Vinita Shah - Academia.edu (original) (raw)
Papers by Vinita Shah
Agriculture plays a crucial role in the life of an economy. It is the backbone for developing cou... more Agriculture plays a crucial role in the life of an economy. It is the backbone for developing countries like India as more than 70% of population depends on agriculture. To increase crop production many factors are responsible like soil, weather, rain, fertilizers and pesticides. We have used soil parameters to increase crop production because it is an essential key factor of agriculture. To maintain nutrient levels in the soil in case of deficiency, fertilizers are added to soil. The common problem existing among the Indian farmers is that they choose approximate amount of fertilizers and add them manually. Excess or insufficient addition of fertilizer can harm the plant life and reduce the yield. This paper provides review of various data mining techniques used on agriculture soil dataset for fertilizer recommendation. Mainly I focused on various soil parameters like Fe, S, Zn, Cu, N and Ph value etc. In this survey, we also describe some Agriculture problems that can be solved by...
2 Abstract: Survey made on this area reveals the importance of data mining techniques on agricult... more 2 Abstract: Survey made on this area reveals the importance of data mining techniques on agriculture. Lots of data mining Techniques have been used in agriculture (2). We present some of the most used data mining techniques in the field of agriculture (1). In the near future the penetration of Information Technology and Agriculture results is more interesting area of research. The main aim of the work is to improve and substantiate the validity of yield prediction which is useful for the farmers (6). Agricultural crop production depends on various factors such as biology, climate, economy and geography. Several factors have different impacts on agriculture, which can be quantified using appropriate statistical methodologies. Agronomic traits such as yield can be affected by a large number of variables. In this survey, we analyzed a DM methods like clustering, classification models to select the most relevant method for the prospect (32).
Crime scene images are very sensitive to do any kind of preprocessing and compression, but the us... more Crime scene images are very sensitive to do any kind of preprocessing and compression, but the use of images is increasing in exponential manner in crime detection and crime solving, so we require to compress the crime scene images as well. For more compression ratio we can use Region of Interest (ROI) compression. For crime scene images our ROI may be evidences of crime. We might have multiple ROIs in crime scene images. Sometimes it may not possible to select ROI manually; because ROI may be too small and even sometimes we can miss some evidences in manual ROI selection. The solution to this problem is automatic separation of ROI and background (BG). In this paper, we had implemented one algorithm for automatic separation of ROI and BG for crime scene images. We had use color crime scene image for automatic separation of ROI and BG and then compression is done using DWT.
Precision medicine is an important and growing area of research, development and healthcare for t... more Precision medicine is an important and growing area of research, development and healthcare for the diagnosis of diseases and patients precare. It involves analysis of a patient's personal data, genetic information, circumstances to diagnose and cure the disease. It allows researchers to design and develop the medication for prevention of specific viruses. It has the potential to improvise the traditional symptom driven retrospective practice of medicine, by allowing earlier interventions with advanced diagnostics, which can further be used for tailoring personalized treatments. Identification of the pathway for developing a personalized medicine involves analyzing comprehensive patient information along with broader aspects to monitor and distinguish between healthy and sick people, which will lead to a better understanding of biological indicators that can signal shifts in health. In order to positively impact the patient’s health and to provide real time decision support, it ...
2013 International Conference on Communication Systems and Network Technologies, 2013
Rice is one of the most important cereal grains. The paper presents a solution for quality evalua... more Rice is one of the most important cereal grains. The paper presents a solution for quality evaluation and grading of Krishna Kamod rice using image processing and soft computing technique. In this paper basic problem of rice industry for quality assessment is defined which is traditionally done manually by human inspector. Machine vision provides one alternative for an automated, non-destructive and cost-effective technique. The proposed method for quality assessment of INDIAN KAMOD ORYZA SATIVA SSP INDICA (Krishna Kamod Rice) using image processing and multi-layer feed forward neural network technique which achieves high degree of quality than human vision inspection. The proposed algorithm based on morphological features is developed for counting the number of Krishna Kamod rice seeds with long seeds as well as small seeds. A trained multi-layer feed forward neural network based classifier is developed for identification of unknown rice seed quality.
International Journal of Computer Applications, 2015
Outlier is a data point that deviates too much from the rest of dataset. Most of real-world datas... more Outlier is a data point that deviates too much from the rest of dataset. Most of real-world dataset have outlier. Outlier analysis is one of the techniques in data mining whose task is to discover the data which have an exceptional behavior compare to remaining dataset. Outlier detection plays an important role in data mining field. Outlier Detection is useful in many fields like Medical, Network intrusion detection, Credit card fraud detection, medical, fault diagnosis in machines, etc. In order to deal with outlier, clustering method is used. Outlier detection contains clustering and finding outlier by applying any outlier detection technique. For that Kmean is widely used to cluster the dataset. Different techniques like statistical-based, distance-based, and deviation-based and density based methods are used to detect outlier. The experiment result shows that existing algorithm perform better than proposed cluster-based and distance-based Algorithm.
International Journal of Computer Applications, 2015
Privacy preservation data mining is novel research area where data mining algorithms are analyzed... more Privacy preservation data mining is novel research area where data mining algorithms are analyzed for their side-effects they done on data privacy. Privacy preservation data mining (PPDM) deals with the problem of hiding the sensitive information while analyzing data. Many techniques are available for PPDM like data distortion, data hiding, rule hiding, data modification etc. Association rule hiding is one of the technique of PPDM. It hides sensitive rules which are generated by association rule generation algorithm before releasing database. This paper discusses different approaches of association rule hiding technique. In this paper, we propose a heuristic algorithm which provides privacy for sensitive rules while ensuring data quality. Proposed algorithm hides as many as possible rules at a time by modifying fewer transactions.
