Showing papers by "International Institute of Information Technology, Hyderabad published in 2015"

A Secure Biometrics-Based Multi-Server Authentication Protocol Using Smart Cards

Abstract: Recently, in 2014, He and Wang proposed a robust and efficient multi-server authentication scheme using biometrics-based smart card and elliptic curve cryptography (ECC). In this paper, we first analyze He–Wang’s scheme and show that their scheme is vulnerable to a known session-specific temporary information attack and impersonation attack. In addition, we show that their scheme does not provide strong user’s anonymity. Furthermore, He–Wang’s scheme cannot provide the user revocation facility when the smart card is lost/stolen or user’s authentication parameter is revealed. Apart from these, He–Wang’s scheme has some design flaws, such as wrong password login and its consequences, and wrong password update during password change phase. We then propose a new secure multi-server authentication protocol using biometric-based smart card and ECC with more security functionalities. Using the Burrows–Abadi–Needham logic, we show that our scheme provides secure authentication. In addition, we simulate our scheme for the formal security verification using the widely accepted and used automated validation of Internet security protocols and applications tool, and show that our scheme is secure against passive and active attacks. Our scheme provides high security along with low communication cost, computational cost, and variety of security features. As a result, our scheme is very suitable for battery-limited mobile devices as compared with He–Wang’s scheme.

Multi-label Cross-Modal Retrieval

Abstract: In this work, we address the problem of cross-modal retrieval in presence of multi-label annotations. In particular, we introduce multi-label Canonical Correlation Analysis (ml-CCA), an extension of CCA, for learning shared subspaces taking into account high level semantic information in the form of multi-label annotations. Unlike CCA, ml-CCA does not rely on explicit pairing between modalities, instead it uses the multi-label information to establish correspondences. This results in a discriminative subspace which is better suited for cross-modal retrieval tasks. We also present Fast ml-CCA, a computationally efficient version of ml-CCA, which is able to handle large scale datasets. We show the efficacy of our approach by conducting extensive cross-modal retrieval experiments on three standard benchmark datasets. The results show that the proposed approach achieves state of the art retrieval performance on the three datasets.

Development of Decadal (1985–1995–2005) Land Use and Land Cover Database for India

Abstract: India has experienced significant Land-Use and Land-Cover Change (LULCC) over the past few decades. In this context, careful observation and mapping of LULCC using satellite data of high to medium spatial resolution is crucial for understanding the long-term usage patterns of natural resources and facilitating sustainable management to plan, monitor and evaluate development. The present study utilizes the satellite images to generate national level LULC maps at decadal intervals for 1985, 1995 and 2005 using onscreen visual interpretation techniques with minimum mapping unit of 2.5 hectares. These maps follow the classification scheme of the International Geosphere Biosphere Programme (IGBP) to ensure compatibility with other global/regional LULC datasets for comparison and integration. Our LULC maps with more than 90% overall accuracy highlight the changes prominent at regional level, i.e., loss of forest cover in central and northeast India, increase of cropland area in Western India, growth of peri-urban area, and relative increase in plantations. We also found spatial correlation between the cropping area and precipitation, which in turn confirms the monsoon dependent agriculture system in the country. On comparison with the existing global LULC products (GlobCover and MODIS), it can be concluded that our dataset has captured the maximum cumulative patch diversity frequency indicating the detailed representation that can be attributed to the on-screen visual interpretation technique. Comparisons with global LULC products (GlobCover and MODIS) show that our dataset captures maximum landscape diversity, which is partly attributable to the on-screen visual interpretation techniques. We advocate the utility of this database for national and regional studies on land dynamics and climate change research. The database would be updated to 2015 as a continuing effort of this study.

A Secure and Efficient User Anonymity-Preserving Three-Factor Authentication Protocol for Large-Scale Distributed Wireless Sensor Networks

Abstract: Critical applications in wireless sensor network (WSN) are real-time based applications. Therefore, users are generally interested in accessing real-time information. This is possible, if the users (called the external parties) are allowed to access the real-time data directly from the sensor nodes inside WSN and not from the base station. The sensory information from nodes are gathered periodically by the base station and so, the gathered information may not be real-time. In order to get the real-time information from the sensor nodes, the user needs to be first authorized to the sensor nodes as well as the base station so that the illegal access to nodes do not happen. In this paper, we propose a novel three-factor user authentication scheme suited for distributed WSNs. Our scheme is light-weight, because it only requires the efficient cryptographic hash function, and symmetric key encryption and decryption operations. Further, our scheme is secure against different known attacks which are proved through the rigorous informal and formal security analysis. In addition, we simulate our scheme for the formal security verification using Automated Validation of Internet Security Protocols and Applications tool. The simulation results clearly demonstrate that our scheme is secure against passive and active adversaries.

