Research Lab

Remote Sensing and Geographic information System together comprise of Geographic Information Science (GIScience) which is a core research field that tries to emphasis on advanced geographic concepts in Geographic Information System and examines the impact of GIS on individuals and society as a whole and re-examines the themes with incorporation of most recent cognitive and Information Science. The Geographic Information System can be defined as a Computer based system and a tool, both hardware, software and procedures, which manages geospatial data, solves spatial problems, and supports collection, storage, transformation, analyzing, retrieving and display of data in a well desired manner. The integration of GIS and Remote Sensing is a field of research and several implementations have been developed to gain the maximum throughput out of these collective fields as these techniques have their own data analysis and data representation methods. The application domain of remote sensing is from a base layer for GIS to the development of thematic datasets, obtaining and extracting data from imagery and generation of unique spatial datasets. In my paper I have focused on the integration of both the fields along with its usage in Analysis and Modelling and also some models of error sources due to the integration of interface of the two techniques. The paper also describes some error sources while integration as GIS and remote sensing both are subject to errors and uncertainty. The paper has discussed some Change Detection Techniques used in the modern sciences with their comparison.
In GIS all the images positioned should be accurate and correctly positioned. All the data layers should be described correctly, must be registered to one another and must be Georeferenced to a specific map projection and coordinate system. Base maps are the frame of reference for positioning and mapping. Remote sensing is the source of thematic data especially data on land use, land cover characteristics and surface elevation. So deriving thematic geospatial data through remote sensing is a big task. The images taken from remote sensing has spatial displacements of objects and variations. Such displacements should be removed in order to create orthorectified image. So for this purpose the data required should be imported from GIS only. Hence they have to be integrated with each other. So for further analysis the output data is fed back into the GIS system and used for other purposes.

Objective: To facilitate the concepts of understanding the problem domain, requirement elicitation and prioritization through real world case. Topic covered in the class to undertake the study: Requirement Elicitation Techniques, Conflict Detection, Requirement Analysis, Requirement Prioritization Techniques, Concept Mapping, Use cases and user stories.

Objective: To facilitate the concepts of understanding the problem domain, requirement elicitation and prioritization through real world case. Topic covered in the class to undertake the study: Requirement Elicitation Techniques, Requirement Analysis, Requirement Prioritization Techniques, Concept Mapping, Use cases and user stories.

—Mining the required information from an enormous amount of data is a critical task. It is arduous to deal with the heterogeneity of astronomically immense data. Withal processing and analyzing it requires a number of resources. In the proposed work, information extraction (relation extraction between two Named entity mentions) from Wikipedia text articles using DeepDive has been carried out. We have experimented Deep-Dive's challenging capabilities for relation extraction, mention extraction and have calculated the probabilities of every variable being true via statistical learning and inference. Further we have tested results by plotting calibration plots on training data set and on whole data set by considering performance measures to check its efficiency on Wikipedia articles.

Use case modeling refers to the process of identifying scenarios written in some natural language text, particularly to capture interactions between the system and associated actors. Several approaches have been proposed to maintain the synergy of use cases with other software models, but no systematic transformation approach is available to extract use case scenarios from the textual requirements specification. In this paper, we propose a systematic transformation approach that automatically extracts various use case elements from textual problem specifications. The approach uses Natural Language (NL) parser to identify Parts-Of-Speech (POS) tags, Type Dependencies (TDs) and semantic roles from the input text specification to populate use case elements. It further makes use of the questionnaire-based approach to develop the remaining unpopulated parts of the use case template. The paper demonstrates the applicability of the proposed approach by applying both industry and research-level case studies. The results highlight that the generated output is correct, consistent, non-redundant and complete, and helpful to use case developers in further analysis and documentation. CCS CONCEPTS • Software and its engineering → Software notations and tools;

Requirements Engineering (RE) is known to be critical for the success of software projects, and hence forms an important part of any Software Engineering (SE) education curriculum offered at tertiary level. In this paper, we report the results of an exploratory pilot study conducted to assess the effectiveness of Case-Based Learning (CBL) methodology in facilitating the learning of several RE concepts. The evaluation was made on the basis of graduate students' responses to a set of questions representing various key learning principles, collected after the execution of two CBL sessions at DA-IICT, Gandhinagar (India). We investigate the perceived effectiveness of CBL in students' learning of various RE concepts, based on factors like case difference, gender diversity, and team size. Additionally, we collect and analyze the Teaching Assistants' (TAs) opinions about the conducted CBL sessions. The outcome of this CBL exercise was positive as maximum students were able to achieve all the five stated learning objectives. The authors also report various challenges, recommendations, and lessons learned while experiencing CBL sessions.

Case-Based Learning (CBL) is an established teaching methodology approach used across several disciplines where students apply their theoretical knowledge to real-world scenarios. Application of CBL in several disciplines raises questions regarding writing cases followed by effectively executing the learning based on them. In this paper, we report the results of a preliminary review study performed in understanding the history behind the adoption of CBL in different domains such as law, science/medical, business, engineering, and software engineering through a targeted literature survey. Consequently, we report various challenges and guidelines recommended by the existing literature on CBL across such disciplines.

