Hybrid Swarm Intelligence Method for Post Clustering Content Based Image Retrieval

AbstractContent Based Image Retrieval is one of the most promising method for image retrieval where searching and retrieving images from large scale image database is a critical task. In Content Based Image Retrieval many visual feature like color, shape, and texture are extracted in order to match query image with stored database images. Matching the query image with each image of large scale database results in large number of disc scans which in turns slows down the systems performance.The proposed work suggested an approach for post clustering Content Based Image Retrieval, in which the database images are clustered into optimized clusters for further retrieval process. Various clustering algorithms are implemented and results are compared. Among all, it is found that hybrid ACPSO algorithm performs better over basic algorithms like k-means, ACO, PSO etc. Hybrid ACPSO has the capability to produce good cluster initialization and form global clustering.This paper discusses work-in-progress where we have implemented till clustering module and intermediate results are produced. These resulted clusters will further be used for effective Content Based Image Retrieval

Feasibility of Late Transplanted Summer Pearl Millet for Prolonged rabi Season With Integrated Nitrogen Management Under Indian Coastal Region

Experiments were conducted in coastal South Gujarat region of India to evaluate the feasibility of late transplanted summer pearl millet under prolonged rabi season with integrated nitrogen management (INM) during 2014, 2015 and 2016. INM treatments were consisted of four combinations of biocompost and inorganic nitrogen fertilizers. Two planting methods were evaluated, namely drilling and transplanting. Premature heading in transplanted pearl millet was observed up to 8-10% population during all the three experimental years, the possible causes for this are slow nitrogen availability, weather conditions, the thickness of the seedlings, root pruning and seedling age at transplanting. Application of 100% Recommended Dose of Fertilizer (RDF) + 5 t biocompost had significantly increased growth, yield (3862 kg ha-1), benefit-cost ratio (B:C ratio) (3.52) and quality of parameters of pearl millet followed by 75% Recommended Dose of Nitrogen (RDN) + 25% RDN through biocompost. Late transplanted summer pearl millet was little feasible to grow over timely drilled pearl millet as it had reduced pearl millet grain yield by 6.07% and also reduced the net profit by 72.46 US $ ha-1. However, overall, it was feasible to grow late transplanted pearl millet and gave yield up to 3150 kg ha-1 in prolonged rabi season condition for brining summer season well in time

Honeypot System: An Intrusion Detection System

The following paper points in the direction of extending and effectively utilizing the honeypot technology for developing an IDS module that will use the PID track technique and will have the capability of detecting the attacker and working out a response. The whole module developed can be further extended for future use and at the same time it will ensure that the intrusion detection is carried out in the fastest possible time

Assessment of air quality around the thermal power plant area, Chandrapur, Maharashtra, India

Air is the critical main constituent of life on the earth due to respiration phenomenon. Chandrapur city is well known for mining activity and industrial area. Thermal power plant, mining activities, factories and so many industries are established in Chandrapur district. Present study examines the ambient air quality around the thermal power plant for compliance parameters viz; Particulate Matter less than 10 microns and 2.5 microns size (i.e., PM10 and PM2.5), as well as gaseous pollutants like Sulphur Dioxide (SO2), Oxides of Nitrogen (NOX), Ozone (O3), Ammonia (NH3), specific contaminant pollutants involving Hydrocarbons (HCs) and Carbon Monoxide (CO), and heavy metals such as Nickel (Ni), Lead (Pb), Arsenic (As), and Benzo [a] pyrene (BaP) at different areas around Thermal Power Plant, Chandrapur, Maharashtra (India). The National Ambient Air Quality Standard (NAAQS) 2009 was compared to the resultant situations. The results showed that although the levels of toxins and other pollutants near the thermal power plant were designed to be below permissible limits, they are nonetheless at alarmingly high levels from a health perspective

Load Time and Link Mapping: Enhancing SEO experience for Private University Websites in Maharashtra

This study focuses on evaluating the load time and link structure of the websites of private universities in Maharashtra. The objectives of the study include measuring the load time of the websites and comparing them to industry benchmarks, conducting a link mapping of the internal and external links and analyzing their structure and hierarchy, and providing recommendations for improving the load time and link structure based on the findings. Additionally, the study aims to analyze the structure and distribution of internal and external links on the websites of private universities in Maharashtra for search engine optimization. This study used python coding for data scraping. The findings of this study will help private universities in Maharashtra to enhance website performance, improve the user experience, and attract more potential students. By optimizing their websites for search engine optimization, these universities will be able to stay competitive and increase their online visibility. This study contributes to the body of knowledge on website optimization for private universities and provides practical recommendations for improving website performance and link structure

Synthesizing High-Utility Patterns from Different Data Sources

In large organizations, it is often required to collect data from the different geographic branches spread over different locations. Extensive amounts of data may be gathered at the centralized location in order to generate interesting patterns via mono-mining the amassed database. However, it is feasible to mine the useful patterns at the data source itself and forward only these patterns to the centralized company, rather than the entire original database. These patterns also exist in huge numbers, and different sources calculate different utility values for each pattern. This paper proposes a weighted model for aggregating the high-utility patterns from different data sources. The procedure of pattern selection was also proposed to efficiently extract high-utility patterns in our weighted model by discarding low-utility patterns. Meanwhile, the synthesizing model yielded high-utility patterns, unlike association rule mining, in which frequent itemsets are generated by considering each item with equal utility, which is not true in real life applications such as sales transactions. Extensive experiments performed on the datasets with varied characteristics show that the proposed algorithm will be effective for mining very sparse and sparse databases with a huge number of transactions. Our proposed model also outperforms various state-of-the-art distributed models of mining in terms of running time