The Smart Sailing Robot for N avigational I nvestigation i s Used to Explore a ll the Details on the Z one of the W ater Pura

Ocean Exploration and Navigational Research is driving undertakings by supporting undertakings with PC vision frameworks have shown potential for Sailboat robots made to make assessments at the surface. The marine environment presents an in each commonsense sense, ideal showing ground for the assessment and improvement of robotized progressions. Robot cruising is a tricky task in both turn of events and controlling the boat consequently it joins a wide degree of orders. The cruising robot researches in comprehension of video film, the ID of cruising features, human-robot correspondence, vehicle control, position assessment and mechanical course of action. Key applications for this vessel are the appraisal of marine living spaces and complex moves. An idea presented has been with a Robotic vehicle what starts normally and truly control the moving thing in the water the robot will get and sends the information to the PC which uses advanced picture managing improvement and investigates appropriate pictures by seeing cut down features which will follow the article present in the outside of ocean. The DC motors are used to turn the arms of the robot to get living spaces.

The Smart Sailing Robot for N avigational Investigation is Used to Explore all the Details on the Zone of the Water Pura

Ocean Exploration and Navigational Research is driving undertakings by supporting undertakings with PC vision frameworks have shown potential for Sailboat robots made to make assessments at the surface. The marine environment presents an in each commonsense sense, ideal showing ground for the assessment and improvement of robotized progressions. Robot cruising is a tricky task in both turn of events and controlling the boat consequently it joins a wide degree of orders. The cruising robot researches in comprehension of video film, the ID of cruising features, human-robot correspondence, vehicle control, position assessment and mechanical course of action. Key applications for this vessel are the appraisal of marine living spaces and complex moves. An idea presented has been with a Robotic vehicle what starts normally and truly control the moving thing in the water the robot will get and sends the information to the PC which uses advanced picture managing improvement and investigates appropriate pictures by seeing cut down features which will follow the article present in the outside of ocean. The DC motors are used to turn the arms of the robot to get living spaces.

Neural Mass Model-Based Different EEG Signal Generation and Analysis in Simulink Sheikh Md. Rabiul Islam1, Md. Shakibul Islam2

The electroencephalogram (EEG) is an electrophysiological monitoring strategy that records the spontaneous electrical movement of the brain coming about from ionic current inside the neurons of the brain. The importance of the EEG signal is mainly the diagnosis of different mental and brain neurodegenerative diseases and different abnormalities like seizure disorder, encephalopathy, dementia, memory problem, sleep disorder, stroke, etc. The EEG signal is very useful for someone in case of a coma to determine the level of brain activity. So, it is very important to study EEG generation and analysis. To reduce the complexity of understanding the pathophysiological mechanism of EEG signal generation and their changes, different simulation-based EEG modeling has been developed which are based on anatomical equivalent data. In this paper, Instead of a detailed model a neural mass model has been used to implement different simulation-based EEG models for EEG signal generation which refers to the simplified and straightforward method. This paper aims to introduce obtained EEG signals of own implementation of the Lopes da Silva model, Jansen-Rit model, and Wendling model in Simulink and to compare characteristic features with real EEG signals and better understanding the EEG abnormalities especially the seizure-like signal pattern.

Performance Analysis of Cognitive Radios in a Cooperative Scheme over Nakagami Fading Channels

Radio spectrum is a primary requisite for wireless technologies and sensor networks. Due to the high demand and expense of the radio spectrum, it is guaranteed to extend its efficient utilization it. To expand the effective operation and serviceability of the radio spectrum in wireless communications, the notion of Cognitive Radio (CR) is presented in where the licensed spectrum of Primary User (PU) is used opportunistically by unlicensed CR users without interfering with the prioritized PU data transmission. Usually, a CR system is applied to detect empty radio bands by exploiting well-known spectrum sensing schemes and then unused spectrum is opportunistically used by the CR system. Various channels fading of the radio environment are to be considered while introducing different spectrum sensing approaches. In this regard, sensing time to find a vacant radio spectrum should be maintained minimum to reliably get the desired throughput. In this paper, an agreement issue is addressed between the time required for effective spectrum sensing and the achievable throughput of the CR network. Our proposed model illustrates the achievable throughput of CR node in cooperation provides better performance than stand-alone CR node. This is achieved by addressing the variation of the number of nodes under the Nakagami fading distribution. In conclusion, the maximum throughputs of the cooperative CR nodes are guaranteed as per simulation and data analysis.

Neural Mass Model-Based Different EEG Signal Generation and Analysis in Simulink

The electroencephalogram (EEG) is an electrophysiological monitoring strategy that records the spontaneous electrical movement of the brain coming about from ionic current inside the neurons of the brain. The importance of the EEG signal is mainly the diagnosis of different mental and brain neurodegenerative diseases and different abnormalities like seizure disorder, encephalopathy, dementia, memory problem, sleep disorder, stroke, etc. The EEG signal is very useful for someone in case of a coma to determine the level of brain activity. So, it is very important to study EEG generation and analysis. To reduce the complexity of understanding the pathophysiological mechanism of EEG signal generation and their changes, different simulation-based EEG modeling has been developed which are based on anatomical equivalent data. In this paper, Instead of a detailed model a neural mass model has been used to implement different simulation-based EEG models for EEG signal generation which refers to the simplified and straightforward method. This paper aims to introduce obtained EEG signals of own implementation of the Lopes da Silva model, Jansen-Rit model, and Wendling model in Simulink and to compare characteristic features with real EEG signals and better understanding the EEG abnormalities especially the seizure-like signal pattern.

