arXiv subjects

Amit Kumar

Publications and source records attributed to Amit Kumar.

At least 253 records · Page 14Linked to original sources

arXiv2016

In-orbit Performance of UVIT on ASTROSAT

We present the in-orbit performance and the first results from the ultra-violet Imaging telescope (UVIT) on ASTROSAT. UVIT consists of two identical 38cm coaligned telescopes, one for the FUV channel (130-180nm) and the other for the NUV (200-300nm) and VIS (320-550nm) channels, with a field of view of 28 $arcmin$. The FUV and the NUV detectors are operated in the high gain photon counting mode whereas the VIS detector is operated in the low gain integration mode. The FUV and NUV channels have filters and gratings, whereas the VIS channel has filters. The ASTROSAT was launched on 28th September 2015. The performance verification of UVIT was carried out after the opening of the UVIT doors on 30th November 2015, till the end of March 2016 within the allotted time of 50 days for calibration. All the on-board systems were found to be working satisfactorily. During the PV phase, the UVIT observed several calibration sources to characterise the instrument and a few objects to demonstrate the capability of the UVIT. The resolution of the UVIT was found to be about 1.4 - 1.7 $arcsec$ in the FUV and NUV. The sensitivity in various filters were calibrated using standard stars (white dwarfs), to estimate the zero-point magnitudes as well as the flux conversion factor. The gratings were also calibrated to estimate their resolution as well as effective area. The sensitivity of the filters were found to be reduced up to 15\% with respect to the ground calibrations. The sensitivity variation is monitored on a monthly basis. UVIT is all set to roll out science results with its imaging capability with good resolution and large field of view, capability to sample the UV spectral region using different filters and capability to perform variability studies in the UV.

astro-ph.IM↗

arXiv2016

Long-range and short-range magnetic correlations, and microscopic origin of net magnetization in the spin-1 trimer chain compound CaNi3P4O14

Spin-spin correlations and microscopic origin of net magnetization in the spin-1 trimer chain compound CaNi3P4O14 have been investigated by powder neutron diffraction. The present study reveals a 3D long-range magnetic ordering below 16 K where the magnetic structure consists of ferromagnetic trimers that are coupled ferromagnetically along the spin-chain. The moment components along the a and c axes arrange antiferromagnetically. Our study establishes that the uncompensated moment components along the b axis result in a net magnetization per unit cell. The magnetic structure, determined in the present study, is in agreement with the results of recent first principles calculation; however, it is in contrast to a fascinating experimental prediction of ferrimagnetic ordering based on the periodicity of the exchange interactions in CaNi3P4O14. Our study also confirms the presence of broad diffuse magnetic scattering, due to 1D short-range spin-spin correlations, over a wide temperature range below ~50 K down to a temperature well below the Tc. Total neutron scattering analysis by the RMC method reveals that the dominating spin-spin correlation above Tc is ferromagnetic and along the b axis. The nearest neighbour spin-spin correlations along the a and c axes are found to be weakly antiferromagnetic. The nature of the trimer spin structure of the short-range state is similar to that of the 3D long-range ordered state. The present investigation of microscopic nature of the magnetic ground state also explains the condition required for the 1/3 magnetization plateau to be observed in the trimer spin-chains. In spite of the S=1 trimer chain system, the present compound CaNi3P4O14 is found to be a good realization of 3D magnet below the Tc=16 K with full ordered moment values of ~2 mu_B/Ni2+ (1.98 and 1.96 mu_B/Ni2+ for two Ni sites, respectively) at 1.5 K.

