The pandemic has reshaped our perspective on education, not just in mainstream schools but also in special education settings. There’s been a widespread shift towards AI and online learning. Within the realm of special education, the shift to online instruction for students with visual disabilities predominantly centered around audio cues. Despite the convenience of audio learning, the importance of Braille education became evident during this transition. This paper provides a comprehensive analytical study on reading comprehension and audio comprehension among students with visual disabilities. It delves into why audio comprehension is often preferred, while emphasizing the ongoing importance of Braille. The objective of this initiative is to promote an inclusive learning environment that proves more effective and fruitful for individuals with visual disabilities.

In recent years, with the emergence of online learning platforms and e-learning resources, many documents are available for a particular topic. For a better learning experience, the learner often needs to know and learn first the prerequisite concepts for a given concept. Traditionally, the identification of such prerequisite concepts is done manually by subject experts, which in turn, often limits self-paced learning. Recently, machine learning models have found encouraging success for the task, obviating manual effort. In this paper, we propose a graph neural network based approach that leverages node attention over a heterogeneous graph to extract the prerequisite concepts for a given concept. Experiments on a set of benchmark data show that the proposed model outperforms the existing models by large margins almost always, making the model a new state-of-the-art for the task.

The consideration of accessibility has become a crucial aspect in system design to eliminate barriers for people with disabilities. This paper presents the android application which transliterates Indian languages like Odia, Bengali, Hindi, Telugu and English to their respective braille script. It includes the prospect of voice-based search apart from the text-based search for people with visual disabilities to access reading materials in Indian regional braille scripts. The goal of this initiative is to foster an inclusive learning environment and assist special educators in acquiring, sharing, and delivering educational resources that are accessible to all.

Reading is an essential component of language skills. But with dyslexia, people face difficulty in reading. As it is a language-based disability, it can be found while reading any language. In the case of Bangla and Hindi, the presence of diphthongs, triphthongs, and nasal vowels increase the difficulty. To address these problems and help the children with dyslexia to read sentences in Bangla and Hindi, the proposed system was developed to offer reading through a multisensory teaching approach using seeing, hearing, speaking, and writing. It teaches sentences using a word-by-word manner, which increases the effectiveness of learning. The proposed system makes the learning experience interactive by offering a feedback mechanism that uses three measures, reading accuracy, writing accuracy, and response time. For each sentence, the response time is being stored in the database in the form of a chart for future evaluation of the user. Using a multisensory teaching approach, the proposed system helps the special educators by reducing their effort, and the performance chart will help the educators to design the future lesson plan for the user.

We present design and development of a web browser that allow easy dissemination of information through World Wide Web for people with cerebral palsy in India. Our focus user group comprises people with severe form of spastic cerebral palsy and highly restricted motor movement skills. Throughout the development process we have interacted with the target users to understand their requirements and to get design advises. The browser is augmented with an intelligent auto-scanning mechanism through which the web contents and browser GUI controls can be accessed with less time and effort. We have field tested the browser with the target users where preliminary evaluation results suggests that the proposed browser is quite effective in terms of task execution time, cognitive effort and overall usability.

In this paper we have developed a toolset that will allow people with severe spastic cerebral palsy (CP) and highly restricted motor movement skills to access popular social-networking and communication mediums like, Facebook and E-mails. To understand the requirements of the intended users we have performed a number of surveys that acted as basis of our system design. The developed tools use special access switch based scanning technique for easy navigation in different applications. We have evaluated the toolset with six target users. The preliminary results demonstrate a positive response.

Numerous sensors are involved in sensing almost everything around us in a cyber-physical system. They generate heterogeneous data which are diverse in format and protocol. Prevailing standards formally define sensor data encodings and provide syntactic interoperability but failed to provide semantic capability required for searching, reasoning, querying on sensors and their observations. The paper extends IEEE SUMO and Onto Sensor to create an ontological structure that captures various sensor concepts and their relationships. It logically classifies sensor information into four major sensor knowledge representation (1) hierarchy (2) data (3) function and (4) data exchange. The proposed sensor ontology has been extended for energy meter as an energy sensor. The represented semantic can be captured through Protégé 4.3.0 and subsequently by OWLXML. Reasoning on the sensor data can be carried out using SWRL.

