Informatics Publishing Limited

Dimple Sethi ¹, Prateek Agrawal ¹, Vishu Madaan ¹, Sanjay Kumar Singh ¹

Affiliations
1 School of Computer Science Engineering, Lovely Professional University, Phagwara – 144411, Punjab, IN

Abstract

Inflammatory disease is the category which is discussed in this paper, early diagnosis of these diseases will help in proper treatment of the disease. The main disorders considered in this research are, Acute Cerviticis, Chronic Cerviticis, Acute Endometritis, Chronic Endometritis, Atrophic Endometeritis, Acute Salpingo-oophortis, Chronic Salpingo-oophoritis. The method employed is Fuzzy Logic and is implemented in MATLAB. In this research we make use of fuzzy logic to develop the fuzzy system for gynaecology. For testing purpose data of nearly 144 patients has been collected to verify the system. Various results obtained showed that the diagnosis of these disorders corresponding to the symptoms that were selected were successful. The data has been acquired and verified with the help of various experts like from Sanjeevani Hospital, Jalandhar, Arora Hospital, Kartarpur. With all these findings, it makes sure that the system will be beneficial not only in the case of cost effectiveness but also help in saving time and by calculating various values 96.1% of efficiency has been achieved.

Keywords

Acute, Cerviticis, Chronic, Diagnosis, Gynaecology Disorders.

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Amandeep Kaur ¹, Vishu Madaan ¹, Prateek Agrawal ¹, Ranjit Kaur ¹, Sanjay Kumar Singh ¹

Affiliations
1 School of Computer Science Engineering, Lovely Professional University, Phagwara - 144411, Punjab, IN

Abstract

Background/Objectives: Banking sector faced many problems like credit assessment, credit worthiness, and credit risk etc. Many techniques are used to solve these problems in artificial intelligence. But these problems are not fully resolved in previous years. Methods/Statistical Analysis: One of the most important problems is credit risk as customer defaulter risk. Recent studies have not discussed about defaulter or non-defaulter customer. This research work has discussed about customer’s defaulter risk as well as credit risk. Findings: A fuzzy expert system has been designed which can categorized customer as defaulter and non- defaulter. The defaulter risk is calculated by considering factors as CS (CIBIL Score), LVR (Loan to Value Ratio), AAL (Already Availed Loan), IRF (Income Ratio Factor). Data of customers are collected from Indian Overseas Bank (IOB) branches. Different defuzzification methods are used to verify the result of customers. It also verified by the expert in banking domain. Further it is also tested on the data of other branches of banks. Application/Improvements: The system can be helpful for the bank employees in decision making process. In addition to this the system can be used for training new employee for loan approval tasks.

Keywords

Banking Sector, Credit Risk, Defaulter, Fuzzy Expert System, Intelligent System.

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Meenakshi Sharma ¹, Sanjay Kumar Singh ¹, Prateek Agrawal ¹, Vishu Madaan ¹

Affiliations
1 School of Computer Science Engineering, Lovely Professional University, Phagwara - 144411, Punjab, IN

Abstract

Background/Objectives: The primary objective of this paper is to classify the clinical dataset of cervical cancer to identify the stage of cancer which helps in proper treatment of patient suffering from cancer. Methods/Statistical Analysis: This research work basically moves toward the detection of cervical cancer using Pap smear images. Analysis of Pap smear of cervical region is an efficient technique to study any abnormality in cervical cells. The proposed system firstly segment the pap image using Edge Detection to separate the cell nuclei from cytoplasm and background and then extract various features of cervical pap images like area, perimeter, elongation and then these features are normalized using min-max method. After normalization KNN method is used to classify cancer according to its abnormality. Findings: The classification accuracy with 84.3% of maximum performance with no validation and classification accuracy with 82.9% of maximum performance with 5 Fold cross validation is achieved.

Keywords

Cervical Cancer, Cell Images, Classification, Pap Smear Test.