cond-mat.str-el↗

arXiv2016

Phase separated behavior in Yttrium doped CaMnO3

The effect of electron doping on the structural, transport, and magnetic properties of Mn (IV) - rich Ca1-xYxMnO3 (x < 0.2) samples have been investigated using neutron diffraction, neutron depolarization, magnetization and resistivity techniques. The temperature dependence of resistivity follows the small polaron model and the activation energy exhibits a minimum for x=0.1 sample. A phase separated magnetic ground state consisting of ferromagnetic domains (~7microns) embedded in G-type antiferromagnetic matrix is observed in the sample, x = 0.1. The transition to the long range magnetically ordered state in this sample is preceded by a Griffiths phase. On lowering temperature below 300K a structural transition from orthorhombic structure (Pnma) to a monoclinic structure (P21/m) is observed in the case of x=0.2 sample. The ferromagnetic behavior in this case is suppressed and the antiferromagnetic ordering is described by coexisting C-type and G-type magnetic structures corresponding to the monoclinic and orthorhombic phases, respectively.<

cond-mat.mtrl-sci↗

arXiv2016

Head Pose Estimation of Occluded Faces using Regularized Regression

This paper presents regression methods for estimation of head pose from occluded 2-D face images. The process primarily involves reconstructing a face from its occluded image, followed by classification. Typical methods for reconstruction assume that the pixel errors of the occluded regions are independent. However, such an assumption is not true in the case of occlusion, because of its inherent contiguous nature. Hence, we use nuclear norm as a metric that can describe well the structure of the error. We also use LASSO Regression based l1 - regularization to improve reconstruction. Next, we implement Nuclear Norm Regularized Regression (NR), and also our proposed method, for reconstruction and subsequent classification. Finally, we compare the performance of the methods in terms of accuracy of head pose estimation of occluded faces.

cs.CV↗

arXiv2016

Face Alignment by Local Deep Descriptor Regression

We present an algorithm for extracting key-point descriptors using deep convolutional neural networks (CNN). Unlike many existing deep CNNs, our model computes local features around a given point in an image. We also present a face alignment algorithm based on regression using these local descriptors. The proposed method called Local Deep Descriptor Regression (LDDR) is able to localize face landmarks of varying sizes, poses and occlusions with high accuracy. Deep Descriptors presented in this paper are able to uniquely and efficiently describe every pixel in the image and therefore can potentially replace traditional descriptors such as SIFT and HOG. Extensive evaluations on five publicly available unconstrained face alignment datasets show that our deep descriptor network is able to capture strong local features around a given landmark and performs significantly better than many competitive and state-of-the-art face alignment algorithms.

cs.CV↗

arXiv2016

Towards the Design of an End-to-End Automated System for Image and Video-based Recognition

Over many decades, researchers working in object recognition have longed for an end-to-end automated system that will simply accept 2D or 3D image or videos as inputs and output the labels of objects in the input data. Computer vision methods that use representations derived based on geometric, radiometric and neural considerations and statistical and structural matchers and artificial neural network-based methods where a multi-layer network learns the mapping from inputs to class labels have provided competing approaches for image recognition problems. Over the last four years, methods based on Deep Convolutional Neural Networks (DCNNs) have shown impressive performance improvements on object detection/recognition challenge problems. This has been made possible due to the availability of large annotated data, a better understanding of the non-linear mapping between image and class labels as well as the affordability of GPUs. In this paper, we present a brief history of developments in computer vision and artificial neural networks over the last forty years for the problem of image-based recognition. We then present the design details of a deep learning system for end-to-end unconstrained face verification/recognition. Some open issues regarding DCNNs for object recognition problems are then discussed. We caution the readers that the views expressed in this paper are from the authors and authors only!

cs.CV↗

arXiv2015

Network Security Threats and Protection Models

In a brave new age of global connectivity and e-commerce, interconnections via networks have heightened, creating for both individuals and organizations, a state of complete dependence upon vulnerable systems for storage and transfer of information. Never before, have so many people had power in their own hands. The power to deface websites, access personal mail accounts, and worse more the potential to bring down entire governments, and financial corporations through openly documented software codes. This paper discusses the possible exploits on typical network components, it will cite real life scenarios, and propose practical measures that can be taken as safeguard. Then, it describes some of the key efforts done by the research community to prevent such attacks, mainly by using Firewall and Intrusion Detection Systems.