The paper presents design and development of WebSanyog, an Android based web browser that helps people with severe form of spastic cerebral palsy and highly restricted motor movement skills to access web contents. The target user group has acted as our design advisors through constant interaction during the whole process. Features like, auto scanning mechanism, predictive keyboard and intelligent link parser make the system suitable for our target users. The browser is primarily developed for mobile and tablet based devices keeping in mind the portability issue.

In recent times, many human-centric applications are being developed to leverage the diverse range of sensors present in Android smartphones. Smartphones are also being used as edge network gateways for fusing data from multiple sensors. These applications often run as background services and usuall

Smartphones are currently being used to develop diverse range of applications (apps) involving sensors. These apps generally acquire and analyze sensor data and are usually implemented as background services. The importance values of Android processes are in a hierarchy of foreground, visible, background etc. in decreasing order of importance. Whenever a new process arrives, it may necessitate removal of old and less important processes for reclaiming memory. Current smartphones do not provide any options through which user's idea of priority can override that of the system defaults. In this work we present an implementation that enables the user to obtain alerts on system load and recommendations to proactively kill a set of processes to reclaim system memory. This enables user selected background process to be spared from the standard android policy of process termination, in lieu of foreground apps, relatively unimportant from user perspective, during that period. We show that manual reclaiming of memory based on recommendations from our app, reduces the automatic killing and measurement lag experienced by a sensor analytics app under test. This work is redundant if processing power and main memory of a smartphone is always surplus than required for its normal usage.

The tagged signal model (TSM) is a formal framework for modeling heterogeneous embedded systems. In the present work, we provide a representation of tagged systems using the semantics of Kleene algebra. We further illustrate mechanisms for both behavioral transformational verification through equivalence checking and property verification of heterogeneous embedded systems based on this algebraic representation.

An emotional text may be judged to belong to multiple emotion categories because it may evoke different emotions with varying degrees of intensity. For emotion analysis of text in a supervised manner, it is required to annotate text corpus with emotion categories. Because emotion is a very subjective entity, producing reliable annotation is of prime requirement for developing a robust emotion analysis model, so it is wise to have the data set annotated by multiple human judges and generate an aggregated data set provided that the emotional responses provided by different annotators over the data set exhibit substantial agreement. In reality, multiple emotional responses for an emotional text are common. So, the data set is a multilabel one where a single data item may belong to more than one category simultaneously. This article presents a new agreement measure to compute interannotator reliability in multilabel annotation. The new reliability coefficient has been applied to measure the quality of an emotion text corpus. The procedure for generating aggregated data and some corpus cleaning techniques are also discussed.

This paper proposes a methodology for performance evaluation of schedules for job-shops modeled using tag machines. The most general tag structure for capturing dependences is shown to be inadequate for the task. A new tag structure is proposed. Comparison of the method with existing ones reveals that the proposed method has no dependence on schedule length in terms of modeling efficiency and it shares the same order of complexity with existing approaches. The proposed method, however, is shown to bear promise of applicability to other models of computation and hence to heterogeneous system models having such constituent models.

In this paper we present a speech enabled bidirectional automatic Indian language text to Braille transliteration system. The system allows bridging the communication gap between a visually impaired and a sighted person. The present system can be configured to take Indian language text document as input and based on some transliteration rules, can generate the corresponding Braille output. The system is augmented by an Indian language text-to-speech (TTS) system through which a user can get instantaneous audio feedback from the input text. We further extended the system to support transliteration of Dzongkha1text to Braille. Finally we present an Audio QWERTY editor which allows a visually impaired person to read and write Indian language texts through a computer.

The performance of the acoustic models is highly reflective on the overall performance of any continuous speech recognition system. Hence generation of an accurate and robust acoustic model holds the key to satisfactory recognition performance. As phones are found to vary according to the position of occurrence within a particular word, context information is of prime importance in acoustic modeling of phonetic signals. In this paper we look at the effect of triphone-based acoustic modeling over monophone based acoustic models in the context of continuous speech recognition in Bengali. Keeping in mind the lack of training resources for triphone-based acoustic modeling in Bengali, we have also described herein, the method of generating triphone clusters using decision tree based techniques. These triphone clusters have then been used to generate tied-state triphone based acoustic models to be used in a continuous speech recognizer.

