Abstract

In this paper we present a new integration method for improving the performance of visual servoing. The method integrates image-based visual servoing (IBVS) and positionbased visual servoing (PBVS) approaches to satisfy the widely varying requirements of the visual servoing process. We define an integration rule for IBVS and PBVS controllers. Density functions that determine the weighting factor of each controller are defined to satisfy the above constraints. We prove that this integration method provides global stability, and avoids local minima. The new integration method is validated on positioning tasks and compared with other switching methods.

Abstract

Many problems in computer vision such as pose recovery and structure estimation are formulated as a minimization process. These problems vary in the use of image measurements directly or using them to extract 3D cues in the minimization process. Hybrid methods have the advantage of combining the 2D and 3D visual information to improve the performance over the above two methods. In this paper, we present a new formulation for minimizing a class of hybrid error functions. This is done by using 2D information from the image space and 3D information from the Cartesian space in one error function. Applications to visual servoing and image alignment problems are presented. The positioning task of a robot arm has been formulated as a minimization problem. Gradient decent as a first order approxima ion and Gauss-Newton as a second order approximation are considered in this paper. Simulation results show, comparing with 2 1/2 D hybrid method, that these two\ methods provide an efficient solution to the features visibility problems and the camera trajectory in the Cartesian space.

Abstract

Security is one of the major concerns of modern software development, but there is a wide gap between the industry practice and the academic instruction. Security issues are usually not addressed in academic setup and those attempt to make it as part of their software engineering curriculum realize quickly that it is difficult to make learning happen in a conventional lecture based approach. We explored a case study centered non-conventional approach and found it to be instrumental in bridging this gap between the industry and the academia. We give a detailed methodology for using the case study and our experience, observations and result of the approach. Whole case exercise aims at creating software professionals who realize the importance of security and are well versed with the related concepts, skills and dispositions and thus handle security related challenges in a structured manner.

Abstract

To bridge the information gap between the agricultural expert and the farmer, International Institute of Information Technology (IIIT), Hyderabad has built the eSagu (“Sagu” means cultivation in Telugu language) system, which is an IT-based personalized agricultural extension system to improve agricultural productivity by disseminating a fresh expert agricultural advice to the farmers, both in a timely and personalized manner. In e-Sagu, the agricultural experts generate the expert advice based on the information about the crop situation received in the form of both text and digital photographs. In Kharif2 2004, a prototype was developed and implemented with 1051 farms. In the prototype, a team of agricultural experts stayed at IIIT, Hyderabad (India) and delivered 20,000 pieces of agricultural expert advice to 1051 cotton farms of three villages (Oorugonda, Gudeppad and Oglapur) in Atmakur Mandal of Warangal district in Andhra Pradesh state, India, by looking at digital photographs and other farm information supplied by some educated and experienced farmers (coordinators) in these villages. The pilot project was implemented successfully. In this article, an analysis of 51 registered farmers’ regarding compliance of advices and corresponding effect is reported. The following of expert advice on pest and disease management and IPM practices were analyzed by giving appropriate scores based on their effect on yield and input cost. The analysis showed that about fifty percent of farmers have followed the practices which increase yield and reduce input cost. A high positive correlation (r=0.46**) was observed between the compliance rate and the yields. Though some farmers obtained same yield as the farmers who have followed the advices, their input costs were significantly higher.

Abstract

Timely agro-advisory service and efficient risk mitigation mechanisms can provide stableincome to the farmers. To provide timely agro-advisory service, e-Sagu systemhas beendeveloped by IIIT-Hyderabad and Media Lab Asia. It is an IT-based personalized agro-advisorysystemwhich is being developedto provide high-qualitypersonalized (farm-specific) agricultural expert adviceto each and everyfarmin a timely manner at thefarmer’s door-step without farmer asking a question. The results show that significantbenefits have flowntothe farmers interms of reducedinputs andenhancedyield.Regarding risk mitigation, the agri-insurance schemes around the worldwhether anadvanced or a developing nation like India are suffering due to catastrophic losses,covariate risks, asymmetric information and lack of quality data. These problems maypose a serious threat to the survival of the implementing agencies unless the there is aneffective monitoring systemin place, with enough man power and robust infrastructure.In this paper we explain how agri-insurance schemes can be effectively implemented ontop of eSagu system. The agri-insurance scheme can bevery cost-effective as it can useresources and processes of eSagu system. Also, as eSagu provides quality and reliabledata at farmlevel,the problemof asymmetric information can be effectively hedged.Most important, eSagualsoimproves the performance offormal risk mitigationmechanisms through farm-specific agro-advisory and monitoring system.