cs.CR↗

arXiv2015

Cost Efficient Design of Reversible Adder Circuits for Low Power Applications

A large amount of research is currently going on in the field of reversible logic, which have low heat dissipation, low power consumption, which is the main factor to apply reversible in digital VLSI circuit design. This paper introduces reversible gate named as Inventive0 gate. The novel gate is synthesis the efficient adder modules with minimum garbage output and gate count. The Inventive0 gate capable of implementing a 4-bit ripple carry adder and carry skip adders.It is presented that Inventive0 gate is much more efficient and optimized approach as compared to their existing design, in terms of gate count, garbage outputs and constant inputs. In addition, some popular available reversible gates are implemented in the MOS transistor design the implementation kept in mind for minimum MOS transistor count and are completely reversible in behavior more precise forward and backward computation. Lesser architectural complexity show that the novel designs are compact, fast as well as low power.

cs.AR↗

arXiv2015

Feasible methodology for optimization of a novel reversible binary compressor

Now a day reversible logic is an attractive research area due to its low power consumption in the area of VLSI circuit design. The reversible logic gate is utilized to optimize power consumption by a feature of retrieving input logic from an output logic because of bijective mapping between input and output. In this manuscript, we design 4 2 and 5 2 reversible compressor circuits using a new type of reversible gate. In addition, we propose new gate, named as inventive0 gate for optimizing a compressor circuit. The utility of the inventive0 gate is that it can be used as full adder and full subtraction with low value of garbage outputs and quantum cost. An algorithm is shown for designing a compressor structure. The comparative study shows that the proposed compressor structure outperforms the existing ones in terms of garbage outputs, number of gates and quantum cost. The compressor can reduce the effect of carry (Produce from full adder) of the arithmetic frame design. In addition, we implement a basic reversible gate of MOS transistor with less number of MOS transistor count.

cs.AR↗

arXiv2015

Faster Algorithms for the Constrained k-means Problem

The classical center based clustering problems such as $k$-means/median/center assume that the optimal clusters satisfy the locality property that the points in the same cluster are close to each other. A number of clustering problems arise in machine learning where the optimal clusters do not follow such a locality property. Consider a variant of the $k$-means problem that may be regarded as a general version of such problems. Here, the optimal clusters $O_1, ..., O_k$ are an arbitrary partition of the dataset and the goal is to output $k$-centers $c_1, ..., c_k$ such that the objective function $\sum_{i=1}^{k} \sum_{x \in O_{i}} ||x - c_{i}||^2$ is minimized. It is not difficult to argue that any algorithm (without knowing the optimal clusters) that outputs a single set of $k$ centers, will not behave well as far as optimizing the above objective function is concerned. However, this does not rule out the existence of algorithms that output a list of such $k$ centers such that at least one of these $k$ centers behaves well. Given an error parameter $\varepsilon > 0$, let $\ell$ denote the size of the smallest list of $k$-centers such that at least one of the $k$-centers gives a $(1+\varepsilon)$ approximation w.r.t. the objective function above. In this paper, we show an upper bound on $\ell$ by giving a randomized algorithm that outputs a list of $2^{\tilde{O}(k/\varepsilon)}$ $k$-centers. We also give a closely matching lower bound of $2^{\tildeΩ(k/\sqrt{\varepsilon})}$. Moreover, our algorithm runs in time $O \left(n d \cdot 2^{\tilde{O}(k/\varepsilon)} \right)$. This is a significant improvement over the previous result of Ding and Xu who gave an algorithm with running time $O \left(n d \cdot (\log{n})^{k} \cdot 2^{poly(k/\varepsilon)} \right)$ and output a list of size $O \left((\log{n})^k \cdot 2^{poly(k/\varepsilon)} \right)$.

cs.DS↗

arXiv2015

Coarse-grain Molecular Dynamics Study of Fullerene Transport across a Cell Membrane