Single frequency filtering approach for discriminating speech and nonspeech

Abstract: In this paper, a signal processing approach is proposed for speech/nonspeech discrimination. The approach is based on single frequency filtering (SFF), where the amplitude envelope of the signal is obtained at each frequency with high temporal and spectral resolution. This high resolution property helps to exploit the resulting high signal-to-noise ratio (SNR) regions in time and frequency. The variance of the spectral information across frequency is higher for speech and lower for many types of noises. The mean and variance of the noise-compensated weighted envelopes are computed across frequency at each time instant. Decision logic is applied to the feature derived from the mean and variance values on varieties of degradations, including NTIMIT, CTIMIT and distance speech, besides degradation due to standard noise types. In all cases, the proposed method gives significantly better performance than the standard Adaptive Multi-rate VAD2 (AMR2) method. AMR2 method is chosen for comparison, as the method adapts itself for different degradations, and is seen to give good performance over different SNR situations. The proposed method does not use training data to derive the characteristics of speech or noise, nor makes any assumption on the nonspeech beginning. The SFF method appears promising in other applications of speech processing, such as pitch extraction and speech enhancement.

EEG-NIRS Based Assessment of Neurovascular Coupling During Anodal Transcranial Direct Current Stimulation - a Stroke Case Series

Abstract: A method for electroencephalography (EEG) - near-infrared spectroscopy (NIRS) based assessment of neurovascular coupling (NVC) during anodal transcranial direct current stimulation (tDCS). Anodal tDCS modulates cortical neural activity leading to a hemodynamic response, which was used to identify impaired NVC functionality. In this study, the hemodynamic response was estimated with NIRS. NIRS recorded changes in oxy-hemoglobin (HbO2) and deoxy-hemoglobin (Hb) concentrations during anodal tDCS-induced activation of the cortical region located under the electrode and in-between the light sources and detectors. Anodal tDCS-induced alterations in the underlying neuronal current generators were also captured with EEG. Then, a method for the assessment of NVC underlying the site of anodal tDCS was proposed that leverages the Hilbert-Huang Transform. The case series including four chronic (>6 months) ischemic stroke survivors (3 males, 1 female from age 31 to 76) showed non-stationary effects of anodal tDCS on EEG that correlated with the HbO2 response. Here, the initial dip in HbO2 at the beginning of anodal tDCS corresponded with an increase in the log-transformed mean-power of EEG within 0.5Hz-11.25Hz frequency band. The cross-correlation coefficient changed signs but was comparable across subjects during and after anodal tDCS. The log-transformed mean-power of EEG lagged HbO2 response during tDCS but then led post-tDCS. This case series demonstrated changes in the degree of neurovascular coupling to a 0.526 A/m2 square-pulse (0---30 s) of anodal tDCS. The initial dip in HbO2 needs to be carefully investigated in a larger cohort, for example in patients with small vessel disease.

An effective ECC-based user access control scheme with attribute-based encryption for wireless sensor networks

Abstract: For critical applications, real-time data access is essential from the nodes inside a wireless sensor network WSN. Only the authorized users with unique access privilege should access the specific, but not all, sensing information gathered by the cluster heads in a hierarchical WSNs. Access rights for the correct information and resources for different services from the cluster heads to the genuine users can be provided with the help of efficient user access control mechanisms. In this paper, we propose a new user access control scheme with attribute-based encryption using elliptic curve cryptography in hierarchical WSNs. In attribute-based encryption, the ciphertexts are labeled with sets of attributes and secret keys of the users that are associated with their own access structures. The authorized users with the relevant set of attributes can able to decrypt the encrypted message coming from the cluster heads. Our scheme provides high security. Moreover, our scheme is efficient as compared with those for other existing user access control schemes. Through both the formal and informal security analysis, we show that our scheme has the ability to tolerate different known attacks required for a user access control designed for WSNs. Furthermore, we simulate our scheme for the formal security verification using the widely-accepted automated validation of Internet security protocols and applications tool. The simulation results demonstrate that our scheme is secure. Copyright © 2014 John Wiley & Sons, Ltd.