Performance Analysis of Cognitive Radios in a Cooperative Scheme over Nakagami Fading Channels

Radio spectrum is a primary requisite for wireless technologies and sensor networks. Due to the high demand and expense of the radio spectrum, it is guaranteed to extend its efficient utilization it. To expand the effective operation and serviceability of the radio spectrum in wireless communications, the notion of Cognitive Radio (CR) is presented in where the licensed spectrum of Primary User (PU) is used opportunistically by unlicensed CR users without interfering with the prioritized PU data transmission. Usually, a CR system is applied to detect empty radio bands by exploiting well-known spectrum sensing schemes and then unused spectrum is opportunistically used by the CR system. Various channels fading of the radio environment are to be considered while introducing different spectrum sensing approaches. In this regard, sensing time to find a vacant radio spectrum should be maintained minimum to reliably get the desired throughput. In this paper, an agreement issue is addressed between the time required for effective spectrum sensing and the achievable throughput of the CR network. Our proposed model illustrates the achievable throughput of CR node in cooperation provides better performance than stand-alone CR node. This is achieved by addressing the variation of the number of nodes under the Nakagami fading distribution. In conclusion, the maximum throughputs of the cooperative CR nodes are guaranteed as per simulation and data analysis.

A Flux Controlled Memristor using 90nm Technology

A flux-controlled memristor using complementary metal–oxide–(CMOS) structure is presented in this study. The proposed circuit provides higher power efficiency, less static power dissipation, lesser area, and can also reduce the power supply by using CMOS 90nm technology. The circuit is implemented based on the use of a second-generation current conveyor circuit (CCII) and operational transconductance amplifier (OTA) with few passive elements. The proposed circuit uses a current-mode approach which improves the high frequency performance. The reduction of a power supply is a crucial aspect to decrease the power consumption in VLSI. An offered emulator in this proposed circuit is made to operate incremental and decremental configurations well up to 26.3 MHZ in cadence virtuoso platform gpdk using 90nm CMOS technology. proposed memristor circuit has very little static power dissipation when operating with ±1V supply. Transient analysis, memductance analysis, and dc analysis simulations are verified practically with the Experimental demonstration by using ideal memristor made up of ICs AD844AN and CA3080, using multisim which exhibits theoretical simulation are verified and discussed.

A Flux Controlled Memristor using 90nm Technology

A flux-controlled memristor using complementary metal–oxide–(CMOS) structure is presented in this study. The proposed circuit provides higher power efficiency, less static power dissipation, lesser area, and can also reduce the power supply by using CMOS 90nm technology. The circuit is implemented based on the use of a second-generation current conveyor circuit (CCII) and operational transconductance amplifier (OTA) with few passive elements. The proposed circuit uses a current-mode approach which improves the high-frequency performance. The reduction of a power supply is a crucial aspect to decrease the power consumption in VLSI. An offered emulator in this proposed circuit is made to operate incremental and decremental configurations well up to 26.3 MHZ in cadence virtuoso platform gpdk using 90nm CMOS technology. proposed memristor circuit has very little static power dissipation when operating with ±1V supply. Transient analysis, memductance analysis, and dc analysis simulations are verified practically with the Experimental demonstration by using ideal memristor made up of ICs AD844AN and CA3080, using multisim which exhibits theoretical simulation are verified and discussed.

ECG Denoising Methodology using Intrinsic Time Scale Decomposition and Adaptive Switching Mean Filter

Electrocardiogram (ECG) is a widely employed tool for the analysis of cardiac disorders. A clean ECG is often desired for proper treatment of cardiac ailments. However, in the real scenario, ECG signals are corrupted with various noises during acquisition and transmission. In this article, an efficient ECG de-noising methodology using combined intrinsic time scale decomposition (ITD) and adaptive switching mean filter (ASMF) is proposed. The standard performance metric namely output SNR improvement measure the efficacy of the proposed technique at various signal to noise ratio (SNR). The proposed de-noising methodology is compared with other existing ECG de-noising approaches. A detail qualitative and quantitative study and analysis indicate that the proposed technique can be used as an effective tool for de-noising of ECG signals and hence can serve for better diagnostic in computer-based automated medical system. The performance of the proposed work is compared with existing ECG de-noising techniques namely wavelet soft thresholding based filter (DWT) [16], EMD with DWT technique [18], DWT with ADTF technique [19]. The effectiveness of the presented work has been evaluated in both qualitative and quantitative analysis. All the simulations are carried out using MATLAB software environment.

ECG Denoising Methodology using Intrinsic Time Scale Decomposition and Adaptive Switching Mean Filter

Electrocardiogram (ECG) is a widely employed tool for the analysis of cardiac disorders. A clean ECG is often desired for proper treatment of cardiac ailments. However, in the real scenario, ECG signals are corrupted with various noises during acquisition and transmission. In this article, an efficient ECG de-noising methodology using combined intrinsic time scale decomposition (ITD) and adaptive switching mean filter (ASMF) is proposed. The standard performance metric namely output SNR improvement measure the efficacy of the proposed technique at various signal to noise ratio (SNR). The proposed de-noising methodology is compared with other existing ECG de-noising approaches. A detail qualitative and quantitative study and analysis indicate that the proposed technique can be used as an effective tool for de-noising of ECG signals and hence can serve for better diagnostic in computer-based automated medical system. The performance of the proposed work is compared with existing ECG de-noising techniques namely wavelet soft thresholding based filter (DWT) [16], EMD with DWT technique [18], DWT with ADTF technique [19]. The effectiveness of the presented work has been evaluated in both qualitative and quantitative analysis. All the simulations are carried out using MATLAB software environment.