Skew recognition
Skew detection has been an important part of the document recognition system. If the document includes the skew it will be difficult for reader to read the document. In the proposed work, new techniques that detecting the angle of skewed document. The main advantage is that the method works on all types of scripts. These techniques successfully handle the skew detection and correction of the printed and handwritten document. The detection and correction of document skew is one of the most important document image analysis steps. Page layout analysis and pre-processing operations used for character recognition depend on an upright image or, at least, knowledge of the angle of skew. A few methodologies have been proposed as choices for skew point identification of document images. Profile project technique is a popular method for skew detection. It is capable of locating fragmented lines in a binary image. Therefore given a group of black pixels, one can find the imaginary line or lines that go through the maximum number of these pixels. Existing techniques doesn’t work for images in which there is unequal space patterns in between the lines. Existing techniques cannot detect the skew in multiscript documents. Existing system is not capable of detecting correcting the upward and downward skew together in a single text document. Existing system Rotate the whole document at once to correct the skew from the given text document. A lot of work is required to be done in context of skew detection and correction for multiscript text images. These problems are required to be solved to make use of the system in the real world applications. The proposed system for skew detection and correction is implemented with the help of scan line algorithm along with hough transformation algorithm. Proposed system works on the document in line by line basis i.e. detect and correct the skew of every line independently. It can work on the documents having multiple scripts on it. It can detect and correct the skew from the documents even if there is an unequal space in between the two adjacent lines. It will rotate the document on line by line basis to correct the skew from the given document. Detects and correct the upward and downward skew together in the single text document. The major problem with the existing systems was that they just rotate the entire document in the reverse direction of the angle detected to remove the skew but the proposed system process the document on the line by line basis using scan line algorithm and skew angle is detected with the help of hough transformation. The performance of the proposed system is calculated on various images having different types of skew in them. The overall accuracy of the proposed system is 98% which is far better than that of existing system. In future the proposed system can be extended for coloured images and other types of documents. Proposed system can also be extended to made it for word level skew detection and correction to get more accuracy.
Published by: Lovepreet, Sarabjeet Kaur
Author: Lovepreet
Paper ID: V6I5-1405
Paper Status: published
Published: October 28, 2020
Cotton plant disease detection
Agriculture is one of the major sectors of the Indian economy and food security. Agriculture needs to find new ways to improve efficiency, production and yields. Approximately 30-35% of the yield gets affected by pests and diseases. The reason it happens is because these diseases are detected at a late stage which gets difficult to control. Hence, advancement in image processing technology and automated learning plays an important role in plant disease detection especially image processing and machine learning. On the other hand, manually detecting diseases in plants needs a tremendous amount of work, expertise and is very expensive because of the involvement of an expert or a plant pathologist. This paper majorly focuses on the need for a solution for early detection of cotton plant diseases, the diseases of cotton and their characteristics, different challenges farmers face while cultivating cotton and while identifying diseases in them, and the step by step technical approaches being used for the detection of cotton plant diseases. There is a lot scope in the advancement of technologies to improve the production by detecting and providing solutions to the farmers on an urgent basis. Agriculture is one of the major sectors of the Indian economy and food security. Agriculture needs to find new ways to improve efficiency, production and yields. Approximately 30-35% of the yield gets affected by pests and diseases. The reason it happens is because these diseases are detected at a late stage which gets difficult to control. Hence, advancement in image processing technology and automated learning plays an important role in plant disease detection especially image processing and machine learning. On the other hand, manually detecting diseases in plants needs a tremendous amount of work, expertise and is very expensive because of the involvement of an expert or a plant pathologist. This paper majorly focuses on the need for a solution for early detection of cotton plant diseases, the diseases of cotton and their characteristics, different challenges farmers face while cultivating cotton and while identifying diseases in them, and the step by step technical approaches being used for the detection of cotton plant diseases. There is a lot scope in the advancement of technologies to improve the production by detecting and providing solutions to the farmers on an urgent basis.