The study of the ability of drug molecules to enter cells through the membrane is of vital importance in the field of drug delivery. In cases where the transport of the drug molecules through the membrane is not easily accomplishable, other carrier molecules are used. Spherical fullerene molecules have been postulated as potential carriers of highly hydrophilic drugs across the plasma membrane. Here we report the coarse-grain molecular dynamics study of the translocation of C60 fullerene and its derivatives across a cell membrane modeled as a 1, 2-distearoyl-sn-glycero-3-phosphocholine (DSPC) bilayer. Simulation results indicate that pristine fullerene molecules enter the bilayer quickly and reside within it. The addition of polar functionalized groups makes the fullerenes less likely to reside within the bilayer but increases their residence time in bulk water. Addition of polar functional groups to one half of the fullerene surface, in effect creating a Janus particle, offers the most promise in developing fullerene models that can achieve complete translocation through the membrane bilayer.

cond-mat.soft↗

arXiv2015

Sampling in Space Restricted Settings

Space efficient algorithms play a central role in dealing with large amount of data. In such settings, one would like to analyse the large data using small amount of "working space". One of the key steps in many algorithms for analysing large data is to maintain a (or a small number) random sample from the data points. In this paper, we consider two space restricted settings -- (i) streaming model, where data arrives over time and one can use only a small amount of storage, and (ii) query model, where we can structure the data in low space and answer sampling queries. In this paper, we prove the following results in above two settings: - In the streaming setting, we would like to maintain a random sample from the elements seen so far. We prove that one can maintain a random sample using $O(\log n)$ random bits and $O(\log n)$ space, where $n$ is the number of elements seen so far. We can extend this to the case when elements have weights as well. - In the query model, there are $n$ elements with weights $w_1, ..., w_n$ (which are $w$-bit integers) and one would like to sample a random element with probability proportional to its weight. Bringmann and Larsen (STOC 2013) showed how to sample such an element using $nw +1 $ space (whereas, the information theoretic lower bound is $n w$). We consider the approximate sampling problem, where we are given an error parameter $\varepsilon$, and the sampling probability of an element can be off by an $\varepsilon$ factor. We give matching upper and lower bounds for this problem.

cs.DS↗

arXiv2014

Greedy Algorithms for Steiner Forest

In the Steiner Forest problem, we are given terminal pairs $\{s_i, t_i\}$, and need to find the cheapest subgraph which connects each of the terminal pairs together. In 1991, Agrawal, Klein, and Ravi, and Goemans and Williamson gave primal-dual constant-factor approximation algorithms for this problem; until now, the only constant-factor approximations we know are via linear programming relaxations. We consider the following greedy algorithm: Given terminal pairs in a metric space, call a terminal "active" if its distance to its partner is non-zero. Pick the two closest active terminals (say $s_i, t_j$), set the distance between them to zero, and buy a path connecting them. Recompute the metric, and repeat. Our main result is that this algorithm is a constant-factor approximation. We also use this algorithm to give new, simpler constructions of cost-sharing schemes for Steiner forest. In particular, the first "group-strict" cost-shares for this problem implies a very simple combinatorial sampling-based algorithm for stochastic Steiner forest.

cs.DS↗

arXiv2014

Understanding the multiple magnetic structures of the intermetallic compound NdMn1.4Co0.6Si2

Magnetic phases for the intermetallic compound NdMn1.4Co0.6Si2 have been investigated at various temperatures by dc magnetization, neutron diffraction and neutron depolarization. Our study shows multiple magnetic phase transitions with temperature (T) over 1.5-300 K. In agreement with dc-magnetization and neutron depolarization results, the temperature dependence of the neutron diffraction patterns shows five distinct regions with different magnetic phases. These temperature regions are (i) T >= 215 K, (ii) 215 K > T >= 50 K, (iii) 50 K > T >= 40 K, (iv) 40 K > T > 15 K, and (v) T =< 15 K. The corresponding magnetic structures are paramagnetic, commensurate collinear antiferromagnetic (AFM-I), incommensurate AFM (AFM-II), mixed ferromagnetic and AFM (FM+AFM-II), and incommensurate AFM (AFM-II), respectively.

cond-mat.str-el↗

arXiv2014

Microstructural Evolution of Charged Defects in the Fatigue Process of Polycrystalline BiFeO3 Thin Films

