Informatics Publishing Limited

S. Gowthami ¹, B. Arunkumar ¹

Affiliations
1 Karpagam University, IN

Abstract

For data collection in various environments the wireless sensor networks (WSNs) is used. In that the sensor nodes are randomly deployed in large quantity, there is a broad range of applications supporting manual deployment. The sensors collect the raw data and forward to a remote base station (the sink) through a series of relay nodes. In the wireless communication environment, the operation time of a relay node depends on its traffic volume and communication range. Relay nodes are battery-limited. To get the maximum network lifetime, the location of the relay node have to be carefully planned. The deployment is ensure connectivity between the data sources and the sink, and also hold the heterogeneous traffic flows from different sources and the dominating many-to-one traffic pattern. For the simple case of one source node, both with single and multiple traffic flows produce the optimal solutions. However, the general form of the deployment problem is difficult, and the existing connectivity-guaranteed solutions cannot be directly applied here. The problem is then transformed into a generalized version of the Euclidean Steiner Minimum Tree problem (ESMT). Solution is in continuous space and may yield fractional numbers of relay nodes, where simple rounding of the solution can lead to poor performance. Thus the algorithms are developed for discrete relay node assignment, together with local adjustments. It yields the high-quality practical solutions. The solution has been evaluated through both numerical analysis and ns-2 simulations and compared with state-ofthe- art approaches. Traffic unaware strategies achieves up to 6 to 14 times improvement on the network lifetime.

Keywords

Heuristic Algorithm, Relay Node Lifetime, Relay Node Placement, Wireless Sensor Networks.

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B. Narendra ¹, S. Gowthami ¹, K. Jayasree ¹

Affiliations
1 Annamacharya Institute of Technology and Science, Rajampet, Kadapa, A.P., IN

Abstract

Designing a group of elevators in a building has long been recognized as an important issue to improve transportation efficiency, since elevator service ranks second after heating, ventilation and air conditioning as the main complaints of building tenants. This project implements the scheduling of a group of elevators with destination entry and future traffic information for normal operations and coordinated emergency evacuation to improve transportation efficiency. The operation of the lifts will vary for different modes like normal, emergency and priority modes. In the normal mode the lift in the nearest floor should move to the destination. The floors are identified through IR sensing. In the emergency mode when smoke is sensed in any of the floor all the lifts should move to that particular floor. Movement of the lift should be faster compared to the normal mode. In the Priority mode, whenever more than one passenger has requested for the lift, the lift should be allotted to the highest priority person, here the priority of the person is identified by the RFID tags.

Keywords

Group Elevator, Normal Mode, Emergency Mode, Priority Mode, IR Sensor, Smoke Sensor, RFID Tag, Key Pad, LCD.

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S. Gowthami ¹, M. Ranjit ¹

Affiliations
1 Dept. of EEE, VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad, IN

Abstract

The Zero Sequence Voltage generated by a conventional two level inverter fed induction motor drive results to various adverse effects like bearing currents and electromagnetic interference. By using conventional multilevel inverter the switching losses, complexity and the cost of the equipment increases as the number of levels increases and also the bearing currents still exists. In this proposed work, the techniques to overcome the drawbacks due to conventional inverter and multilevel inverter have been presented i.e, by using proposed multilevel inverter fed open end winding. In this paper, the performance characteristics of Induction motor with different PWM techniques like SPWM, THIPWM have been analyzed and the harmonic analysis has been carried out using MATLAB/SIMULINK environment and to validate the results for different modulation index are listed out.

Keywords

Zero Sequence Voltage (ZSV), Bearing Currents, Open End Winding Induction Motor Drive, SPWM, THIPWM, Modulation Index.

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K. Kavitha ¹, S. Gowthami ²

Affiliations
1 Assistant Professor Department of Foods and Nutrition, Vellalar College for Women, Erode – 638 012, Tamil Nadu, IN
2 PG Student, Vellalar College for Women, Erode – 638 012, Tamil Nadu, IN

Abstract

As grape seed is the waste material in grape processing, these waste material is generally utilized as cattle feed in many countries, while grape seed has been shown to contain high amount of antioxidant compounds and is a good source of polyphenols a wide variety of proanthocyanidins. For the current study, grape seeds were collected, dried and powdered separately and incorporated in different variety of noodles such as tomato, mint and beetroot at 10%, 20% and 30% levels. Among the three varieties, 20% grape seed powder incorporated beetroot noodles was highly accepted. Grape seed powder incorporated noodles were found to be rich in protein, vitamins like carotene, vitamins C and Vitamin E and minerals like iron and calcium. The microbial load was assessed for highly accepted grape seed powder incorporated homemade noodles and it was found to be safe level.

Keywords

Antioxidant, Grape Seed Powder, Homemade Noodles, Microbial Load, Polyphenols

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S. Gowthami ¹

Affiliations
1 Department of Biomedical Engineering, Bannari Amman Institute of Technology, IN

Abstract

Melanoma, a deadly form of skin cancer, demands accurate and early diagnosis for effective treatment. In this study, we propose a novel approach to improve melanoma classification by integrating Graph Attention Layers (GALs) into the Group Method of Data Handling (GMDH) framework. Our method leverages the power of GMDH to automatically generate and select informative features from complex melanoma-related data. Simultaneously, GALs are employed to capture intricate relationships and dependencies within the data, often overlooked by traditional classification models. We construct a graph representation where nodes represent data elements (patients or genetic markers) and edges signify relationships between them. GALs are applied to the graph, allowing the model to attend to relevant nodes and connections, enhancing its ability to discern subtle patterns indicative of melanoma. We then train a classification model on this enriched feature set, aiming for superior accuracy in melanoma diagnosis. Experimental results on a diverse melanoma dataset demonstrate the effectiveness of our approach. The model consistently outperforms traditional methods in terms of accuracy, precision, and recall. This study highlights the potential of combining GMDH-based feature extraction with GALs in melanoma classification. This approach not only advances diagnostic accuracy but also provides valuable insights into the underlying factors driving melanoma risk. As early detection remains the key to melanoma treatment success, our proposed method holds promise for improving patient outcomes.

Keywords

Melanoma Classification, Graph Attention Layers, GMDH, Feature Extraction, Early Diagnosis

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