An efficient approach for mining association rules from high utility itemsets

Abstract: This paper addresses mining association rules from high utility itemsets.Designed FHIM algorithm extracts all high utility itemsets effectively.HUCI-Miner algorithm is used to derive itemsets with their generators efficiently.Condensed representation of association rules in share-confidence model is proposed.The method for extracting all rules from the compact representation is also proposed. Traditional association rule mining based on the support-confidence framework provides the objective measure of the rules that are of interest to users. However, it does not reflect the semantic measure among the items. The semantic measure of an itemset is characterized with utility values that are typically associated with transaction items, where a user will be interested to an itemset only if it satisfies a given utility constraint. In this paper, we first define the problem of finding association rules using utility-confidence framework, which is a generalization of the amount-confidence measure. Using this semantic concept of rules, we then propose a compressed representation for association rules having minimal antecedent and maximal consequent. This representation is generated with the help of high utility closed itemsets (HUCI) and their generators. We propose the algorithms to generate the utility based non-redundant association rules and methods for reconstructing all association rules. Furthermore, we describe the algorithms which generate high utility itemsets (HUI) and high utility closed itemsets with their generators. These proposed algorithms are implemented using both synthetic and real datasets. The results demonstrate better efficiency and effectiveness of the proposed HUCI-Miner algorithm compared to other well-known existing algorithms. In addition, the experimental results show better quality in the compressed representation of the entire rule set under the considered framework.

Understanding the thermostability and activity of Bacillus subtilis lipase mutants: insights from molecular dynamics simulations.

Abstract: Improving the thermostability of industrial enzymes is an important protein engineering challenge. Point mutations, induced to increase thermostability, affect the structure and dynamics of the target protein in several ways and thus can also affect its activity. There appears to be no general rules for improving the thermostabilty of enzymes without adversely affecting their enzymatic activity. We report MD simulations, of wild type Bacillus subtilis lipase (WT) and its six progressively thermostable mutants (2M, 3M, 4M, 6M, 9M, and 12M), performed at different temperatures, to address this issue. Less thermostable mutants (LTMs), 2M to 6M, show WT-like dynamics at all simulation temperatures. However, the two more thermostable mutants (MTMs) show the required flexibility at appropriate temperature ranges and maintain conformational stability at high temperature. They show a deep and rugged free-energy landscape, confining them within a near-native conformational space by conserving noncovalent interactions, and thus protecting them from possible aggregation. In contrast, the LTMs having marginally higher thermostabilities than WT show greater probabilities of accessing non-native conformations, which, due to aggregation, have reduced possibilities of reverting to their respective native states under refolding conditions. Our analysis indicates the possibility of nonadditive effects of point mutations on the conformational stability of LTMs.

"Answer ka type kya he?": Learning to Classify Questions in Code-Mixed Language

Abstract: Code-Mixing (CM) is defined as the embedding of linguistic units such as phrases, words, and morphemes of one language into an utterance of another language. CM is a natural phenomenon observed in many multilingual societies. It helps in speeding-up communication and allows wider variety of expression due to which it has become a popular mode of communication in social media forums like Facebook and Twitter. However, current Question Answering (QA) research and systems only support expressing a question in a single language which is an unrealistic and hard proposition especially for certain domains like health and technology. In this paper, we take the first step towards the development of a full-fledged QA system in CM language which is building a Question Classification (QC) system. The QC system analyzes the user question and infers the expected Answer Type (AType). The AType helps in locating and verifying the answer as it imposes certain type-specific constraints. In this paper, we present our initial efforts towards building a full-fledged QA system for CM language. We learn a basic Support Vector Machine (SVM) based QC system for English-Hindi CM questions. Due to the inherent complexities involved in processing CM language and also the unavailability of language processing resources such POS taggers, Chunkers, Parsers, we design our current system using only word-level resources such as language identification, transliteration and lexical translation. To reduce data sparsity and leverage resources available in a resource-rich language, in stead of extracting features directly from the original CM words, we translate them commonly into English and then perform featurization. We created an evaluation dataset for this task and our system achieves an accuracy of 63% and 45% in coarse-grained and fine-grained categories of the question taxanomy. The idea of translating features into English indeed helps in improving accuracy over the unigram baseline.