This paper presents a prototype Text-To-Indian Sign Language (ISL) translation system. The system will help dissemination of information to the deaf people in India. This paper also presents the SL-dictionary tool, which can be used to create bilingual ISL dictionary and can store ISL phonological information.

Scanning keyboards are used as augmentative communication aids by persons with severe speech and motion impairments. Literature reports two approaches for the design of scanning keyboards; design based on the experience and intuition of designers and user model based design methods. None of these approaches, however, considers user errors in the design process, potentially limiting the practical usefulness of the designs. We have performed experiments in order to study user errors on scanning keyboards. We have found that two types of errors affect performance of scanning keyboard users significantly, namely (a) timing error that occurs when a user fails to select a key at the appropriate time and (b) selection error that occurs when the user selects a wrong key. These errors have been found to increase users’ text entry time by as high as 65% and 35%, respectively. Based on empirical observations, we have developed a state transition model of user behavior during user–keyboard interaction. The model comprises of four states, each of which represents the physical and cognitive state of the user at particular instant of the interaction. The transitions are caused by users’ physical, cognitive and perceptual activities. We have found that the errors could be explained as caused due to the problems in making the transitions properly. In addition to explaining errors, the model has helped us to predict distribution of error probabilities with respect to the distance between keys. We have used the model predicted error distributions to develop principles for scanning keyboard design that aim to reduce user errors. The principles state that the frequently used key pairs should be placed apart by a minimum distance, which has been obtained from the error distributions, in order to reduce errors. The method and results of the study, the user model and the design principles are presented in this paper.

The increasing processing power of embedded devices have created the scope for certain applications that could previously be executed in desktop environments only, to migrate into handheld platforms. An important feature of the computing systems of modern times is their support for applications that interact with the user by synthesizing natural speech output. Such applications deliver state of the art performance in desktop environments. However, the real-time performance of such applications in handheld platforms with on-line incoming text streams have not been explored till date. In this work, the performance of a text to speech synthesis application is evaluated on embedded processor architectures and modifications in the underlying hardware platform are proposed for real time performance improvement of the concerned application.

Virtual scanning keyboards are augmentative communication systems used by people with speech and motor impairments. Each of these systems consists of (a) a virtual keyboard and (b) a scanning input method. Designers of these systems need to choose from a large number of design alternatives, which requires evaluating alternate designs. Evaluation of alternate virtual scanning keyboard designs with disabled users is problematic due to the difficulties in (a) getting sufficient number of users for evaluation, particularly in countries like India where social conditions prevent many potential users from participating in the design process and (b) collecting sufficiently large data for analysis due to users' physical disabilities. The problems can be alleviated with the use of model based design methods. In model based design, models of user performance are employed to evaluate designs automatically, thus reducing the need for extensive user testing. Existing performance models of motion impaired users, however, do not consider scanning input methods. This limits the applicability of the existing models to the design of virtual scanning keyboards. To address the limitation, we developed performance models of virtual scanning keyboards. The models are validated by comparing the model predictions with results from user trials. Development and validation of the performance models are described in this paper.

In countries like India, a great deal of diversity exists in language, culture and socio-economic conditions. In order to deliver computer aided education, efforts have to be put for proper management of concerned domain and learning materials keeping in mind this diversity. Participatory authoring of domain knowledge structure is of immense importance in this regard. In this paper, we describe a knowledge structure which is effective in capturing the structure of the learning materials of school level subjects. Ontologies have gained importance in representing the knowledge of the domain in a formal and machine understandable form in areas like intelligent information processing. Thus it can provide the platform for effective extraction of information and many other applications. We describe different aspects of manual ontology engineering in developing application specific domain ontology. The domain of our interest is the education domain where we are interested in retrieving relevant Web documents for the curriculum related requirements of school students. We identify an effective way of structuring the knowledge about these domains, which allows us to clearly demarcate the roles of topics, concepts, and actual words. We also describe applications in the area of information retrieval and in indexing document repositories in connection with e-learning where our ontology plays an important role. In this paper, we have provided a framework, Sahayika, for building knowledge structures in education domain.

