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Balasubramanian, S.
- Analysis of Spatio-temporal Disease Pattern Using Spatial Auto Correlation Methods: Case of Acute Gastroenteritis in Coimbatore District, Tamilnadu, India
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Authors
Affiliations
1 Dept. of Zoology, Nirmala College for Women (Autonomous), Redfields, Coimbatore, Tamilnadu, IN
2 Department of Environmental Management, Bharathidasan University, Tiruchirapalli, Tamilnadu, IN
3 National Institute of Epidemiology, III Avenue, Ayapakkam, Ambattur, Chennai, IN
4 JSS Medical University, Srivratheeswarar Nagar, Mysore, IN
1 Dept. of Zoology, Nirmala College for Women (Autonomous), Redfields, Coimbatore, Tamilnadu, IN
2 Department of Environmental Management, Bharathidasan University, Tiruchirapalli, Tamilnadu, IN
3 National Institute of Epidemiology, III Avenue, Ayapakkam, Ambattur, Chennai, IN
4 JSS Medical University, Srivratheeswarar Nagar, Mysore, IN
Source
Indian Journal of Public Health Research & Development, Vol 5, No 3 (2014), Pagination: 296-301Abstract
Background and Objectives: In epidemiology many of the infectious disease events do not occur randomly in geographical context but occur in clusters. Geographical or spatial analysis comes into play due to the existence of spatial dependence in data. The main objective was to examine the variation in the prevalence of Acute Gastroenteritis using space time autocorrelation methods and to explore possible factors that might have influenced these variations in the study area.
Method: To identify the spatial similarity between the estimated Acute gastroenteritis values in the study region spatial autocorrelation was attempted to study the aggregated data of disease incidences. Different methods for measuring seasonal variations was adopted - Simple Averages, Ratio to Trend, Ratio to Moving Average and Link-Relative Methods. Results: The results show that a high incidence is recorded in the I and IV quarters, in all the taluks of Coimbatore district. It is observed that the incidence of Acute gastroenteritis is high in the months of January, February, March, April and November for all the taluks of Coimbatore district. The seasonal trend observations displayed a more comprehensive pattern of disease movement rather than the monthly pattern.
Interpretation and conclusion: It is evident that Acute Gastroenteritis is a seasonally dependent disease with more number of cases increasing in the winter season and less cases in the summer season. This methodology will improve the accuracy of public health forecasting and will help in developing mechanisms to combat large seasonal surges of infectious diseases.
Keywords
Link-relative, Ratio to Trend, Ratio to Moving Average, Seasonal Oscillations, Simple Averages, Spatial Autocorrelation
- Fuzzy Logic Association Rules Integrating with Matlab for Effective Policing in Crime Analysis
Abstract Views :148 |
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Authors
Affiliations
1 DRDO-BU CLS, Bharathiar University, Coimbatore-641046, IN
2 Department of MCA, Sri Ramakrishna Mission Vidyalaya, Coimbatore-641020, IN
3 Department of Environmental Science, JSS University, Mysore-500015, IN
1 DRDO-BU CLS, Bharathiar University, Coimbatore-641046, IN
2 Department of MCA, Sri Ramakrishna Mission Vidyalaya, Coimbatore-641020, IN
3 Department of Environmental Science, JSS University, Mysore-500015, IN
Source
Fuzzy Systems, Vol 4, No 1 (2012), Pagination: 23-29Abstract
Fuzzy logic systems are generally recovered for device, system identification, and pattern gratitude complications. Fuzzy logic has become a much conversed technique in mathematical, engineering literature; it has not yet found application in social science fields. Currently, this system is a nonlinear mapping from an input space to an output space that can be parameterized in various ways. Fuzzy logic is widely used in the current application and to solve social problems (for identification and management of law enforcement) and criminal justices when compared to classic logic. Fuzzy logic has the potential to add human-like subjective reasoning capabilities to machine intelligence.Keywords
Association Rules, Crime Data, Fuzzy Logic, Matlab, Map Object.- Exploratory Model Using Fuzzy Logic for Evaluation of Attitude and Aptitude
Abstract Views :167 |
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Authors
Affiliations
1 Department of MCA, SRMVCAS, Coimbatore, IN
2 JSS University, Mysore, IN
1 Department of MCA, SRMVCAS, Coimbatore, IN
2 JSS University, Mysore, IN
Source
Data Mining and Knowledge Engineering, Vol 5, No 9 (2013), Pagination: 350-355Abstract