A Secure User Anonymity-Preserving Three-Factor Remote User Authentication Scheme for the Telecare Medicine Information Systems

Abstract: Recent advanced technology enables the telecare medicine information system (TMIS) for the patients to gain the health monitoring facility at home and also to access medical services over the Internet of mobile networks. Several remote user authentication schemes have been proposed in the literature for TMIS. However, most of them are either insecure against various known attacks or they are inefficient. Recently, Tan proposed an efficient user anonymity preserving three-factor authentication scheme for TMIS. In this paper, we show that though Tan's scheme is efficient, it has several security drawbacks such as (1) it fails to provide proper authentication during the login phase, (2) it fails to provide correct updation of password and biometric of a user during the password and biometric update phase, and (3) it fails to protect against replay attack. In addition, Tan's scheme lacks the formal security analysis and verification. Later, Arshad and Nikooghadam also pointed out some security flaws in Tan's scheme and then presented an improvement on Tan's s scheme. However, we show that Arshad and Nikooghadam's scheme is still insecure against the privileged-insider attack through the stolen smart-card attack, and it also lacks the formal security analysis and verification. In order to withstand those security loopholes found in both Tan's scheme, and Arshad and Nikooghadam's scheme, we aim to propose an effective and more secure three-factor remote user authentication scheme for TMIS. Our scheme provides the user anonymity property. Through the rigorous informal and formal security analysis using random oracle models and the widely-accepted AVISPA (Automated Validation of Internet Security Protocols and Applications) tool, we show that our scheme is secure against various known attacks, including the replay and man-in-the-middle attacks. Furthermore, our scheme is also efficient as compared to other related schemes.

Analysis of excitation source features of speech for emotion recognition

Abstract: During production of emotional speech there are deviations in the components of speech production mechanism when compared to normal speech. The objective of this study is to capture the deviations in features related to the excitation source component of speech, and to develop a system for automatic recognition of emotions based on these deviations. The emotions considered for this study are: anger, happy, neutral and sad. The study shows that there are useful features in the deviations of the excitation source features at subsegmental level, and they can be exploited to develop an emotion recognition system. A hierarchical binary decision tree approach is used for classification.

An efficient ECC-based privacy-preserving client authentication protocol with key agreement using smart card

Abstract: The authentication protocols are trusted components in a communication system in order to protect sensitive information against a malicious adversary in the client-server environment by means of providing a variety of services including users' privacy and authentication. In the cryptographic protocols, understanding the security failures is the key for both patching to the existing protocols and designing the future protocols. Recently, in 2014, Wang proposed an improved Elliptic Curve Cryptography (ECC) based anonymous remote authentication scheme using smart card and claimed that the proposed scheme is secure against password guessing attack, smart card lost/stolen verifier attack, and also preserves user anonymity and prevents credential leakage. However, in this paper, we show that Wang's scheme fails to preserve the user anonymity and does not prevent the off-line password guessing attack, credential leakage and smart card lost/stolen verifier attack. In order to withstand those security pitfalls found in Wang's scheme, we aim to propose a new secure privacy-preserving ECC-based client authentication with key agreement protocol using smart card. Through the formal and informal security analysis we show that our scheme is secure against possible known attacks including the off-line password guessing attack, credential leakage attack and smart card lost/stolen verifier attack. Our scheme also preserves the user anonymity property. In addition, we simulate our scheme for the formal security verification using the widely-accepted AVISPA (Automated Validation of Internet Security Protocols and Applications) tool and show that our scheme is secure against passive and active attacks. Our scheme provides high security along with low computational and communication costs. As a result, our scheme is practically suitable for mobile devices in the client-server environment as compared to other related schemes in the literature.