Internet is a huge repository of quality learning materials and continues to grow in a faster rate. The school students may be benefited immensely as these learning materials may well supplement their curricular requirements. But Access to the Internet is costly, because it is very expensive to maintain a persistent Internet connection. For some schools in the developing countries like India, this cost may not be affordable specifically in rural schools. This makes way to a digital divide between the rural and urban schools which is unwanted. For these rural schools, limiting the amount of bandwidth consumed is of paramount importance. It is necessary that the schools be connected to the Internet for the least time, in order to minimize the access cost. In this paper, we present a system Samvidha that allows the rural school students to access the Internet contents in an offline fashion.

Low literacy scenario in India and other developing nation demands an alternative learning environment to deal with the problem. Lack of trained teachers, high dropout rates are some of the major problems that need to be addressed. Intelligent Tutoring System (ITS) or ITS Authoring tools (ITSAT) can be thought of as a possible solution to these problems. In this paper we present Shikshak, an ITSAT developed by us and discuss its deployment in the district of Paschim Medinipur, West Bengal along with its sample effect on primary education.

The advent of multi-core embedded processors has brought along new challenges for embedded system design. This paper presents an efficient, battery aware, code partitioning technique for a text to speech system, which is executed on a multi-core embedded processor. The system achieves significant performance improvements both in terms of execution time as well as battery lifetimes. The mentioned technique provides a new paradigm for battery aware embedded system design which can be easily extended to other applications

Braille and audio feedback based systems have vastly improved the lives of the visually impaired across a wide majority of the globe. However, more than 13 million visually impaired people in the Indian sub-continent could not benefit much from such systems. This was primarily due to the difference in the technology required for Indian languages compared to those corresponding to other popular languages of the world. In this paper, we describe the Sparsha toolset. The contribution made by this research has enabled the visually impaired to read and write in Indian vernaculars with the help of a computer.

In India, the population with severe neuro-motor impairments (like people suffering from cerebral palsy) faces an acute problem with electronic-learning because there is a dearth of quality learning aids available for them. By quality learning aids we mean certain softwares that can help this section of special users to learn fast and at the same time with ease. Though similar systems are available in the international market, all of such products have a cost ranging from a few hundred to a few thousand dollars. For an average Indian user, they are too costly to afford. Moreover these products come in foreign languages which cannot facilitate the learning of the Indian languages. Keeping these two problems in focus, we have tried to design and develop a few learning aids which helps these section of users to learn and that too in their own languages. All these tools are indigenous and at the same time available at an affordable price. In this paper we would discuss about a predictive virtual keyboard, which not only helps these users to learn typing but also helps them to write essays, letters, and even compose poetry. All of these they can do in their own language.

The contract net protocol (CNP) is a widely used coordination mechanism in multiagent systems. It has a lot of communication overhead due to the broadcast of the task announcements. The performance of the CNP degrades drastically when the number of communicating agents and the number of tasks announced increases. Hence, it has problems of scalability. In order to overcome this limitation, an instance-based learning (IBL) mechanism is designed that uses previously stored instances in order to select a target agent. This avoids the expensive bidding process. The scheme is implemented in a simulated distributed hospital system where the CNP is used for resource sharing across hospitals. Experimental results demonstrate that with the incorporation of the IBL, the system performance improves significantly. The system is better scalable with respect to the number of tasks.

An important feature in a distributed problem solving system is that the resources of different nodes can be shared through cooperation. In this paper, the generalized partial global planning (GPGP) approach used for multiagent systems is extended by providing a coordination mechanism for resource sharing across nodes. In our framework, multiple conflicting criteria (or objectives) like quality, cost, and duration may be associated with an input task. Preference ratings expressed subjectively may be assigned to each of the criteria. Task assignment in this system, which is a multiobjective decision making problem, is important for the satisfaction of the criteria. It has to be done with imprecise information since the system is dynamic and preference ratings are specified subjectively. A technique for task assignment using the fuzzy set approach is also presented in this paper. Simulation studies for the coordination mechanism and the task assignment have been performed to demonstrate their effectiveness.

