International Institute of Information Technology, Hyderabad

About: International Institute of Information Technology, Hyderabad is a education organization based out in Hyderabad, India. It is known for research contribution in the topics: Computer science & Authentication. The organization has 2048 authors who have published 3677 publications receiving 45319 citations. The organization is also known as: IIIT Hyderabad & International Institute of Information Technology (IIIT).

Non invasive estimation of blood glucose using near infra red spectroscopy and double regression analysis

Abstract: This paper presents a unique technique for noninvasive estimation of blood glucose concentration using near infra red spectroscopy. The spectroscopy has been performed at the second overtone of glucose which falls in the near infra red region. The near infra red spectroscopy has been performed using transmission photoplethsymography (PPG). The analog front end system has been implemented to get the PPG signal at the near infra red wavelengths of 1070nm, 950nm, 935nm. The PPG signal that has been obtained is processed and double regression analysis is carried out with the artificial neural network for estimating the glucose levels. The root mean square error of the prediction was 5.84mg/dL.

Towards Automatic Assessment of Voice Disorders: A Clinical Approach.

Abstract: Automatic detection and assessment of voice disorders is important in diagnosis and treatment planning of voice disorders. This work proposes an approach for automatic detection and assessment of voice disorders from a clinical perspective. To accomplish this, a multi-level classification approach was explored in which four binary classifiers were used for the assessment of voice disorders. The binary classifiers were trained using support vector machines with excitation source features, vocal-tract system features, and state-of-art OpenSMILE features. In this study source features namely, glottal parameters obtained from glottal flow waveform, perturbation measures obtained from epoch locations, and cepstral features obtained from linear prediction residual and zero frequency filtered signal were explored. The present study used the Saarbucken voice disorders database to evaluate the performance of proposed approach. The OpenSMILE features namely ComParE and eGEMAPS feature sets shown better performance in terms of classification accuracies of 82.8% and 76%, respectively for voice disorder detection. The combination of excitation source features with baseline feature sets further improved the performance of detection and assessment systems, that highlight the complimentary nature of exciting source features.

Breathy to Tense Voice Discrimination using Zero-Time Windowing Cepstral Coefficients (ZTWCCs).

Abstract: In this paper, we consider breathy to tense voices, which are often considered to be opposite ends of a voice quality continuum. Along with these, other aspects of a speaker’s voice play an important role to convey the information to the listener such as mood, attitude and emotional state. The glottal pulse characteristics in different phonation types vary due to the tension of laryngeal muscles together with the respiratory effort. In the present study, we are deriving the features that can capture effects of excitation on the vocal tract system through a signal processing method, called as zero-time windowing (ZTW) method. The ZTW method gives the instantaneous spectrum which captures the changes in the speech production mechanism, providing higher spectral resolution. The cepstral coefficients derived from ZTW method are used for the classification of phonation types. Along with zero-time windowing cepstral coefficients (ZTWCCs), we use the excitation source features derived from zero frequency filtering (ZFF) method. The excitation features used are: strength of excitation, energy of excitation, loudness measure and ZFF signal energy. Classification experiments using ZTWCC and excitation features reveal a significant improvement in the detection of phonation type compared to the existing voice quality features and MFCC features.

Offline Mobile Instance Retrieval with a Small Memory Footprint

Abstract: Existing mobile image instance retrieval applications assume a network-based usage where image features are sent to a server to query an online visual database. In this scenario, there are no restrictions on the size of the visual database. This paper, however, examines how to perform this same task offline, where the entire visual index must reside on the mobile device itself within a small memory footprint. Such solutions have applications on location recognition and product recognition. Mobile instance retrieval requires a significant reduction in the visual index size. To achieve this, we describe a set of strategies that can reduce the visual index up to 60-80 times compared to a standard instance retrieval implementation found on desktops or servers. While our proposed reduction steps affect the overall mean Average Precision (mAP), they are able to maintain a good Precision for the top K results (PK). We argue that for such offline application, maintaining a good PK is sufficient. The effectiveness of this approach is demonstrated on several standard databases. A working application designed for a remote historical site is also presented. This application is able to reduce an 50,000 image index structure to 25 MBs while providing a precision of 97% for P10 and 100% for P1.

HEAP: An Efficient and Fault-Tolerant Authentication and Key Exchange Protocol for Hadoop-Assisted Big Data Platform

Abstract: Hadoop framework has been evolved to manage big data in cloud. Hadoop distributed file system and MapReduce, the vital components of this framework, provide scalable and fault-tolerant big data storage and processing services at a lower cost. However, Hadoop does not provide any robust authentication mechanism for principals’ authentication. In fact, the existing state-of-the-art authentication protocols are vulnerable to various security threats, such as man-in-the-middle, replay, password guessing, stolen-verifier, privileged-insider, identity compromization, impersonation, denial-of-service, online/off-line dictionary, chosen plaintext, workstation compromization, and server-side compromisation attacks. Beside these threats, the state-of-the-art mechanisms lack to address the server-side data integrity and confidentiality issues. In addition to this, most of the existing authentication protocols follow a single-server-based user authentication strategy, which, in fact, originates single point of failure and single point of vulnerability issues. To address these limitations, in this paper, we propose a fault-tolerant authentication protocol suitable for the Hadoop framework, which is called the efficient authentication protocol for Hadoop (HEAP). HEAP alleviates the major issues of the existing state-of-the-art authentication mechanisms, namely operating-system-based authentication, password-based approach, and delegated token-based schemes, respectively, which are presently deployed in Hadoop. HEAP follows two-server-based authentication mechanism. HEAP authenticates the principal based on digital signature generation and verification strategy utilizing both advanced encryption standard and elliptic curve cryptography. The security analysis using both the formal security using the broadly accepted real-or-random (ROR) model and the informal (non-mathematical) security shows that HEAP protects several well-known attacks. In addition, the formal security verification using the widely used automated validation of Internet security protocols and applications ensures that HEAP is resilient against replay and man-in-the-middle attacks. Finally, the performance study contemplates that the overheads incurred in HEAP is reasonable and is also comparable to that of other existing state-of-the-art authentication protocols. High security along with comparable overheads makes HEAP to be robust and practical for a secure access to the big data storage and processing services.