High-Throughput LDPC-Decoder Architecture Using Efficient Comparison Techniques & Dynamic Multi-Frame Processing Schedule

Abstract: This paper presents architecture of block-level-parallel layered decoder for irregular LDPC code. It can be reconfigured to support various block lengths and code rates of IEEE 802.11n (WiFi) wireless-communication standard. We have proposed efficient comparison techniques for both column and row layered schedule and rejection-based high-speed circuits to compute the two minimum values from multiple inputs required for row layered processing of hardware-friendly min-sum decoding algorithm. The results show good speed with lower area as compared to state-of-the-art circuits. Additionally, this work proposes dynamic multi-frame processing schedule which efficiently utilizes the layered-LDPC decoding with minimum pipeline stages. The suggested LDPC-decoder architecture has been synthesized and post-layout simulated in 90 nm-CMOS process. This decoder occupies 5.19 ${\rm mm}^{2}$ area and supports multiple code rates like 1/2, 2/3, 3/4 & 5/6 as well as block-lengths of 648, 1296 & 1944. At a clock frequency of 336 MHz, the proposed LDPC-decoder has achieved better throughput of 5.13 Gbps and energy efficiency of 0.01 nJ/bits/iterations, as compared to the similar state-of-the-art works.

Functional characterization of drought-responsive modules and genes in Oryza sativa: a network-based approach

Abstract: Drought is one of the major environmental stress conditions affecting the yield of rice across the globe. Unraveling the functional roles of the drought-responsive genes and their underlying molecular mechanisms will provide important leads to improve the yield of rice. Co-expression relationships derived from condition-dependent gene expression data is an effective way to identify the functional associations between genes that are part of the same biological process and may be under similar transcriptional control. For this purpose, vast amount of freely available transcriptomic data can be used for functional annotation. In this study we consider gene expression data for different tissues and developmental stages in response to drought stress. We analyze the network of co-expressed genes to identify drought-responsive genes modules in a tissue and stage-specific manner based on differential expression and gene enrichment analysis. Taking cues from the systems-level behavior of these modules, we propose two approaches to identify clusters of tightly co-expressed/co-regulated genes. Using graph-centrality measures and differential gene expression, we identify biologically informative genes that lack any functional annotation. We show that using orthologous information from other plant species, the conserved co-expression patterns of the uncharacterized genes can be identified. Presence of a conserved neighborhood enables us to extrapolate functional annotation. Alternatively, we show that ‘guide-gene’ approach can help in understanding the tissue-specific transcriptional regulation of uncharacterized genes. Finally, we confirm the predicted roles of uncharacterized genes by the analysis of conserved cis-elements and explain the possible roles of these genes towards drought tolerance

A secure password-based authentication and key agreement scheme using smart cards

Abstract: Authentication schemes present a user-friendly and scalable mechanism to establish the secure and authorized communication between the remote entities over the insecure public network. Later, several authentication schemes have proposed in the literature. However, most of the existing schemes do not satisfy the desirable attributes, such as resistance against known attacks and user anonymity. In 2012, Chen et?al. designed a robust authentication scheme to erase the weaknesses of Sood et?al.'s scheme. In 2013, Jiang et?al. showed that Chen et?al.'s scheme is vulnerable to password guessing attack. Furthermore, Jiang et?al. presented an efficient solution to overcome the shortcoming of Chen et?al.'s scheme. We demonstrate that Jiang et?al.'s scheme does not withstand insider attack, on-line and off-line password guessing attacks, and user impersonation attack. Their scheme also fails to provide user's anonymity. To overcome these drawbacks, we aim to propose an enhanced scheme, which reduces the computation overhead and satisfies all desirable security attributes, while retaining the original merits of Jiang et?al.'s scheme. The proposed scheme is also comparable in terms of the communication and computational overheads with Jiang et?al.'s scheme and other existing schemes. Furthermore, we simulate the enhanced scheme for the formal security analysis utilizing the widely-accepted AVISPA tool and show that the proposed scheme is resistant against active and passive attacks.

