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- 저자 : Prakasam.P (검색결과 4 건)
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Antihyperglycemic Activity of Piper betle Leaf on Streptozotocin-Induced Diabetic Rats
K.V. Pugalendi,P. Santhakumari,A. Prakasam 한국식품영양과학회 2006 Journal of medicinal food Vol.9 No.1
Piper betle, an indigenous medicinal plant, has a folk (Siddha and Ayurvedha) reputation in the rural south-ern India. The present study was carried out to evaluate the effect of P. betleon glucose metabolism since it is consumed asbetel-quid after meals. Plasma levels of glucose and glycosylated hemoglobin and activities of liver hexokinase and gluco-neogenic enzymes such as glucose-6-phosphatase and fructose-1,6-bisphosphatase in control and streptozotocin (STZ) dia-betic rats were assayed. Oral administration of leaf suspension of P. betle (75 and 150 mg/kg of body weight) for 30 days re-sulted in significant reduction in blood glucose (from 205.00. 10.80 mg/dL to 151.30. 6.53 mg/dL) and glycosylatedhemoglobin and decreased activities of liver glucose-6-phosphatase and fructose-1,6-bisphosphatase, while liver hexokinaseincreased (P. .05), in STZ diabetic rats when compared with untreated diabetic rats. P. betleat a dose of 75 mg/kg of bodyweight exhibited better sugar reduction than 150 mg/kg of body weight. In addition, protection against body weight loss ofdiabetic animals was also observed. The effects produced by P. betlewere compared with the standard drug glibenclamide.Thus, the present study clearly shows that P. betle intake influences glucose metabolism beneficially.
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An Enhanced Energy Efficient Lightweight Cryptography Method for various IoT Devices
Prakasam P.,Madheswaran M.,Sujith K.P.,Md Shohel Sayeed 한국통신학회 2021 ICT Express Vol.7 No.4
Internet of Things (IoT) is an auspicious technology that will connect more number of devices through an internet. The huge number of communication expected to transmit high data securely is an important problem in recent days. In this paper, an Enhanced Energy Efficient Lightweight Cryptography Method which utilizes 8 bit manipulation principle (E3LCM) has been proposed. The proposed method has been verified for speech signal using MATLAB. The hardware complexity has been validated using Sparten3E XC3S500E FPGA devices and it has been found that the proposed method consumes 202mW power and 0.9 Kbytes RAM and it outperforms other methods.
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Non-Linear Error Identifier Algorithm for Configuring Mobile Sensor Robot
Rajaram.P,Prakasam.P 대한전기학회 2015 Journal of Electrical Engineering & Technology Vol.10 No.3
WSN acts as an effective tool for tracking the large scale environments. In such environment, the battery life of the sensor networks is limited due to collection of the data, usage of sensing, computation and communication. To resolve this, a mobile robot is presented to identify the data present in the partitioned sensor networks and passed onto the sink. In novel data collection algorithm, the performance of the data collecting operation is reduced because mobile robot can be used only within the limited range. To enhance the data collection in a changing environment, Non Linear Error Identifier (NLEI) algorithm has been developed and presented in this paper to configure the robot by means of error models which are non-linear. Experimental evaluation has been conducted to estimate the performance of the proposed NLEI and it has been observed that the proposed NLEI algorithm increases the error correction rate upto 42% and efficiency upto 60%.
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Design of Mobile Sensor Robot using Non-Linear Fault Recognizer Algorithm
Rajaram.P,Prakasam Periasamy 제어로봇시스템학회 2015 제어로봇시스템학회 국제학술대회 논문집 Vol.2015 No.10
For tracking the large scale environments, Wireless Sensor Network is an efficient tool. In such environment, restriction of battery life of the sensor networks is done because of the grouping of data, utilization of sensing, computation and communication. To determine this, a mobile robot is designed to recognize the data exist in the separated sensor networks and moved on to the sink. In new data collection technique, the outcome of the data grouping process is minimized as mobile robot can be employed in the restricted range. To improve the data collection in a varying environment, Non Linear Fault Recognizer (NLFR) algorithm has been introduced and designed in this paper to construct the robot using fault models that are non-linear. Experimental evaluation has been performed to calculate the outcome of the proposed NLFR and it has been examined that the proposed NLFR algorithm improves the fault correction rate upto 25% and efficiency upto 57%.
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