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Nandini Sethi ¹, Prateek Agrawal ¹, Vishu Madaan ¹, Sanjay Kumar Singh ¹

Affiliations
1 School of Computer Science Engineering, Lovely Professional University, Phagwara – 144411, Punjab, IN

Abstract

Background/Objectives: Nowadays, most of the automatic work has been done in English language but not much work has been done in Hindi language. The main objective is to convert the existing sentence in different form by remaining the semantic or meaning same. This will helpful in converting the complex sentence into simpler one.Methods/Statistical Analysis:Our system mainly deals with Hindi Sentences and its different forms. It takes a sentence as input and produces another sentence without changing its semantic after applying synonyms and antonyms replacement method.Findings:Reframing of Hindi sentences can be used to change a complex sentence in simplified form.The system is implemented in java. WampServer is used as database for our system. In our paper, we have described complete algorithm to paraphrase the sentences. The performance of the system is totally dependent on the size of Database. Application/Improvements:This application can be helpful in designing robots to understand different forms of Hindi sentences, to use as Hindi tutor for students to get them idea about different form of sentences and in plagiarism tools to find the higher level of plagiarized text up to certain extent. The test results have been verified by various tutors.

Keywords

Antonyms, Paraphrase, Parsing, Synonyms, Transliteration.

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Ranjit Kaur ¹, Vishu Madaan ¹, Prateek Agrawal ¹

Affiliations
1 School of Computer Science Engineering, Lovely Professional University, Phagwara - 144411, Punjab, IN

Abstract

Objectives: Determining the level of strength of patients’ body is essential for an Ayurvedic Physician to provide the appropriate dose of medicines to them. The proposed work is a stepping stone towards a vigilant and proper diagnosis that will surely leads to an efficacious treatment. Methods/Statistical Analysis: A fuzzy logic based expert system is designed to calculate the quality of the seven tissues (Lymph, Blood, Muscle, Fat tissue, Bone, Bone Marrow, Reproductive tissues) and mind of a human body. Based on that quality the overall body strength is computed. All the required parameters are finalized after consulting an Ayurvedic Expert during knowledge acquisition phase. Findings: The accuracy and veracity of the system is evaluated by ranking all results of different defuzzification methods. Data collection is performed by survey method and results were highlighted as false positives and false negatives after verifying from expert. Maximum results depict that the outputs produced by the proposed system matches with those of Ayurvedic Expert. Application/ Improvements: The proposed system will guide the physicians to plan the dose of medicines and treatment for the patients. This fuzzy based system will prove itself as a learning kit for Ayurveda and Vedic practitioner.

Keywords

Defuzzification, Examination of Strength, Fuzzy Expert System, Fuzzy Logic, Fuzzification, Inference System.

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Prateek Agrawal ¹, Vishu Madaan ¹, Naveen Kundu ¹, Dimple Sethi ¹, Sanjay Kumar Singh ¹

Affiliations
1 School of Computer Science Engineering, Lovely Professional University, Phagwara – 144411, Punjab, IN

Abstract

Objectives: In this paper, an attempt is made to identify the behaviour of human based on his/her body gesture. Body gesture recognition is very important and prime feature to detect the behaviour of the human being so behaviour and frame of mind of any person can be judged from one’s body gesture. Methods/Statistical Analysis: Our proposed system captures an image of a person and recognizes different gestures related to head, hands and legs positions. The different types of rules are defined in fuzzy system that will produce the behaviour and mood after analysing the captured image with knowledge base. Findings: The result is produced in the form of classes which tells the behavior and other characteristics of the person. There are 3 main classes that describe the behavior of the person that is: Positive mood, Negative mood and Neutral mood. These three gestures are matched in the database. Name of gestures are passed to fuzzy system and fuzzy system will produce the result. Application/Improvements: This system can be used to identify the behavior of a person. So it can be used to identify any criminals and terrorists.This proposed system can be used to analyse psychological behaviour of human being which may help in different medical treatments.

Keywords

Fuzzy System, Frame of Mind Identification, Gesture Recognition, Image Processing, Psychological Behaviour Tracing.

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