A robust anonymous biometric-based remote user authentication scheme using smart cards

Abstract: Several biometric-based remote user authentication schemes using smart cards have been proposed in the literature in order to improve the security weaknesses in user authentication system. In 2012, An proposed an enhanced biometric-based remote user authentication scheme using smart cards. It was claimed that the proposed scheme is secure against the user impersonation attack, the server masquerading attack, the password guessing attack, and the insider attack and provides mutual authentication between the user and the server. In this paper, we first analyze the security of An's scheme and we show that this scheme has three serious security flaws in the design of the scheme: (i) flaw in user's biometric verification during the login phase, (ii) flaw in user's password verification during the login and authentication phases, and (iii) flaw in user's password change locally at any time by the user. Due to these security flaws, An's scheme cannot support mutual authentication between the user and the server. Further, we show that An's scheme cannot prevent insider attack. In order to remedy the security weaknesses found in An's scheme, we propose a new robust and secure anonymous biometric-based remote user authentication scheme using smart cards. Through the informal and formal security analysis, we show that our scheme is secure against all possible known attacks including the attacks found in An's scheme. The simulation results of our scheme using the widely-accepted AVISPA (Automated Validation of Internet Security Protocols and Applications) tool ensure that our scheme is secure against passive and active attacks. In addition, our scheme is also comparable in terms of the communication and computational overheads with An's scheme and other related existing schemes. As a result, our scheme is more appropriate for practical applications compared to other approaches.

Optimizing roof insulation for roofs with high albedo coating and radiant barriers in India

Abstract: To make roofs energy efficient, typically two types of techniques are followed: surface treatments (cool roofs, radiant barriers) and thermal property modifications (roof insulation). The interplay between these two techniques has been studied using energy simulations. A single storey, daytime operational, office building of 200 m2 area has been simulated for five climatic zones in India. A total of 88 different roof combinations have been studied for each climatic zone. An economic analysis using Internal Rate of Return has been performed to identify a suitable roof insulation thickness for a roof with high albedo, and radiant barrier combination. The incremental benefits in energy savings reduces by adding insulation after a limit. For a roof with albedo of 0.6 and radiant barrier emittance of 0.2, the optimized roof R-value is 0.49 m2 K/W in hot and dry and composite climates, 0.31 m2 K/W in warm and humid and temperate climates, and 1.02 m2 K/W for cold climates.

Measurement-device-independent randomness from local entangled states

Abstract: Nonlocal correlations are useful for device-independent (DI) randomness certification (Pironio S. et al. , Nature (London) , 464 (2010) 1021). The advantage of this DI protocol over the conventional quantum protocol is that randomness can be certified even when experimental apparatuses are not trusted. Quantum entanglement is the necessary physical source for the nonlocal correlation required for such DI task. However, nonlocality and entanglement are distinct concepts. There exist entangled states which produce no nonlocal correlation and hence are not useful for the DI randomness certification task. Here we introduce the measurement-device–independent randomness certification task where one has trusted quantum state preparation devices but the mesurement devices are completely unspecified. Interestingly we show that there exist entangled states, with local description, that are a useful resource in such task but are useless in the corresponding DI scenario.

Noninvasive Blood Glucose Sensing Using Near Infra-Red Spectroscopy and Artificial Neural Networks Based on Inverse Delayed Function Model of Neuron

Abstract: In this paper, a non-invasive blood glucose sensing system is presented using near infra-red(NIR) spectroscopy. The signal from the NIR optodes is processed using artificial neural networks (ANN) to estimate the glucose level in blood. In order to obtain accurate values of the synaptic weights of the ANN, inverse delayed (ID) function model of neuron has been used. The ANN model has been implemented on field programmable gate array (FPGA). Error in estimating glucose levels using ANN based on ID function model of neuron implemented on FPGA, came out to be 1.02 mg/dl using 15 hidden neurons in the hidden layer as against 5.48 mg/dl using ANN based on conventional neuron model.

Autonomous navigation of generic monocular quadcopter in natural environment

Abstract: Autonomous navigation of generic monocular quadcopter in the natural environment requires sophisticated mechanism for perception, planning and control In this work, we have described a framework which performs perception using monocular camera and generates minimum time collision free trajectory and control for any commercial quadcopter flying through cluttered unknown environment The proposed framework first utilizes supervised learning approach to estimate the dense depth map for video stream obtained from frontal monocular camera This depth map is initially transformed into Ego Dynamic Space and subsequently, is used for computing locally traversable way-points utilizing binary integer programming methodology Finally, trajectory planning and control module employs a convex programming technique to generate collision-free trajectory which follows these way-points and produces appropriate control inputs for the quadcopter These control inputs are computed from the generated trajectory in each update Hence, they are applicable to achieve closed-loop control similar to model predictive controller We have demonstrated the applicability of our system in controlled indoors and in unstructured natural outdoors environment