For Part I, see ibid., pp. 2162-7 (2000). We present an algorithm for state estimation under partial observation with time using an extended TTM (timed transition models). In particular, given the reachability graph (RG) of the original underlying TTM, the observer computes the state uncertainty that arises due to immeasurable state transitions along the given trajectories of the RG of the system, after the occurrence of every measurable transition or tick. The algorithm is illustrated by an example of a single-cylinder hydraulic punching machine.

For pt. II, see ibid., pp. 2168-73 (2000). Discusses the problem of fault diagnosis in a discrete event dynamic system (DEDS). We consider the timed transition model (TTM) framework for modeling DEDS behavior over time. We continue our discussion of issues related to modeling and state observation in TTMs for systems with unmeasurable variables by first discussing how faults are modeled in the extended framework of Part I (see ibid., pp. 2162-7, 2000). We then discuss the problem of state observation with delay, originally discussed in the context of finite state machines by C.M. Ozveren et al. (1990) and S. Bose et al. (1994). Finally, we show how a "with-delay observer" can be used for the detection and diagnosis of faults in a system modeled as a DEDS using the TTM framework.

Presents a timed automata approach for modeling discrete event dynamic systems (DEDS) in the context of supervision and monitoring of industrial processes by extending the TTM (timed transition model) framework. First, we propose the notion of measurement, and the consequent measurability or distinguishability of the measurement equivalence of state maps and transitions. This framework can be used for solving inferential problems in the area of state estimation and fault diagnosis. The state observation problem using this framework is solved with an example in a companion paper. We also characterize a number of reachability relations that help to capture the uncertainty of the system for a given sequence of measurable transitions.

An increasing number of components in embedded systems are implemented by software running on embedded processors. This trend creates a need for compilers for embedded processors capable of generating high quality machine code. Particularly for DSPs, such compilers are hardly available, and novel DSP-specific code optimization techniques are required. In this paper we focus on efficient address computation for array accesses in loops. Based on previous work, we present a new and optimal algorithm for address register allocation and provide an experimental evaluation of different algorithms. Furthermore, an efficient and close-to-optimum heuristic is proposed for large problems.

This paper describes a new code optimization technique for digital signal processors (DSPs). One important characteristic of DSP algorithms are iterative accesses to data array elements within loops. DSPs support efficient address computations for such array accesses by means of dedicated address generation units (AGUs). We present a heuristic technique which, given an AGU with a fixed number of address registers, minimizes the number of instructions needed for array address computations in a program loop.

This paper presents the knowledge representation schemes adopted in MICKEY, a knowledge based system for designing microprocessor based systems. MICKEY is essentially a hybrid expert system, using rules and procedures for achieving the different design tasks. We briefly describe the hierarchy of tasks in this problem domain, and emphasize on the refinement paradigm, constraint propagation, conflict resolution and task management strategies adopted in MICKEY. Next, we dwell upon the different knowledge sources and their functions, with respect to the particular design domain. Finally, we present an industrial design, achieved by MICKEY, to demonstrate its applicability.

In CAD systems, it is often required to implement desired behaviors by some available device. The selection of the device that can implement the behavior, and the required interfacing, is usually done by human experts. The interface consists of transformations that may have to be performed on the inputs and outputs of the device. This paper describes an approach to automatically derive the specifications of the device's interface. For sequential circuits, the behaviors are often represented as FSMs, and hence the task is to determine whether the FSM of the desired function can be contained in the FSM of the device, subject to the transformations of the interface. A related objective, addressed in this paper, is to model the behaviors of complex devices in a way that facilitates the analysis.