Fatigue failure in ferroelectrics has been intensively investigated in the past few decades. Most of the mechanisms discussed for ferroelectric fatigue have been built on the "hypothesis of variation in charged defects", which however are rarely evidenced by experimental observation. Here, using a combination of complex impedance spectra techniques, piezoresponse force microscopy and first-principles theory, we examine the microscopic evolution and redistribution of charged defects during the electrical cycling in BiFeO3 thin films. The dynamic formation and melting behaviors of oxygen vacancy (VO) order are identified during the fatigue process. It reveals that the isolated VO tend to self-order along grain boundaries to form a planar-aligned structure, which blocks the domain reversals. Upon further electrical cycling, migration of VO within vacancy clusters is accommodated with a lower energy barrier (~0.2 eV) and facilitates the formation of nearby-electrode layer incorporated with highly concentrated VO. The interplay between the macroscopic fatigue and microscopic evolution of charged defects clearly demonstrates the role of ordered VO cluster in the fatigue failure of BiFeO3 thin films.

cond-mat.mtrl-sci↗

arXiv2014

Rejecting Jobs to Minimize Load and Maximum Flow-time

Online algorithms are usually analyzed using the notion of competitive ratio which compares the solution obtained by the algorithm to that obtained by an online adversary for the worst possible input sequence. Often this measure turns out to be too pessimistic, and one popular approach especially for scheduling problems has been that of "resource augmentation" which was first proposed by Kalyanasundaram and Pruhs. Although resource augmentation has been very successful in dealing with a variety of objective functions, there are problems for which even a (arbitrary) constant speedup cannot lead to a constant competitive algorithm. In this paper we propose a "rejection model" which requires no resource augmentation but which permits the online algorithm to not serve an epsilon-fraction of the requests. The problems considered in this paper are in the restricted assignment setting where each job can be assigned only to a subset of machines. For the load balancing problem where the objective is to minimize the maximum load on any machine, we give $O(\log^2 1/\eps)$-competitive algorithm which rejects at most an $\eps$-fraction of the jobs. For the problem of minimizing the maximum weighted flow-time, we give an $O(1/\eps^4)$-competitive algorithm which can reject at most an $\eps$-fraction of the jobs by weight. We also extend this result to a more general setting where the weights of a job for measuring its weighted flow-time and its contribution towards total allowed rejection weight are different. This is useful, for instance, when we consider the objective of minimizing the maximum stretch. We obtain an $O(1/\eps^6)$-competitive algorithm in this case. Our algorithms are immediate dispatch, though they may not be immediate reject. All these problems have very strong lower bounds in the speed augmentation model.

cs.DS↗

arXiv2014

Electronic structure and stability of hydrogen defects in diamond and boron doped diamond: A density functional theory study

Isolated hydrogen and hydrogen pairs in bulk diamond matrix have been studied using density functional theory calculations. The electronic structure and stability of isolated and paired hydrogen defects are investigated at different possible lattice sites in pure diamond and boron doped diamond. Calculations revealed that isolated hydrogen defect is stable at bond center sites for pure diamond and bond center puckered site for boron doped diamond. In case of hydrogen pairs, H2 defect (one hydrogen at bond center and second at anti-bonding site) is stable for pure diamond, while for boron doped diamond B-H2BC complex (one H atom at the B-C bond centered puckered position and the other one at the puckered position of one of the C-C bond first neighbor of the B atom) is most stable. Multiple hydrogen trapping sites in boron doped diamond has also been studied. Calculated results are discussed and compared with previously reported theoretical results in detailed.

cond-mat.mtrl-sci↗

arXiv2014

Carrier type modulation in current annealed graphene layers

We report on the electrical properties of current annealed graphene and few layer graphene devices. It is observed that current annealing for several hours results the n-type doping in the graphene layers. After current annealing Dirac point start to shift toward positive gate voltage and saturate at some fixed gate voltage. N-type conduction in current annealed graphene layers is caused by the charge trapping in oxide layer during current annealing and recovery of charge neutrality point with time span is understood due to the de-trapping of charge with time.

cond-mat.mes-hall↗