Informatics Publishing Limited

R. S. Bhuvaneeswaran ¹, M. Sujatha ¹, S. Sivaranjani

Affiliations
1 Sathyabama University, IN

Abstract

In recent years, we have witnessed an increasing interest in deploying wireless sensor networks (WSNs) for real-life applications. Object-tracking sensor network (OTSN)-based applications are widely viewed as being among the most interesting applications of WSNs. OTSN is mainly used to track certain objects in a monitored area and to report their location to the application’s users. However, OTSNs are well known for their energy consumption when compared with other WSN applications. In this paper, we propose a prediction based tracking technique using sequential patterns (PTSPs) designed to achieve significant reductions in the energy dissipated by the OTSNs while maintaining acceptable missing rate levels. PTSP outperforms all the other basic tracking techniques and exhibits significant amounts of savings in terms of the entire network’s energy consumption.

Keywords

Network Simulator (ns-2), Object Tracking, Wireless Sensor Networks (WSNs).

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S. Sivaranjani ¹, D. Palanikkumar ²

Affiliations
1 Department of CSE, Avinashilingam University for Women, Coimbatore, IN
2 Department of CSE, Anna University of Technology, Coimbatore, IN

Abstract

This paper deals with the shopping cart in which an item can be chosen in advance and made available for the customer for buying an item which he/she is going to buy. It describes about the market basket in which the similar items are grouped together and they lead a group. It uses the Association Rule in which the common items are held in a group and provides a chance for the customer to choose one among them. This can be done with the help of certain percentage amount of buying the same thing by the regular customer. It uses a specialized algorithm for providing the association methodology. A commonly-used and naive solution to process data with missing attribute values is to ignore the instances which contain missing attribute values. This method may neglect important information within the data and a significant amount of data could be easily discarded. Some methods, such as assigning the most common values or assigning an average value to the missing attribute, make good use of all the available data. However the assigned value may not come from the information which the data originally derived from, thus noise is brought to the data.

Keywords

Association Rule Mining (ARM),classification Rule Mining.

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S. Sivaranjani ¹, A. Rakshit ²

Affiliations
1 Soil and Water Conservation, Department of Soil Science and Agricultural Chemistry, Institute of Agricultural Science, RGSC Banaras Hindu University, Mirzapur, UP, IN
2 Department of Soil Science and Agricultural Chemistry, Institute of Agricultural Science, Banaras Hindu University, Varanasi, UP, IN

Abstract

In rural areas, most people rely on private water supplies such as wells and dugouts. Quality water is vital to the social, health, and economic well-being of people. It sustains ecological processes that support native fish population, vegetation, wetlands and bird life. Water quality is commonly defined by its physical, chemical, biological and aesthetic characteristics. Presently, there are no appropriate low-cost technologies available for removal of several contaminants present in groundwater. Microbial degradation, chemical oxidation, photolysis and adsorption are used for the treatment of wastewater. Although aluminium is the most commonly used coagulant in the developing countries, studies have linked it to the development of neurological diseases. There are several methods used for the purification of water. Activated carbons are the most common adsorbent, and they are made from different plants, animal residues and bituminous coal. Moringa oleifera seeds are also used as a primary coagulant in drinking water clarification and wastewater treatment due to the presence of a water-soluble cationic coagulant protein, which is able to reduce turbidity of the treated water. There are many other species like Vigna unguiculata, Voandzeia subterranea, Arachis hypogaea, Vicia faba and Parkinsonia aculeata, which are also used for purification of water for drinking and cooking purposes while wood ashes are mainly used for clarifying water for activities such as laundry, bathing, washing utensils but very rarely for drinking. Hence, there is an urgent need for development of alternative, cost effective and also environmental friendly coagulants to address the issue.

Keywords

Water Quality, Biocoagulants, Low-Cost Technology, Wastewater Treatment.

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S. Sivaranjani ¹, S. Sivakumari ¹

Affiliations
1 Department of Computer Science and Engineering, Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore - 641108, Tamil Nadu, IN

Abstract

Objective: The main objective of this research is to reduce the burden of crime investigators by identifying the series of crimes happening at different places. And also, this work aims to reduce the investigation time by grouping similar crimes happened in different places based on its behavior with the consideration of the class imbalance problem. Methods: In this research, Majority Weighted Class Oversampling (MWCS) method is introduced which overcomes the problem of class imbalance problem. It is introduced to handle class imbalance problem by identifying the hard to learn information which is named as minority class samples from the major class samples. And also in this work, the Incremental Clustering (IC) is introduced which can handle the insertion and deletion operations where the existing methodology called graph cut clustering algorithm cant handle these problems. The proposed methodologies deal with the class imbalance problems effectively and also the modification processes over the partitioned graphs are supported well than the existing researches. Results: The methods used in this work namely MWCS and IC are used to detect the series of crimes by identifying the similarity relationship exists among the crimes happened in different places. The experimental tests conducted were proves that the proposed methodology can leads to well detection of serial residential crimes than the existing methodologies. The experimental results of this work prove that the proposed methodology is improved in terms of all performance metrics called jaccard index, mantel index and the journey distance time. Conclusion: The findings demonstrate that serial residential crimes are identified by clustering them effectively using the methodologies called MWCs and IC and it has high possibility of detection of crimes than the existing methodology.