Abstract

Biological systems function with the aid of large number of proteins involved in complex network of chemical reactions. Interfering with the expression of proteins native or foreign leads to overall changes in the functioning of the biological systems . Manipulating the expression of proteins responsible for the manifestation of diseases has therefore been an interesting area for alternative efficient therapautic possibilities. Proteins are expressed from the correspondig genes involving the trancription and translation of messenger RNAs . Interfering with these RNA has emerged as an effective method of silencing unwanted genes. This project deals with designing effective methods for gene silencing through RNA Interference. RNA interference (RNAi) has emerged as an effective method of silencing gene expression in eukaryotic cells. This technology allows scientists to study the phenotypic effect of reducing expression levels of individual genes, and essentially negates the arduous task of producing single gene knockout or dominant negative expressing cell lines. RNAi has very quickly been utilized both in basic science and medical research. Among its many applications are the characterization and regulation of gene function, signaling pathway analysis and target validation. The potential therapeutic value of RNAi is indicated in recent studies showing that the RNAi pathway is functional in mice and is effective against a variety of infectious diseases including HIV and Hepatitis B. Since the early work describing the use of double-stranded RNA (dsRNA) for post-transcriptional gene silencing (PTGS) by Fire and Mello and the application of short interfering RNA (siRNA) to induce specific gene suppression in mammalian cells by Elbashir et al., there has been a flurry of RNAi-related developments and applications. The vast number of recent scientific journal articles, the scramble for intellectual property, and the formation of multiple biotechnology tools, kits, reagents and therapeutics companies all reflect the power and popularity of this technique. In 2002, Science voted RNAi scientific breakthrough of the year. This paper talks about a novel method of finding efficient siRNA targets on the mRNA sequences. It consists of two parts. In the first part program was written to select suitable targets based on the Elbashir's guidelines. In the second part involves prediction of secondary structure of siRNA antisense strands of the targets predicted in the first part and also the secondary structure of the mRNA sequence, and using these results to further filter the targets.

Abstract

Noncanonical base pairs in RNA have strong structural and functional implications but are currently not considered for secondary structure predictions. We present results of comparative ab initio studies of stabilities and interaction energies for the three standard and 24 selected unusual RNA base pairs reported in the literature. Hydrogen added models of isolated base pairs, with heavy atoms frozen in their away from equilibrium geometries, built from coordinates extracted from NDB, were geometry optimized using HF/6-31G** basis set, both before and after unfreezing the heavy atoms. Interaction energies, including BSSE and deformation energy corrections, were calculated, compared with respective single point MP2 energies, and correlated with occurrence frequencies and with types and geometries of hydrogen bonding interactions. Systems having two or more N-HO/N hydrogen bonds had reasonable interaction energies which correlated well with respective occurrence frequencies and highlighted the possibility of some of them playing important roles in improved secondary structure prediction methods. Several of the remaining base pairs with one N-HO/N and/or one C-HO/N interactions respectively, had poor interaction energies and negligible occurrences. High geometry variations on optimization of some of these were suggestive of their conformational switch like characteristics.

Abstract

We present a computationally simple and general purpose scheme for the detection of all salient object contours in real images. The scheme is inspired by the mechanism of surround influence that is exhibited in 80% of neurons in the primary visual cortex of primates. It is based on the observation that the local context of a contour significantly affects the global saliency of the contour. The proposed scheme consists of two steps: first find the edge response at all points in an image using gradient computation and in the second step modulate the edge response at a point by the response in its surround. In this paper, we present the results of implementing this scheme using a Sobel edge operator followed by a mask operation for the surround influence. The proposed scheme has been tested successfully on a large set of images. The performance of the proposed detector compares favourably both computationally and qualitatively, in comparison with another contour detector which is also based on surround influence. Hence, the proposed scheme can serve as a low cost preprocessing step for high level tasks such shape based recognition and image retrieval.

Abstract

Automatic identification of a script in a given document image facilitates many important applications such as automatic archiving of multilingual documents, searching online archives of document images and for the selection of script specific OCR in a multilingual environment. In this paper, we present a scheme to identify different Indian scripts from a document image. This scheme employs hierarchical classification which uses features consistent with human perception. Such features are extracted from the responses of a multi-channel log-Gabor filter bank, designed at an optimal scale and multiple orientations. In the first stage, the classifier groups the scripts into five major classes using global features. At the next stage, a sub-classification is performed based on script-specific features. All features are extracted globally from a given text block which does not require any complex and reliable segmentation of the document image into lines and characters. Thus the proposed scheme is efficient and can be used for many practical applications which require processing large volumes of data. The scheme has been tested on 10 Indian scripts and found to be robust to skew generated in the process of scanning and relatively insensitive to change in font size. This proposed system achieves an overall classification accuracy of 97.11% on a large testing data set. These results serve to establish the utility of global approach to classification of scripts.

Abstract

In this paper, we study the problem of perfectly reliable message transmission(PRMT) and perfectly secure message transmission(PSMT) between a sender S and a receiver R in a synchronous network, where S and R are connected by n vertex disjoint paths called wires, each of which facilitates bidirectional communication. We assume that atmost t of these wires are under the control of adversary. We present two-phase-bit optimal PRMT protocol considering Byzantine adversary as well as mixed adversary. We also present a three phase PRMT protocol which reliably sends a message containing l field elements by overall communicating O(l) field elements. This is a significant improvement over the PRMT protocol proposed in [10] to achieve the same task which takes log(t) phases. We also present a three-phase-bit-optimal PSMT protocol which securely sends a message consisting of t field elements by communicating O(t 2) field elements.