Towards Multimodal Affective Feedback: Interaction between Visual and Haptic Modalities

Abstract: We explored how emotional cues presented in visual and haptic modalities interact. We constructed an affective haptic dataset, and used the emotional visual stimuli from the International Affective Picture System (IAPS). Participants were asked to rate the visual stimuli, haptic stimuli and visualhaptic stimuli. Analysis of the results indicates that the presence of haptic stimulus affects the arousal of the visual stimulus, but does not affect the valence significantly. We further explored this interaction in terms of the intensity, frequency, waveform and rhythm of the haptic stimuli. We then provide a set of guidelines on visual-haptic interaction that could be used in design of multimodal affective feedback.

Accurate localization by fusing images and GPS signals

Abstract: Localization in 3D is an important problem with wide ranging applications from autonomous navigation in robotics to location specific services on mobile devices. GPS sensors are a commercially viable option for localization, and are ubiquitous in their use, especially in portable devices. With the proliferation of mobile cameras however, maturing localization algorithms based on computer vision are emerging as a viable alternative. Although both vision and GPS based localization algorithms have many limitations and inaccuracies, there are some interesting complimentarities in their success/failure scenarios that justify an investigation into their joint utilization. Such investigations are further justified considering that many of the modern wearable and mobile computing devices come with sensors for both GPS and vision. In this work, we investigate approaches to reinforce GPS localization with vision algorithms and vice versa. Specifically, we show how noisy GPS signals can be rectified by vision based localization of images captured in the vicinity. Alternatively, we also show how GPS readouts might be used to disambiguate images when they are visually similar looking but belong to different places. Finally, we empirically validate our solutions to show that fusing both these approaches can result in a more accurate and reliable localization of videos captured with a Contour action camera, over a 600 meter long path, over 10 different days.

Study of characteristics of aperiodicity in Noh voices.

Abstract: The feasibility of representing the excitation source characteristics in expressive voice signals by an aperiodic sequence of impulses in the time domain is examined in this paper. In particular, the aperiodic components of excitation of expressive voices, like the Noh voice, are examined in some detail. The aperiodic component is extracted from the speech signal using a modified zero-frequency filtering method, and it is represented using a sequence of impulses with amplitudes corresponding to the relative strength of excitation around each impulse. The spectral characteristics of the aperiodic sequence show subharmonics and harmonics of the fundamental frequency corresponding to pitch. The effects of aperiodicity are examined using spectrograms and saliency plots of synthetic amplitude and duration (i.e., frequency) modulation of sequences of impulses.

Development of Point of Care Testing Device for Neurovascular Coupling From Simultaneous Recording of EEG and NIRS During Anodal Transcranial Direct Current Stimulation

Abstract: This paper presents a point of care testing device for neurovascular coupling (NVC) from simultaneous recording of electroencephalogram (EEG) and near infrared spectroscopy (NIRS) during anodal transcranial direct current stimulation (tDCS). Here, anodal tDCS modulated cortical neural activity leading to hemodynamic response can be used to identify the impaired cerebral microvessels functionality. The impairments in the cerebral microvessels functionality may lead to impairments in the cerebrovascular reactivity (CVR), where severely reduced CVR predicts the chances of transient ischemic attack and ipsilateral stroke. The neural and hemodynamic responses to anodal tDCS were studied through joint imaging with EEG and NIRS, where NIRS provided optical measurement of changes in tissue oxy-( $HbO2)$ and deoxy-( $Hb$ ) hemoglobin concentration and EEG captured alterations in the underlying neuronal current generators. Then, a cross-correlation method for the assessment of NVC underlying the site of anodal tDCS is presented. The feasibility studies on healthy subjects and stroke survivors showed detectable changes in the EEG and the NIRS responses to a 0.526 A/ $\mathrm{m}^{2}$ of anodal tDCS. The NIRS system was bench tested on 15 healthy subjects that showed a statistically significant (p $HbO2$ than the nonlesioned side in response to anodal tDCS. The EEG study on healthy subjects showed a statistically significant (p $HbO2$ response in one of the stroke survivors with white matter lesions. Therefore, it was concluded that the anodal tDCS can perturb the local neural and the vascular activity (via NVC) which can be used for assessing regional NVC functionality where confirmatory clinical studies are required.