Keywords

Cut Clustering, Incremental Clustering, Majority Weighted Class Oversampling, Serial Crimes

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S. Sivaranjani ¹, A. Rakshit ²

Affiliations
1 Department of Soil Science and Agricultural Chemistry, Institute of Agricultural Science, RGSC BHU, Mirzapur-231001, U.P., IN
2 Department of Soil Science and Agricultural Chemistry, Institute of Agricultural Science, Banaras Hindu University, Varanasi-221005, U.P., IN

Abstract

The conventional methods of water treatment involve various water clarification processes which include coagulation, flocculation, sedimentation and disinfection. Coagulation is a critical step in water treatment because it involves removing the colloidal particles as well as pathogens that are often attached to the particles. These methods are often not suitable because of the high cost and low availability of chemical coagulants and disinfectants. Synthetic coagulants are not always available at a reasonable price and can leave undesirable residues in treated water. In the present study, the removal efficiency of Moringa oleifera and alum were compared using different types of wastewater. The efficacy of two coagulants has been tested based on some critical parameters including dosages of coagulant, pH, EC, TDS, hardness, DO and COD of turbid water and change in values of these parameters in finished water. These coagulants obviously possessed positive coagulation abilities. There are about nine treatments with one control been used for the study. From the observed results, the blended coagulant MO: (Al₂(SO₄)₃ treatments T7(25:25) and T8(50:50) dosage ratio gives better removal efficiencies with respect to pH, EC, TDS, hardness, DO, COD, Na and K, and appears to be suitable for treatment of wastewater, when compared with other dosages.

Keywords

Wastewaters, Alum, Moringa oleifera, Coagulants.

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S. Sivaranjani ¹, S. Mohanraj ¹, V. Kavitha ¹

Affiliations
1 Department of ECE, M. Kumarasamy College of Engineering, Karur, Thalavapalayam – 639113, Tamil Nadu, IN

Abstract

Objective: To direct channel selection in WSNs. The tests indicate execution enhancements on the conveyance rate and conveyance defer when the proposed cognitive arrangements are utilized. Methods/Statistical Analysis: The utilization of administered Machine Learning (ML) for direct determination in WSNs. The proposed models were broke down utilizing ML apparatuses and strategies, and the best calculations were assessed on genuine sensor hubs. Findings: Wireless Sensor Networks (WSNs) utilize Industrial, Logical and Medical (ISM) range groups for correspondence, which are over-burden because of different innovations for example, WLANs and different WSNs. In this way, such systems must utilize astute strategies, for example, Cognitive Radio (CR) to exist together with different systems. The tests indicate execution enhancements on the delivery rate and delivery delay when the proposed psychological arrangements are utilized. Application/Improvements: Intelligent spectrum decision machine learning idea we can utilize all sort of use, for example, restorative field, Miltary applications, and so forth.

Keywords

Cognitive Radio, Delivery Delay, Delivery Rate, Machine Learning Algorithm, Wireless Sensor Networks

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S. Saravanan ¹, K. S. S. Parthasarathy ², D. Abijith ³, S. Sivaranjani ⁴

Affiliations
1 Department of Civil Engineering, National Institute of Technology, Tiruchirappalli, IN
2 Department of Applied Mechanics and Hydraulics, National Institute of Technology, Surathkal, Karnataka, IN
3 Department of Civil Engineering, Anna University Regional Campus, Tirunelveli, IN
4 Department of Geography, Bharathidasan University, Tiruchirappalli, IN

Abstract

Urban Heat Island (UHI) is a major urban environmental issue throughout the world. UHI is a climatic phenomenon where anthropogenic modification leads to increased air temperature in urban areas when compared to that of the surrounding rural areas. Over urbanisation leads to an increase in UHI, resulting in the decrease of human health and a healthy environment. Remote sensing plays a major role in mapping the UHI as it can sense the top of the atmosphere radiances. From brightness, temperatures can be derived using Planck’s constant. In this study, UHI of Coimbatore was determined by using the single channel algorithm during winter season. Landsat data of TM, ETM+ and OLI/TIRS were used. Thus, LST helps to identify the increase in heat due to expansion urban areas. Supervised classification with maximum likelihood technique was used to classify the imageries into five landuse classes.Based on this study, the result emphasies that the land use changes was observed to be 14.55 per cent, where as vegetation reduction was 11.6 per cent.Thus, by correlating all these scenario from the year 1990 to 2015 with a five-year interval, the rapid development that took place in the Coimbatore region led to decrease in vegetation and increase in built-up land and temperature. This study reveals that there was an increase of 3.8°C in land surface temperature during in the study periods. Also, the result indicates that there is a strong linearly negative correlation between land surface temperature and vegetation.

Keywords

GIS, LST, Landsat, Urbanisation and UHI.

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S. Sivaranjani ¹, V. Geethalakshmi ¹, S. Pazhanivelan ¹, J. S. Kennedy ¹, S. P. Ramanathan ¹, R. Gowtham ², K. Pugazenthi ¹

Affiliations
1 Tamil Nadu Agricultural University, Coimbatore 641 003, India., IN
2 Indian Farmers Fertilizers Cooperative Limited, Coimbatore 641 003, India., IN

Abstract

Hyperspectral remote sensing captures images in multiple wavelengths and is widely used to detect plant stress in agriculture. A study was conducted on brown planthopper (BPH) infestation in rice at various temperature regimes (15°C, 20°C, 25°C, 30°C and 35°C). The experimentation was done in the Environmental Control Chamber, Tamil Nadu Agricultural University, Coimbatore, India. The field spectroradiometer and vegetation indices were used to study the early and late infestations of BPH in rice. The results reveal that reflectance at certain wavelengths (550, 670 and 700 nm) indicates plant stress. Among the vegetation indices, MCARI performed better than NDVI, PRI, NDRE and SR for the detection of early and late infestation of BPH. Hence, hyperspectral reflectance from rice has been used to detect pest damage and improve management policies.

Keywords

Brown planthopper, hyperspectral sensor, Plant stress, rice, vegetation indices.

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