Published by: Tejaswi Pallapothu, Harshita Nangia, Manmeet Singh, Riya Sinha, Prashant Udawant
Author: Tejaswi Pallapothu
Paper ID: V6I5-1401
Paper Status: published
Published: October 28, 2020
Encroaching the legislative field? Purposivism v. Textualism in practice: A clear distinction or a convergence of theories: Analysis of Cardozo’s Methods of statutory interpretation
The Judge laws down the law, is a statement that is more often that not under dispute. Interpretation of States has a wider connotation and an impressive history situated in the common law tradition. In certain events the judges interpret the statute as it means i.e. to the text and at others wherein there exist legislative discrepancies the judges interpret the law as per individual judicial discretion. The statement the Judge laws down the law is under dispute because it is the task of the legislative to draft the laws of a nation and that of the judiciary to implement in practice. The idea of judicial law-making albeit not ideal to separation of powers has seen a growth in recent times. This paper aims in delimiting judicial discretion as explained by Benjamin Cardozo in several of his works. While judicial discretion prima facie cannot be disputed upon but there exist limits to such discretion. This paper primarily focuses upon textualism and purposivism in the interpretation of statutes. As different they are, they also need to co-exist and operate separately at times for the functioning of the judicial machinery.
Published by: Priya Dharshini A.
Author: Priya Dharshini A.
Paper ID: V6I5-1374
Paper Status: published
Published: October 28, 2020
Using ensemble random forest, boosting and base classifiers to ameliorate prediction of students’ academic performance
In recent time, educational data mining (EDM) has received substantial considerations. Many techniques of data mining have been proposed to dig out out-of-sight knowledge in educational data. The Knowledge obtained assists the academic institutions to further enhance their process of learning and methods of passing knowledge to students. Education Data Mining have been playing substantial role in predicting student’s academic performance. In this study, a novel student’s performance prediction model premised on techniques of data mining with Students’ Essential Features (SEF). Students’ Essential Features (SEF) are linked to the learner’s interactivity with the e-learning management system. The performance of student’s predictive model is assessed by set of classifiers, viz. Bayes Network, Logistic Regression and REP Tree. Consequently, ensemble methods of Boosting and Random Forest using WEKA as an Open Source Tool are applied to improve the performance of these single classifiers. The results obtained reveal that there is a robust affinity between learner’s behaviours and their academic attainment. Results from the study shows that REP Tree and its ensemble record the highest accuracy of 83.33% using SEF. Hence, in terms of Receiver Operating Curve (ROC), boosting method of REP Tree records 0.903, which is the best. This result further demonstrates the dependability of the proposed model.
Published by: Olukoya Bamidele Musiliu
Author: Olukoya Bamidele Musiliu
Paper ID: V6I5-1348
Paper Status: published
Published: October 28, 2020
Survey on nurses perception on care of Traumatic Brain Injury (TBI) patients
Background: Traumatic brain injury (TBI) is a leading cause of illness, death, disability and socio-economic damage in India and other developing countries. Each year, approximately 1.5–1.7 million people are neurologically disabled due to TBI in India. Nurses are health professionals who see the full impact of TBI and have the skills to change a patient's recovery path. Nurses have a large role to play in the acute and chronic management of patients with moderate-to-severe TB because nurses are important members of interdisciplinary teams. Nurses have a lot of responsibilities in caring for these patients at all stages of treatment and recovery. Methods: The research approach adopted for the study was cross-sectional, exploratory design to determine nurses’ perceptions about care for patients with traumatic brain injury (TBI). As samples, 120 Staff nurses were selected through purposive sampling technique at PESIMSR Hospital inkpad, Andhra Pradesh. The collected data were analysed by using descriptive and inferential statistics in terms of Frequencies, Percentage distribution and chi-square test. Results: majority of the samples were 26-30 years old, female, undergraduates, critical care nurses, had 2.1-5 years of working experience and had no specific training regarding TBI patient care. Majority of the nurses had moderate knowledge and high level of confidence on care of TBI patients. The perceived confidence of nurses at PESIMSR hospital on care of TBI patients was significantly higher than their perceived knowledge. Age, professional qualification and professional experience of nurses had significant association with their perceptions. Conclusion: Results of this study suggested enhancing the knowledge of critical care and emergency room nurses through additional education and training on evidence-based TBI care.
Published by: Dr. Metilda, Dr. Jaganath
Author: Dr. Metilda
Paper ID: V6I5-1326
Paper Status: published
Published: October 28, 2020
Comparison between sliding mode and PID controller for fully interaction three-tank system
Regulating the amount of liquids is a critical condition in many manufacturing processes. The tanks are also so linked together that the levels communicate and display a nonlinear conduct. The sliding mode control (SMC) is used to regulate the level of the coupling tank structure. We initially developed a mathematical model for a nonlinear multi input single output system. A simulation to track a non-linear three tank system model is performed using MATLB / SIMULINK. The performance of SMC is compared to PID controller
Published by: Shrvan Venkatesh K.
Author: Shrvan Venkatesh K.
Paper ID: V6I5-1294
Paper Status: published
Published: October 28, 2020