Agriculture plays a crucial role in the life of an economy. It is the backbone for developing cou... more Agriculture plays a crucial role in the life of an economy. It is the backbone for developing countries like India as more than 70% of population depends on agriculture. To increase crop production many factors are responsible like soil, weather, rain, fertilizers and pesticides. We have used soil parameters to increase crop production because it is an essential key factor of agriculture. To maintain nutrient levels in the soil in case of deficiency, fertilizers are added to soil. The common problem existing among the Indian farmers is that they choose approximate amount of fertilizers and add them manually. Excess or insufficient addition of fertilizer can harm the plant life and reduce the yield. This paper provides review of various data mining techniques used on agriculture soil dataset for fertilizer recommendation. Mainly I focused on various soil parameters like Fe, S, Zn, Cu, N and Ph value etc. In this survey, we also describe some Agriculture problems that can be solved by...
2 Abstract: Survey made on this area reveals the importance of data mining techniques on agricult... more 2 Abstract: Survey made on this area reveals the importance of data mining techniques on agriculture. Lots of data mining Techniques have been used in agriculture (2). We present some of the most used data mining techniques in the field of agriculture (1). In the near future the penetration of Information Technology and Agriculture results is more interesting area of research. The main aim of the work is to improve and substantiate the validity of yield prediction which is useful for the farmers (6). Agricultural crop production depends on various factors such as biology, climate, economy and geography. Several factors have different impacts on agriculture, which can be quantified using appropriate statistical methodologies. Agronomic traits such as yield can be affected by a large number of variables. In this survey, we analyzed a DM methods like clustering, classification models to select the most relevant method for the prospect (32).
Crime scene images are very sensitive to do any kind of preprocessing and compression, but the us... more Crime scene images are very sensitive to do any kind of preprocessing and compression, but the use of images is increasing in exponential manner in crime detection and crime solving, so we require to compress the crime scene images as well. For more compression ratio we can use Region of Interest (ROI) compression. For crime scene images our ROI may be evidences of crime. We might have multiple ROIs in crime scene images. Sometimes it may not possible to select ROI manually; because ROI may be too small and even sometimes we can miss some evidences in manual ROI selection. The solution to this problem is automatic separation of ROI and background (BG). In this paper, we had implemented one algorithm for automatic separation of ROI and BG for crime scene images. We had use color crime scene image for automatic separation of ROI and BG and then compression is done using DWT.
Precision medicine is an important and growing area of research, development and healthcare for t... more Precision medicine is an important and growing area of research, development and healthcare for the diagnosis of diseases and patients precare. It involves analysis of a patient's personal data, genetic information, circumstances to diagnose and cure the disease. It allows researchers to design and develop the medication for prevention of specific viruses. It has the potential to improvise the traditional symptom driven retrospective practice of medicine, by allowing earlier interventions with advanced diagnostics, which can further be used for tailoring personalized treatments. Identification of the pathway for developing a personalized medicine involves analyzing comprehensive patient information along with broader aspects to monitor and distinguish between healthy and sick people, which will lead to a better understanding of biological indicators that can signal shifts in health. In order to positively impact the patient’s health and to provide real time decision support, it ...
2013 International Conference on Communication Systems and Network Technologies, 2013
Rice is one of the most important cereal grains. The paper presents a solution for quality evalua... more Rice is one of the most important cereal grains. The paper presents a solution for quality evaluation and grading of Krishna Kamod rice using image processing and soft computing technique. In this paper basic problem of rice industry for quality assessment is defined which is traditionally done manually by human inspector. Machine vision provides one alternative for an automated, non-destructive and cost-effective technique. The proposed method for quality assessment of INDIAN KAMOD ORYZA SATIVA SSP INDICA (Krishna Kamod Rice) using image processing and multi-layer feed forward neural network technique which achieves high degree of quality than human vision inspection. The proposed algorithm based on morphological features is developed for counting the number of Krishna Kamod rice seeds with long seeds as well as small seeds. A trained multi-layer feed forward neural network based classifier is developed for identification of unknown rice seed quality.
International Journal of Computer Applications, 2015
Outlier is a data point that deviates too much from the rest of dataset. Most of real-world datas... more Outlier is a data point that deviates too much from the rest of dataset. Most of real-world dataset have outlier. Outlier analysis is one of the techniques in data mining whose task is to discover the data which have an exceptional behavior compare to remaining dataset. Outlier detection plays an important role in data mining field. Outlier Detection is useful in many fields like Medical, Network intrusion detection, Credit card fraud detection, medical, fault diagnosis in machines, etc. In order to deal with outlier, clustering method is used. Outlier detection contains clustering and finding outlier by applying any outlier detection technique. For that Kmean is widely used to cluster the dataset. Different techniques like statistical-based, distance-based, and deviation-based and density based methods are used to detect outlier. The experiment result shows that existing algorithm perform better than proposed cluster-based and distance-based Algorithm.
International Journal of Computer Applications, 2015
Privacy preservation data mining is novel research area where data mining algorithms are analyzed... more Privacy preservation data mining is novel research area where data mining algorithms are analyzed for their side-effects they done on data privacy. Privacy preservation data mining (PPDM) deals with the problem of hiding the sensitive information while analyzing data. Many techniques are available for PPDM like data distortion, data hiding, rule hiding, data modification etc. Association rule hiding is one of the technique of PPDM. It hides sensitive rules which are generated by association rule generation algorithm before releasing database. This paper discusses different approaches of association rule hiding technique. In this paper, we propose a heuristic algorithm which provides privacy for sensitive rules while ensuring data quality. Proposed algorithm hides as many as possible rules at a time by modifying fewer transactions.