This is an Android-based application in which an automatic alarm ringing system is implemented. It focuses on doctor and patient interaction. Patients need not remember their medicine dosage timings as they can set an alarm on their dosage timings. The alarm can be set for multiple medicines and timings including date, time and medicine description. A notification will be sent to them through email or message inside the system preferably chosen by the patients. They can search doctor disease wise. The patients will get the contact details of doctors as per their availability. Also the users can see different articles related to medical fields and health care tips. The system focuses on easy navigation and good user interface. Many such Medical Reminder Systems have been developed where a new hardware is required but in our work we have made an attempt to develop a system which is economical, time-saving and supports medication adherence.

Remote Sensing and Geographic information System together comprise of Geographic Information Science (GIScience) which is a core research field that tries to emphasis on advanced geographic concepts in Geographic Information System and examines the impact of GIS on individuals and society as a whole and reexamines the themes with incorporation of most recent cognitive and Information Science. The Geographic Information System can be defined as a Computer based system and a tool, both hardware, software and procedures, which manages geospatial data, solves spatial problems, and supports collection, storage, transformation, analyzing, retrieving and display of data in a well desired manner. The integration of GIS and Remote Sensing is a field of research and several implementations have been developed to gain the maximum throughput out of these collective fields as these techniques have their own data analysis and data representation methods. The application domain of remote sensing is from a base layer for GIS to the development of thematic datasets, obtaining and extracting data from imagery and generation of unique spatial datasets. In my paper I have focused on the integration of both the fields along with its usage in Analysis and Modelling and also some models of error sources due to the integration of interface of the two techniques. The paper also describes some error sources while integration as GIS and remote sensing both are subject to errors and uncertainty. The paper has discussed some Change Detection Techniques used in the modern sciences with their comparison. In GIS all the images positioned should be accurate and correctly positioned. All the data layers should be described correctly, must be registered to one another and must be Georeferenced to a specific map projection and coordinate system. Base maps are the frame of reference for positioning and mapping. Remote sensing is the source of thematic data especially data on land use, land cover characteristics and surface elevation. So deriving thematic geospatial data through remote sensing is a big task. The images taken from remote sensing has spatial displacements of objects and variations. Such displacements should be removed in order to create orthorectified image. So for this purpose the data required should be imported from GIS only. Hence they have to be integrated with each other. So for further analysis the output data is fed back into the GIS system and used for other purposes.

Case-Based Learning (CBL) is an established teaching methodology approach used across several disciplines where students apply their theoretical knowledge to real-world scenarios. Application of CBL in several disciplines raises questions regarding writing cases followed by effectively executing the learning based on them. In this paper, we report the results of a preliminary review study performed in understanding the history behind the adoption of CBL in different domains such as law, science/medical, business, engineering, and software engineering through a targeted literature survey. Consequently, we report various challenges and guidelines recommended by the existing literature on CBL across such disciplines. CCS CONCEPTS • Social and professional topic → Software engineering education; • General and reference → Document Types; Surveys and overviews;

The diagnosed cases of Breast cancer is increasing annually and unfortunately getting converted into a high mortality rate. Cancer, at the early stages, is hard to detect because the malicious cells show similar properties (density) as shown by the non-malicious cells. The mortality ratio could have been minimized if the breast cancer could have been detected in its early stages. But the current systems have not been able to achieve a fully automatic system which is not just capable of detecting the breast cancer but also can detect the stage of it. Estimation of malignancy grading is important in diagnosing the degree of growth of malicious cells as well as in selecting a proper therapy for the patient. Therefore, a complete and efficient clinical decision support system is proposed which is capable of achieving breast cancer malignancy grading scheme very efficiently. The system is based on Image processing and machine learning domains. Classification Imbalance problem, a machine learning problem, occurs when instances of one class is much higher than the instances of the other class resulting in an inefficient classification of samples and hence a bad decision support system. Therefore EUSBoost, ensemble based classifier is proposed which is efficient and is able to outperform other classifiers as it takes the benefits of both-boosting algorithm with Random Undersampling techniques. Also comparison of EUSBoost with other techniques is shown in the paper.

Remote Sensing and Geographic information System together comprise of Geographic Information Science (GIScience) which is a core research field that tries to emphasis on advanced geographic concepts in Geographic Information System and examines the impact of GIS on individuals and society as a whole and re-examines the themes with incorporation of most recent cognitive and Information Science. The Geographic Information System can be defined as a Computer based system and a tool, both hardware, software and procedures, which manages geospatial data, solves spatial problems, and supports collection, storage, transformation, analyzing, retrieving and display of data in a well desired manner. The integration of GIS and Remote Sensing is a field of research and several implementations have been developed to gain the maximum throughput out of these collective fields as these techniques have their own data analysis and data representation methods. The application domain of remote sensing ...

Case-Based Learning (CBL) is an established teaching methodology approach used across several disciplines where students apply their theoretical knowledge to real-world scenarios. Application of CBL in several disciplines raises questions regarding writing cases followed by effectively executing the learning based on them. In this paper, we report the results of a preliminary review study performed in understanding the history behind the adoption of CBL in different domains such as law, science/medical, business, engineering, and software engineering through a targeted literature survey. Consequently, we report various challenges and guidelines recommended by the existing literature on CBL across such disciplines. CCS CONCEPTS • Social and professional topic → Software engineering education; • General and reference → Document Types; Surveys and overviews;