Human development depends on Physical health, Aptitude and Attitude. Physical health refers to Overweight, Normal and Underweight using Body Mass Index. Aptitude refers to intellectual ability or talent to solve the problem and Attitude refers to gunas which indicates the 'inherent energy or tendency' with which the mind functions. Attitude are categorized as Sattvic, Rajasic and Tamasic type. Aptitude are classified as high, medium and low. We developed statistical based method and Fuzzy Logic based method, to find the relationship between attitude, aptitude and physical. 535 males and 320 females were given questionnaire based on attitude, aptitude and physical. We are able to find each individual inherent tendency with intellectual ability and physical has no effect on it. Males are rajasic nature with low aptitude and females are rajasic nature with medium aptitude. The inherent tendency of 855 candidates are rajasic nature with low aptitude. Attitude plays dominant role in the development of aptitude.Keywords
Attitude, Aptitude, Fuzzy Logic, BMI.- Area Based Crime Analysis in Spatial Data Mining Approach for Association Rule in Geo-Referenced Data
Abstract Views :188 |
PDF Views:2
Authors
Affiliations
1 DRDO-BU CLS, Bharathiar University, Coimbatore-641046, IN
2 Sri Ramakrishna Mission Vidyalaya, Coimbatore-641020, IN
3 CJSS University, Mysore-500015, IN
1 DRDO-BU CLS, Bharathiar University, Coimbatore-641046, IN
2 Sri Ramakrishna Mission Vidyalaya, Coimbatore-641020, IN
3 CJSS University, Mysore-500015, IN
Source
Data Mining and Knowledge Engineering, Vol 4, No 2 (2012), Pagination: 59-63Abstract
In this paper which passion to integrate a large volume of data sets into useful information by adopting a various information techniques in the most modern technology world. The adopted approaches of Single variate Association Rule for Area to Crime based on the knowledge discovery techniques such as, clustering and association-rule mining. It reveals with an inherent of patterns of information into a fruitful exploratory tool for the discovery of spatio-temporal patterns. This tool is an autonomous pattern detector to reveal plausible cause-effect associations between layers of point and area data. We present VATA algorithm with an exploratory analysis for the effectively explore geo-referenced data. The present study of this paper was focuses through the real crime dataset by using algorithm. We demonstrate approach to a new type of analysis of the spatio-temporal dimensions of records of criminal events. We hope this will lead to new approaches in the exploration of large volumes of spatio-temporal data.Keywords
Algorithm, Clustering Association Rule, Crime Data, Data Mining, GIS, Spatio-Temporal Data.- Association Rule-Spatial Data Mining Approach for Geo-Referenced in Crime to Crime Analysis
Abstract Views :206 |
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Authors
Affiliations
1 DRDO-BU CLS, Bharathiar University, Coimbatore-641046, IN
2 Department of MCA, Sri Ramakrishna Mission Vidyalaya, Coimbatore-641020, IN
3 Department of Environmental Science, JSS University, Mysore-500015, IN
1 DRDO-BU CLS, Bharathiar University, Coimbatore-641046, IN
2 Department of MCA, Sri Ramakrishna Mission Vidyalaya, Coimbatore-641020, IN
3 Department of Environmental Science, JSS University, Mysore-500015, IN
Source
Data Mining and Knowledge Engineering, Vol 4, No 1 (2012), Pagination: 31-36Abstract
Spatial data mining is a demanding field since huge amounts of spatial data that has been processed and turned into useful information by this paper. The increased crime rate and enormous amount of data being stored in crime databases by police personnel which has been collected from various jurisdiction of Coimbatore are gathered for the application of technologies which provides the means to turn data into information by data fusion and data mining. Data fusion organizes, combines and interprets information from multiple sources and it overcomes confusion from conflicting reports and cluttered or noisy backgrounds. Data mining is concerned with the automatic discovery of patterns and relationships with (crime to crime) in large databases. Technically, it is the process of finding correlations or patterns among dozens of fields in large relational databases using the tools of GIS. This paper provides a clear finding to prevent from crime with associated to another crime occurrence with the naked observation on correlation between one crime to another crime.Keywords
Algorithm, Association Rule, Data Mining, Crime Data, GIS.- Effects of CO2 Exhaled and Human Metabolism on Comfort Conditions in Air-Conditioned Indoor Environment
Abstract Views :127 |
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Authors
Affiliations
1 Deptt. of Mechanical Engineering, Govt. College of Engineering, Bargur-635 104, IN
2 Anna University, Coimbatore-641 047, T.N., IN
3 Dept. of Mechanical Engineering, Anna University, Tirunelveli, T. N., IN
1 Deptt. of Mechanical Engineering, Govt. College of Engineering, Bargur-635 104, IN
2 Anna University, Coimbatore-641 047, T.N., IN
3 Dept. of Mechanical Engineering, Anna University, Tirunelveli, T. N., IN
Source
Nature Environment and Pollution Technology, Vol 9, No 4 (2010), Pagination: 829-835Abstract