Geometry-Aware Feature Matching for Structure from Motion Applications

Abstract: We present a two-stage, geometry-aware approach for matching SIFT-like features in a fast and reliable manner. Our approach first uses a small sample of features to estimate the epipolar geometry between the images and leverages it for guided matching of the remaining features. This simple and generalized two-stage matching approach produces denser feature correspondences while allowing us to formulate an accelerated search strategy to gain significant speedup over the traditional matching. The traditional matching punitively rejects many true feature matches due to a global ratio test. The adverse effect of this is particularly visible when matching image pairs with repetitive structures. The geometry-aware approach prevents such pre-emptive rejection using a selective ratio-test and works effectively even on scenes with repetitive structures. We also show that the proposed algorithm is easy to parallelize and implement it on the GPU. We experimentally validate our algorithm on publicly available datasets and compare the results with state-of-the-art methods.

An efficient biometric-based privacy-preserving three-party authentication with key agreement protocol using smart cards

Abstract: In communication systems, authentication protocols play an important role in protecting sensitive information against a malicious adversary by means of providing a variety of services such as mutual authentication, user credentials' privacy, and user revocation facility when the smart card of the user is lost/stolen or user's authentication parameters are revealed. Recently, several three-party authentication with key agreement 3PAKA schemes are proposed in the literature, but most of them do not provide the basic security requirements such as user anonymity as well as user revocation and re-registration with the same identity. Thus, we feel that there is a great need to design a secure 3PAKA scheme with these security properties. In this paper, we propose a new secure biometric-based privacy-preserving 3PAKA scheme using the elliptic curve cryptography with efficient mechanism for the user revocation and re-registration with the same identity. The formal security analysis using the widely accepted Burrows-Abadi-Needham logic shows that our scheme provides secure authentication. In addition, we simulate our scheme for the formal security verification using the widely accepted Automated Validation of Internet Security Protocols and Applications tool. The simulation results show that our scheme is secure against passive and active attacks. Furthermore, our scheme is efficient as compared with other related schemes. Our scheme provides high security along with low computation and communication costs, and extra features as compared with other related existing schemes in the literature, and as a result, our scheme is suitable for battery-limited mobile devices. Copyright © 2015 John Wiley & Sons, Ltd.

A Secure and Robust User Authenticated Key Agreement Scheme for Hierarchical Multi-medical Server Environment in TMIS

Abstract: The telecare medicine information system (TMIS) helps the patients to gain the health monitoring facility at home and access medical services over the Internet of mobile networks. Recently, Amin and Biswas presented a smart card based user authentication and key agreement security protocol usable for TMIS system using the cryptographic one-way hash function and biohashing function, and claimed that their scheme is secure against all possible attacks. Though their scheme is efficient due to usage of one-way hash function, we show that their scheme has several security pitfalls and design flaws, such as (1) it fails to protect privileged-insider attack, (2) it fails to protect strong replay attack, (3) it fails to protect strong man-in-the-middle attack, (4) it has design flaw in user registration phase, (5) it has design flaw in login phase, (6) it has design flaw in password change phase, (7) it lacks of supporting biometric update phase, and (8) it has flaws in formal security analysis. In order to withstand these security pitfalls and design flaws, we aim to propose a secure and robust user authenticated key agreement scheme for the hierarchical multi-server environment suitable in TMIS using the cryptographic one-way hash function and fuzzy extractor. Through the rigorous security analysis including the formal security analysis using the widely-accepted Burrows-Abadi-Needham (BAN) logic, the formal security analysis under the random oracle model and the informal security analysis, we show that our scheme is secure against possible known attacks. Furthermore, we simulate our scheme using the most-widely accepted and used Automated Validation of Internet Security Protocols and Applications (AVISPA) tool. The simulation results show that our scheme is also secure. Our scheme is more efficient in computation and communication as compared to Amin-Biswas's scheme and other related schemes. In addition, our scheme supports extra functionality features as compared to other related schemes. As a result, our scheme is very appropriate for practical applications in TMIS.