An environment with multiple expert modules is essential for proper handling of diagnosis and monitoring of chronic endemic diseases. In this paper, we present LEPDIAG/spl minus/a knowledge based system for diagnosis and monitoring of leprosy. The proposed architecture is a conglomeration of three expert modules and a procedural performance evaluator. A novel feature of the architecture is inclusion of the homeostatic expert module which models the immunological reaction of the patient. The entire system provides a closed loop diagnosis and follow-up environment. LEPDIAG is built around the fuzzy expert system building tool FRUIT for dealing with imprecise knowledge. The domain knowledge in LEPDIAG is expressed by fuzzy production rules. The rules have been partitioned using suitable clustering criteria. The rule conflict is resolved using metarules. The information objects used and the fuzzy inference strategy adopted have been illustrated.>

In order to design microprocessor-based application systems, several cooperating tasks have to be performed, such as the design of the skeletal process, hardware-software partitioning, design of the hardware configuration, interface design for the selected I/O devices, and generation of application specific software code. This paper presents an integrated CAD framework for automatically designing such hardware configurations and software code, to achieve the functionalities of the desired application. The design of an ECG monitoring system has been presented to illustrate the efficacy of the system.

We present a computationally efficient method for deriving the most appropriate transformation and mapping of a nested loop for a given hierarchical parallel machine. This method is in the context of our systematic and general theory of unimodular loop transformations for the problem of iteration space partitioning [7]. Finding an optimal mapping or an optimal associated unimodular transformation is NP-complete. We present a polynomial time method for obtaining a ‘good’ transformation using a simple parameterized model of the hierarchical machine. We outline a systematic methodology for obtaining the most appropriate mapping.

The authors address the issue of area-time trade off in VLSI circuits using the BILBO methodology of BIST. The issue has been dealt with in an integrated manner. Two distinct approaches, integer linear programming and graph theoretic have been presented.>

The authors present a parallel algorithm for logic simulation of VLSI circuits. It is implemented on a network of transputers connected in a ring topology. The approach is based on partitioning a functionality matrix representation of the circuit among the transputers and adopting a data flow technique for the solution. A significant aspect of the algorithm is that it overlaps computation with communication, thereby reducing the communication overhead. It also attempts even distribution of load in order to reduce processor idle time. The algorithm possesses the advantages of ease of implementation and ease of extension to incorporate additional parameters for simulation. Performance results of the algorithm are given.>

When BILBO tests are being generated and scheduled, resource conflicts between I-paths and tests present many difficulties. The authors explore: how pipelining is limited by potential internal conflicts; ways to promote pipelining during test plan generation and how to incorporate a test into a test phase already containing tests that conflict with it. They do not directly address the general problems of test plan generation or test scheduling. What is offered is insight into the difficulties that (potential) conflicts provide and techniques for handling these difficulties. The insights are primarily theoretical, but the resulting techniques could be viewed as possible extensions to existing methodologies.>

Article Free Access Share on Loop partitioning for distributed memory multiprocessors as unimodular transformations Authors: D. Kulkarni Center for Development of Advanced Computing, 2/1 Brunton Road, Bangalore 560 025, India Center for Development of Advanced Computing, 2/1 Brunton Road, Bangalore 560 025, IndiaView Profile , K. G. Kumar Center for Development of Advanced Computing, 2/1 Brunton Road, Bangalore 560 025, India Center for Development of Advanced Computing, 2/1 Brunton Road, Bangalore 560 025, IndiaView Profile , A. Basu Center for Development of Advanced Computing, 2/1 Brunton Road, Bangalore 560 025, India Center for Development of Advanced Computing, 2/1 Brunton Road, Bangalore 560 025, IndiaView Profile , A. Paulraj Center for Development of Advanced Computing, 2/1 Brunton Road, Bangalore 560 025, India Center for Development of Advanced Computing, 2/1 Brunton Road, Bangalore 560 025, IndiaView Profile Authors Info & Claims ICS '91: Proceedings of the 5th international conference on SupercomputingJune 1991 Pages 206–215https://doi.org/10.1145/109025.109079Published:01 June 1991Publication History 7citation207DownloadsMetricsTotal Citations7Total Downloads207Last 12 Months7Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF

The architecture of CONEX-expert system for control system design and analysis-is presented. The important features of CONEX are discussed and they include: a structured organization of the short-term database, a clustering criteria for partitioning the rule-base into connected rule-spaces, a language for representing the domain-specific rules, and an inference engine that can adopt different search strategies for different rule-spaces. Additionally, an explanation generation module gives CONEX the attribute of user friendliness.>