Thermal and atmospheric conditions in an enclosed space are usually controlled to ensure the health and comfort of the occupants, and proper functioning of sensitive electronic equipment such as computers, etc. The former is referred as comfort conditioning and the latter is called process air conditioning. The conditions required for optimum operation of machinery may not coincide with those conductive to human comfort. Process air-conditioning requirements are highly specific to the equipment or operation. Once the necessary condition for process or machinery is established, attention must be paid to the acceptable human comfort. Although human beings can be considered very versatile machines having the capacity to adapt the wide variations in the working environment, their productivity depends on the immediate environment. This paper discusses about the CO2 generation of the human beings based on their working environment, activity, metabolism and its effects inside the indoor environment. The indoor pollutants created by the human beings and the rate of ventilation required to dilute the pollutant levels to meet ASHRAE standards is also discussed.Keywords
Comfort Conditions, CO2 Exhaled, Indoor Environment, Human Metabolism.Full Text
- Nano Particle a Reliable Source for Energy Efficient Eco Friendly Chilling for Fish Processing
Abstract Views :195 |
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Authors
Affiliations
1 Department of Basic Engineering, College of Fisheries Engineering, Tamil Nadu Fisheries University, Nagapattinam (T.N.), IN
2 Department of Aquacultural Engineering, College of Fisheries Engineering, Tamil Nadu Fisheries University, Nagapattinam (T.N.), IN
3 College of Fisheries Engineering, Tamil Nadu Fisheries University, Nagapattinam (T.N.), IN
1 Department of Basic Engineering, College of Fisheries Engineering, Tamil Nadu Fisheries University, Nagapattinam (T.N.), IN
2 Department of Aquacultural Engineering, College of Fisheries Engineering, Tamil Nadu Fisheries University, Nagapattinam (T.N.), IN
3 College of Fisheries Engineering, Tamil Nadu Fisheries University, Nagapattinam (T.N.), IN
Source
Rashtriya Krishi (English), Vol 12, No 2 (2017), Pagination: 159-159Abstract
Need: Cold chain management is the only art which is very tedious in this current scenario. To save the fish and agricultural products from decay and biological activities it is mandatory to keep them in sub zero temperature. Vapour compression refrigeration system provide a suitable and viable option to do so. But energy loss is inevitable. Hence the nano additives along with refrigerants were tried to be incorporated in the freezer technology for fish preservation and processing.- Gelatin Based Edible Coating:Preservation Technique for Seer (Scomberomorus guttatus) Fish Slices
Abstract Views :226 |
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Authors
Affiliations
1 Department of Fish Process Engineering, College of Fisheries Engineering, Tamil Nadu Fisheries University, Nagapattinam-611001, Tamil Nadu, IN
2 College of Fisheries Engineering, Tamil Nadu Fisheries University, Nagapattinam-611001, Tamil Nadu, IN
3 Department of Basic Science, College of Fisheries Engineering, Tamil Nadu Fisheries University, Nagapattinam-611001, Tamil Nadu, IN
1 Department of Fish Process Engineering, College of Fisheries Engineering, Tamil Nadu Fisheries University, Nagapattinam-611001, Tamil Nadu, IN
2 College of Fisheries Engineering, Tamil Nadu Fisheries University, Nagapattinam-611001, Tamil Nadu, IN
3 Department of Basic Science, College of Fisheries Engineering, Tamil Nadu Fisheries University, Nagapattinam-611001, Tamil Nadu, IN
Source
The Indian Journal of Nutrition and Dietetics, Vol 55, No 2 (2018), Pagination: 177-186Abstract
The aim of this work is to examine the performance of gelatin based edible coating in preserving the seer fish slices. A composite edible coating solution was prepared with three different concentrations of gelatin, chitosan and vinegar. Coating experiments were performed in a laboratory scale edible coating tank which was fabricated for this purpose. The seer fish slices (13.65±2.50 mm thick and 43.89±6.82 g weight) were subjected to coating for three different soaking times (min). While coating performance of the solution was assessed through coating uptake (%), texture quality of the seer fish slices was assessed through weight loss (%) and microbial quality was assessed through Total Plate Count (CFU/g). Experiment was designed using Box-Behnken Design (BBD). The application of edible coating treatment to seer fish slices resulted in improvement of overall keeping quality of the seer fish slices (9 days) against the control (3 days) when stored under low temperature (7±1°C).Keywords
Edible Coating, Seer Fish, Texture, Weight Loss, Coating Uptake, Weight Loss.References
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- Song, Y., Liu, L., Shen, H., You, J. and Luo, Y., Effect of sodium alginate-based edible coating containing different anti-oxidants on quality and shelf life of refrigerated bream (Megalobrama amblycephala). Fd. Control., 2011, 22, (3-4), 608-615.
