensional heterostructures achieving effective electron/hole separation