Secret Image Sharing Scheme Based on Compressed Sensing
Implementation of HOG Based Feature Extraction Method
Soldier Health and Position Monitoring System using GPS and IOT Technology
A Review on the Closed-Loop Strategy for Speed Control of BLDC Motors
V/F Based Speed Controller of Induction Motor using Ann Controller - A Review
Blockchain 3.0: Towards a Secure Ballotcoin Democracy through a Digitized Public Ledger in Developing Countries
Fetal ECG Extraction from Maternal ECG using MATLAB
Brief Introduction to Modular Multilevel Converters and Relative Concepts and Functionalities
Detection of Phase to Phase Faults and Identification of Faulty Phases in Series Capacitor Compensated Six Phase Transmission Line using the Norm of Wavelet Transform
A Novel Approach to Reduce Deafness in Classical Earphones: MUEAR
A novel mathematical ECG signal analysis approach for features extraction using LabVIEW
Filtering of ECG Signal Using Adaptive and Non Adaptive Filters
Application of Polynomial Approximation Techniques for Smoothing ECG Signals
A Novel Approach to Improve the Wind Profiler Doppler Spectra Using Wavelets
Implementation of HOG Based Feature Extraction Method
The present method of monitoring patients in hospitals keeping the patients tied to their beds can be uncomfortable for patients. The number of nurses in the work area is also expected to decline by 2020, causing strain in the environment where excess pressure can lead to unfortunate accidents happening to patients. The goal of this paper was to produce a wireless ECG and PULSE sensor for patient monitoring systems that could allow patients to be mobile in their environment. This system includes a pulse sensor that measures the pulse of the patient and an ECG sensor to measure the complete body condition of the patient. The entire kit will be connected to the patient, and if the patient's condition reaches an abnormal situation, then an SMS will be sent to the doctor's mobile via GSM SIM 800 module.
Adders are very important in Digital Signal Processing (DSP) for filter designing. It is profoundly accepted that the main processing unit of any device capable of carrying out computations is the Central Processing Unit (CPU). The most fundamental and integral part of the CPU is an Arithmetic and Logical Unit (ALU). Adders are the primary and indispensable component of ALU. There are various adders available in the literature such as Ripple Carry Adder (RCA), Carry Look Ahead Adder (CLA), Carry Skip Adder (CSA), and Carry Increment Adder (CIA), etc. In this paper, a new hybrid adder is designed by combining the two significant adders such as the Carry Skip adder and the Carry increment adder. The hybrid adder has two main peripheral components namely RCA and Multiplexer. In this paper, the GDI technique is applied in both RCA and Multiplexer to design a new low-powerhigh-speed hybrid adder. Simulation is done using the Tanner EDA tool in 180nm technology and the results obtained show a significant improvement in power consumption and delay.
The most important part of Digital signal processing (DSP) application is a digital Finite Impulse Response (FIR) Filter bank. Designing and implementing the filter bank is a challenging task in Very Large Scale Integrated (VLSI) circuits. The multiplier and adder are the key blocks in the filter bank that consume high power, more area, and need high computation time. In this paper, an efficient FIR filter bank is designed based on the sub-band coding technique. In this proposed filter bank design, a total of 10 filters are present, and each filter has 5 taps so that the order of each filter in the filter bank structure is 4. This proposed filter bank splits the input audio signal into six sub-band signals based on its frequency, mostly used in hearing aids for audiogram matching. In hearing aids, the frequencies of the audio signal are split into different bands and then amplification is provided according to the different levels of hearing threshold, which is called audiogram matching. To improve the performance of this filter bank, Pipelined Floating Arithmetic has been used.
This paper presents a smart traffic signal system for congestion control and smooth clearance for an emergency vehicle. Every vehicle is equipped with an RFID Tag which is placed in such a way that it cannot be tampered with or removed. We use an RFID reader and Raspberry Pi3 system-on-chip to read the RFID tags equipped vehicle. It counts the number of vehicles that pass on a particular lane during a specified duration. It also determines the network congestion, and according to that the green signal duration for the lane is decided. In addition, if an RFID tag of a vehicle is detected in the stolen vehicle records, then a message would be sent to the police control room using the GSM Module (SIM800) and can be tracked. For the emergency vehicle, when it is approaching the junction, using the RF module with Arduino Uno system-on-chip for wireless communication between the vehicle and the traffic controller, will notify the controller to turn the signals green
Voice Activity Detection (VAD), also known as speech activity detection or speech detection, is a technique used in speech processing in which the presence or absence of human speech is detected. The main uses of VAD are in speech coding and speech recognition. It can facilitate speech processing, and can also be used to deactivate some processes during a non-speech section of an audio session: it can avoid unnecessary coding/transmission of silence packets in Voice over Internet Protocol applications, saving on computation and network bandwidth. VAD is an important enabling technology for a variety of speech-based applications. Therefore, various VAD algorithms have been developed that provide varying features and compromises between latency, sensitivity, accuracy, and computational cost. Some VAD algorithms also provide further analysis, for example, whether the speech is voiced, unvoiced, or sustained. Voice activity detection is usually language-independent. This paper discusses various voice activity detection techniques, their results, and their projection towards how they are going through VAD.