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- Kilincceker, O., Dogan, I.S. and Kucukoner, E., Effect of edible coatings on the quality of frozen fish fillets. LWT- Fd. Sci.Technol., 200, 42, 868-873.
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- Statistical Analysis of M-Mode Echocardiographic Normal Reference Values in South Indian Adults
Abstract Views :644 |
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Authors
Affiliations
1 Department of Water and Health, Faculty of Life Sciences, JSS Academy of Higher Education & Research, IN
2 Department of Community Medicine, JSS Medical College & Assistant Director Research, JSS Academy of Higher Education & Research, IN
3 Department of Water and Health, JSS Academy of Higher Education & Research, IN
4 Department of Cardiology, JSS Hospital, Mysuru, Karnataka, IN
1 Department of Water and Health, Faculty of Life Sciences, JSS Academy of Higher Education & Research, IN
2 Department of Community Medicine, JSS Medical College & Assistant Director Research, JSS Academy of Higher Education & Research, IN
3 Department of Water and Health, JSS Academy of Higher Education & Research, IN
4 Department of Cardiology, JSS Hospital, Mysuru, Karnataka, IN
Source
Indian Journal of Public Health Research & Development, Vol 10, No 12 (2019), Pagination: 24-29Abstract
Background: Normal values for echocardiographic measurements are derived from American Society of echocardiography and European Society of Cardiology/European Association of Cardio-Vascular Imaging and their publications. Indians have smaller cardiac chamber dimensions than the Europeans. However, it has been long felt that reference range from western data cannot be fully applied in our scenario.
Aim: The objective of this study was to develop age and gender-specific normative reference range values for echocardiography measurements.
Methodology: This was a retrospective cross-sectional single-center study conduct on 111 healthy Indian adults who were selected out of the 336 patients aged from 18– 76 years, who visited the cardiac medical check-up unit in a tertiary hospital. Echocardiograms were done in participants free of cardiovascular diseases, hypertension, diabetes, high blood pressure or other clinical evident disorders. M-mode Echocardiography in the left parasternal long-axis view was used to measure aorta, left atrium, left ventricle in systole and diastole,right ventricle, interventricular septum, and posterior wall thickness. The 95% reference range of the echocardiographic parameters calculated as a mean±2 “standard deviation for overall and genders specific”.
Results: This study provides a set of data with reference ranges for normal M-mode parameters according to age and gender. Around 58 males and 53 females were classified into the age group from 18-76 years as exclusive class intervals. Age group above of 38 years Indians had higher volume in all the echocardiographic measurements are observed in this study. On examining all our healthy participants, we found that the reference range of most echocardiographic parameters is a highly statistically significant difference as compared with those used in western studies.
Conclusion: The normal reference values for echocardiographic measurements derived from this study could be used for future reference in our local population.
Keywords
Echocardiography Normative Data, M-Mode Parameters, Normal Reference Values, South Indian Adults.- Co-Curing Noisy Annotations for Facial Expression Recognition
Abstract Views :213 |
PDF Views:1
Authors
Affiliations
1 Department of Mathematics and Computer Science, Sri Sathya Sai Institute of Higher Learning, IN
1 Department of Mathematics and Computer Science, Sri Sathya Sai Institute of Higher Learning, IN
Source
ICTACT Journal on Image and Video Processing, Vol 12, No 1 (2021), Pagination: 2508-2516Abstract
Driven by the advancement in technology that can facilitate implementation of deep neural networks (DNNs), and due to the availability of large scale datasets, automatic recognition performance of the machines has increased by leaps and bounds. This is also true with regard to facial expression recognition (FER) wherein the machine automatically classifies a given facial image in to one of the basic expressions. However, annotations of large scale datasets in FER suffer from noise due to various factors like crowd sourcing, automatic labelling based on key word search etc. Such noisy annotations impede the performance of FER due to the memorization ability of DNNs. To address it, this paper proposes a learning algorithm called Co-curing: peer training of two joint networks using a supervision loss and a mimicry loss that are balanced dynamically, and supplemented with a relabeling module to correct the noisy annotations. Specifically, peer networks are trained independently using supervision loss during early part of the training. As training progresses, mimicry loss is given higher weightage to bring consensus between the two networks. Our Co-curing does not need to know the noise rate. Samples with wrong annotations are relabeled based on the agreement of peer networks. Experiments on synthetic as well real world noisy datasets validate the effectiveness of our method. State-of-the-art (SOTA) results on benchmark in-the-wild FER datasets like RAF-DB (89.70%), FERPlus (89.6%) and AffectNet (61.7%) are reported.Keywords
Noisy Annotations, Facial Expression Recognition, Co-Curing, Mimicry Loss, Peer LearningReferences
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- Iterative Collaborative Routing among Equivariant Capsules for Transformation-Robust Capsule Networks
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Authors
Affiliations
1 Department of Mathematics and Computer Science, Sri Sathya Sai Institute of Higher Learning, IN
1 Department of Mathematics and Computer Science, Sri Sathya Sai Institute of Higher Learning, IN
Source
ICTACT Journal on Image and Video Processing, Vol 13, No 2 (2022), Pagination: 2865-2873Abstract
Transformation-robustness is an important feature for machine learning models that perform image classification. Many methods aim to bestow this property to models by the use of data augmentation strategies, while more formal guarantees are obtained via the use of equivariant models. We recognise that compositional, or part-whole structure is also an important aspect of images that has to be considered for building transformation-robust models. Thus, we propose a capsule network model that is, at once, equivariant and compositionality aware. Equivariance of our capsule network model comes from the use of equivariant convolutions in a carefully-chosen novel architecture. The awareness of compositionality comes from the use of our proposed novel, iterative, graph-based routing algorithm, termed Iterative collaborative routing (ICR). ICR, the core of our contribution, weights the predictions made for capsules based on an iteratively averaged score of the degree-centralities of its nearest neighbours. Experiments on transformed image classification on FashionMNIST, CIFAR-10, and CIFAR-100 show that our model that uses ICR outperforms convolutional and capsule baselines to achieve state-of-the-art performance.Keywords
Equivariance, Transformation Robustness, Capsule Network, Image Classification, Deep Learning.References
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- Robustcaps: A Transformation-Robust Capsule Network For Image Classification
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Authors
Affiliations
1 Department of Mathematics and Computer Science, Sri Sathya Sai Institute of Higher Learning, India., IN
1 Department of Mathematics and Computer Science, Sri Sathya Sai Institute of Higher Learning, India., IN
Source
ICTACT Journal on Image and Video Processing, Vol 13, No 3 (2023), Pagination: 2883-2892Abstract
Geometric transformations of the training data as well as the test data present challenges to the use of deep neural networks to vision-based learning tasks. To address this issue, we present a deep neural network model that exhibits the desirable property of transformationrobustness. Our model, termed RobustCaps, uses group-equivariant convolutions in an improved capsule network model. RobustCaps uses a global context-normalised procedure in its routing algorithm to learn transformation-invariant part-whole relationships within image data. This learning of such relationships allows our model to outperform both capsule and convolutional neural network baselines on transformation-robust classification tasks. Specifically, RobustCaps achieves state-of-the-art accuracies on CIFAR-10, FashionMNIST, and CIFAR-100 when the images in these datasets are subjected to train and test-time rotations and translations.Keywords
Deep Learning, Capsule Networks, Transformation Robustness, Equivariance.References
- T. Cohen and M. Welling, “Group Equivariant Convolutional Networks”, Proceedings of International Conference on Machine Learning, pp. 2990-2999, 2016.
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- R. Pucci, C. Micheloni and N. Martinel, “Self-Attention Agreement Among Capsules”, Proceedings of International Conference on Computer Vision, pp. 272-280, 2021.
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